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Krieger N, Testa C, Chen JT, Johnson N, Watkins SH, Suderman M, Simpkin AJ, Tilling K, Waterman PD, Coull BA, De Vivo I, Smith GD, Roux AVD, Relton C. Epigenetic aging & embodying injustice: US My Body My Story and Multi-Ethnic Atherosclerosis Study. medRxiv 2023:2023.12.13.23299930. [PMID: 38168159 PMCID: PMC10760288 DOI: 10.1101/2023.12.13.23299930] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Importance Epigenetic accelerated aging is associated with exposure to social and economic adversity and may increase risk of premature morbidity and mortality. However, no studies have included measures of structural racism and few have compared estimates within or across the 1st and 2nd generation of epigenetic clocks (the latter additionally trained on phenotypic data). Objective To determine if accelerated epigenetic aging is associated with exposures to diverse measures of racialized, economic, and environmental injustice measured at different levels and time periods. Design Cross-sectional My Body My Story Study (MBMS; US, 2008-2010) and Exam 5 Multi-Ethnic Atherosclerosis Study (MESA; US, 2010-2012). MBMS DNA extraction: 2021; linkage of structural measures to MBMS and MESA: 2022. Setting MBMS recruited a random sample of US-born Black non-Hispanic (BNH) and white non-Hispanic (WNH) participants from 4 community health centers in Boston, MA. The MESA Exam 5 epigenetic component included 975 randomly selected US-born BNH, WNH, and Hispanic participants from four field sites: Baltimore, MD; Forsyth County, NC; New York City, NY; St. Paul, MN. Participants US-born persons (MBMS: 224 BNH, 69 WNH; MESA: 229 BNH, 555 WNH, 191 Hispanic). Main outcome and measures 10 epigenetic clocks (six 1st generation; four 2nd generation), computed using DNA methylation data (DNAm) from blood spots (MBMS; N = 293) and purified monocytes (MESA; N = 975). Results Among Black non-Hispanic MBMS participants, epigenetic age acceleration was associated with being born in a Jim Crow state by 0.14 standard deviations (95% confidence interval [CI] 0.00, 0.27) and with birth state conservatism (0.06, 95% CI 0.00, 0.05), pooling across all clocks, as was low parental education for both Black non-Hispanic and white non-Hispanic MBMS participants (respectively: 0.24, 95% CI 0.08, 0.39, and 0.27, 95% CI 0.03, 0.51. Adult impoverishment was positively associated with the pooled 2nd generation clocks among the MESA participants (Black non-Hispanic: 0.06, 95% CI 0.01, 0.12; white non-Hispanic: 0.05, 95% CI 0.01, 0.08; Hispanic: 0.07, 95% CI 0.01, 0.14). Conclusions and Relevance Epigenetic accelerated aging may be one of the biological mechanisms linking exposure to racialized and economic injustice to well-documented inequities in premature morbidity and mortality.
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Affiliation(s)
- Nancy Krieger
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Christian Testa
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Jarvis T. Chen
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Nykesha Johnson
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Sarah H. Watkins
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
| | - Andrew J. Simpkin
- School of Mathematical and Statistical Sciences, National University of Ireland, Galway, Ireland
| | - Kate Tilling
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
| | - Pamela D. Waterman
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Brent A. Coull
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - Immaculata De Vivo
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, United States
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
| | - Ana V. Diez Roux
- Urban Health Collective and Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, United Kingdom
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Watkins SH, Testa C, Simpkin AJ, Smith GD, Coull B, De Vivo I, Tilling K, Waterman PD, Chen JT, Diez-Roux AV, Krieger N, Suderman M, Relton C. An epigenome-wide analysis of DNA methylation, racialized and economic inequities, and air pollution. bioRxiv 2023:2023.12.07.570610. [PMID: 38105971 PMCID: PMC10723401 DOI: 10.1101/2023.12.07.570610] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Importance DNA methylation (DNAm) provides a plausible mechanism by which adverse exposures become embodied and contribute to health inequities, due to its role in genome regulation and responsiveness to social and biophysical exposures tied to societal context. However, scant epigenome-wide association studies (EWAS) have included structural and lifecourse measures of exposure, especially in relation to structural discrimination. Objective Our study tests the hypothesis that DNAm is a mechanism by which racial discrimination, economic adversity, and air pollution become biologically embodied. Design A series of cross-sectional EWAS, conducted in My Body My Story (MBMS, biological specimens collected 2008-2010, DNAm assayed in 2021); and the Multi Ethnic Study of Atherosclerosis (MESA; biological specimens collected 2010-2012, DNAm assayed in 2012-2013); using new georeferenced social exposure data for both studies (generated in 2022). Setting MBMS was recruited from four community health centers in Boston; MESA was recruited from four field sites in: Baltimore, MD; Forsyth County, NC; New York City, NY; and St. Paul, MN. Participants Two population-based samples of US-born Black non-Hispanic (Black NH), white non-Hispanic (white NH), and Hispanic individuals (MBMS; n=224 Black NH and 69 white NH) and (MESA; n=229 Black NH, n=555 white NH and n=191 Hispanic). Exposures Eight social exposures encompassing racial discrimination, economic adversity, and air pollution. Main outcome Genome-wide changes in DNAm, as measured using the Illumina EPIC BeadChip (MBMS; using frozen blood spots) and Illumina 450k BeadChip (MESA; using purified monocytes). Our hypothesis was formulated after data collection. Results We observed the strongest associations with traffic-related air pollution (measured via black carbon and nitrogen oxides exposure), with evidence from both studies suggesting that air pollution exposure may induce epigenetic changes related to inflammatory processes. We also found suggestive associations of DNAm variation with measures of structural racial discrimination (e.g., for Black NH participants, born in a Jim Crow state; adult exposure to racialized economic residential segregation) situated in genes with plausible links to effects on health. Conclusions and Relevance Overall, this work suggests that DNAm is a biological mechanism through which structural racism and air pollution become embodied and may lead to health inequities.
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Affiliation(s)
- Sarah Holmes Watkins
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Christian Testa
- Department of Social and Behavioral Sciences, Harvard T H Chan School of Public Health, Harvard University, Boston, MA 02115, USA
- Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
| | - Andrew J. Simpkin
- School of Mathematical and Statistical Sciences, University of Galway, Galway, Ireland
| | - George Davey Smith
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Brent Coull
- Department of Biostatistics, Harvard School of Public Health, Boston, MA 02115, USA
| | - Immaculata De Vivo
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Kate Tilling
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Pamela D. Waterman
- Department of Social and Behavioral Sciences, Harvard T H Chan School of Public Health, Harvard University, Boston, MA 02115, USA
| | - Jarvis T. Chen
- Department of Social and Behavioral Sciences, Harvard T H Chan School of Public Health, Harvard University, Boston, MA 02115, USA
| | - Ana V. Diez-Roux
- Department of Epidemiology and Biostatistics and Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, USA
| | - Nancy Krieger
- Department of Social and Behavioral Sciences, Harvard T H Chan School of Public Health, Harvard University, Boston, MA 02115, USA
| | - Matthew Suderman
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Caroline Relton
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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Haycock PC, Borges MC, Burrows K, Lemaitre RN, Harrison S, Burgess S, Chang X, Westra J, Khankari NK, Tsilidis KK, Gaunt T, Hemani G, Zheng J, Truong T, O’Mara TA, Spurdle AB, Law MH, Slager SL, Birmann BM, Saberi Hosnijeh F, Mariosa D, Amos CI, Hung RJ, Zheng W, Gunter MJ, Davey Smith G, Relton C, Martin RM. Design and quality control of large-scale two-sample Mendelian randomization studies. Int J Epidemiol 2023; 52:1498-1521. [PMID: 38587501 PMCID: PMC10555669 DOI: 10.1093/ije/dyad018] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 02/10/2023] [Indexed: 03/27/2024] Open
Abstract
Background Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).
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Affiliation(s)
- Philip C Haycock
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kimberley Burrows
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Sean Harrison
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Stephen Burgess
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Xuling Chang
- Department of Paediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Khoo Teck Puat—National University Children's Medical Institute, National University Health System, Singapore, Singapore
| | - Jason Westra
- Department of Mathematics, Statistics, and Computer Science, Dordt College, Sioux Center, IA, USA
| | - Nikhil K Khankari
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Kostas K Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Tom Gaunt
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jie Zheng
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Therese Truong
- Université Paris-Saclay, UVSQ, Inserm, Gustave Roussy, Team “Exposome, Heredity, Cancer and Health”, CESP, Villejuif, France
| | - Tracy A O’Mara
- Genetics and Computational Biology Division, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Medicine, Faculty of Health Sciences, University of Queensland, Brisbane, Australia
| | - Amanda B Spurdle
- Genetics and Computational Biology Division, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Medicine, Faculty of Health Sciences, University of Queensland, Brisbane, Australia
| | - Matthew H Law
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, QLD, Australia
- School of Biomedical Sciences, Faculty of Health, and Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, QLD, Australia
| | - Susan L Slager
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Brenda M Birmann
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Daniela Mariosa
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC), Lyon, France
| | - Christopher I Amos
- Dan L Duncan Comprehensive Cancer Center Baylor College of Medicine, Houston, USA
| | - Rayjean J Hung
- Lunenfeld-Tanenbaum Research Institute, Sinai Health and University of Toronto, Toronto, Canada
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Marc J Gunter
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC), Lyon, France
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Richard M Martin
- MRC Integrative Epidemiology Unit (IEU), University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Biomedical Research Centre at University Hospitals Bristol and Weston NHS Foundation Trust and the University of Bristol, Bristol, UK
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Villicaña S, Castillo-Fernandez J, Hannon E, Christiansen C, Tsai PC, Maddock J, Kuh D, Suderman M, Power C, Relton C, Ploubidis G, Wong A, Hardy R, Goodman A, Ong KK, Bell JT. Genetic impacts on DNA methylation help elucidate regulatory genomic processes. Genome Biol 2023; 24:176. [PMID: 37525248 PMCID: PMC10391992 DOI: 10.1186/s13059-023-03011-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Accepted: 07/10/2023] [Indexed: 08/02/2023] Open
Abstract
BACKGROUND Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk. RESULTS We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2358 blood samples from three UK cohorts. Methylation levels at 34.2% of CpGs are affected by SNPs, and 98% of effects are cis-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both SNPs and CpGs with meQTLs are overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identify 1520 co-localisations across 1325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such as USP1 and DOCK7 (total cholesterol levels), and ICOSLG (inflammatory bowel disease). Enrichment analysis of meQTLs and integration with expression QTLs give insights into mechanisms underlying cis-meQTLs (e.g. through disruption of transcription factor binding sites for CTCF and SMC3) and trans-meQTLs (e.g. through regulating the expression of ACD and SENP7 which can modulate DNA methylation at distal sites). CONCLUSIONS Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. The MeQTL EPIC Database and viewer are available online at https://epicmeqtl.kcl.ac.uk .
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Affiliation(s)
- Sergio Villicaña
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
| | | | | | - Colette Christiansen
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Jane Maddock
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Christine Power
- Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population, Policy and Practice, UCL Great Ormond Street Institute of Child Health, University College London, London, UK
| | - George Ploubidis
- Centre for Longitudinal Studies, Institute of Education, University College London, London, UK
| | - Andrew Wong
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - Rebecca Hardy
- School of Sport, Exercise & Health Sciences, Loughborough University, Loughborough, UK
- UCL Social Research Institute, University College London, London, UK
| | - Alissa Goodman
- Centre for Longitudinal Studies, Institute of Education, University College London, London, UK
| | - Ken K Ong
- MRC Epidemiology Unit and Department of Paediatrics, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge School of Clinical Medicine, Cambridge, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
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Watkins SH, Testa C, Chen JT, De Vivo I, Simpkin AJ, Tilling K, Diez Roux AV, Davey Smith G, Waterman PD, Suderman M, Relton C, Krieger N. Epigenetic clocks and research implications of the lack of data on whom they have been developed: a review of reported and missing sociodemographic characteristics. Environ Epigenet 2023; 9:dvad005. [PMID: 37564905 PMCID: PMC10411856 DOI: 10.1093/eep/dvad005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Revised: 06/17/2023] [Accepted: 07/13/2023] [Indexed: 08/12/2023]
Abstract
Epigenetic clocks are increasingly being used as a tool to assess the impact of a wide variety of phenotypes and exposures on healthy ageing, with a recent focus on social determinants of health. However, little attention has been paid to the sociodemographic characteristics of participants on whom these clocks have been based. Participant characteristics are important because sociodemographic and socioeconomic factors are known to be associated with both DNA methylation variation and healthy ageing. It is also well known that machine learning algorithms have the potential to exacerbate health inequities through the use of unrepresentative samples - prediction models may underperform in social groups that were poorly represented in the training data used to construct the model. To address this gap in the literature, we conducted a review of the sociodemographic characteristics of the participants whose data were used to construct 13 commonly used epigenetic clocks. We found that although some of the epigenetic clocks were created utilizing data provided by individuals from different ages, sexes/genders, and racialized groups, sociodemographic characteristics are generally poorly reported. Reported information is limited by inadequate conceptualization of the social dimensions and exposure implications of gender and racialized inequality, and socioeconomic data are infrequently reported. It is important for future work to ensure clear reporting of tangible data on the sociodemographic and socioeconomic characteristics of all the participants in the study to ensure that other researchers can make informed judgements about the appropriateness of the model for their study population.
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Affiliation(s)
- Sarah Holmes Watkins
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Christian Testa
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
| | - Jarvis T Chen
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
| | - Immaculata De Vivo
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
- Department of Medicine, Harvard Medical School, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Andrew J Simpkin
- School of Medicine, National University of Ireland Galway, Galway H91 TK33, Ireland
| | - Kate Tilling
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Ana V Diez Roux
- Department of Epidemiology and Biostatistics and Urban Health Collaborative, Dornsife School of Public Health, Drexel University, Philadelphia, PA 19104, USA
| | - George Davey Smith
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Pamela D Waterman
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
| | - Matthew Suderman
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Caroline Relton
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
- Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Nancy Krieger
- Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA 02115, USA
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Krieger N, Chen JT, Testa C, Diez Roux A, Tilling K, Watkins S, Simpkin AJ, Suderman M, Davey Smith G, De Vivo I, Waterman PD, Relton C. Use of Correct and Incorrect Methods of Accounting for Age in Studies of Epigenetic Accelerated Aging: Implications and Recommendations for Best Practices. Am J Epidemiol 2023; 192:800-811. [PMID: 36721372 PMCID: PMC10160768 DOI: 10.1093/aje/kwad025] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Revised: 11/28/2022] [Accepted: 01/27/2023] [Indexed: 02/02/2023] Open
Abstract
Motivated by our conduct of a literature review on social exposures and accelerated aging as measured by a growing number of epigenetic "clocks" (which estimate age via DNA methylation (DNAm) patterns), we report on 3 different approaches in the epidemiologic literature-1 incorrect and 2 correct-on the treatment of age in these and other studies using other common exposures (i.e., body mass index and alcohol consumption). Among the 50 empirical articles reviewed, the majority (n = 29; 58%) used the incorrect method of analyzing accelerated aging detrended for age as the outcome and did not control for age as a covariate. By contrast, only 42% used correct methods, which are either to analyze accelerated aging detrended for age as the outcome and control for age as a covariate (n = 16; 32%) or to analyze raw DNAm age as the outcome and control for age as a covariate (n = 5; 10%). In accord with prior demonstrations of bias introduced by use of the incorrect approach, we provide simulation analyses and additional empirical analyses to illustrate how the incorrect method can lead to bias towards the null, and we discuss implications for extant research and recommendations for best practices.
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Affiliation(s)
- Nancy Krieger
- Correspondence to Dr. Nancy Krieger, Department of Social and Behavioral Sciences, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Kresge 717, Boston, MA 02115 (e-mail: )
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7
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Haycock PC, Borges MC, Burrows K, Lemaitre RN, Burgess S, Khankari NK, Tsilidis KK, Gaunt TR, Hemani G, Zheng J, Truong T, Birmann BM, OMara T, Spurdle AB, Iles MM, Law MH, Slager SL, Saberi Hosnijeh F, Mariosa D, Cotterchio M, Cerhan JR, Peters U, Enroth S, Gharahkhani P, Le Marchand L, Williams AC, Block RC, Amos CI, Hung RJ, Zheng W, Gunter MJ, Smith GD, Relton C, Martin RM. The association between genetically elevated polyunsaturated fatty acids and risk of cancer. EBioMedicine 2023; 91:104510. [PMID: 37086649 PMCID: PMC10148095 DOI: 10.1016/j.ebiom.2023.104510] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2022] [Revised: 02/10/2023] [Accepted: 02/20/2023] [Indexed: 04/24/2023] Open
Abstract
BACKGROUND The causal relevance of polyunsaturated fatty acids (PUFAs) for risk of site-specific cancers remains uncertain. METHODS Using a Mendelian randomization (MR) framework, we assessed the causal relevance of PUFAs for risk of cancer in European and East Asian ancestry individuals. We defined the primary exposure as PUFA desaturase activity, proxied by rs174546 at the FADS locus. Secondary exposures were defined as omega 3 and omega 6 PUFAs that could be proxied by genetic polymorphisms outside the FADS region. Our study used summary genetic data on 10 PUFAs and 67 cancers, corresponding to 562,871 cases and 1,619,465 controls, collected by the Fatty Acids in Cancer Mendelian Randomization Collaboration. We estimated odds ratios (ORs) for cancer per standard deviation increase in genetically proxied PUFA exposures. FINDINGS Genetically elevated PUFA desaturase activity was associated (P < 0.0007) with higher risk (OR [95% confidence interval]) of colorectal cancer (1.09 [1.07-1.11]), esophageal squamous cell carcinoma (1.16 [1.06-1.26]), lung cancer (1.06 [1.03-1.08]) and basal cell carcinoma (1.05 [1.02-1.07]). There was little evidence for associations with reproductive cancers (OR = 1.00 [95% CI: 0.99-1.01]; Pheterogeneity = 0.25), urinary system cancers (1.03 [0.99-1.06], Pheterogeneity = 0.51), nervous system cancers (0.99 [0.95-1.03], Pheterogeneity = 0.92) or blood cancers (1.01 [0.98-1.04], Pheterogeneity = 0.09). Findings for colorectal cancer and esophageal squamous cell carcinoma remained compatible with causality in sensitivity analyses for violations of assumptions. Secondary MR analyses highlighted higher omega 6 PUFAs (arachidonic acid, gamma-linolenic acid and dihomo-gamma-linolenic acid) as potential mediators. PUFA biosynthesis is known to interact with aspirin, which increases risk of bleeding and inflammatory bowel disease. In a phenome-wide MR study of non-neoplastic diseases, we found that genetic lowering of PUFA desaturase activity, mimicking a hypothetical intervention to reduce cancer risk, was associated (P < 0.0006) with increased risk of inflammatory bowel disease but not bleeding. INTERPRETATION The PUFA biosynthesis pathway may be an intervention target for prevention of colorectal cancer and esophageal squamous cell carcinoma but with potential for increased risk of inflammatory bowel disease. FUNDING Cancer Resesrch UK (C52724/A20138, C18281/A19169). UK Medical Research Council (MR/P014054/1). National Institute for Health Research (NIHR202411). UK Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4). National Cancer Institute (R00 CA215360). National Institutes of Health (U01 CA164973, R01 CA60987, R01 CA72520, U01 CA74806, R01 CA55874, U01 CA164973 and U01 CA164973).
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Affiliation(s)
- Philip C Haycock
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, University of Bristol, Bristol, United Kingdom.
| | - Maria Carolina Borges
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Kimberley Burrows
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Rozenn N Lemaitre
- Department of Medicine, Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
| | | | - Nikhil K Khankari
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Konstantinos K Tsilidis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK; Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Tom R Gaunt
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China; Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Therese Truong
- Université Paris-Saclay, UVSQ, Inserm, Gustave Roussy, Team "Exposome, Heredity, Cancer and Health", CESP, Villejuif, France
| | - Brenda M Birmann
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Tracy OMara
- Genetics and Computational Biology Division, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia; School of Medicine, Faculty of Health Sciences, University of Queensland, Australia
| | - Amanda B Spurdle
- Genetics and Computational Biology Division, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia; School of Medicine, Faculty of Health Sciences, University of Queensland, Australia
| | - Mark M Iles
- Leeds Institute for Data Analytics, University of Leeds, Leeds, UK; NIHR Leeds Biomedical Research Centre, Leeds Teaching Hospitals NHS Trust, Leeds, UK
| | - Matthew H Law
- Statistical Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia; School of Biomedical Sciences, Faculty of Health, and Institute of Health and Biomedical Innovation, Queensland University of Technology, Kelvin Grove, Queensland, Australia
| | - Susan L Slager
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | - Daniela Mariosa
- Genomic Epidemiology Branch, International Agency for Research on Cancer (IARC/WHO), Lyon, France
| | - Michelle Cotterchio
- Dalla Lana School of Public Health, University of Toronto, Canada; Prevention and Cancer Control, Cancer Care Ontario, Ontario Health, Toronto, ON, Canada
| | - James R Cerhan
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, USA; Department of Epidemiology, School of Public Health, University of Washington, Seattle, USA
| | - Stefan Enroth
- Department of Immunology, Genetics, and Pathology, Biomedical Center, Science for Life Laboratory (SciLifeLab) Uppsala, Uppsala University, Uppsala, Sweden
| | - Puya Gharahkhani
- Statistical Genetics Lab, QIMR Berghofer Medical Research Institute, 300 Herston Road, Herston QLD, 4006, Australia
| | | | - Ann C Williams
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
| | - Robert C Block
- Department of Public Health Sciences, University of Rochester, NY, USA
| | - Christopher I Amos
- Dan L Duncan Comprehensive Cancer Center Baylor College of Medicine, USA
| | - Rayjean J Hung
- Lunenfeld-Tanenbaum Research Institute Mount Sinai Hospital and University of Toronto, Canada
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Marc J Gunter
- Section of Nutrition and Metabolism, International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, Lyon, France
| | - George Davey Smith
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Caroline Relton
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Richard M Martin
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, University of Bristol, Bristol, United Kingdom; The National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, Bristol, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
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8
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Howell AE, Relton C, Martin RM, Zheng J, Kurian KM. Role of DNA methylation in the relationship between glioma risk factors and glioma incidence: a two-step Mendelian randomization study. Sci Rep 2023; 13:6590. [PMID: 37085538 PMCID: PMC10121678 DOI: 10.1038/s41598-023-33621-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2022] [Accepted: 04/15/2023] [Indexed: 04/23/2023] Open
Abstract
Genetic evidence suggests glioma risk is altered by leukocyte telomere length, allergic disease (asthma, hay fever or eczema), alcohol consumption, childhood obesity, low-density lipoprotein cholesterol (LDLc) and triglyceride levels. DNA methylation (DNAm) variation influences many of these glioma-related traits and is an established feature of glioma. Yet the causal relationship between DNAm variation with both glioma incidence and glioma risk factors is unknown. We applied a two-step Mendelian randomization (MR) approach and several sensitivity analyses (including colocalization and Steiger filtering) to assess the association of DNAm with glioma risk factors and glioma incidence. We used data from a recently published catalogue of germline genetic variants robustly associated with DNAm variation in blood (32,851 participants) and data from a genome-wide association study of glioma risk (12,488 cases and 18,169 controls, sub-divided into 6191 glioblastoma cases and 6305 non-glioblastoma cases). MR evidence indicated that DNAm at 3 CpG sites (cg01561092, cg05926943, cg01584448) in one genomic region (HEATR3) had a putative association with glioma and glioblastoma risk (False discovery rate [FDR] < 0.05). Steiger filtering provided evidence against reverse causation. Colocalization presented evidence against genetic confounding and suggested that differential DNAm at the 3 CpG sites and glioma were driven by the same genetic variant. MR provided little evidence to suggest that DNAm acts as a mediator on the causal pathway between risk factors previously examined and glioma onset. To our knowledge, this is the first study to use MR to appraise the causal link of DNAm with glioma risk factors and glioma onset. Subsequent analyses are required to improve the robustness of our results and rule out horizontal pleiotropy.
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Affiliation(s)
- Amy E Howell
- Brain Tumour Research Centre, Institute of Clinical Neurosciences, University of Bristol, Bristol, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - Richard M Martin
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol and Weston NHS Foundation Trust and University of Bristol, Bristol, UK
| | - Jie Zheng
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Kathreena M Kurian
- Brain Tumour Research Centre, Institute of Clinical Neurosciences, University of Bristol, Bristol, UK.
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Richenberg G, Gray V, Owen C, Gaunt T, Relton C, Vincent E, Kar S. Abstract 6504: Germline genetically predicted body mass index is associated with endometrial cancer somatic transcriptomic, immune, and mutational signatures in The Cancer Genome Atlas. Cancer Res 2023. [DOI: 10.1158/1538-7445.am2023-6504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/07/2023]
Abstract
Abstract
High body mass index (BMI) is a causal risk factor for endometrial cancer but the molecular mechanisms underlying this association remain elusive. Here we sought to characterize the tumor genomic landscape of endometrial cancers that have developed on a germline genetic background of predisposition to elevated BMI. We built a polygenic score (PGS) for adult BMI in women using effect size estimates and allele information on 242 independent (r2<0.05) variants associated with BMI at genome-wide significance (P<5x10-9) in 379,501 women of European ancestry. We performed sample and germline (blood) genotype quality control and imputation into the 1000 Genomes reference panel on data from 354 endometrial cancer cases of genetically inferred European ancestry from The Cancer Genome Atlas (TCGA). We assigned each woman in this TCGA cohort her genetically predicted life-course BMI based on the BMI PGS and found this to be modestly correlated with BMI at the point of diagnosis (r2=0.23; P=2.1x10-5). Multivariable linear (default) and quasi-Poisson (for zero-inflated counts) regression models were used to test for associations between the BMI germline PGS and endometrial cancer tumor genomic, transcriptomic, proteomic, and immune traits in TCGA. All analyses were adjusted for age, stage, microsatellite status and 10 genetic principal components. Mutational signature models were also adjusted for signature accuracy. We ranked 18,458 genes based on the association between their tumor expression and the BMI PGS and performed gene set enrichment analysis to identify associations between the BMI PGS and upregulation of genes in the IL6-JAK-STAT3 signaling (false discovery rate (FDR)=8.50x10-7), inflammatory response (FDR=7.03x10-6), interferon gamma response (FDR=5.49x10-5) and glycolysis (FDR=3.28x10-4) pathways. High BMI PGS had an inverse association with endometrial tumor EGFR (FDR=0.07) protein levels of the 131 tumor proteins profiled by reverse phase protein array. Endometrial tumors that had developed on a germline background predictive of high BMI were also associated with increased infiltration of activated mast cells (FDR=9.55x10-3) in our evaluation of 22 tumor immune cell infiltrates quantified by the CIBERSORT algorithm, as well as the mitotic and aging clock-like single base substitution (SBS) signatures 1 (FDR=0.01) and 5 (FDR=0.04). The two SBS signature associations and the activated mast cell association with the BMI PGS were substantially more pronounced in the subgroup of endometrial cancers with microsatellite instability. Thus, we combined germline and somatic data using a novel approach to identify endometrial cancer tumor molecular features associated with genetically predicted higher BMI, providing precision multi-omic portraits of endometrial cancers that develop on a background of adiposity.
Citation Format: George Richenberg, Victoria Gray, Carina Owen, Tom Gaunt, Caroline Relton, Emma Vincent, Siddhartha Kar. Germline genetically predicted body mass index is associated with endometrial cancer somatic transcriptomic, immune, and mutational signatures in The Cancer Genome Atlas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6504.
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Affiliation(s)
| | | | - Carina Owen
- 1University of Bristol, Bristol, United Kingdom
| | - Tom Gaunt
- 1University of Bristol, Bristol, United Kingdom
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10
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Kalla R, Adams AT, Nowak JK, Bergemalm D, Vatn S, Ventham NT, Kennedy NA, Ricanek P, Lindstrom J, Söderholm J, Pierik M, D’Amato M, Gomollón F, Olbjørn C, Richmond R, Relton C, Jahnsen J, Vatn MH, Halfvarson J, Satsangi J. Analysis of Systemic Epigenetic Alterations in Inflammatory Bowel Disease: Defining Geographical, Genetic and Immune-Inflammatory influences on the Circulating Methylome. J Crohns Colitis 2023; 17:170-184. [PMID: 36029471 PMCID: PMC10024547 DOI: 10.1093/ecco-jcc/jjac127] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Indexed: 02/08/2023]
Abstract
BACKGROUND Epigenetic alterations may provide valuable insights into gene-environment interactions in the pathogenesis of inflammatory bowel disease [IBD]. METHODS Genome-wide methylation was measured from peripheral blood using the Illumina 450k platform in a case-control study in an inception cohort (295 controls, 154 Crohn's disease [CD], 161 ulcerative colitis [UC], 28 IBD unclassified [IBD-U)] with covariates of age, sex and cell counts, deconvoluted by the Houseman method. Genotyping was performed using Illumina HumanOmniExpressExome-8 BeadChips and gene expression using the Ion AmpliSeq Human Gene Expression Core Panel. Treatment escalation was characterized by the need for biological agents or surgery after initial disease remission. RESULTS A total of 137 differentially methylated positions [DMPs] were identified in IBD, including VMP1/MIR21 [p = 9.11 × 10-15] and RPS6KA2 [6.43 × 10-13], with consistency seen across Scandinavia and the UK. Dysregulated loci demonstrate strong genetic influence, notably VMP1 [p = 1.53 × 10-15]. Age acceleration is seen in IBD [coefficient 0.94, p < 2.2 × 10-16]. Several immuno-active genes demonstrated highly significant correlations between methylation and gene expression in IBD, in particular OSM: IBD r = -0.32, p = 3.64 × 10-7 vs non-IBD r = -0.14, p = 0.77]. Multi-omic integration of the methylome, genome and transcriptome also implicated specific pathways that associate with immune activation, response and regulation at disease inception. At follow-up, a signature of three DMPs [TAP1, TESPA1, RPTOR] were associated with treatment escalation to biological agents or surgery (hazard ratio of 5.19 [CI: 2.14-12.56], logrank p = 9.70 × 10-4). CONCLUSION These data demonstrate consistent epigenetic alterations at diagnosis in European patients with IBD, providing insights into the pathogenetic importance and translational potential of epigenetic mapping in complex disease.
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Affiliation(s)
- Rahul Kalla
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- MRC Centre for Inflammation Research, Queens Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - Alex T Adams
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Translational Gastroenterology Unit, Nuffield Department of Medicine, Experimental Medicine Division, University of Oxford, John Radcliffe Hospital, Oxford, UK
| | - Jan K Nowak
- Department of Paediatric Gastroenterology and Metabolic Diseases, Poznan University of Medical Sciences, Poznan, Poland
| | - Daniel Bergemalm
- Department of Gastroenterology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Simen Vatn
- Department of Gastroenterology, Akershus University Hospital, Lørenskog, Norway
| | - Nicholas T Ventham
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Nicholas A Kennedy
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Exeter IBD and Pharmacogenetics group, University of Exeter, Exeter, UK
| | - Petr Ricanek
- Department of Gastroenterology, Akershus University Hospital, Lørenskog, Norway
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - Jonas Lindstrom
- Health Services Research Unit, Akershus University Hospital, Lørenskog, Norway
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - Johan Söderholm
- Department of Surgery and Clinical and Experimental Medicine, Linköping University, Linköping, Sweden
| | - Marie Pierik
- Maastricht University Medical Centre (MUMC), Department of Gastroenterology and Hepatology, Maastricht, Netherlands
| | - Mauro D’Amato
- CIC bioGUNE – BRTA, Derio, SpainIKERBASQUE, Basque Foundation for Science, Bilbao, Spain
| | | | - Christine Olbjørn
- Department of Gastroenterology, Akershus University Hospital, Lørenskog, Norway
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - Rebecca Richmond
- Medical Research Council Integrative Epidemiology Unit (MRC IEU), School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Caroline Relton
- Medical Research Council Integrative Epidemiology Unit (MRC IEU), School of Social and Community Medicine, University of Bristol, Bristol, UK
| | - Jørgen Jahnsen
- Department of Gastroenterology, Akershus University Hospital, Lørenskog, Norway
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - Morten H Vatn
- Institute of Clinical Medicine, Campus Ahus, University of Oslo, Oslo, Norway
| | - Jonas Halfvarson
- Department of Gastroenterology, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
| | - Jack Satsangi
- Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Translational Gastroenterology Unit, Nuffield Department of Medicine, Experimental Medicine Division, University of Oxford, John Radcliffe Hospital, Oxford, UK
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Waterfield S, Yousefi P, Webster A, Relton C, Thirlwell C, Suderman M. Chromosome 18 Loss of Heterozygosity in Small Intestinal Neuroendocrine Tumours: Multi-Omic and Tumour Composition Analyses. Neuroendocrinology 2023; 113:915-923. [PMID: 36907174 PMCID: PMC10614519 DOI: 10.1159/000530106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Accepted: 03/06/2023] [Indexed: 03/12/2023]
Abstract
INTRODUCTION Small intestinal neuroendocrine tumours (siNETs) are rare neoplasms which present with low mutational burden and can be subtyped based on copy number variation (CNV). Currently, siNETs can be molecularly classified as having chromosome 18 loss of heterozygosity (18LOH), multiple CNVs (MultiCNV), or no CNVs. 18LOH tumours have better progression-free survival when compared to MultiCNV and NoCNV tumours, however, the mechanism underlying this is unknown, and clinical practice does not currently consider CNV status. METHODS Here, we use genome-wide tumour DNA methylation (n = 54) and gene expression (n = 20 matched to DNA methylation) to better understand how gene regulation varies by 18LOH status. We then use multiple cell deconvolution methods to analyse how cell composition varies between 18LOH status and determine potential associations with progression-free survival. RESULTS We identified 27,464 differentially methylated CpG sites and 12 differentially expressed genes between 18LOH and non-18LOH (MultiCNV + NoCNV) siNETs. Although few differentially expressed genes were identified, these genes were highly enriched with the differentially methylated CpG sites compared to the rest of the genome. We identified differences in tumour microenvironment between 18LOH and non-18LOH tumours, including CD14+ infiltration in a subset of non-18LOH tumours which had the poorest clinical outcomes. CONCLUSIONS We identify a small number of genes which appear to be linked to the 18LOH status of siNETs, and find evidence of potential epigenetic dysregulation of these genes. We also find a potential prognostic marker for worse progression-free outcomes in the form of higher CD14 infiltration in non-18LOH siNETs.
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Affiliation(s)
- Scott Waterfield
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Cancer Research UK Integrative Cancer Epidemiology Programme, University of Bristol, Bristol, UK
| | - Paul Yousefi
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Amy Webster
- University of Exeter Medical School, Exeter, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Chrissie Thirlwell
- University of Exeter Medical School, Exeter, UK
- UCL Cancer Institute, London, UK
| | - Matt Suderman
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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Watkins SH, Ho K, Testa C, Falk L, Soule P, Nguyen LV, FitzGibbon S, Slack C, Chen JT, Davey Smith G, De Vivo I, Simpkin AJ, Tilling K, Waterman PD, Krieger N, Suderman M, Relton C. The impact of low input DNA on the reliability of DNA methylation as measured by the Illumina Infinium MethylationEPIC BeadChip. Epigenetics 2022; 17:2366-2376. [PMID: 36239035 DOI: 10.1080/15592294.2022.2123898] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022] Open
Abstract
DNA methylation (DNAm) is commonly assayed using the Illumina Infinium MethylationEPIC BeadChip, but there is currently little published evidence to define the lower limits of the amount of DNA that can be used whilst preserving data quality. Such evidence is valuable for analyses utilizing precious or limited DNA sources. We used a single pooled sample of DNA in quadruplicate at three dilutions to define replicability and noise, and an independent population dataset of 328 individuals (from a community-based study including US-born non-Hispanic Black and white persons) to assess the impact of total DNA input on the quality of data generated using the Illumina Infinium MethylationEPIC BeadChip. We found that data are less reliable and more noisy as DNA input decreases to 40ng, with clear reductions in data quality; and that low DNA input is associated with a reduction in power to detect EWAS associations, requiring larger sample sizes. We conclude that DNA input as low as 40ng can be used with the Illumina Infinium MethylationEPIC BeadChip, provided quality checks and sensitivity analyses are undertaken.
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Affiliation(s)
- Sarah Holmes Watkins
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Karen Ho
- Bristol Bioresource Laboratories, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Christian Testa
- Department of Social and Behavioral Sciences, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Louise Falk
- Integrative Cancer Epidemiology Programme (ICEP), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Patrice Soule
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Linda V Nguyen
- Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Sophie FitzGibbon
- Bristol Bioresource Laboratories, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Catherine Slack
- Bristol Bioresource Laboratories, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jarvis T Chen
- Department of Social and Behavioral Sciences, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Immaculata De Vivo
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.,Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrew J Simpkin
- School of Medicine, National University of Ireland Galway, Galway, Ireland
| | - Kate Tilling
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Pamela D Waterman
- Department of Social and Behavioral Sciences, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Nancy Krieger
- Department of Social and Behavioral Sciences, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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Woodhouse MJ, Aspinall WP, Sparks RSJ, Brooks-Pollock E, Relton C. Alternative COVID-19 mitigation measures in school classrooms: analysis using an agent-based model of SARS-CoV-2 transmission. R Soc Open Sci 2022; 9:211985. [PMID: 35958084 PMCID: PMC9363991 DOI: 10.1098/rsos.211985] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/25/2022] [Accepted: 07/20/2022] [Indexed: 06/15/2023]
Abstract
The SARS-CoV-2 epidemic has impacted children's education, with schools required to implement infection control measures that have led to periods of absence and classroom closures. We developed an agent-based epidemiological model of SARS-CoV-2 transmission in a school classroom that allows us to quantify projected infection patterns within primary school classrooms, and related uncertainties. Our approach is based on a contact model constructed using random networks, informed by structured expert judgement. The effectiveness of mitigation strategies in suppressing infection outbreaks and limiting pupil absence are considered. COVID-19 infections in primary schools in England in autumn 2020 were re-examined and the model was then used to estimate infection levels in autumn 2021, as the Delta variant was emerging and it was thought likely that school transmission would play a major role in an incipient new wave of the epidemic. Our results were in good agreement with available data. These findings indicate that testing-based surveillance is more effective than bubble quarantine, both for reducing transmission and avoiding pupil absence, even accounting for insensitivity of self-administered tests. Bubble quarantine entails large numbers of absences, with only modest impact on classroom infections. However, maintaining reduced contact rates within the classroom can have a major benefit for managing COVID-19 in school settings.
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Affiliation(s)
- M. J. Woodhouse
- School of Earth Sciences, University of Bristol, Wills Memorial Building, Queens Road, Bristol BS8 1RJ, UK
| | - W. P. Aspinall
- School of Earth Sciences, University of Bristol, Wills Memorial Building, Queens Road, Bristol BS8 1RJ, UK
- Aspinall and Associates, Tisbury SP3 6HF, UK
| | - R. S. J. Sparks
- School of Earth Sciences, University of Bristol, Wills Memorial Building, Queens Road, Bristol BS8 1RJ, UK
| | - E. Brooks-Pollock
- Bristol Veterinary School, University of Bristol, Churchill Building, Langford, Bristol BS40 5DU, UK
| | - C. Relton
- Bristol Medical School (PHS), University of Bristol, Oakfield House, Oakfield Grove, Clifton, Bristol BS8 2BN, UK
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14
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Wielscher M, Mandaviya PR, Kuehnel B, Joehanes R, Mustafa R, Robinson O, Zhang Y, Bodinier B, Walton E, Mishra PP, Schlosser P, Wilson R, Tsai PC, Palaniswamy S, Marioni RE, Fiorito G, Cugliari G, Karhunen V, Ghanbari M, Psaty BM, Loh M, Bis JC, Lehne B, Sotoodehnia N, Deary IJ, Chadeau-Hyam M, Brody JA, Cardona A, Selvin E, Smith AK, Miller AH, Torres MA, Marouli E, Gào X, van Meurs JBJ, Graf-Schindler J, Rathmann W, Koenig W, Peters A, Weninger W, Farlik M, Zhang T, Chen W, Xia Y, Teumer A, Nauck M, Grabe HJ, Doerr M, Lehtimäki T, Guan W, Milani L, Tanaka T, Fisher K, Waite LL, Kasela S, Vineis P, Verweij N, van der Harst P, Iacoviello L, Sacerdote C, Panico S, Krogh V, Tumino R, Tzala E, Matullo G, Hurme MA, Raitakari OT, Colicino E, Baccarelli AA, Kähönen M, Herzig KH, Li S, Conneely KN, Kooner JS, Köttgen A, Heijmans BT, Deloukas P, Relton C, Ong KK, Bell JT, Boerwinkle E, Elliott P, Brenner H, Beekman M, Levy D, Waldenberger M, Chambers JC, Dehghan A, Järvelin MR. DNA methylation signature of chronic low-grade inflammation and its role in cardio-respiratory diseases. Nat Commun 2022; 13:2408. [PMID: 35504910 PMCID: PMC9065016 DOI: 10.1038/s41467-022-29792-6] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2021] [Accepted: 03/31/2022] [Indexed: 02/02/2023] Open
Abstract
We performed a multi-ethnic Epigenome Wide Association study on 22,774 individuals to describe the DNA methylation signature of chronic low-grade inflammation as measured by C-Reactive protein (CRP). We find 1,511 independent differentially methylated loci associated with CRP. These CpG sites show correlation structures across chromosomes, and are primarily situated in euchromatin, depleted in CpG islands. These genomic loci are predominantly situated in transcription factor binding sites and genomic enhancer regions. Mendelian randomization analysis suggests altered CpG methylation is a consequence of increased blood CRP levels. Mediation analysis reveals obesity and smoking as important underlying driving factors for changed CpG methylation. Finally, we find that an activated CpG signature significantly increases the risk for cardiometabolic diseases and COPD.
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Affiliation(s)
- Matthias Wielscher
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
- Department of Dermatology, Medical University of Vienna, Vienna, Austria.
| | - Pooja R Mandaviya
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
- Maastricht Centre for Systems Biology (MaCSBio), Maastricht University, Maastricht, The Netherlands
| | - Brigitte Kuehnel
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
| | - Roby Joehanes
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Rima Mustafa
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Oliver Robinson
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Yan Zhang
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Barbara Bodinier
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Esther Walton
- Department of Psychology, University of Bath, Bath, UK
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
| | - Pashupati P Mishra
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Pascal Schlosser
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
| | - Rory Wilson
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Biomedical Sciences, Chang Gung University, Taoyuan City, Taiwan
| | - Saranya Palaniswamy
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Pentti Kaiteran katu 1, Linnanmaa, Oulu, Finland
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Giovanni Fiorito
- Laboratory of Biostatistics, Department of Biomedical Sciences, University of Sassari, Sassari, Italy
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | | | - Ville Karhunen
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, The Netherlands
- Department of Genetics, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Bruce M Psaty
- Cardiovacular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Department of Health Services, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Marie Loh
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Mandalay Road, Singapore, Singapore
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Benjamin Lehne
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Marc Chadeau-Hyam
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - Alexia Cardona
- MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Elizabeth Selvin
- Dept. of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Alicia K Smith
- Departments of Gynecology and Obstetrics & Psychiatry and Behavioral Science, Emory University School of Medicine, Atlanta, GA, USA
| | - Andrew H Miller
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia
| | - Mylin A Torres
- Department of Radiation Oncology, Winship Cancer Institute, Emory University School of Medicine, Atlanta, GA, USA
| | - Eirini Marouli
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Xin Gào
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Johanna Graf-Schindler
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
| | - Wolfgang Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Resesarch at Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Wolfgang Koenig
- Deutsches Herzzentrum München, Technische Universität München, Munich, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, Ulm, Germany
| | - Annette Peters
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Wolfgang Weninger
- Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | - Matthias Farlik
- Department of Dermatology, Medical University of Vienna, Vienna, Austria
| | - Tao Zhang
- Deptarment of Biostatistics, School of Public Health, Shandong University, Jinan, China
| | - Wei Chen
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Yujing Xia
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
| | - Matthias Nauck
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Macus Doerr
- DZHK (German Center for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere, Finland
| | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Lili Milani
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Toshiko Tanaka
- Translational Gerontology Branch, Biomedical Research Center, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Krista Fisher
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
- Institute of Mathematics and Statistics, University of Tartu, Tartu, Estonia
| | - Lindsay L Waite
- HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA
| | - Silva Kasela
- Estonian Genome Centre, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Paolo Vineis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Hanzeplein 1, Groningen, The Netherlands
| | - Pim van der Harst
- Department of Cardiology, Division of Heart and Lungs, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Licia Iacoviello
- Department of Epidemiology and Prevention, IRCCS NEUROMED, Pozzilli, IS, Italy
- Department of Medicine and Surgery, Research Center in Epidemiology and Preventive Medicine (EPIMED), University of Insubria, Varese-Como, Italy
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Citta' della Salute e della Scienza Hospital and Centre for Cancer Prevention, Turin, Italy
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia Federico II University, Naples, Italy
| | - Vittorio Krogh
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, "Civic - MPP Arezzo" Hospital, ASP Ragusa, Ragusa, Italy
| | - Evangelia Tzala
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Giuseppe Matullo
- Department of Medical Sciences, University of Turin, Turin, Italy
- AOU Città della Salute e della Scienza di Torino, Torino, Italy
| | - Mikko A Hurme
- Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Olli T Raitakari
- Research centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
| | - Elena Colicino
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Andrea A Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences and Epidemiology, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Mika Kähönen
- Finnish Cardiovascular Research Centre, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
| | - Karl-Heinz Herzig
- Research Unit of Biomedicine, Medical Research Center, Faculty of Medicine, University of Oulu, and Oulu University Hospital, Oulu, Finland
- Department of Gastroenterology and Metabolism, Institute of Pediatrics, Poznan University of Medical Sciences, Poznan, Poland
| | - Shengxu Li
- Children's Minnesota Research Institute, Children's Minnesota, Minneapolis, MN, USA
| | | | - Karen N Conneely
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Jaspal S Kooner
- National Heart and Lung Institute, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK
| | - Anna Köttgen
- Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany
- Dept. of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Bastiaan T Heijmans
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
| | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Caroline Relton
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ken K Ong
- MRC Epidemiology Unit, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, Houston, TX, USA
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- Imperial Biomedical Research Centre, Imperial College London, London, UK
- British Heart Foundation, BHF, Centre for Research Excellence, Imperial College London, London, UK
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
- Network Aging Research, Heidelberg University, Heidelberg, Germany
| | - Marian Beekman
- Department of Medical Statistics and Bioinformatics, Leiden University Medical Center, Leiden, The Netherlands
| | - Daniel Levy
- Framingham Heart Study, Framingham, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD, USA
| | - Melanie Waldenberger
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Bavaria, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - John C Chambers
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Mandalay Road, Singapore, Singapore
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, UK
- UK Dementia Research Institute at Imperial College London, London, UK
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK.
- Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Pentti Kaiteran katu 1, Linnanmaa, Oulu, Finland.
- Unit of Primary Care, Oulu University Hospital, Oulu, Finland.
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK.
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15
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Barbu MC, Amador C, Kwong ASF, Shen X, Adams MJ, Howard DM, Walker RM, Morris SW, Min JL, Liu C, van Dongen J, Ghanbari M, Relton C, Porteous DJ, Campbell A, Evans KL, Whalley HC, McIntosh AM. Complex trait methylation scores in the prediction of major depressive disorder. EBioMedicine 2022; 79:104000. [PMID: 35490552 PMCID: PMC9062752 DOI: 10.1016/j.ebiom.2022.104000] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Revised: 03/28/2022] [Accepted: 03/29/2022] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND DNA methylation (DNAm) is associated with time-varying environmental factors that contribute to major depressive disorder (MDD) risk. We sought to test whether DNAm signatures of lifestyle and biochemical factors were associated with MDD to reveal dynamic biomarkers of MDD risk that may be amenable to lifestyle interventions. METHODS Here, we calculated methylation scores (MS) at multiple p-value thresholds for lifestyle (BMI, smoking, alcohol consumption, and educational attainment) and biochemical (high-density lipoprotein (HDL) and total cholesterol) factors in Generation Scotland (GS) (N=9,502) and in a replication cohort (ALSPACadults, N=565), using CpG sites reported in previous well-powered methylome-wide association studies. We also compared their predictive accuracy for MDD to a MDD MS in an independent GS sub-sample (N=4,432). FINDINGS Each trait MS was significantly associated with its corresponding phenotype in GS (βrange=0.089-1.457) and in ALSPAC (βrange=0.078-2.533). Each MS was also significantly associated with MDD before and after adjustment for its corresponding phenotype in GS (βrange=0.053-0.145). After accounting for relevant lifestyle factors, MS for educational attainment (β=0.094) and alcohol consumption (MSp-value<0.01-0.5; βrange=-0.069-0.083) remained significantly associated with MDD in GS. Smoking (AUC=0.569) and educational attainment (AUC=0.585) MSs could discriminate MDD from controls better than the MDD MS (AUC=0.553) in the independent GS sub-sample. Analyses implicating MDD did not replicate across ALSPAC, although the direction of effect was consistent for all traits when adjusting for the MS corresponding phenotypes. INTERPRETATION We showed that lifestyle and biochemical MS were associated with MDD before and after adjustment for their corresponding phenotypes (pnominal<0.05), but not when smoking, alcohol consumption, and BMI were also included as covariates. MDD results did not replicate in the smaller, female-only independent ALSPAC cohort (NALSPAC=565; NGS=9,502), potentially due to demographic differences or low statistical power, but effect sizes were consistent with the direction reported in GS. DNAm scores for modifiable MDD risk factors may contribute to disease vulnerability and, in some cases, explain additional variance to their observed phenotypes. FUNDING Wellcome Trust.
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Affiliation(s)
- Miruna C Barbu
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, United Kingdom.
| | - Carmen Amador
- MRC Human Genetics Unit, The Institute of Genetics and Cancer, The University of Edinburgh, United Kingdom
| | - Alex S F Kwong
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, United Kingdom
| | - Xueyi Shen
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, United Kingdom
| | - Mark J Adams
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, United Kingdom
| | - David M Howard
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, United Kingdom; Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, United Kingdom
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, United Kingdom
| | - Stewart W Morris
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, United Kingdom
| | - Josine L Min
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, United Kingdom
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- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA; The Framingham Heart Study, Framingham, MA, USA
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, the Netherlands
| | - Caroline Relton
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, United Kingdom
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, United Kingdom
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, The Institute of Genetics and Cancer, The University of Edinburgh, United Kingdom
| | - Heather C Whalley
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, United Kingdom
| | - Andrew M McIntosh
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh EH10 5HF, United Kingdom
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16
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Lozano M, Yousefi P, Broberg K, Soler-Blasco R, Miyashita C, Pesce G, Kim WJ, Rahman M, Bakulski KM, Haug LS, Ikeda-Araki A, Huel G, Park J, Relton C, Vrijheid M, Rifas-Shiman S, Oken E, Dou JF, Kishi R, Gutzkow KB, Annesi-Maesano I, Won S, Hivert MF, Fallin MD, Vafeiadi M, Ballester F, Bustamante M, Llop S. DNA methylation changes associated with prenatal mercury exposure: A meta-analysis of prospective cohort studies from PACE consortium. Environ Res 2022; 204:112093. [PMID: 34562483 PMCID: PMC10879652 DOI: 10.1016/j.envres.2021.112093] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 09/17/2021] [Accepted: 09/18/2021] [Indexed: 06/13/2023]
Abstract
Mercury (Hg) is a ubiquitous heavy metal that originates from both natural and anthropogenic sources and is transformed in the environment to its most toxicant form, methylmercury (MeHg). Recent studies suggest that MeHg exposure can alter epigenetic modifications during embryogenesis. In this study, we examined associations between prenatal MeHg exposure and levels of cord blood DNA methylation (DNAm) by meta-analysis in up to seven independent studies (n = 1462) as well as persistence of those relationships in blood from 7 to 8 year-old children (n = 794). In cord blood, we found limited evidence of differential DNAm at cg24184221 in MED31 (β = 2.28 × 10-4, p-value = 5.87 × 10-5) in relation to prenatal MeHg exposure. In child blood, we identified differential DNAm at cg15288800 (β = 0.004, p-value = 4.97 × 10-5), also located in MED31. This repeated link to MED31, a gene involved in lipid metabolism and RNA Polymerase II transcription function, may suggest a DNAm perturbation related to MeHg exposure that persists into early childhood. Further, we found evidence for association between prenatal MeHg exposure and child blood DNAm levels at two additional CpGs: cg12204245 (β = 0.002, p-value = 4.81 × 10-7) in GRK1 and cg02212000 (β = -0.001, p-value = 8.13 × 10-7) in GGH. Prenatal MeHg exposure was associated with DNAm modifications that may influence health outcomes, such as cognitive or anthropometric development, in different populations.
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Affiliation(s)
- Manuel Lozano
- Preventive Medicine and Public Health, Food Sciences, Toxicology and Forensic Medicine Department, Universitat de València, Valencia, Spain; Epidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain.
| | - Paul Yousefi
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Karin Broberg
- Unit of Metals and Health, Institute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden; Division of Occupational and Environmental Medicine, Lund University, Lund, Sweden
| | - Raquel Soler-Blasco
- Epidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain
| | - Chihiro Miyashita
- Center for Environmental and Health Sciences, Hokkaido University, Hokkaido, Japan
| | - Giancarlo Pesce
- INSERM UMR1018, Université Paris-Saclay, UVSQ, Centre for Epidemiology and Public Health (CESP), Villejuif, France
| | - Woo Jin Kim
- Department of Internal Medicine and Environmental Health Center, Kangwon National University, Chuncheon, South Korea
| | - Mohammad Rahman
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | - Kelly M Bakulski
- School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Line S Haug
- Norwegian Institute of Public Health, Division of Climate and Environment, Oslo, Norway
| | - Atsuko Ikeda-Araki
- Center for Environmental and Health Sciences, Hokkaido University, Hokkaido, Japan; Faculty of Health Sciences, Hokkaido University, Hokkaido, Japan
| | - Guy Huel
- INSERM UMR1018, Université Paris-Saclay, UVSQ, Centre for Epidemiology and Public Health (CESP), Villejuif, France
| | - Jaehyun Park
- Interdisciplinary Program of Bioinformatics, College of Natural Sciences, Seoul National University, Seoul, South Korea
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Martine Vrijheid
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain; ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra, Barcelona, Spain
| | - Sheryl Rifas-Shiman
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | - Emily Oken
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, United States
| | - John F Dou
- School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Reiko Kishi
- Center for Environmental and Health Sciences, Hokkaido University, Hokkaido, Japan
| | - Kristine B Gutzkow
- Norwegian Institute of Public Health, Division of Climate and Environment, Oslo, Norway
| | - Isabella Annesi-Maesano
- INSERM UMR1302, Montpellier University, Insitut Desbrest d'Épidémiologie et de Santé Publique (IDESP), Montpellier, France
| | - Sungho Won
- Interdisciplinary Program of Bioinformatics, College of Natural Sciences, Seoul National University, Seoul, South Korea; Department of Public Health Sciences, Seoul National University, Seoul, South Korea
| | - Marie-France Hivert
- Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, United States; Diabetes Unit, Massachusetts General Hospital, Boston, MA, United States
| | - M Daniele Fallin
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Marina Vafeiadi
- Department of Social Medicine, School of Medicine, University of Crete, Heraklion, Greece
| | - Ferran Ballester
- Epidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain; School of Nursing, Universitat de València, Valencia, Spain
| | - Mariona Bustamante
- Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain; ISGlobal, Barcelona, Spain; Universitat Pompeu Fabra, Barcelona, Spain
| | - Sabrina Llop
- Epidemiology and Environmental Health Joint Research Unit, FISABIO-Universitat Jaume I-Universitat de València, Valencia, Spain; Spanish Consortium for Research on Epidemiology and Public Health (CIBERESP), Madrid, Spain
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17
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Corbin LJ, White SJ, Taylor AE, Williams CM, Taylor K, van den Bosch MT, Teasdale JE, Jones M, Bond M, Harper MT, Falk L, Groom A, Hazell GG, Paternoster L, Munafò MR, Nordestgaard BG, Tybjærg-Hansen A, Bojesen SE, Relton C, Min JL, Davey Smith G, Mumford AD, Poole AW, Timpson NJ. Epigenetic Regulation of F2RL3 Associates With Myocardial Infarction and Platelet Function. Circ Res 2022; 130:384-400. [PMID: 35012325 PMCID: PMC8812435 DOI: 10.1161/circresaha.121.318836] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Revised: 12/30/2021] [Accepted: 01/04/2022] [Indexed: 11/24/2022]
Abstract
BACKGROUND DNA hypomethylation at the F2RL3 (F2R like thrombin or trypsin receptor 3) locus has been associated with both smoking and atherosclerotic cardiovascular disease; whether these smoking-related associations form a pathway to disease is unknown. F2RL3 encodes protease-activated receptor 4, a potent thrombin receptor expressed on platelets. Given the role of thrombin in platelet activation and the role of thrombus formation in myocardial infarction, alterations to this biological pathway could be important for ischemic cardiovascular disease. METHODS We conducted multiple independent experiments to assess whether DNA hypomethylation at F2RL3 in response to smoking is associated with risk of myocardial infarction via changes to platelet reactivity. Using cohort data (N=3205), we explored the relationship between smoking, DNA hypomethylation at F2RL3, and myocardial infarction. We compared platelet reactivity in individuals with low versus high DNA methylation at F2RL3 (N=41). We used an in vitro model to explore the biological response of F2RL3 to cigarette smoke extract. Finally, a series of reporter constructs were used to investigate how differential methylation could impact F2RL3 gene expression. RESULTS Observationally, DNA methylation at F2RL3 mediated an estimated 34% of the smoking effect on increased risk of myocardial infarction. An association between methylation group (low/high) and platelet reactivity was observed in response to PAR4 (protease-activated receptor 4) stimulation. In cells, cigarette smoke extract exposure was associated with a 4.9% to 9.3% reduction in DNA methylation at F2RL3 and a corresponding 1.7-(95% CI, 1.2-2.4, P=0.04) fold increase in F2RL3 mRNA. Results from reporter assays suggest the exon 2 region of F2RL3 may help control gene expression. CONCLUSIONS Smoking-induced epigenetic DNA hypomethylation at F2RL3 appears to increase PAR4 expression with potential downstream consequences for platelet reactivity. Combined evidence here not only identifies F2RL3 DNA methylation as a possible contributory pathway from smoking to cardiovascular disease risk but from any feature potentially influencing F2RL3 regulation in a similar manner.
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Affiliation(s)
- Laura J. Corbin
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| | - Stephen J. White
- Department of Life Sciences, Manchester Metropolitan University, United Kingdom (S.J.W.)
| | - Amy E. Taylor
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, United Kingdom (A.E.T.)
| | - Christopher M. Williams
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
- School of Physiology, Pharmacology and Neuroscience (C.M.W., M.T.v.d.B., A.W.P.), University of Bristol, United Kingdom
| | - Kurt Taylor
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
- School of Physiology, Pharmacology and Neuroscience (C.M.W., M.T.v.d.B., A.W.P.), University of Bristol, United Kingdom
- Translational Health Sciences, Bristol Medical School (J.E.T., M.J., M.B.), University of Bristol, United Kingdom
- UK Centre for Tobacco and Alcohol Studies and School of Experimental Psychology (M.R.M.), University of Bristol, United Kingdom
- School of Cellular and Molecular Medicine (A.D.M.), University of Bristol, United Kingdom
- Department of Life Sciences, Manchester Metropolitan University, United Kingdom (S.J.W.)
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, United Kingdom (A.E.T.)
- Department of Pharmacology, University of Cambridge, Tennis Court Road (M.T.H., G.G.J.H.)
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital (B.G.N., S.E.B.), Copenhagen University Hospital, Denmark
- The Copenhagen City Heart Study, Frederiksberg Hospital (B.G.N., A.T.-H., S.E.B.), Copenhagen University Hospital, Denmark
- Department of Clinical Biochemistry, Rigshospitalet (A.T.-H.), Copenhagen University Hospital, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Denmark (B.G.N., A.T.-H., S.E.B.)
| | - Marion T. van den Bosch
- School of Physiology, Pharmacology and Neuroscience (C.M.W., M.T.v.d.B., A.W.P.), University of Bristol, United Kingdom
| | - Jack E. Teasdale
- Translational Health Sciences, Bristol Medical School (J.E.T., M.J., M.B.), University of Bristol, United Kingdom
| | - Matthew Jones
- Translational Health Sciences, Bristol Medical School (J.E.T., M.J., M.B.), University of Bristol, United Kingdom
| | - Mark Bond
- Translational Health Sciences, Bristol Medical School (J.E.T., M.J., M.B.), University of Bristol, United Kingdom
| | - Matthew T. Harper
- Department of Pharmacology, University of Cambridge, Tennis Court Road (M.T.H., G.G.J.H.)
| | - Louise Falk
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| | - Alix Groom
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| | - Georgina G.J. Hazell
- Department of Pharmacology, University of Cambridge, Tennis Court Road (M.T.H., G.G.J.H.)
| | - Lavinia Paternoster
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| | - Marcus R. Munafò
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- UK Centre for Tobacco and Alcohol Studies and School of Experimental Psychology (M.R.M.), University of Bristol, United Kingdom
| | - Børge G. Nordestgaard
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital (B.G.N., S.E.B.), Copenhagen University Hospital, Denmark
- The Copenhagen City Heart Study, Frederiksberg Hospital (B.G.N., A.T.-H., S.E.B.), Copenhagen University Hospital, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Denmark (B.G.N., A.T.-H., S.E.B.)
| | - Anne Tybjærg-Hansen
- The Copenhagen City Heart Study, Frederiksberg Hospital (B.G.N., A.T.-H., S.E.B.), Copenhagen University Hospital, Denmark
- Department of Clinical Biochemistry, Rigshospitalet (A.T.-H.), Copenhagen University Hospital, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Denmark (B.G.N., A.T.-H., S.E.B.)
| | - Stig E. Bojesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital (B.G.N., S.E.B.), Copenhagen University Hospital, Denmark
- The Copenhagen City Heart Study, Frederiksberg Hospital (B.G.N., A.T.-H., S.E.B.), Copenhagen University Hospital, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Denmark (B.G.N., A.T.-H., S.E.B.)
| | - Caroline Relton
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| | - Josine L. Min
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
| | - Andrew D. Mumford
- School of Cellular and Molecular Medicine (A.D.M.), University of Bristol, United Kingdom
| | - Alastair W. Poole
- School of Physiology, Pharmacology and Neuroscience (C.M.W., M.T.v.d.B., A.W.P.), University of Bristol, United Kingdom
| | - Nicholas J. Timpson
- MRC Integrative Epidemiology Unit at University of Bristol, United Kingdom (L.J.C., L.F., A.G., L.P., M.R.M., C.R., J.L.M., G.D.S., N.J.T.)
- Population Health Sciences, Bristol Medical School (L.J.C., A.E.T., K.T., L.F., A.G., L.P., C.R., J.L.M., G.D.S., N.J.T.), University of Bristol, United Kingdom
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18
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Beynon RA, Ingle SM, Langdon R, May M, Ness A, Martin RM, Suderman M, Ingarfield K, Marioni RE, McCartney DL, Waterboer T, Pawlita M, Relton C, Smith GD, Richmond RC. Epigenetic biomarkers of ageing are predictive of mortality risk in a longitudinal clinical cohort of individuals diagnosed with oropharyngeal cancer. Clin Epigenetics 2022; 14:1. [PMID: 34980250 PMCID: PMC8725548 DOI: 10.1186/s13148-021-01220-4] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Accepted: 12/14/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Epigenetic clocks are biomarkers of ageing derived from DNA methylation levels at a subset of CpG sites. The difference between age predicted by these clocks and chronological age, termed "epigenetic age acceleration", has been shown to predict age-related disease and mortality. We aimed to assess the prognostic value of epigenetic age acceleration and a DNA methylation-based mortality risk score with all-cause mortality in a prospective clinical cohort of individuals with head and neck cancer: Head and Neck 5000. We investigated two markers of intrinsic epigenetic age acceleration (IEAAHorvath and IEAAHannum), one marker of extrinsic epigenetic age acceleration (EEAA), one optimised to predict physiological dysregulation (AgeAccelPheno), one optimised to predict lifespan (AgeAccelGrim) and a DNA methylation-based predictor of mortality (ZhangScore). Cox regression models were first used to estimate adjusted hazard ratios (HR) and 95% confidence intervals (CI) for associations of epigenetic age acceleration with all-cause mortality in people with oropharyngeal cancer (n = 408; 105 deaths). The added prognostic value of epigenetic markers compared to a clinical model including age, sex, TNM stage and HPV status was then evaluated. RESULTS IEAAHannum and AgeAccelGrim were associated with mortality risk after adjustment for clinical and lifestyle factors (HRs per standard deviation [SD] increase in age acceleration = 1.30 [95% CI 1.07, 1.57; p = 0.007] and 1.40 [95% CI 1.06, 1.83; p = 0.016], respectively). There was weak evidence that the addition of AgeAccelGrim to the clinical model improved 3-year mortality prediction (area under the receiver operating characteristic curve: 0.80 vs. 0.77; p value for difference = 0.069). CONCLUSION In the setting of a large, clinical cohort of individuals with head and neck cancer, our study demonstrates the potential of epigenetic markers of ageing to enhance survival prediction in people with oropharyngeal cancer, beyond established prognostic factors. Our findings have potential uses in both clinical and non-clinical contexts: to aid treatment planning and improve patient stratification.
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Affiliation(s)
- Rhona A Beynon
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Suzanne M Ingle
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ryan Langdon
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Margaret May
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Andy Ness
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
| | - Richard M Martin
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kate Ingarfield
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
- Centre for Trials Research, Neuadd Meirionnydd, Heath Park Way, Cardiff, UK
- Community Oral Health, University of Glasgow Dental School, Sauchiehall Street, Glasgow, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Tim Waterboer
- Infections and Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael Pawlita
- Infections and Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Bristol, BS8 2BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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19
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Solomon O, Huen K, Yousefi P, Küpers LK, González JR, Suderman M, Reese SE, Page CM, Gruzieva O, Rzehak P, Gao L, Bakulski KM, Novoloaca A, Allard C, Pappa I, Llambrich M, Vives M, Jima DD, Kvist T, Baccarelli A, White C, Rezwan FI, Sharp GC, Tindula G, Bergström A, Grote V, Dou JF, Isaevska E, Magnus MC, Corpeleijn E, Perron P, Jaddoe VWV, Nohr EA, Maitre L, Foraster M, Hoyo C, Håberg SE, Lahti J, DeMeo DL, Zhang H, Karmaus W, Kull I, Koletzko B, Feinberg JI, Gagliardi L, Bouchard L, Ramlau-Hansen CH, Tiemeier H, Santorelli G, Maguire RL, Czamara D, Litonjua AA, Langhendries JP, Plusquin M, Lepeule J, Binder EB, Verduci E, Dwyer T, Carracedo Á, Ferre N, Eskenazi B, Kogevinas M, Nawrot TS, Munthe-Kaas MC, Herceg Z, Relton C, Melén E, Gruszfeld D, Breton C, Fallin MD, Ghantous A, Nystad W, Heude B, Snieder H, Hivert MF, Felix JF, Sørensen TIA, Bustamante M, Murphy SK, Raikkönen K, Oken E, Holloway JW, Arshad SH, London SJ, Holland N. Meta-analysis of epigenome-wide association studies in newborns and children show widespread sex differences in blood DNA methylation. Mutat Res Rev Mutat Res 2022; 789:108415. [PMID: 35690418 PMCID: PMC9623595 DOI: 10.1016/j.mrrev.2022.108415] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2021] [Revised: 02/27/2022] [Accepted: 03/08/2022] [Indexed: 11/26/2022]
Abstract
BACKGROUND Among children, sex-specific differences in disease prevalence, age of onset, and susceptibility have been observed in health conditions including asthma, immune response, metabolic health, some pediatric and adult cancers, and psychiatric disorders. Epigenetic modifications such as DNA methylation may play a role in the sexual differences observed in diseases and other physiological traits. METHODS We performed a meta-analysis of the association of sex and cord blood DNA methylation at over 450,000 CpG sites in 8438 newborns from 17 cohorts participating in the Pregnancy And Childhood Epigenetics (PACE) Consortium. We also examined associations of child sex with DNA methylation in older children ages 5.5-10 years from 8 cohorts (n = 4268). RESULTS In newborn blood, sex was associated at Bonferroni level significance with differences in DNA methylation at 46,979 autosomal CpG sites (p < 1.3 × 10-7) after adjusting for white blood cell proportions and batch. Most of those sites had lower methylation levels in males than in females. Of the differentially methylated CpG sites identified in newborn blood, 68% (31,727) met look-up level significance (p < 1.1 × 10-6) in older children and had methylation differences in the same direction. CONCLUSIONS This is a large-scale meta-analysis examining sex differences in DNA methylation in newborns and older children. Expanding upon previous studies, we replicated previous findings and identified additional autosomal sites with sex-specific differences in DNA methylation. Differentially methylated sites were enriched in genes involved in cancer, psychiatric disorders, and cardiovascular phenotypes.
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Affiliation(s)
- Olivia Solomon
- Children's Environmental Health Laboratory, Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Karen Huen
- Children's Environmental Health Laboratory, Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA.
| | - Paul Yousefi
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN, UK
| | - Leanne K Küpers
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
| | - Juan R González
- ISGlobal, Barcelona Institute for Global Health, Dr Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN, UK
| | - Sarah E Reese
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, Norway
| | - Olena Gruzieva
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Center for Occupational and Environmental Medicine, Region Stockholm, Sweden
| | - Peter Rzehak
- Div. Metabolic and Nutritional Medicine, Dept. Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Lu Gao
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA
| | - Kelly M Bakulski
- School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | | | - Catherine Allard
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, QC, Canada
| | - Irene Pappa
- Department of Child and Adolescent Psychiatry/ Psychology, Erasmus Medical Center, Sophia Children's Hospital, P.O. Box 2060, 3000 CB Rotterdam, The Netherlands; The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2060, 3000 CB Rotterdam, The Netherlands
| | - Maria Llambrich
- ISGlobal, Barcelona Institute for Global Health, Dr Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Marta Vives
- ISGlobal, Barcelona Institute for Global Health, Dr Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; Centre for Genomic Regulation (CRG), The Barcelona Institute of Science and Technology, Dr. Aiguader 88, Barcelona 08003, Spain
| | - Dereje D Jima
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC 27606, USA; Bioinformatics Research Center, North Carolina State University, Raleigh, NC 27606, USA
| | - Tuomas Kvist
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Finland
| | - Andrea Baccarelli
- Laboratory of Precision Environmental Biosciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Cory White
- Merck Exploratory Science Center, Merck Research Laboratories, Cambridge, MA 02141, USA
| | - Faisal I Rezwan
- Department of Computer Science, Aberystwyth University, Aberystwyth, Ceredigion, SY23 3DB, United Kingdom; Human Development and Health, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, UK
| | - Gemma C Sharp
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN, UK
| | - Gwen Tindula
- Children's Environmental Health Laboratory, Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Anna Bergström
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Center for Occupational and Environmental Medicine, Region Stockholm, Sweden
| | - Veit Grote
- Div. Metabolic and Nutritional Medicine, Dept. Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - John F Dou
- School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA
| | - Elena Isaevska
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Maria C Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Eva Corpeleijn
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
| | - Patrice Perron
- Centre de Recherche du Centre Hospitalier Universitaire de Sherbrooke, QC, Canada; Department of Medicine, Universite de Sherbrooke, QC, Canada
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2060, 3000 CB Rotterdam, The Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2060, 3000 CB Rotterdam, The Netherlands
| | - Ellen A Nohr
- Institute of Clinical Research, University of Southern Denmark, Odense, Denmark; Centre of Women's, Family and Child Health, University of South-Eastern Norway, Kongsberg, Norway
| | - Lea Maitre
- ISGlobal, Barcelona Institute for Global Health, Dr Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Maria Foraster
- ISGlobal, Barcelona Institute for Global Health, Dr Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; PHAGEX Research Group, Blanquerna School of Health Science, Universitat Ramon Llull, Barcelona, Spain
| | - Cathrine Hoyo
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC 27606, USA; Department of Biological Sciences, North Carolina State University, NC, USA
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Jari Lahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Finland
| | - Dawn L DeMeo
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Hongmei Zhang
- Division of Epidemiology, Biostatistics and Environmental Health, School of Public Health, University of Memphis, Memphis, USA
| | - Wilfried Karmaus
- Division of Epidemiology, Biostatistics and Environmental Health, School of Public Health, University of Memphis, Memphis, USA
| | - Inger Kull
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden; Sachs' Children and Youth Hospital, Södersjukhuset, Stockholm, Sweden
| | - Berthold Koletzko
- Div. Metabolic and Nutritional Medicine, Dept. Pediatrics, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Jason I Feinberg
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Luigi Gagliardi
- Department of Woman and Child Health, Ospedale Versilia, Azienda USL Toscana Nord Ovest, Viareggio, Italy
| | - Luigi Bouchard
- Department of Biochemistry and Functional Genomics, Université de Sherbrooke, QC, Canada; Department of Medical Biology, CIUSSS Saguenay-Lac-Saint-Jean, Chicoutimi Hospital, Saguenay, QC, Canada
| | | | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry/ Psychology, Erasmus Medical Center, Sophia Children's Hospital, P.O. Box 2060, 3000 CB Rotterdam, The Netherlands; Department of Social and Behavioral Science, Harvard TH Chan School of Public Health, 677 Huntington Ave, Boston, MA, USA
| | - Gillian Santorelli
- Bradford Institute of Health Research, Bradford Royal Infirmary, Bradford BD9 6RJ, UK
| | - Rachel L Maguire
- Department of Biological Sciences, North Carolina State University, NC, USA; Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, NC 27701, USA
| | - Darina Czamara
- Dept. Translational Research in Psychiatry, Max-Planck-Institute of Psychiatry, Munich, Germany
| | - Augusto A Litonjua
- Division of Pediatric Pulmonology, Department of Pediatrics, University of Rochester Medical Center, Rochester, NY, USA
| | | | - Michelle Plusquin
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium
| | - Johanna Lepeule
- Univ. Grenoble Alpes, Inserm, CNRS, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, IAB, 38000 Grenoble, France
| | - Elisabeth B Binder
- Dept. Translational Research in Psychiatry, Max-Planck-Institute of Psychiatry, Munich, Germany; Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, USA
| | - Elvira Verduci
- Department of Pediatrics, Ospedale dei Bambini Vittore Buzzi, University of Milan, Milan, Italy; Department of Health Sciences, University of Milan, Milan, Italy
| | - Terence Dwyer
- Clinical Sciences, Heart Group, Murdoch Children's Research Institute, Melbourne, Australia; Department of Pediatrics, University of Melbourne, Melbourne, Australia; Nuffield Department of Women's & Reproductive Health, University of Oxford, Oxford, UK
| | - Ángel Carracedo
- Grupo de Medicina Xenómica, Fundación Pública Galega de Merdicina Xenómica, Instituto de Investigación Sanitaria de Santiago de Compostela (IDIS), SERGAS, Santiago de Compostela, Spain; Centro de Investigación en Red de Enfermedades Raras (CIBERER) y Centro Nacional de Genotipado (CEGEN-PRB3), Universidad de Santiago de Compostela, Santiago de Compostela, Spain
| | - Natalia Ferre
- Pediatric Nutrition and Human Development Research Unit, Universitat Rovira i Virgili, IISPV, Reus, Spain
| | - Brenda Eskenazi
- Center for Environmental Research and Children's Health, School of Public Health, University of California, Berkeley, CA, USA
| | - Manolis Kogevinas
- ISGlobal, Barcelona Institute for Global Health, Dr Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain; IMIM (Hospital del Mar Medical Research Institute), Carrer del Dr. Aiguader 88, 08003 Barcelona, Spain
| | - Tim S Nawrot
- Centre for Environmental Sciences, Hasselt University, Hasselt, Belgium; Department Public Health & Primary care, Leuven University, Belgium
| | - Monica C Munthe-Kaas
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; Department of Pediatric Oncology and Hematology, Oslo University Hospital, Norway
| | - Zdenko Herceg
- International Agency for Research on Cancer, Lyon, France
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN, UK
| | - Erik Melén
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden; Sachs' Children and Youth Hospital, Södersjukhuset, Stockholm, Sweden
| | - Dariusz Gruszfeld
- Neonatal Department, Children's Memorial Health Institute, Warsaw, Poland
| | - Carrie Breton
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA 90089, USA
| | - M D Fallin
- Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
| | - Akram Ghantous
- International Agency for Research on Cancer, Lyon, France
| | - Wenche Nystad
- Department of Chronic Diseases and Ageing, Division of Mental and Physical Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Barbara Heude
- Université de Paris, Centre for Research in Epidemiology and Statistics (CRESS), INSERM, INRAE, F-75004 Paris, France
| | - Harold Snieder
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
| | - Marie-France Hivert
- Department of Medicine, Universite de Sherbrooke, QC, Canada; Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA; Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2060, 3000 CB Rotterdam, The Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, P.O. Box 2060, 3000 CB Rotterdam, The Netherlands
| | - Thorkild I A Sørensen
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK; MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN, UK; Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark; The Novo Nordisk Foundation Center for Basic Metabolic Research, Section on Metabolic Genetics, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mariona Bustamante
- ISGlobal, Barcelona Institute for Global Health, Dr Aiguader 88, 08003 Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Susan K Murphy
- Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, NC 27701, USA
| | - Katri Raikkönen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Finland
| | - Emily Oken
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - John W Holloway
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton General Hospital, Southampton, UK; Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Syed Hasan Arshad
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK; David Hide Asthma and Allergy Research Centre, Isle of Wight, UK
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Nina Holland
- Children's Environmental Health Laboratory, Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
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20
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Brooks-Pollock E, Christensen H, Trickey A, Hemani G, Nixon E, Thomas AC, Turner K, Finn A, Hickman M, Relton C, Danon L. High COVID-19 transmission potential associated with re-opening universities can be mitigated with layered interventions. Nat Commun 2021; 12:5017. [PMID: 34404780 PMCID: PMC8371131 DOI: 10.1038/s41467-021-25169-3] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2020] [Accepted: 07/21/2021] [Indexed: 12/17/2022] Open
Abstract
Controlling COVID-19 transmission in universities poses challenges due to the complex social networks and potential for asymptomatic spread. We developed a stochastic transmission model based on realistic mixing patterns and evaluated alternative mitigation strategies. We predict, for plausible model parameters, that if asymptomatic cases are half as infectious as symptomatic cases, then 15% (98% Prediction Interval: 6-35%) of students could be infected during the first term without additional control measures. First year students are the main drivers of transmission with the highest infection rates, largely due to communal residences. In isolation, reducing face-to-face teaching is the most effective intervention considered, however layering multiple interventions could reduce infection rates by 75%. Fortnightly or more frequent mass testing is required to impact transmission and was not the most effective option considered. Our findings suggest that additional outbreak control measures should be considered for university settings.
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Affiliation(s)
- Ellen Brooks-Pollock
- Bristol Veterinary School, University of Bristol, Langford, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Hannah Christensen
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Adam Trickey
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Gibran Hemani
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Emily Nixon
- School of Biological Sciences, University of Bristol, Bristol, Bristol, UK
| | - Amy C Thomas
- Bristol Veterinary School, University of Bristol, Langford, Bristol, UK
| | - Katy Turner
- Bristol Veterinary School, University of Bristol, Langford, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Adam Finn
- Bristol Children's Vaccine Centre, University of Bristol, Bristol, Bristol, UK
| | - Matt Hickman
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Caroline Relton
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Leon Danon
- Department of Engineering Mathematics, University of Bristol, Bristol, Bristol, UK
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21
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McBride N, Yousefi P, Sovio U, Taylor K, Vafai Y, Yang T, Hou B, Suderman M, Relton C, Smith GCS, Lawlor DA. Do Mass Spectrometry-Derived Metabolomics Improve the Prediction of Pregnancy-Related Disorders? Findings from a UK Birth Cohort with Independent Validation. Metabolites 2021; 11:530. [PMID: 34436471 PMCID: PMC8399752 DOI: 10.3390/metabo11080530] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Revised: 07/23/2021] [Accepted: 07/30/2021] [Indexed: 12/01/2022] Open
Abstract
Many women who experience gestational diabetes (GDM), gestational hypertension (GHT), pre-eclampsia (PE), have a spontaneous preterm birth (sPTB) or have an offspring born small/large for gestational age (SGA/LGA) do not meet the criteria for high-risk pregnancies based upon certain maternal risk factors. Tools that better predict these outcomes are needed to tailor antenatal care to risk. Recent studies have suggested that metabolomics may improve the prediction of these pregnancy-related disorders. These have largely been based on targeted platforms or focused on a single pregnancy outcome. The aim of this study was to assess the predictive ability of an untargeted platform of over 700 metabolites to predict the above pregnancy-related disorders in two cohorts. We used data collected from women in the Born in Bradford study (BiB; two sub-samples, n = 2000 and n = 1000) and the Pregnancy Outcome Prediction study (POPs; n = 827) to train, test and validate prediction models for GDM, PE, GHT, SGA, LGA and sPTB. We compared the predictive performance of three models: (1) risk factors (maternal age, pregnancy smoking, BMI, ethnicity and parity) (2) mass spectrometry (MS)-derived metabolites (n = 718 quantified metabolites, collected at 26-28 weeks' gestation) and (3) combined risk factors and metabolites. We used BiB for the training and testing of the models and POPs for independent validation. In both cohorts, discrimination for GDM, PE, LGA and SGA improved with the addition of metabolites to the risk factor model. The models' area under the curve (AUC) were similar for both cohorts, with good discrimination for GDM (AUC (95% CI) BiB 0.76 (0.71, 0.81) and POPs 0.76 (0.72, 0.81)) and LGA (BiB 0.86 (0.80, 0.91) and POPs 0.76 (0.60, 0.92)). Discrimination was improved for the combined models (compared to the risk factors models) for PE and SGA, with modest discrimination in both studies (PE-BiB 0.68 (0.58, 0.78) and POPs 0.66 (0.60, 0.71); SGA-BiB 0.68 (0.63, 0.74) and POPs 0.64 (0.59, 0.69)). Prediction for sPTB was poor in BiB and POPs for all models. In BiB, calibration for the combined models was good for GDM, LGA and SGA. Retained predictors include 4-hydroxyglutamate for GDM, LGA and PE and glycerol for GDM and PE. MS-derived metabolomics combined with maternal risk factors improves the prediction of GDM, PE, LGA and SGA, with good discrimination for GDM and LGA. Validation across two very different cohorts supports further investigation on whether the metabolites reflect novel causal paths to GDM and LGA.
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Affiliation(s)
- Nancy McBride
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (P.Y.); (K.T.); (M.S.); (C.R.); (D.A.L.)
- NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol BS8 2BN, UK
- Department of Population Health Sciences, University of Bristol, Bristol BS8 2BN, UK
| | - Paul Yousefi
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (P.Y.); (K.T.); (M.S.); (C.R.); (D.A.L.)
- Department of Population Health Sciences, University of Bristol, Bristol BS8 2BN, UK
| | - Ulla Sovio
- NIHR Cambridge Biomedical Research Centre, Department of Obstetrics and Gynaecology, University of Cambridge, Cambridge CB2 0QQ, UK; (U.S.); (G.C.S.S.)
| | - Kurt Taylor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (P.Y.); (K.T.); (M.S.); (C.R.); (D.A.L.)
| | - Yassaman Vafai
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford BD9 6DA, UK; (Y.V.); (T.Y.); (B.H.)
| | - Tiffany Yang
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford BD9 6DA, UK; (Y.V.); (T.Y.); (B.H.)
| | - Bo Hou
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford BD9 6DA, UK; (Y.V.); (T.Y.); (B.H.)
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (P.Y.); (K.T.); (M.S.); (C.R.); (D.A.L.)
- Department of Population Health Sciences, University of Bristol, Bristol BS8 2BN, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (P.Y.); (K.T.); (M.S.); (C.R.); (D.A.L.)
- Department of Population Health Sciences, University of Bristol, Bristol BS8 2BN, UK
| | - Gordon C. S. Smith
- NIHR Cambridge Biomedical Research Centre, Department of Obstetrics and Gynaecology, University of Cambridge, Cambridge CB2 0QQ, UK; (U.S.); (G.C.S.S.)
| | - Deborah A. Lawlor
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol BS8 2BN, UK; (P.Y.); (K.T.); (M.S.); (C.R.); (D.A.L.)
- NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol BS8 2BN, UK
- Department of Population Health Sciences, University of Bristol, Bristol BS8 2BN, UK
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22
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Rathod R, Zhang H, Karmaus W, Ewart S, Kadalayil L, Relton C, Ring S, Arshad SH, Holloway JW. BMI trajectory in childhood is associated with asthma incidence at young adulthood mediated by DNA methylation. Allergy Asthma Clin Immunol 2021; 17:77. [PMID: 34301314 PMCID: PMC8299682 DOI: 10.1186/s13223-021-00575-w] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/10/2021] [Accepted: 07/02/2021] [Indexed: 11/10/2022]
Abstract
PURPOSE Body mass index (BMI) is associated with asthma but associations of BMI temporal patterns with asthma incidence are unclear. Previous studies suggest that DNA methylation (DNAm) is associated with asthma status and variation in DNAm is a consequence of BMI changes. This study assessed the direct and indirect (via DNAm) effects of BMI trajectories in childhood on asthma incidence at young adulthood. METHODS Data from the Isle of Wight (IoW) birth cohort were included in the analyses. Group-based trajectory modelling was applied to infer latent BMI trajectories from ages 1 to 10 years. An R package, ttscreening, was applied to identify differentially methylated CpGs at age 10 years associated with BMI trajectories, stratified for sex. Logistic regressions were used to further exclude CpGs with DNAm at age 10 years not associated with asthma incidence at 18 years. CpGs discovered via path analyses that mediated the association of BMI trajectories with asthma incidence in the IoW cohort were further tested in an independent cohort, the Avon Longitudinal Study of Children and Parents (ALSPAC). RESULTS Two BMI trajectories (high vs. normal) were identified. Of the 442,474 CpG sites, DNAm at 159 CpGs in males and 212 in females were potentially associated with BMI trajectories. Assessment of their association with asthma incidence identified 9 CpGs in males and 6 CpGs in females. DNAm at 4 of these 15 CpGs showed statistically significant mediation effects (p-value < 0.05). At two of the 4 CpGs (cg23632109 and cg10817500), DNAm completely mediated the association (i.e., only statistically significant indirect effects were identified). In the ALSPAC cohort, at all four CpGs, the same direction of mediating effects were observed as those found in the IoW cohort, although statistically insignificant. CONCLUSION The association of BMI trajectory in childhood with asthma incidence at young adulthood is possibly mediated by DNAm.
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Affiliation(s)
- Rutu Rathod
- Division of Epidemiology, Biostatistics and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA
| | - Hongmei Zhang
- Division of Epidemiology, Biostatistics and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA.
| | - Wilfried Karmaus
- Division of Epidemiology, Biostatistics and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA
| | - Susan Ewart
- College of Veterinary Medicine, Michigan State University, East Lansing, MI, USA
| | - Latha Kadalayil
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Research Centre, University of Bristol and University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Susan Ring
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- National Institute for Health Research Bristol Biomedical Research Centre, University of Bristol and University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - S Hasan Arshad
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- David Hide Asthma and Allergy Research Centre, Isle of Wight, UK
- NIHR Southampton Biomedical Research Centre, University Hospital Southampton, Southampton, UK
| | - John W Holloway
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
- NIHR Southampton Biomedical Research Centre, University Hospital Southampton, Southampton, UK
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23
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Lee SM, Mitchell R, Knight JA, Mazzulli T, Relton C, Khodayari Moez E, Hung RJ. Early-childhood cytomegalovirus infection and children's neurocognitive development. Int J Epidemiol 2021; 50:538-549. [PMID: 33306803 DOI: 10.1093/ije/dyaa232] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2020] [Accepted: 10/21/2020] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Despite a clear association seen in congenitally infected children, the effect of postnatal cytomegalovirus (CMV) infection during early childhood on cognitive development has not yet been determined. METHODS CMV-infection status was obtained based on serological measurements when children were 7 years old. Using population-based longitudinal data, we employed multivariate Poisson regression with a robust variance estimator to characterize the relationship between childhood CMV infection and adverse neurocognitive outcomes in children. Suboptimal neurocognitive outcomes were compared between CMV-positive and CMV-negative children using various cognitive assessments from 8 to 15 years of age. Children were evaluated on the cognitive domains of language, reading, memory and general intelligence, with a suboptimal score being >2 standard deviations lower than the mean score. Approximate Bayes factor (ABF) analysis was used to determine the level of evidence for the observed associations. RESULTS With adjustment for potential confounders, we observed that early-childhood CMV infection was associated with suboptimal total intelligence quotient (IQ) at 8 years of age [incidence-rate ratio (IRR) = 2.50, 95% confidence interval (CI) 1.35-4.62, ABF = 0.08], but not with suboptimal total IQ at 15 years of age (IRR = 0.97, 95% CI 0.43-2.19, ABF = 1.68). Suboptimal attentional control at 8 years (IRR = 1.74, 95% CI 1.13-2.68, ABF = 0.18) and reading comprehension at 9 years (IRR = 1.93, 95% CI 1.12-3.33, ABF = 0.24) were also associated with CMV infection. ABF analysis provided strong evidence for the association between CMV infection and total IQ at 8 years, and only anecdotal evidence for attentional control at 8 years and reading comprehension at 9 years. All other cognitive measures assessed were not associated with CMV infection. CONCLUSION In this large-scale prospective cohort, we observed some evidence for adverse neurocognitive effects of postnatal CMV infection on general intelligence during early childhood, although not with lasting effect. If confirmed, these results could support the implementation of preventative measures to combat postnatal CMV infection.
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Affiliation(s)
- Samantha M Lee
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Ruth Mitchell
- MRC Integrative Epidemiology Unit, Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, UK
| | - Julia A Knight
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Tony Mazzulli
- Department of Microbiology, Mount Sinai Hospital, Sinai Health System, Toronto, ON, Canada.,Public Health Ontario Laboratory, Toronto, ON, Canada
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, Bristol Medical School: Population Health Sciences, University of Bristol, Bristol, UK
| | | | - Rayjean J Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.,Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
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24
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Nixon E, Trickey A, Christensen H, Finn A, Thomas A, Relton C, Montgomery C, Hemani G, Metz J, Walker JG, Turner K, Kwiatkowska R, Sauchelli S, Danon L, Brooks-Pollock E. Contacts and behaviours of university students during the COVID-19 pandemic at the start of the 2020/2021 academic year. Sci Rep 2021; 11:11728. [PMID: 34083593 PMCID: PMC8175593 DOI: 10.1038/s41598-021-91156-9] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2020] [Accepted: 05/21/2021] [Indexed: 11/08/2022] Open
Abstract
University students have unique living, learning and social arrangements which may have implications for infectious disease transmission. To address this data gap, we created CONQUEST (COroNavirus QUESTionnaire), a longitudinal online survey of contacts, behaviour, and COVID-19 symptoms for University of Bristol (UoB) staff/students. Here, we analyse results from 740 students providing 1261 unique records from the start of the 2020/2021 academic year (14/09/2020-01/11/2020), where COVID-19 outbreaks led to the self-isolation of all students in some halls of residences. Although most students reported lower daily contacts than in pre-COVID-19 studies, there was heterogeneity, with some reporting many (median = 2, mean = 6.1, standard deviation = 15.0; 8% had ≥ 20 contacts). Around 40% of students' contacts were with individuals external to the university, indicating potential for transmission to non-students/staff. Only 61% of those reporting cardinal symptoms in the past week self-isolated, although 99% with a positive COVID-19 test during the 2 weeks before survey completion had self-isolated within the last week. Some students who self-isolated had many contacts (mean = 4.3, standard deviation = 10.6). Our results provide context to the COVID-19 outbreaks seen in universities and are available for modelling future outbreaks and informing policy.
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Affiliation(s)
- Emily Nixon
- School of Biological Sciences, University of Bristol, Bristol Life Sciences Building, 24 Tyndall Avenue, Bristol, BS8 1TQ, UK.
- Bristol Veterinary School, University of Bristol, Bristol, UK.
| | - Adam Trickey
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Hannah Christensen
- Population Health Sciences, University of Bristol, Bristol, UK
- NIHR Health Protection Research Unit in Behavioural Science and Evaluation, University of Bristol, Bristol, UK
| | - Adam Finn
- Population Health Sciences, University of Bristol, Bristol, UK
- NIHR Health Protection Research Unit in Behavioural Science and Evaluation, University of Bristol, Bristol, UK
- School of Cellular and Molecular Medicine, University of Bristol, Bristol, UK
| | - Amy Thomas
- Bristol Veterinary School, University of Bristol, Bristol, UK
| | - Caroline Relton
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Clara Montgomery
- School of Biological Sciences, University of Bristol, Bristol Life Sciences Building, 24 Tyndall Avenue, Bristol, BS8 1TQ, UK
| | - Gibran Hemani
- Population Health Sciences, University of Bristol, Bristol, UK
| | - Jane Metz
- Bristol Children's Vaccine Centre, University of Bristol, Bristol, UK
| | | | - Katy Turner
- NIHR Health Protection Research Unit in Behavioural Science and Evaluation, University of Bristol, Bristol, UK
- Bristol Veterinary School, University of Bristol, Bristol, UK
| | | | - Sarah Sauchelli
- National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals of Bristol, Weston NHS Foundation Trust, University of Bristol, Bristol, UK
| | - Leon Danon
- Department of Engineering Mathematics, University of Bristol, Bristol, UK, BS8 1TW
- Alan Turing Institute, British Library, London, UK
| | - Ellen Brooks-Pollock
- NIHR Health Protection Research Unit in Behavioural Science and Evaluation, University of Bristol, Bristol, UK
- Bristol Veterinary School, University of Bristol, Bristol, UK
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25
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Luo M, Meehan AJ, Walton E, Röder S, Herberth G, Zenclussen AC, Cosín-Tomás M, Sunyer J, Mulder RH, Cortes Hidalgo AP, Bakermans-Kranenburg MJ, Felix JF, Relton C, Suderman M, Pappa I, Kok R, Tiemeier H, van IJzendoorn MH, Barker ED, Cecil CAM. Neonatal DNA methylation and childhood low prosocial behavior: An epigenome-wide association meta-analysis. Am J Med Genet B Neuropsychiatr Genet 2021; 186:228-241. [PMID: 34170065 DOI: 10.1002/ajmg.b.32862] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 05/26/2021] [Accepted: 06/02/2021] [Indexed: 11/10/2022]
Abstract
Low prosocial behavior in childhood has been consistently linked to later psychopathology, with evidence supporting the influence of both genetic and environmental factors on its development. Although neonatal DNA methylation (DNAm) has been found to prospectively associate with a range of psychological traits in childhood, its potential role in prosocial development has yet to be investigated. This study investigated prospective associations between cord blood DNAm at birth and low prosocial behavior within and across four longitudinal birth cohorts from the Pregnancy And Childhood Epigenetics (PACE) Consortium. We examined (a) developmental trajectories of "chronic-low" versus "typical" prosocial behavior across childhood in a case-control design (N = 2,095), and (b) continuous "low prosocial" scores at comparable cross-cohort time-points (N = 2,121). Meta-analyses were performed to examine differentially methylated positions and regions. At the cohort-specific level, three CpGs were found to associate with chronic low prosocial behavior; however, none of these associations was replicated in another cohort. Meta-analysis revealed no epigenome-wide significant CpGs or regions. Overall, we found no evidence for associations between DNAm patterns at birth and low prosocial behavior across childhood. Findings highlight the importance of employing multi-cohort approaches to replicate epigenetic associations and reduce the risk of false positive discoveries.
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Affiliation(s)
- Mannan Luo
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands.,Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Alan J Meehan
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Yale Child Study Center, Yale School of Medicine, New Haven, USA
| | - Esther Walton
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,Department of Psychology, University of Bath, Bath, UK
| | - Stefan Röder
- Department for Environmental Immunology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany
| | - Gunda Herberth
- Department for Environmental Immunology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany
| | - Ana C Zenclussen
- Department for Environmental Immunology, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany
| | - Marta Cosín-Tomás
- ISGlobal, Barcelona, Catalonia, Spain.,Universitat Pompeu Fabra, Barcelona, Catalonia, Spain.,Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Jordi Sunyer
- ISGlobal, Barcelona, Catalonia, Spain.,Universitat Pompeu Fabra, Barcelona, Catalonia, Spain.,Centro de Investigación Biomédica en Red en Epidemiología y Salud Pública (CIBERESP), Madrid, Spain.,IMIM Parc Salut Mar, Barcelona, Catalonia, Spain
| | - Rosa H Mulder
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Andrea P Cortes Hidalgo
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | | | - Janine F Felix
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Irene Pappa
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - Rianne Kok
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands
| | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Social and Behavioral Science, Harvard TH Chan School of Public Health, Boston, Massachusetts, USA
| | - Marinus H van IJzendoorn
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands.,Department of Clinical, Educational and Health Psychology, Faculty of Brain Sciences, University College London, London, UK
| | - Edward D Barker
- Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Charlotte A M Cecil
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Department of Psychology, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK.,Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands.,Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, The Netherlands
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26
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van Dongen J, Hagenbeek FA, Suderman M, Roetman PJ, Sugden K, Chiocchetti AG, Ismail K, Mulder RH, Hafferty JD, Adams MJ, Walker RM, Morris SW, Lahti J, Küpers LK, Escaramis G, Alemany S, Jan Bonder M, Meijer M, Ip HF, Jansen R, Baselmans BML, Parmar P, Lowry E, Streit F, Sirignano L, Send TS, Frank J, Jylhävä J, Wang Y, Mishra PP, Colins OF, Corcoran DL, Poulton R, Mill J, Hannon E, Arseneault L, Korhonen T, Vuoksimaa E, Felix JF, Bakermans-Kranenburg MJ, Campbell A, Czamara D, Binder E, Corpeleijn E, Gonzalez JR, Grazuleviciene R, Gutzkow KB, Evandt J, Vafeiadi M, Klein M, van der Meer D, Ligthart L, Kluft C, Davies GE, Hakulinen C, Keltikangas-Järvinen L, Franke B, Freitag CM, Konrad K, Hervas A, Fernández-Rivas A, Vetro A, Raitakari O, Lehtimäki T, Vermeiren R, Strandberg T, Räikkönen K, Snieder H, Witt SH, Deuschle M, Pedersen NL, Hägg S, Sunyer J, Franke L, Kaprio J, Ollikainen M, Moffitt TE, Tiemeier H, van IJzendoorn MH, Relton C, Vrijheid M, Sebert S, Jarvelin MR, Caspi A, Evans KL, McIntosh AM, Bartels M, Boomsma DI. DNA methylation signatures of aggression and closely related constructs: A meta-analysis of epigenome-wide studies across the lifespan. Mol Psychiatry 2021; 26:2148-2162. [PMID: 33420481 PMCID: PMC8263810 DOI: 10.1038/s41380-020-00987-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 11/04/2020] [Accepted: 12/04/2020] [Indexed: 01/06/2023]
Abstract
DNA methylation profiles of aggressive behavior may capture lifetime cumulative effects of genetic, stochastic, and environmental influences associated with aggression. Here, we report the first large meta-analysis of epigenome-wide association studies (EWAS) of aggressive behavior (N = 15,324 participants). In peripheral blood samples of 14,434 participants from 18 cohorts with mean ages ranging from 7 to 68 years, 13 methylation sites were significantly associated with aggression (alpha = 1.2 × 10-7; Bonferroni correction). In cord blood samples of 2425 children from five cohorts with aggression assessed at mean ages ranging from 4 to 7 years, 83% of these sites showed the same direction of association with childhood aggression (r = 0.74, p = 0.006) but no epigenome-wide significant sites were found. Top-sites (48 at a false discovery rate of 5% in the peripheral blood meta-analysis or in a combined meta-analysis of peripheral blood and cord blood) have been associated with chemical exposures, smoking, cognition, metabolic traits, and genetic variation (mQTLs). Three genes whose expression levels were associated with top-sites were previously linked to schizophrenia and general risk tolerance. At six CpGs, DNA methylation variation in blood mirrors variation in the brain. On average 44% (range = 3-82%) of the aggression-methylation association was explained by current and former smoking and BMI. These findings point at loci that are sensitive to chemical exposures with potential implications for neuronal functions. We hope these results to be a starting point for studies leading to applications as peripheral biomarkers and to reveal causal relationships with aggression and related traits.
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Affiliation(s)
- Jenny van Dongen
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Fiona A Hagenbeek
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Matthew Suderman
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Peter J Roetman
- Curium-LUMC, Department of Child and Adolescent Psychiatry, Leiden University Medical Center, Oegstgeest, The Netherlands
| | - Karen Sugden
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Andreas G Chiocchetti
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe-Universität, Frankfurt am Main, Germany
| | - Khadeeja Ismail
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Rosa H Mulder
- Institute of Education and Child Studies, Leiden University, Leiden, The Netherlands
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | | | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Stewart W Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Jari Lahti
- Turku Institute for Advanced Studies, University of Turku, Turku, Finland
- Department of Psychology and logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Leanne K Küpers
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
| | - Georgia Escaramis
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
- Department of Biomedical Science, Faculty of Medicine and Health Science, University of Barcelona, Barcelona, Spain
- Research Group on Statistics, Econometrics and Health (GRECS), UdG, Girona, Spain
| | - Silvia Alemany
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Marc Jan Bonder
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Mandy Meijer
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Hill F Ip
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Rick Jansen
- Department of Psychiatry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Bart M L Baselmans
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Priyanka Parmar
- Center for Life Course Health Research, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
- Biocenter Oulu, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
| | - Estelle Lowry
- Center for Life Course Health Research, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
- Queen's University Belfast, Belfast, UK
| | - Fabian Streit
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Lea Sirignano
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Tabea S Send
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Josef Frank
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Juulia Jylhävä
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Pashupati Prasad Mishra
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33520, Finland
| | - Olivier F Colins
- Curium-LUMC, Department of Child and Adolescent Psychiatry, Leiden University Medical Center, Oegstgeest, The Netherlands
- Department of Special Needs Education, Ghent University, Ghent, Belgium
| | - David L Corcoran
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Jonathan Mill
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Eilis Hannon
- University of Exeter Medical School, University of Exeter, Exeter, UK
| | - Louise Arseneault
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Tellervo Korhonen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Eero Vuoksimaa
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Janine F Felix
- Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
| | | | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Darina Czamara
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, Germany
| | - Elisabeth Binder
- Department of Translational Research in Psychiatry, Max Planck Institute of Psychiatry, Kraepelinstr. 2-10, 80804, Munich, Germany
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, 12 Executive Park Dr, Atlanta, GA, 30329, USA
| | - Eva Corpeleijn
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
| | - Juan R Gonzalez
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Regina Grazuleviciene
- Department of Environmental Sciences, Vytautas Magnus University, K. Donelaicio str. 58, 44248, Kaunas, Lithuania
| | - Kristine B Gutzkow
- Department of Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Jorunn Evandt
- Department of Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Marina Vafeiadi
- Department of Social Medicine, University of Crete, Heraklion, Greece
| | - Marieke Klein
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- University Medical Center Utrecht, UMC Utrecht Brain Center, Department of Psychiatry, Utrecht, The Netherlands
| | - Dennis van der Meer
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- School of Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Maastricht, The Netherlands
| | - Lannie Ligthart
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | | | - Gareth E Davies
- Avera Institute for Human Genetics, 3720 W. 69th Street, Sioux Falls, SD, 57108, USA
| | - Christian Hakulinen
- Department of Psychology and logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | | | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Psychiatry, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Christine M Freitag
- Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, University Hospital Frankfurt, Goethe-Universität, Frankfurt am Main, Germany
| | - Kerstin Konrad
- University Hospital, RWTH Aachen, Child Neuropsychology Section, Department of Child and Adolescent Psychiatry, Psychosomatics and Psychotherapy, Aachen, Germany
- JARA-Brain Institute II, Molecular Neuroscience and Neuroimaging (INM-11), RWTH Aachen & Research Centre Juelich, Juelich, Germany
| | - Amaia Hervas
- Hospital Universitario Mutua de Terrassa, Child and Adolescent Mental Health Service, Barcelona, Spain
| | | | - Agnes Vetro
- Szeged University, Department of Pediatrics and Pediatrics health center, Child and Adolescent Psychiatry, Szeged, Hungary
| | - Olli Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33520, Finland
| | - Robert Vermeiren
- Curium-LUMC, Department of Child and Adolescent Psychiatry, Leiden University Medical Center, Oegstgeest, The Netherlands
- Youz, Parnassia Group, The Hague, The Netherlands
| | - Timo Strandberg
- Helsinki University Central Hospital, Geriatrics, Helsinki, Finland
| | - Katri Räikkönen
- Department of Psychology and logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Harold Snieder
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, The Netherlands
| | - Stephanie H Witt
- Department of Genetic Epidemiology in Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Michael Deuschle
- Department of Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Jordi Sunyer
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
| | - Lude Franke
- Department of Genetics, University of Groningen, University Medical Centre Groningen, Groningen, The Netherlands
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Miina Ollikainen
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Terrie E Moffitt
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Henning Tiemeier
- Department of Child and Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, The Netherlands
- Department of Social and Behavioral Science, Harvard TH Chan School of Public Health, Boston, USA
| | - Marinus H van IJzendoorn
- Department of Psychology, Education and Child Studies, Erasmus University Rotterdam, Rotterdam, The Netherlands
- Department of Clinical, Educational and Health Psychology, UCL, University of London, London, UK
| | - Caroline Relton
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- MRC Medical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Martine Vrijheid
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
- Biocenter Oulu, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
- Section of Genomics of Common Disease, Department of Medicine, Imperial College London, Hammersmith Hospital Campus, Burlington Danes Building, Du Cane Road, London, W12 0NN, UK
| | - Marjo-Riitta Jarvelin
- Center for Life Course Health Research, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
- Biocenter Oulu, University of Oulu, P.O. Box 5000, 90014, Oulu, Finland
- MRC-PHE Centre for Environment and Health, Imperial College London, Hammersmith Hospital Campus, Burlington Danes Building, Du Cane Road, London, W12 0NN, UK
| | - Avshalom Caspi
- Department of Psychology and Neuroscience, Duke University, Durham, NC, USA
- Center for Genomic and Computational Biology, Duke University, Durham, NC, USA
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, USA
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | | | - Meike Bartels
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Dorret I Boomsma
- Department of Biological Psychology, Amsterdam Public Health Research Institute, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
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27
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Karabegović I, Portilla-Fernandez E, Li Y, Ma J, Maas SCE, Sun D, Hu EA, Kühnel B, Zhang Y, Ambatipudi S, Fiorito G, Huang J, Castillo-Fernandez JE, Wiggins KL, de Klein N, Grioni S, Swenson BR, Polidoro S, Treur JL, Cuenin C, Tsai PC, Costeira R, Chajes V, Braun K, Verweij N, Kretschmer A, Franke L, van Meurs JBJ, Uitterlinden AG, de Knegt RJ, Ikram MA, Dehghan A, Peters A, Schöttker B, Gharib SA, Sotoodehnia N, Bell JT, Elliott P, Vineis P, Relton C, Herceg Z, Brenner H, Waldenberger M, Rebholz CM, Voortman T, Pan Q, Fornage M, Levy D, Kayser M, Ghanbari M. Epigenome-wide association meta-analysis of DNA methylation with coffee and tea consumption. Nat Commun 2021; 12:2830. [PMID: 33990564 PMCID: PMC8121846 DOI: 10.1038/s41467-021-22752-6] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 03/26/2021] [Indexed: 02/03/2023] Open
Abstract
Coffee and tea are extensively consumed beverages worldwide which have received considerable attention regarding health. Intake of these beverages is consistently linked to, among others, reduced risk of diabetes and liver diseases; however, the mechanisms of action remain elusive. Epigenetics is suggested as a mechanism mediating the effects of dietary and lifestyle factors on disease onset. Here we report the results from epigenome-wide association studies (EWAS) on coffee and tea consumption in 15,789 participants of European and African-American ancestries from 15 cohorts. EWAS meta-analysis of coffee consumption reveals 11 CpGs surpassing the epigenome-wide significance threshold (P-value <1.1×10-7), which annotated to the AHRR, F2RL3, FLJ43663, HDAC4, GFI1 and PHGDH genes. Among them, cg14476101 is significantly associated with expression of the PHGDH and risk of fatty liver disease. Knockdown of PHGDH expression in liver cells shows a correlation with expression levels of genes associated with circulating lipids, suggesting a role of PHGDH in hepatic-lipid metabolism. EWAS meta-analysis on tea consumption reveals no significant association, only two CpGs annotated to CACNA1A and PRDM16 genes show suggestive association (P-value <5.0×10-6). These findings indicate that coffee-associated changes in DNA methylation levels may explain the mechanism of action of coffee consumption in conferring risk of diseases.
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Affiliation(s)
- Irma Karabegović
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Genetic Identification, Erasmus University Medical Center, Rotterdam, the Netherlands
- Epidemiology and Microbial Genomics, National Health Laboratory, Dudelange, Luxembourg
| | | | - Yang Li
- Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Jiantao Ma
- Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA, USA
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland and the Framingham Heart Study, Framingham, MA, USA
| | - Silvana C E Maas
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
- Department of Genetic Identification, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Daokun Sun
- Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Emily A Hu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Brigitte Kühnel
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Yan Zhang
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Srikant Ambatipudi
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- AMCHSS, Sree Chitra Tirunal Institute for Medical Sciences and Technology, Thiruvananthapuram, Kerala, India
- Epigenetics Group, International Agency for Research on Cancer (IARC), Lyon, Cedex 08, France
| | - Giovanni Fiorito
- Laboratory of Biostatistics, Department of Biomedical Sciences, University of Sassari, Sassari, Italy
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's Campus, Imperial College London, Norfolk Place, London, UK
| | - Jian Huang
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's Campus, Imperial College London, Norfolk Place, London, UK
- UK Dementia Research Institute at Imperial College London, London, UK
- Imperial College NIHR Biomedical Research Centre, London, UK
| | - Juan E Castillo-Fernandez
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
- Epigenetics Programme, Babraham Institute, Cambridge, UK
| | - Kerri L Wiggins
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, CHRU, Seattle, WA, USA
| | - Niek de Klein
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Sara Grioni
- Epidemiology and Prevention Unit, IRCCS National Cancer Institute Foundation, Milan, Italy
| | - Brenton R Swenson
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, CHRU, Seattle, WA, USA
| | - Silvia Polidoro
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's Campus, Imperial College London, Norfolk Place, London, UK
- Italian Institute for Genomic Medicine (IIGM, former HuGeF), c/o IRCCS Candiolo, Candiolo, Italy
| | - Jorien L Treur
- Department of Psychiatry, Amsterdam UMC, Amsterdam, the Netherlands
| | - Cyrille Cuenin
- Epigenetics Group, International Agency for Research on Cancer (IARC), Lyon, Cedex 08, France
| | - Pei-Chien Tsai
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
- Department of Biomedical Sciences, Chang Gung University, Taoyuan, Taiwan
- Genomic Medicine Research Core Laboratory, Chang Gung Memorial Hospital, Linkou, Taiwan
| | - Ricardo Costeira
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Veronique Chajes
- Nutritional Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Kim Braun
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Niek Verweij
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Genomics plc, Park End St, Oxford, UK
| | - Anja Kretschmer
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Lude Franke
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Oncode Institute, Utrecht, The Netherlands
| | - Joyce B J van Meurs
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - André G Uitterlinden
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Robert J de Knegt
- Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Abbas Dehghan
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's Campus, Imperial College London, Norfolk Place, London, UK
- UK Dementia Research Institute at Imperial College London, London, UK
| | - Annette Peters
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Sina A Gharib
- Computational Medicine Core at Center for Lung Biology, Division of Pulmonary, Critical Care and Sleep Medicine, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Nona Sotoodehnia
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, CHRU, Seattle, WA, USA
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, Kings College London, London, UK
| | - Paul Elliott
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's Campus, Imperial College London, Norfolk Place, London, UK
- UK Dementia Research Institute at Imperial College London, London, UK
- Imperial College NIHR Biomedical Research Centre, London, UK
- Health Data Research UK-London, London, UK
| | - Paolo Vineis
- MRC Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, St Mary's Campus, Imperial College London, Norfolk Place, London, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Zdenko Herceg
- Epigenetics Group, International Agency for Research on Cancer (IARC), Lyon, Cedex 08, France
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research, University of Heidelberg, Heidelberg, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Casey M Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Trudy Voortman
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Qiuwei Pan
- Department of Gastroenterology and Hepatology, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Myriam Fornage
- Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland and the Framingham Heart Study, Framingham, MA, USA
| | - Manfred Kayser
- Department of Genetic Identification, Erasmus University Medical Center, Rotterdam, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands.
- Department of Genetics, School of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
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Russell AE, Hemani G, Jones HJ, Ford T, Gunnell D, Heron J, Joinson C, Moran P, Relton C, Suderman M, Watkins S, Mars B. An exploration of the genetic epidemiology of non-suicidal self-harm and suicide attempt. BMC Psychiatry 2021; 21:207. [PMID: 33892675 PMCID: PMC8066869 DOI: 10.1186/s12888-021-03216-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2020] [Accepted: 04/14/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Empirical evidence supporting the distinction between suicide attempt (SA) and non-suicidal self-harm (NSSH) is lacking. Although NSSH is a risk factor for SA, we do not currently know whether these behaviours lie on a continuum of severity, or whether they are discrete outcomes with different aetiologies. We conducted this exploratory genetic epidemiology study to investigate this issue further. METHODS We explored the extent of genetic overlap between NSSH and SA in a large, richly-phenotyped cohort (the Avon Longitudinal Study of Parents and Children; N = 4959), utilising individual-level genetic and phenotypic data to conduct analyses of genome-wide complex traits and polygenic risk scores (PRS). RESULTS The single nucleotide polymorphism heritability of NSSH was estimated to be 13% (SE 0.07) and that of SA to be 0% (SE 0.07). Of the traits investigated, NSSH was most strongly correlated with higher IQ (rG = 0.31, SE = 0.22), there was little evidence of high genetic correlation between NSSH and SA (rG = - 0.1, SE = 0.54), likely due to the low heritability estimate for SA. The PRS for depression differentiated between those with NSSH and SA in multinomial regression. The optimal PRS prediction model for SA (Nagelkerke R2 0.022, p < 0.001) included ADHD, depression, income, anorexia and neuroticism and explained more variance than the optimal prediction model for NSSH (Nagelkerke R2 0.010, p < 0.001) which included ADHD, alcohol consumption, autism spectrum conditions, depression, IQ, neuroticism and suicide attempt. CONCLUSIONS Our findings suggest that SA does not have a large genetic component, and that although NSSH and SA are not discrete outcomes there appears to be little genetic overlap between the two. The relatively small sample size and resulting low heritability estimate for SA was a limitation of the study. Combined with low heritability estimates, this implies that family or population structures in SA GWASs may contribute to signals detected.
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Affiliation(s)
- Abigail Emma Russell
- Children and Young People's Mental Health Research Collaboration (ChYMe), University of Exeter College of Medicine and Health, Exeter, UK.
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit, University of Bristol Medical School, Bristol, UK
- Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Hannah J Jones
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Tamsin Ford
- University of Cambridge Department of Psychiatry, Cambridge, UK
| | - David Gunnell
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Jon Heron
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Carol Joinson
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Paul Moran
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol Medical School, Bristol, UK
- Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, University of Bristol Medical School, Bristol, UK
- Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Sarah Watkins
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Becky Mars
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
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Mukherjee N, Arathimos R, Chen S, Kheirkhah Rahimabad P, Han L, Zhang H, Holloway JW, Relton C, Henderson AJ, Arshad SH, Ewart S, Karmaus W. DNA methylation at birth is associated with lung function development until age 26 years. Eur Respir J 2021; 57:2003505. [PMID: 33214203 DOI: 10.1183/13993003.03505-2020] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Accepted: 10/14/2020] [Indexed: 12/14/2022]
Abstract
Little is known about whether DNA methylation (DNAm) of cytosine-phosphate-guanine (CpG) sites at birth predicts patterns of lung function development. We used heel prick DNAm from the F1-generation of Isle of Wight birth cohort (IOWBC-F1) for discovery of CpGs associated with lung function trajectories (forced expiratory volume in 1 s, forced vital capacity, their ratio, and forced expiratory flow at 25-75% of forced vital capacity) over the first 26 years, stratified by sex. We replicated the findings in the Avon Longitudinal Study of Parents and Children (ALSPAC) using cord blood DNAm.Epigenome-wide screening was applied to identify CpGs associated with lung function trajectories in 396 boys and 390 girls of IOWBC-F1. Replication in ALSPAC focussed on lung function at ages 8, 15 and 24 years. Statistically significantly replicated CpGs were investigated for consistency in direction of association between cohorts, stability of DNAm over time in IOWBC-F1, relevant biological processes and for association with gene expression (n=161) in IOWBC F2-generation (IOWBC-F2).Differential DNAm of eight CpGs on genes GLUL, MYCN, HLX, LHX1, COBL, COL18A1, STRA6, and WNT11 involved in developmental processes, were significantly associated with lung function in the same direction in IOWBC-F1 and ALSPAC, and showed stable patterns at birth, aged 10 and 18 years between high and low lung function trajectories in IOWBC-F1. CpGs on LHX1 and COL18A1 were linked to gene expression in IOWBC-F2.In two large cohorts, novel DNAm at birth were associated with patterns of lung function in adolescence and early adulthood providing possible targets for preventative interventions against adverse pulmonary function development.
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Affiliation(s)
- Nandini Mukherjee
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA
| | - Ryan Arathimos
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Social Genetic & Developmental Psychiatry Centre, Kings College London, London, UK
- NIHR Biomedical Research Centre for Mental Health, South London and Maudsley NHS Trust, London, UK
| | - Su Chen
- Dept of Mathematical Sciences, The University of Memphis, Memphis, TN, USA
| | - Parnian Kheirkhah Rahimabad
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA
| | - Luhang Han
- Dept of Mathematical Sciences, The University of Memphis, Memphis, TN, USA
| | - Hongmei Zhang
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA
| | - John W Holloway
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - A John Henderson
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Syed Hasan Arshad
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- The David Hide Asthma and Allergy Research Centre, Isle of Wight, UK
- NIHR Southampton Biomedical Research Centre, University Hospital Southampton, Southampton, UK
| | - Susan Ewart
- College of Veterinary Medicine, Michigan State University, East Lansing, MI, USA
| | - Wilfried Karmaus
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA
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Hemani G, Thomas AC, Walker JG, Trickey A, Nixon E, Ellis D, Kwiatkowska R, Relton C, Danon L, Christensen H, Brooks-Pollock E. Modelling pooling strategies for SARS-CoV-2 testing in a university setting. Wellcome Open Res 2021. [DOI: 10.12688/wellcomeopenres.16639.1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023] Open
Abstract
Background: Pre-symptomatic and asymptomatic transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are important elements in the coronavirus disease 2019 (COVID-19) pandemic, and there remains a reliance on testing to manage the spread of the disease. In the UK, many universities opened for blended learning for the 2020-2021 academic year, with a mixture of face to face and online teaching. Methods: In this study we present a simulation framework to evaluate the effectiveness of different mass testing strategies within a university setting, across a range of transmission scenarios. Results: The sensitivity of 5x pooled RT-qPCR tests appears to be higher than testing using the lateral flow device with relatively little loss compared to single RT-qPCR tests, and is improved by pooling by social cluster. The range of strategies that we evaluated give comparable results for estimating prevalence. Conclusions: Pooling tests by known social structures, such as student households can substantially improve the cost effectiveness of RT-qPCR tests. We also note that routine recording of quantitative RT-qPCR results would facilitate future modelling studies.
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Wang J, Zhang H, Rezwan FI, Relton C, Arshad SH, Holloway JW. Pre-adolescence DNA methylation is associated with BMI status change from pre- to post-adolescence. Clin Epigenetics 2021; 13:64. [PMID: 33766110 PMCID: PMC7995693 DOI: 10.1186/s13148-021-01042-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Accepted: 02/28/2021] [Indexed: 11/27/2022] Open
Abstract
BACKGROUND Previous studies have shown that DNA methylation (DNAm) is associated with body mass index (BMI). However, it is unknown whether DNAm at pre-adolescence is associated with BMI status transition from pre- to post-adolescence. In the Isle of Wight (IoW) birth cohort, genome-wide DNA methylation in whole blood was measured using Illumina Infinium Human450 and EPIC BeadChip arrays in n = 325 subjects, and pre- to post-adolescence BMI transition was classified into four groups: (1) normal to normal, (2) normal to overweight or obese, (3) overweight or obese to normal, and (4) persistent overweight or obese. We used recursive random forest to screen genome-wide Cytosine-phosphate-Guanine (CpG) sites with DNAm potentially associated with BMI transition for each gender, and the association of BMI status transition with DNAm at an earlier age was assessed via logistic regressions. To evaluate gender specificity, interactions between DNAm and gender were included in the model. Findings in the IoW cohort were further tested in an independent cohort, the Avon Longitudinal Study of Parents and Children (ALSPAC). RESULTS In total, 174 candidate CpGs were selected including CpGs from screening and CpGs previously associated correctionally with BMI in children and adults. Of these 174 CpGs, pre-adolescent DNAm of 38 CpGs in the IoW cohort was associated with BMI status transition, including 30 CpGs showing gender-specific associations. Thirteen CpGs showed consistent associations between the IoW cohort and the ALSPAC cohort (11 of which were gender-specific). CONCLUSION Pre-adolescence DNAm is associated with the change in BMI status from pre- to post-adolescence and such associations are likely to be gender-specific.
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Affiliation(s)
- Jiajing Wang
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA
| | - Hongmei Zhang
- Division of Epidemiology, Biostatistics, and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA.
| | - Faisal I Rezwan
- School of Water, Energy and Environment, Cranfield University, Cranfield, MK43 0AL, Bedfordshire, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - S Hasan Arshad
- The David Hide Asthma and Allergy Research Centre, St Mary's, Hospital, Parkhurst Road, Newport, PO30 5TG, Isle of Wight, UK
- Faculty of Medicine, Human Development and Health, University of Southampton, Southampton, SO16 6YD, UK
| | - John W Holloway
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, SO16 6YD, UK
- Faculty of Medicine, Human Development and Health, University of Southampton, Southampton, SO16 6YD, UK
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Russell AE, Joinson C, Roberts E, Heron J, Ford T, Gunnell D, Moran P, Relton C, Suderman M, Mars B. Childhood adversity, pubertal timing and self-harm: a longitudinal cohort study. Psychol Med 2021; 52:1-9. [PMID: 33682658 PMCID: PMC9811347 DOI: 10.1017/s0033291721000611] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2020] [Revised: 01/27/2021] [Accepted: 02/08/2021] [Indexed: 01/12/2023]
Abstract
BACKGROUND The occurrence of early childhood adversity is strongly linked to later self-harm, but there is poor understanding of how this distal risk factor might influence later behaviours. One possible mechanism is through an earlier onset of puberty in children exposed to adversity, since early puberty is associated with an increased risk of adolescent self-harm. We investigated whether early pubertal timing mediates the association between childhood adversity and later self-harm. METHODS Participants were 6698 young people from a UK population-based birth cohort (ALSPAC). We measured exposure to nine types of adversity from 0 to 9 years old, and self-harm when participants were aged 16 and 21 years. Pubertal timing measures were age at peak height velocity (aPHV - males and females) and age at menarche (AAM). We used generalised structural equation modelling for analyses. RESULTS For every additional type of adversity; participants had an average 12-14% increased risk of self-harm by 16. Relative risk (RR) estimates were stronger for direct effects when outcomes were self-harm with suicidal intent. There was no evidence that earlier pubertal timing mediated the association between adversity and self-harm [indirect effect RR 1.00, 95% confidence interval (CI) 1.00-1.00 for aPHV and RR 1.00, 95% CI 1.00-1.01 for AAM]. CONCLUSIONS A cumulative measure of exposure to multiple types of adversity does not confer an increased risk of self-harm via early pubertal timing, however both childhood adversity and early puberty are risk factors for later self-harm. Research identifying mechanisms underlying the link between childhood adversity and later self-harm is needed to inform interventions.
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Affiliation(s)
- Abigail Emma Russell
- Children and Young People's Mental Health Research Collaboration, University of Exeter College of Medicine and Health, Exeter, UK
| | - Carol Joinson
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Elystan Roberts
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Jon Heron
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Tamsin Ford
- Department of Psychiatry, University of Cambridge, Cambridge, UK
| | - David Gunnell
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Paul Moran
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Becky Mars
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
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Christiansen C, Castillo-Fernandez JE, Domingo-Relloso A, Zhao W, El-Sayed Moustafa JS, Tsai PC, Maddock J, Haack K, Cole SA, Kardia SLR, Molokhia M, Suderman M, Power C, Relton C, Wong A, Kuh D, Goodman A, Small KS, Smith JA, Tellez-Plaza M, Navas-Acien A, Ploubidis GB, Hardy R, Bell JT. Novel DNA methylation signatures of tobacco smoking with trans-ethnic effects. Clin Epigenetics 2021; 13:36. [PMID: 33593402 PMCID: PMC7888173 DOI: 10.1186/s13148-021-01018-4] [Citation(s) in RCA: 44] [Impact Index Per Article: 14.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 01/24/2021] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Smoking remains one of the leading preventable causes of death. Smoking leaves a strong signature on the blood methylome as shown in multiple studies using the Infinium HumanMethylation450 BeadChip. Here, we explore novel blood methylation smoking signals on the Illumina MethylationEPIC BeadChip (EPIC) array, which also targets novel CpG-sites in enhancers. METHOD A smoking-methylation meta-analysis was carried out using EPIC DNA methylation profiles in 1407 blood samples from four UK population-based cohorts, including the MRC National Survey for Health and Development (NSHD) or 1946 British birth cohort, the National Child Development Study (NCDS) or 1958 birth cohort, the 1970 British Cohort Study (BCS70), and the TwinsUK cohort (TwinsUK). The overall discovery sample included 269 current, 497 former, and 643 never smokers. Replication was pursued in 3425 trans-ethnic samples, including 2325 American Indian individuals participating in the Strong Heart Study (SHS) in 1989-1991 and 1100 African-American participants in the Genetic Epidemiology Network of Arteriopathy Study (GENOA). RESULTS Altogether 952 CpG-sites in 500 genes were differentially methylated between smokers and never smokers after Bonferroni correction. There were 526 novel smoking-associated CpG-sites only profiled by the EPIC array, of which 486 (92%) replicated in a meta-analysis of the American Indian and African-American samples. Novel CpG sites mapped both to genes containing previously identified smoking-methylation signals and to 80 novel genes not previously linked to smoking, with the strongest novel signal in SLAMF7. Comparison of former versus never smokers identified that 37 of these sites were persistently differentially methylated after cessation, where 16 represented novel signals only profiled by the EPIC array. We observed a depletion of smoking-associated signals in CpG islands and an enrichment in enhancer regions, consistent with previous results. CONCLUSION This study identified novel smoking-associated signals as possible biomarkers of exposure to smoking and may help improve our understanding of smoking-related disease risk.
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Affiliation(s)
- C Christiansen
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | | | - A Domingo-Relloso
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, USA
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
- Department of Statistics and Operative Research, University of Valencia, Valencia, Spain
| | - W Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, USA
| | - J S El-Sayed Moustafa
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - P-C Tsai
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
- Department of Biomedical Sciences, Chang Gung University, Taoyuan, Taiwan
- Genomic Medicine Research Core Laboratory, Chang Gung Memorial Hospital, Linkou, Taiwan
| | - J Maddock
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - K Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, USA
| | - S A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, USA
| | - S L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, USA
| | - M Molokhia
- School of Population Health and Environmental Sciences, King's College London, London, UK
| | - M Suderman
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - C Power
- Population, Policy and Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
| | - C Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population, Policy and Practice Research and Teaching Department, UCL Great Ormond Street Institute of Child Health, London, UK
| | - A Wong
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - D Kuh
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - A Goodman
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK
| | - K S Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - J A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, USA
| | - M Tellez-Plaza
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| | - A Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, USA
| | - G B Ploubidis
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK
| | - R Hardy
- MRC Unit for Lifelong Health and Ageing, Institute of Cardiovascular Science, University College London, London, UK
| | - J T Bell
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK.
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Patel R, Solatikia F, Zhang H, Wolde A, Kadalayil L, Karmaus W, Ewart S, Arathimos R, Relton C, Ring S, Henderson AJ, Arshad SH, Holloway JW. Sex-specific associations of asthma acquisition with changes in DNA methylation during adolescence. Clin Exp Allergy 2020; 51:318-328. [PMID: 33150670 DOI: 10.1111/cea.13776] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2020] [Revised: 09/24/2020] [Accepted: 10/08/2020] [Indexed: 12/11/2022]
Abstract
BACKGROUND Underlying biological mechanisms involved in sex differences in asthma status changes from pre- to post-adolescence are unclear. DNA methylation (DNAm) has been shown to be associated with the risk of asthma. OBJECTIVE We hypothesized that asthma acquisition from pre- to post-adolescence was associated with changes in DNAm during this period at asthma-associated cytosine-phosphate-guanine (CpG) sites and such an association was sex-specific. METHODS Subjects from the Isle of Wight birth cohort (IOWBC) with DNAm in blood at ages 10 and 18 years (n = 124 females, 151 males) were studied. Using a training-testing approach, epigenome-wide CpGs associated with asthma were identified. Logistic regression was used to examine sex-specific associations of DNAm changes with asthma acquisition between ages 10 and 18 at asthma-associated CpGs. The ALSPAC birth cohort was used for independent replication. To assess functional relevance of identified CpGs, association of DNAm with gene expression in blood was assessed. RESULTS We identified 535 CpGs potentially associated with asthma. Significant interaction effects of DNAm changes and sex on asthma acquisition in adolescence were found at 13 of the 535 CpGs in IOWBC (P-values <1.0 × 10-3 ). In the replication cohort, consistent interaction effects were observed at 10 of the 13 CpGs. At 7 of these 10 CpGs, opposite DNAm changes across adolescence were observed between sexes in both cohorts. In both cohorts, cg20891917, located on IFRD1 linked to asthma, shows strong sex-specific effects on asthma transition (P-values <.01 in both cohorts). CONCLUSION AND CLINICAL RELEVANCE Gender reversal in asthma acquisition is associated with opposite changes in DNAm (males vs females) from pre- to post-adolescence at asthma-associated CpGs. These CpGs are potential biomarkers of sex-specific asthma acquisition in adolescence.
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Affiliation(s)
- Rutu Patel
- Division of Epidemiology, Biostatistics and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA
| | - Farnaz Solatikia
- Division of Epidemiology, Biostatistics and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA.,Department of Mathematical Sciences, University of Memphis, Memphis, TN, USA
| | - Hongmei Zhang
- Division of Epidemiology, Biostatistics and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA
| | - Alemayehu Wolde
- Department of Mathematical Sciences, University of Memphis, Memphis, TN, USA
| | - Latha Kadalayil
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Wilfried Karmaus
- Division of Epidemiology, Biostatistics and Environmental Health, School of Public Health, University of Memphis, Memphis, TN, USA
| | - Susan Ewart
- College of Veterinary Medicine, Michigan State University, East Lansing, MI, USA
| | - Ryan Arathimos
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,National Institute for Health Research Bristol Biomedical Research Centre, University of Bristol, University Hospitals Bristol NHS Foundation Trust, Bristol, UK.,Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry Psychology and Neuroscience, King's College London, London, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,National Institute for Health Research Bristol Biomedical Research Centre, University of Bristol, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | - Susan Ring
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.,National Institute for Health Research Bristol Biomedical Research Centre, University of Bristol, University Hospitals Bristol NHS Foundation Trust, Bristol, UK
| | | | - Syed Hasan Arshad
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK.,David Hide Asthma and Allergy Research Centre, Isle of Wight, UK.,NIHR Southampton Biomedical Research Centre, University Hospital Southampton, Southampton, UK
| | - John W Holloway
- Human Development and Health, Faculty of Medicine, University of Southampton, Southampton, UK.,NIHR Southampton Biomedical Research Centre, University Hospital Southampton, Southampton, UK
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McBride N, Yousefi P, White SL, Poston L, Farrar D, Sattar N, Nelson SM, Wright J, Mason D, Suderman M, Relton C, Lawlor DA. Do nuclear magnetic resonance (NMR)-based metabolomics improve the prediction of pregnancy-related disorders? Findings from a UK birth cohort with independent validation. BMC Med 2020; 18:366. [PMID: 33222689 PMCID: PMC7681995 DOI: 10.1186/s12916-020-01819-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 10/19/2020] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND Prediction of pregnancy-related disorders is usually done based on established and easily measured risk factors. Recent advances in metabolomics may provide earlier and more accurate prediction of women at risk of pregnancy-related disorders. METHODS We used data collected from women in the Born in Bradford (BiB; n = 8212) and UK Pregnancies Better Eating and Activity Trial (UPBEAT; n = 859) studies to create and validate prediction models for pregnancy-related disorders. These were gestational diabetes mellitus (GDM), hypertensive disorders of pregnancy (HDP), small for gestational age (SGA), large for gestational age (LGA) and preterm birth (PTB). We used ten-fold cross-validation and penalised regression to create prediction models. We compared the predictive performance of (1) risk factors (maternal age, pregnancy smoking, body mass index (BMI), ethnicity and parity) to (2) nuclear magnetic resonance-derived metabolites (N = 156 quantified metabolites, collected at 24-28 weeks gestation) and (3) combined risk factors and metabolites. The multi-ethnic BiB cohort was used for training and testing the models, with independent validation conducted in UPBEAT, a multi-ethnic study of obese pregnant women. RESULTS Maternal age, pregnancy smoking, BMI, ethnicity and parity were retained in the combined risk factor and metabolite models for all outcomes apart from PTB, which did not include maternal age. In addition, 147, 33, 96, 51 and 14 of the 156 metabolite traits were retained in the combined risk factor and metabolite model for GDM, HDP, SGA, LGA and PTB, respectively. These include cholesterol and triglycerides in very low-density lipoproteins (VLDL) in the models predicting GDM, HDP, SGA and LGA, and monounsaturated fatty acids (MUFA), ratios of MUFA to omega 3 fatty acids and total fatty acids, and a ratio of apolipoprotein B to apolipoprotein A-1 (APOA:APOB1) were retained predictors for GDM and LGA. In BiB, discrimination for GDM, HDP, LGA and SGA was improved in the combined risk factors and metabolites models. Risk factor area under the curve (AUC 95% confidence interval (CI)): GDM (0.69 (0.64, 0.73)), HDP (0.74 (0.70, 0.78)) and LGA (0.71 (0.66, 0.75)), and SGA (0.59 (0.56, 0.63)). Combined risk factor and metabolite models AUC 95% (CI): GDM (0.78 (0.74, 0.81)), HDP (0.76 (0.73, 0.79)) and LGA (0.75 (0.70, 0.79)), and SGA (0.66 (0.63, 0.70)). For GDM, HDP and LGA, but not SGA, calibration was good for a combined risk factor and metabolite model. Prediction of PTB was poor for all models. Independent validation in UPBEAT at 24-28 weeks and 15-18 weeks gestation confirmed similar patterns of results, but AUCs were attenuated. CONCLUSIONS Our results suggest a combined risk factor and metabolite model improves prediction of GDM, HDP and LGA, and SGA, when compared to risk factors alone. They also highlight the difficulty of predicting PTB, with all models performing poorly.
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Affiliation(s)
- Nancy McBride
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK. .,NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK. .,Population Health Sciences, University of Bristol, Bristol, UK.
| | - Paul Yousefi
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.,Population Health Sciences, University of Bristol, Bristol, UK
| | - Sara L White
- Department of Women and Children's Health, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Lucilla Poston
- Department of Women and Children's Health, Faculty of Life Sciences and Medicine, King's College London, London, UK
| | - Diane Farrar
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Naveed Sattar
- NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK.,Cardiovascular and Medical Sciences, British Heart Foundation Glasgow, Cardiovascular Research Centre, University of Glasgow, Glasgow, UK.,School of Medicine, University of Glasgow, Glasgow, UK
| | - Scott M Nelson
- NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK.,Cardiovascular and Medical Sciences, British Heart Foundation Glasgow, Cardiovascular Research Centre, University of Glasgow, Glasgow, UK.,School of Medicine, University of Glasgow, Glasgow, UK
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Dan Mason
- Bradford Institute for Health Research, Bradford Teaching Hospitals NHS Foundation Trust, Bradford, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.,Population Health Sciences, University of Bristol, Bristol, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.,Population Health Sciences, University of Bristol, Bristol, UK
| | - Deborah A Lawlor
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.,NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK.,Population Health Sciences, University of Bristol, Bristol, UK
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36
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Relton C, Crowder M, Blake M, Strong M. Fresh street: the development and feasibility of a place-based, subsidy for fresh fruit and vegetables. J Public Health (Oxf) 2020; 44:184-191. [PMID: 33164095 PMCID: PMC8904189 DOI: 10.1093/pubmed/fdaa190] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 08/10/2020] [Accepted: 09/25/2020] [Indexed: 11/26/2022] Open
Abstract
Background Many UK communities experience food insecurity, and consume diets high in energy-dense, nutrient poor, processed foods and low in fruit and vegetables (FV). We explored a novel area-based approach to promote FV consumption and healthy eating in one such community. Methods We developed a weekly subsidy scheme for fresh FV with key local stakeholders in an area of socioeconomic deprivation in Northern England. The scheme (Fresh Street) offered five £1 vouchers to every household, regardless of income or household type. Vouchers were redeemable with local suppliers of fresh FV (not supermarkets). The feasibility of the scheme was assessed in four streets using rapid ethnographic assessment and voucher redemption information. Results Local councillors and public health teams were supportive of the scheme. Most eligible households joined the scheme (n = 80/97, 83%), and 89.3% (17 849/19 982) of vouchers issued were redeemed. Householders reported that the scheme made them think about what they were eating, and prompted them to buy and eat more FV. Conclusions This feasibility study reported high levels of acceptance for a place-based, household-level weekly FV subsidy scheme. Further research is required to evaluate the effectiveness of this approach to creating healthy diets, eating behaviours and food systems.
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Affiliation(s)
- C Relton
- Institute of Population Health Sciences, Queen Mary University of London, London E1 2AB, UK.,School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
| | - M Crowder
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
| | - M Blake
- Department of Geography, University of Sheffield, Sheffield, UK
| | - M Strong
- School of Health and Related Research, University of Sheffield, Sheffield S1 4DA, UK
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37
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Sharp TH, McBride NS, Howell AE, Evans CJ, Jones DK, Perry G, Dimitriadis SI, Lancaster TM, Zuccolo L, Relton C, Matthews SM, Breeze T, David AS, Drakesmith M, Linden DEJ, Paus T, Walton E. Population neuroimaging: generation of a comprehensive data resource within the ALSPAC pregnancy and birth cohort. Wellcome Open Res 2020; 5:203. [PMID: 33043145 PMCID: PMC7531050 DOI: 10.12688/wellcomeopenres.16060.1] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/20/2020] [Indexed: 11/20/2022] Open
Abstract
Neuroimaging offers a valuable insight into human brain development by allowing in vivo assessment of structure, connectivity and function. Multimodal neuroimaging data have been obtained as part of three sub-studies within the Avon Longitudinal Study of Parents and Children, a prospective multigenerational pregnancy and birth cohort based in the United Kingdom. Brain imaging data were acquired when offspring were between 18 and 24 years of age, and included acquisition of structural, functional and magnetization transfer magnetic resonance, diffusion tensor, and magnetoencephalography imaging. This resource provides a unique opportunity to combine neuroimaging data with extensive phenotypic and genotypic measures from participants, their mothers, and fathers.
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Affiliation(s)
- Tamsin H Sharp
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, BS8 2BN, UK
| | - Nancy S McBride
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, BS8 2BN, UK
| | - Amy E Howell
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, BS8 2BN, UK
| | - C John Evans
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, CF24 4HQ, UK
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, CF24 4HQ, UK
| | - Gavin Perry
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, CF24 4HQ, UK
| | - Stavros I Dimitriadis
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, CF24 4HQ, UK
| | - Thomas M Lancaster
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, CF24 4HQ, UK
| | - Luisa Zuccolo
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, BS8 2BN, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, BS8 2BN, UK
| | - Sarah M Matthews
- ALSPAC, Population Health Sciences, Bristol Medical School, University of Bristol, University of Bristol, Bristol, BS8 2BN, UK
| | - Thomas Breeze
- ALSPAC, Population Health Sciences, Bristol Medical School, University of Bristol, University of Bristol, Bristol, BS8 2BN, UK
| | - Anthony S David
- Institute of Mental Health, University College London Medical School, London, W1T 7NF, UK
| | - Mark Drakesmith
- Cardiff University Brain Research Imaging Centre (CUBRIC), School of Psychology, Cardiff University, Cardiff, CF24 4HQ, UK
| | - David E J Linden
- MRC Centre for Neuropsychiatric Genetics and Genomics, Division of Psychological Medicine and Clinical Neurosciences, Cardiff University, Cardiff, CF24 4HQ, UK
| | - Tomas Paus
- Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital and Departments of Psychology and Psychiatry, University of Toronto, Ontario, M4G 1R8, Canada
| | - Esther Walton
- MRC Integrative Epidemiology Unit, Population Health Sciences, University of Bristol, Bristol, BS8 2BN, UK.,Department of Psychology, University of Bath, Bath, BA2 7AY, UK
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38
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Russell AE, Ford T, Gunnell D, Heron J, Joinson C, Moran P, Relton C, Suderman M, Hemani G, Mars B. Investigating evidence for a causal association between inflammation and self-harm: A multivariable Mendelian Randomisation study. Brain Behav Immun 2020; 89:43-50. [PMID: 32473944 PMCID: PMC7575900 DOI: 10.1016/j.bbi.2020.05.065] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/23/2020] [Revised: 05/11/2020] [Accepted: 05/24/2020] [Indexed: 02/07/2023] Open
Abstract
BACKGROUND The causal role of inflammatory markers on self-harm and suicidal risk has been studied using observational data, with conflicting results. Confounding and reverse causation can lead to bias, so we appraised question from a genetic perspective to protect against these biases. We measured associations between genetic liability for high levels of inflammatory markers Interleukin-6 (IL-6) and C-reactive protein (CRP) on self-harm, and conducted a secondary analysis restricted to self-harm with suicidal intent. METHODS We conducted two sample and multivariable Mendelian randomisation (MR) to assess the effects of IL-6 and CRP on self-harm utilising existing data and conducting new genome wide association studies to instrument IL-6 and CRP, and for the outcome of self-harm. RESULTS No single nucleotide polymorphisms (SNPs) reached genome-wide significance for self-harm, however 193 SNPs met suggestive significance levels (p < 5 × 10-6). We found no evidence of an association between our instruments for IL-6 and self-harm in the two-sample MR, however we found an inverse association between instruments for CRP and self-harm, indicating that higher levels of circulating CRP may protect against self-harm (inverse variance weighted OR 0.92, 95%CI 0.84, 1.01, p = 0.08; MR Egger OR 0.86, 95% CI 0.74, 1.00, p = 0.05). The direct effect estimate for IL-6 was slightly smaller in the multivariable MR than in the two sample MR, while the CRP effect estimates were consistent with the two sample MR (OR 0.92, SE 1.05, p = 0.09). CONCLUSIONS Our findings are conflicting and indicate that IL-6 and CRP are not robust etiological markers of increased self-harm or suicide risk.
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Affiliation(s)
- Abigail Emma Russell
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, United Kingdom.
| | - Tamsin Ford
- University of Cambridge, Department of Psychiatry, United Kingdom
| | - David Gunnell
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, United Kingdom; NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, United Kingdom
| | - Jon Heron
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, United Kingdom
| | - Carol Joinson
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, United Kingdom
| | - Paul Moran
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, United Kingdom; NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, United Kingdom
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol Medical School, Population Health Sciences, University of Bristol Medical School, United Kingdom
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, University of Bristol Medical School, Population Health Sciences, University of Bristol Medical School, United Kingdom
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit, University of Bristol Medical School, Population Health Sciences, University of Bristol Medical School, United Kingdom
| | - Becky Mars
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, United Kingdom; NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, United Kingdom
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Langdon R, Richmond R, Elliott HR, Dudding T, Kazmi N, Penfold C, Ingarfield K, Ho K, Bretherick A, Haley C, Zeng Y, Walker RM, Pawlita M, Waterboer T, Gaunt T, Smith GD, Suderman M, Thomas S, Ness A, Relton C. Identifying epigenetic biomarkers of established prognostic factors and survival in a clinical cohort of individuals with oropharyngeal cancer. Clin Epigenetics 2020; 12:95. [PMID: 32600451 PMCID: PMC7322918 DOI: 10.1186/s13148-020-00870-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Accepted: 05/19/2020] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND Smoking status, alcohol consumption and HPV infection (acquired through sexual activity) are the predominant risk factors for oropharyngeal cancer and are thought to alter the prognosis of the disease. Here, we conducted single-site and differentially methylated region (DMR) epigenome-wide association studies (EWAS) of these factors, in addition to ∼ 3-year survival, using Illumina Methylation EPIC DNA methylation profiles from whole blood in 409 individuals as part of the Head and Neck 5000 (HN5000) study. Overlapping sites between each factor and survival were then assessed using two-step Mendelian randomization to assess whether methylation at these positions causally affected survival. RESULTS Using the MethylationEPIC array in an OPC dataset, we found novel CpG associations with smoking, alcohol consumption and ~ 3-year survival. We found no CpG associations below our multiple testing threshold associated with HPV16 E6 serological response (used as a proxy for HPV infection). CpG site associations below our multiple-testing threshold (PBonferroni < 0.05) for both a prognostic factor and survival were observed at four gene regions: SPEG (smoking), GFI1 (smoking), PPT2 (smoking) and KHDC3L (alcohol consumption). Evidence for a causal effect of DNA methylation on survival was only observed in the SPEG gene region (HR per SD increase in methylation score 1.28, 95% CI 1.14 to 1.43, P 2.12 × 10-05). CONCLUSIONS Part of the effect of smoking on survival in those with oropharyngeal cancer may be mediated by methylation at the SPEG gene locus. Replication in data from independent datasets and data from HN5000 with longer follow-up times is needed to confirm these findings.
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Affiliation(s)
- Ryan Langdon
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Rebecca Richmond
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Hannah R. Elliott
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Tom Dudding
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Nabila Kazmi
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Chris Penfold
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
| | - Kate Ingarfield
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
| | - Karen Ho
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Andrew Bretherick
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Scotland Bristol, EH4 2XU UK
| | - Chris Haley
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Scotland Bristol, EH4 2XU UK
| | - Yanni Zeng
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Scotland Bristol, EH4 2XU UK
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
- Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Rosie M. Walker
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - Michael Pawlita
- Infections and Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tim Waterboer
- Infections and Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tom Gaunt
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Steve Thomas
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
| | - Andy Ness
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
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40
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Howell AE, Robinson JW, Wootton RE, McAleenan A, Tsavachidis S, Ostrom QT, Bondy M, Armstrong G, Relton C, Haycock P, Martin RM, Zheng J, Kurian KM. Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study. BMC Cancer 2020; 20:508. [PMID: 32493226 PMCID: PMC7268455 DOI: 10.1186/s12885-020-06967-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2019] [Accepted: 05/17/2020] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Whilst epidemiological studies have provided evidence of associations between certain risk factors and glioma onset, inferring causality has proven challenging. Using Mendelian randomization (MR), we assessed whether associations of 36 reported glioma risk factors showed evidence of a causal relationship. METHODS We performed a systematic search of MEDLINE from inception to October 2018 to identify candidate risk factors and conducted a meta-analysis of two glioma genome-wide association studies (5739 cases and 5501 controls) to form our exposure and outcome datasets. MR analyses were performed using genetic variants to proxy for candidate risk factors. We investigated whether risk factors differed by subtype diagnosis (either glioblastoma (n = 3112) or non-glioblastoma (n = 2411)). MR estimates for each risk factor were determined using multiplicative random effects inverse-variance weighting (IVW). Sensitivity analyses investigated potential pleiotropy using MR-Egger regression, the weighted median estimator, and the mode-based estimator. To increase power, trait-specific polygenic risk scores were used to test the association of a genetically predicated increase in each risk factor with glioma onset. RESULTS Our systematic search identified 36 risk factors that could be proxied using genetic variants. Using MR, we found evidence that four genetically predicted traits increased risk of glioma, glioblastoma or non-glioblastoma: longer leukocyte telomere length, liability to allergic disease, increased alcohol consumption and liability to childhood extreme obesity (> 3 standard deviations from the mean). Two traits decreased risk of non-glioblastoma cancers: increased low-density lipoprotein cholesterol (LDLc) and triglyceride levels. Our findings were similar across sensitivity analyses that made allowance for pleiotropy (genetic confounding). CONCLUSIONS Our comprehensive investigation provides evidence of a causal link between both genetically predicted leukocyte telomere length, allergic disease, alcohol consumption, childhood extreme obesity, and LDLc and triglyceride levels, and glioma. The findings from our study warrant further research to uncover mechanisms that implicate these traits in glioma onset.
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Affiliation(s)
- A E Howell
- Brain Tumour Research Centre, Institute of Clinical Neurosciences, University of Bristol, Bristol, UK
| | - J W Robinson
- Brain Tumour Research Centre, Institute of Clinical Neurosciences, University of Bristol, Bristol, UK
| | - R E Wootton
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- School of Psychological Science, University of Bristol, Bristol, UK
- NIHR Biomedical Research Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, BS8 2BN, UK
| | - A McAleenan
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - S Tsavachidis
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX, UK
| | - Q T Ostrom
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX, UK
| | - M Bondy
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX, UK
| | - G Armstrong
- Section of Epidemiology and Population Sciences, Department of Medicine, Baylor College of Medicine, Houston, TX, UK
| | - C Relton
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - P Haycock
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - R M Martin
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
- The National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK
| | - J Zheng
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS8 2BN, UK.
| | - K M Kurian
- Brain Tumour Research Centre, Institute of Clinical Neurosciences, University of Bristol, Bristol, UK.
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Huang JY, Larose TL, Wang R, Fanidi A, Alcala K, Stevens VL, Weinstein SJ, Albanes D, Caporaso N, Purdue M, Zeigler R, Freedman N, Lan Q, Prentice R, Pettinger M, Thomsen CA, Cai Q, Wu J, Blot WJ, Shu XO, Zheng W, Arslan AA, Zeleniuch-Jacquotte A, Le Marchand L, Wilkens LR, Haiman CA, Zhang X, Stampfer M, Smith-Warner S, Han J, Giles GG, Hodge AM, Severi G, Johansson M, Grankvist K, Langhammer A, Hveem K, Xiang YB, Li HL, Gao YT, Visvanathan K, Bolton JH, Ueland PM, Midttun Ø, Ulvik A, Buring JE, Lee IM, Sesso HD, Gaziano JM, Manjer J, Relton C, Koh WP, Brennan P, Johansson M, Yuan JM. Circulating markers of cellular immune activation in prediagnostic blood sample and lung cancer risk in the Lung Cancer Cohort Consortium (LC3). Int J Cancer 2020; 146:2394-2405. [PMID: 31276202 PMCID: PMC6960354 DOI: 10.1002/ijc.32555] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2019] [Revised: 05/21/2019] [Accepted: 06/14/2019] [Indexed: 01/08/2023]
Abstract
Cell-mediated immune suppression may play an important role in lung carcinogenesis. We investigated the associations for circulating levels of tryptophan, kynurenine, kynurenine:tryptophan ratio (KTR), quinolinic acid (QA) and neopterin as markers of immune regulation and inflammation with lung cancer risk in 5,364 smoking-matched case-control pairs from 20 prospective cohorts included in the international Lung Cancer Cohort Consortium. All biomarkers were quantified by mass spectrometry-based methods in serum/plasma samples collected on average 6 years before lung cancer diagnosis. Odds ratios (ORs) and 95% confidence intervals (CIs) for lung cancer associated with individual biomarkers were calculated using conditional logistic regression with adjustment for circulating cotinine. Compared to the lowest quintile, the highest quintiles of kynurenine, KTR, QA and neopterin were associated with a 20-30% higher risk, and tryptophan with a 15% lower risk of lung cancer (all ptrend < 0.05). The strongest associations were seen for current smokers, where the adjusted ORs (95% CIs) of lung cancer for the highest quintile of KTR, QA and neopterin were 1.42 (1.15-1.75), 1.42 (1.14-1.76) and 1.45 (1.13-1.86), respectively. A stronger association was also seen for KTR and QA with risk of lung squamous cell carcinoma followed by adenocarcinoma, and for lung cancer diagnosed within the first 2 years after blood draw. This study demonstrated that components of the tryptophan-kynurenine pathway with immunomodulatory effects are associated with risk of lung cancer overall, especially for current smokers. Further research is needed to evaluate the role of these biomarkers in lung carcinogenesis and progression.
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Affiliation(s)
- Joyce Yongxu Huang
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Tricia L. Larose
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health & Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
| | - Renwei Wang
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Anouar Fanidi
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Karine Alcala
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Victoria L. Stevens
- Epidemiology Research Program, American Cancer Society, Inc. 250 Williams St. Atlanta, GA 30303
| | | | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
| | - Neil Caporaso
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
| | - Mark Purdue
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
| | - Regina Zeigler
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
| | - Neal Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
| | - Qin Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH
| | - Ross Prentice
- Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, Seattle, Washington 98109, U.S.A
| | - Mary Pettinger
- Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, Seattle, Washington 98109, U.S.A
| | - Cynthia A. Thomsen
- Department of Health Promotion Science, Mel & Enid Zuckerman College of Public Health, University of Arizona, Tucson, AZ, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Jie Wu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - William J. Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Alan A. Arslan
- Departments of Obstetrics and Gynecology, Population Health, Environmental Medicine and Perlmutter Cancer Center, New York University School of Medicine, New York, NY
| | - Anne Zeleniuch-Jacquotte
- Departments of Population Health and Environmental Medicine and Perlmutter Cancer Centre, New York University School of Medicine, New York, NY, USA
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Lynn R. Wilkens
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Christopher A. Haiman
- Department of Prevention, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Xuehong Zhang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
| | - Meir Stampfer
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Stephanie Smith-Warner
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jiali Han
- Department of Epidemiology, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA
| | - Graham G Giles
- Cancer Epidemiology Center, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
| | - Allison M Hodge
- Cancer Epidemiology Center, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
| | - Gianluca Severi
- Cancer Epidemiology Center, Cancer Council Victoria, Melbourne, Australia
- Italian Institute for Genomic Medicine (IIGM), Torino, Italy
- Centre de Recherche en Epidemiologie et Santé des Populations (CESP) UMR1018 Inserm, Facultés de Médicine Université Paris-Saclay, UPS, UVSQ, Gustave Roussy, 94805, Villejuif, France
| | - Mikael Johansson
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - Kjell Grankvist
- Department of Medical Biosciences, Clinical Chemistry, Umeå University, Umeå, Sweden
| | - Arnulf Langhammer
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Kristian Hveem
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health & Nursing, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway
| | - Yong-Bing Xiang
- Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Hong-Lan Li
- Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Kala Visvanathan
- George W Comstock Center for Public Health Research and Prevention Health Monitoring Unit, Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, USA
| | - Judy Hoffman Bolton
- George W Comstock Center for Public Health Research and Prevention Health Monitoring Unit, Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, USA
| | - Per M Ueland
- Department of Clinical Science, University of Bergen, Bergen, Norway
- Laboratory of Clinical Biochemistry, Haukeland University Hospital, Bergen, Norway
| | | | | | - Julie E. Buring
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - I-Min Lee
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - Howard D. Sesso
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
| | - J. Michael Gaziano
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
- Division of Aging, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA, USA
- Boston VA Medical Center, Boston, MA USA
| | - Jonas Manjer
- Department of Surgery, Skåne University Hospital Malmö Lund University, Malmö Sweden
| | - Caroline Relton
- Institute of Genetic Medicine, Newcastle University, Newcastle, United Kingdom
- MRC Integrative Epidemiology Unit, School of Social & Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Woon-Puay Koh
- Health Services and Systems Research, Duke-NUS Medical School, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Paul Brennan
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Mattias Johansson
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
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Langdon RJ, Beynon RA, Ingarfield K, Marioni RE, McCartney DL, Martin RM, Ness AR, Pawlita M, Waterboer T, Relton C, Thomas SJ, Richmond RC. Epigenetic prediction of complex traits and mortality in a cohort of individuals with oropharyngeal cancer. Clin Epigenetics 2020; 12:58. [PMID: 32321578 PMCID: PMC7178612 DOI: 10.1186/s13148-020-00850-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2020] [Accepted: 04/08/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND DNA methylation (DNAm) variation is an established predictor for several traits. In the context of oropharyngeal cancer (OPC), where 5-year survival is ~ 65%, DNA methylation may act as a prognostic biomarker. We examined the accuracy of DNA methylation biomarkers of 4 complex exposure traits (alcohol consumption, body mass index [BMI], educational attainment and smoking status) in predicting all-cause mortality in people with OPC. RESULTS DNAm predictors of alcohol consumption, BMI, educational attainment and smoking status were applied to 364 individuals with OPC in the Head and Neck 5000 cohort (HN5000; 19.6% of total OPC cases in the study), followed up for median 3.9 years; inter-quartile range (IQR) 3.3 to 5.2 years (time-to-event-death or censor). The proportion of phenotypic variance explained in each trait was as follows: 16.5% for alcohol consumption, 22.7% for BMI, 0.4% for educational attainment and 51.1% for smoking. We then assessed the relationship between each DNAm predictor and all-cause mortality using Cox proportional-hazard regression analysis. DNAm prediction of smoking was most consistently associated with mortality risk (hazard ratio [HR], 1.38 per standard deviation (SD) increase in smoking DNAm score; 95% confidence interval [CI] 1.04 to 1.83; P 0.025, in a model adjusted for demographic, lifestyle, health and biological variables). Finally, we examined the accuracy of each DNAm predictor of mortality. DNAm predictors explained similar levels of variance in mortality to self-reported phenotypes. Receiver operator characteristic (ROC) curves for the DNAm predictors showed a moderate discrimination of alcohol consumption (area under the curve [AUC] 0.63), BMI (AUC 0.61) and smoking (AUC 0.70) when predicting mortality. The DNAm predictor for education showed poor discrimination (AUC 0.57). Z tests comparing AUCs between self-reported phenotype ROC curves and DNAm score ROC curves did not show evidence for difference between the two (alcohol consumption P 0.41, BMI P 0.62, educational attainment P 0.49, smoking P 0.19). CONCLUSIONS In the context of a clinical cohort of individuals with OPC, DNAm predictors for smoking, alcohol consumption, educational attainment and BMI exhibit similar predictive values for all-cause mortality compared to self-reported data. These findings may have translational utility in prognostic model development, particularly where phenotypic data are not available.
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Affiliation(s)
- Ryan J Langdon
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Rhona A Beynon
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Kate Ingarfield
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
- Centre for Trials Research, Neuadd Meirionnydd, Heath Park Way, Cardiff, UK
- Community Oral Health, University of Glasgow Dental School, Sauchiehall Street, Glasgow, UK
| | - Riccardo E Marioni
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, Scotland, EH4 2XU, UK
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Daniel L McCartney
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh, Scotland, EH4 2XU, UK
- Medical Genetics Section, Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Richard M Martin
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
| | - Andy R Ness
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
| | - Michael Pawlita
- Infections and Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Tim Waterboer
- Infections and Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Caroline Relton
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
| | - Steven J Thomas
- NIHR Bristol Biomedical Research Centre, University Hospitals Bristol and University of Bristol, Bristol, UK
| | - Rebecca C Richmond
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
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43
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Jamieson E, Korologou-Linden R, Wootton RE, Guyatt AL, Battram T, Burrows K, Gaunt TR, Tobin MD, Munafò M, Davey Smith G, Tilling K, Relton C, Richardson TG, Richmond RC. Smoking, DNA Methylation, and Lung Function: a Mendelian Randomization Analysis to Investigate Causal Pathways. Am J Hum Genet 2020; 106:315-326. [PMID: 32084330 PMCID: PMC7058834 DOI: 10.1016/j.ajhg.2020.01.015] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Accepted: 01/21/2020] [Indexed: 12/18/2022] Open
Abstract
Whether smoking-associated DNA methylation has a causal effect on lung function has not been thoroughly evaluated. We first investigated the causal effects of 474 smoking-associated CpGs on forced expiratory volume in 1 s (FEV1) in UK Biobank (n = 321,047) by using two-sample Mendelian randomization (MR) and then replicated this investigation in the SpiroMeta Consortium (n = 79,055). Second, we used two-step MR to investigate whether DNA methylation mediates the effect of smoking on FEV1. Lastly, we evaluated the presence of horizontal pleiotropy and assessed whether there is any evidence for shared causal genetic variants between lung function, DNA methylation, and gene expression by using a multiple-trait colocalization ("moloc") framework. We found evidence of a possible causal effect for DNA methylation on FEV1 at 18 CpGs (p < 1.2 × 10-4). Replication analysis supported a causal effect at three CpGs (cg21201401 [LIME1 and ZGPAT], cg19758448 [PGAP3], and cg12616487 [EML3 and AHNAK] [p < 0.0028]). DNA methylation did not clearly mediate the effect of smoking on FEV1, although DNA methylation at some sites might influence lung function via effects on smoking. By using "moloc", we found evidence of shared causal variants between lung function, gene expression, and DNA methylation. These findings highlight potential therapeutic targets for improving lung function and possibly smoking cessation, although larger, tissue-specific datasets are required to confirm these results.
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Affiliation(s)
- Emily Jamieson
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Roxanna Korologou-Linden
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Robyn E Wootton
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; School of Psychological Science, University of Bristol, 12a Priory Road, Bristol BS8 1TU, UK; National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol National Health Service Foundation Trust and University of Bristol, Bristol, UK
| | - Anna L Guyatt
- Department of Health Sciences, University of Leicester, University Road, Leicester LE1 7RH, UK
| | - Thomas Battram
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Kimberley Burrows
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Tom R Gaunt
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol National Health Service Foundation Trust and University of Bristol, Bristol, UK
| | - Martin D Tobin
- Department of Health Sciences, University of Leicester, University Road, Leicester LE1 7RH, UK
| | - Marcus Munafò
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; School of Psychological Science, University of Bristol, 12a Priory Road, Bristol BS8 1TU, UK; National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol National Health Service Foundation Trust and University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; National Institute for Health Research Bristol Biomedical Research Centre, University Hospitals Bristol National Health Service Foundation Trust and University of Bristol, Bristol, UK
| | - Kate Tilling
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Caroline Relton
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Tom G Richardson
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK
| | - Rebecca C Richmond
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, UK.
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Howey R, Shin SY, Relton C, Davey Smith G, Cordell HJ. Bayesian network analysis incorporating genetic anchors complements conventional Mendelian randomization approaches for exploratory analysis of causal relationships in complex data. PLoS Genet 2020; 16:e1008198. [PMID: 32119656 PMCID: PMC7067488 DOI: 10.1371/journal.pgen.1008198] [Citation(s) in RCA: 29] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2019] [Revised: 03/12/2020] [Accepted: 01/21/2020] [Indexed: 12/26/2022] Open
Abstract
Mendelian randomization (MR) implemented through instrumental variables analysis is an increasingly popular causal inference tool used in genetic epidemiology. But it can have limitations for evaluating simultaneous causal relationships in complex data sets that include, for example, multiple genetic predictors and multiple potential risk factors associated with the same genetic variant. Here we use real and simulated data to investigate Bayesian network analysis (BN) with the incorporation of directed arcs, representing genetic anchors, as an alternative approach. A Bayesian network describes the conditional dependencies/independencies of variables using a graphical model (a directed acyclic graph) with an accompanying joint probability. In real data, we found BN could be used to infer simultaneous causal relationships that confirmed the individual causal relationships suggested by bi-directional MR, while allowing for the existence of potential horizontal pleiotropy (that would violate MR assumptions). In simulated data, BN with two directional anchors (mimicking genetic instruments) had greater power for a fixed type 1 error than bi-directional MR, while BN with a single directional anchor performed better than or as well as bi-directional MR. Both BN and MR could be adversely affected by violations of their underlying assumptions (such as genetic confounding due to unmeasured horizontal pleiotropy). BN with no directional anchor generated inference that was no better than by chance, emphasizing the importance of directional anchors in BN (as in MR). Under highly pleiotropic simulated scenarios, BN outperformed both MR (and its recent extensions) and two recently-proposed alternative approaches: a multi-SNP mediation intersection-union test (SMUT) and a latent causal variable (LCV) test. We conclude that BN incorporating genetic anchors is a useful complementary method to conventional MR for exploring causal relationships in complex data sets such as those generated from modern "omics" technologies.
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Affiliation(s)
- Richard Howey
- Institute of Genetic Medicine, Newcastle University, Newcastle, United Kingdom
| | - So-Youn Shin
- Institute of Genetic Medicine, Newcastle University, Newcastle, United Kingdom
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, United Kingdom
- Population Health Sciences, University of Bristol, Bristol, United Kingdom
| | - Heather J. Cordell
- Institute of Genetic Medicine, Newcastle University, Newcastle, United Kingdom
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45
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Kachuri L, Johansson M, Rashkin SR, Graff RE, Bossé Y, Manem V, Caporaso NE, Landi MT, Christiani DC, Vineis P, Liu G, Scelo G, Zaridze D, Shete SS, Albanes D, Aldrich MC, Tardón A, Rennert G, Chen C, Goodman GE, Doherty JA, Bickeböller H, Field JK, Davies MP, Dawn Teare M, Kiemeney LA, Bojesen SE, Haugen A, Zienolddiny S, Lam S, Le Marchand L, Cheng I, Schabath MB, Duell EJ, Andrew AS, Manjer J, Lazarus P, Arnold S, McKay JD, Emami NC, Warkentin MT, Brhane Y, Obeidat M, Martin RM, Relton C, Davey Smith G, Haycock PC, Amos CI, Brennan P, Witte JS, Hung RJ. Immune-mediated genetic pathways resulting in pulmonary function impairment increase lung cancer susceptibility. Nat Commun 2020; 11:27. [PMID: 31911640 PMCID: PMC6946810 DOI: 10.1038/s41467-019-13855-2] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2019] [Accepted: 11/29/2019] [Indexed: 02/07/2023] Open
Abstract
Impaired lung function is often caused by cigarette smoking, making it challenging to disentangle its role in lung cancer susceptibility. Investigation of the shared genetic basis of these phenotypes in the UK Biobank and International Lung Cancer Consortium (29,266 cases, 56,450 controls) shows that lung cancer is genetically correlated with reduced forced expiratory volume in one second (FEV1: rg = 0.098, p = 2.3 × 10-8) and the ratio of FEV1 to forced vital capacity (FEV1/FVC: rg = 0.137, p = 2.0 × 10-12). Mendelian randomization analyses demonstrate that reduced FEV1 increases squamous cell carcinoma risk (odds ratio (OR) = 1.51, 95% confidence intervals: 1.21-1.88), while reduced FEV1/FVC increases the risk of adenocarcinoma (OR = 1.17, 1.01-1.35) and lung cancer in never smokers (OR = 1.56, 1.05-2.30). These findings support a causal role of pulmonary impairment in lung cancer etiology. Integrative analyses reveal that pulmonary function instruments, including 73 novel variants, influence lung tissue gene expression and implicate immune-related pathways in mediating the observed effects on lung carcinogenesis.
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Affiliation(s)
- Linda Kachuri
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada
| | | | - Sara R Rashkin
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Rebecca E Graff
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Yohan Bossé
- Institut universitaire de cardiologie et de pneumologie de Québec - Université Laval, Quebec City, Canada
| | - Venkata Manem
- Institut universitaire de cardiologie et de pneumologie de Québec - Université Laval, Quebec City, Canada
| | - Neil E Caporaso
- Division of Cancer Epidemiology & Genetics, US NCI, Bethesda, MD, USA
| | | | - David C Christiani
- Departments of Environmental Health and Epidemiology, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Paolo Vineis
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Geoffrey Liu
- Princess Margaret Cancer Center, University Health Network, Toronto, ON, Canada
| | | | - David Zaridze
- Russian N.N. Blokhin Cancer Research Centre, Moscow, Russian Federation
| | - Sanjay S Shete
- Department of Biostatistics, Division of Basic Sciences, MD Anderson Cancer Center, Houston, TX, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology & Genetics, US NCI, Bethesda, MD, USA
| | - Melinda C Aldrich
- Department of Thoracic Surgery and Division of Epidemiology, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Adonina Tardón
- Faculty of Medicine, University of Oviedo and ISPA and CIBERESP, Campus del Cristo, Oviedo, Spain
| | - Gad Rennert
- Clalit National Cancer Control Center, Technion Faculty of Medicine, Haifa, Israel
| | - Chu Chen
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Gary E Goodman
- Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Jennifer A Doherty
- Department of Population Health Sciences, Huntsman Cancer Institute, Salt Lake City, UT, USA
| | - Heike Bickeböller
- Department of Genetic Epidemiology, University Medical Center, Georg-August-Universität Göttingen, Göttingen, Germany
| | - John K Field
- Roy Castle Lung Cancer Research Programme, Department of Molecular and Clinical Cancer Medicine, The University of Liverpool, London, UK
| | - Michael P Davies
- Roy Castle Lung Cancer Research Programme, Department of Molecular and Clinical Cancer Medicine, The University of Liverpool, London, UK
| | - M Dawn Teare
- Biostatistics Research Group, Institute of Health and Society, Newcastle University, Newcastle upon Tyne, UK
| | - Lambertus A Kiemeney
- Radboud Institute for Health Sciences, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Stig E Bojesen
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Aage Haugen
- The National Institute of Occupational Health, Oslo, Norway
| | | | | | - Loïc Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Iona Cheng
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Matthew B Schabath
- Department of Cancer Epidemiology, H. Lee Moffitt Cancer Center & Research Institute, Tampa, FL, USA
| | - Eric J Duell
- Unit of Biomarkers and Susceptibility, Oncology Data Analytics Program, Catalan Institute of Oncology (ICO), Bellvitge Biomedical Research Institute (IDIBELL), Barcelona, Spain
| | - Angeline S Andrew
- Department of Epidemiology, Geisel School of Medicine, Dartmouth College, Hanover, NH, USA
| | - Jonas Manjer
- Skåne University Hospital, Lund University, Lund, Sweden
| | - Philip Lazarus
- Department of Pharmaceutical Sciences, College of Pharmacy and Pharmaceutical Sciences, Washington State University, Spokane, WA, USA
| | - Susanne Arnold
- Markey Cancer Center, University of Kentucky, Lexington, KY, USA
| | - James D McKay
- International Agency for Research on Cancer, Lyon, France
| | - Nima C Emami
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA
| | - Matthew T Warkentin
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada
- Epidemiology Division, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada
| | - Yonathan Brhane
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada
| | - Ma'en Obeidat
- University of British Columbia, Centre for Heart Lung Innovation, Vancouver, BC, Canada
| | - Richard M Martin
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
- National Institute for Health Research (NIHR) Bristol Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol, Bristol, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Philip C Haycock
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Christopher I Amos
- Institute for Clinical and Translational Research, Baylor College of Medicine, Houston, TX, USA
| | - Paul Brennan
- International Agency for Research on Cancer, Lyon, France
| | - John S Witte
- Department of Epidemiology & Biostatistics, University of California San Francisco, San Francisco, CA, USA.
| | - Rayjean J Hung
- Prosserman Centre for Population Health Research, Lunenfeld-Tanenbaum Research Institute, Sinai Health System, Toronto, ON, Canada.
- Epidemiology Division, Dalla Lana School of Public Health, University of Toronto, Toronto, ON, Canada.
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Yousefi PD, Richmond R, Langdon R, Ness A, Liu C, Levy D, Relton C, Suderman M, Zuccolo L. Validation and characterisation of a DNA methylation alcohol biomarker across the life course. Clin Epigenetics 2019; 11:163. [PMID: 31775873 PMCID: PMC6880546 DOI: 10.1186/s13148-019-0753-7] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Accepted: 09/23/2019] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND Recently, an alcohol predictor was developed using DNA methylation at 144 CpG sites (DNAm-Alc) as a biomarker for improved clinical or epidemiologic assessment of alcohol-related ill health. We validate the performance and characterise the drivers of this DNAm-Alc for the first time in independent populations. RESULTS In N = 1049 parents from the Avon Longitudinal Study of Parents and Children (ALSPAC) Accessible Resource for Integrated Epigenomic Studies (ARIES) at midlife, we found DNAm-Alc explained 7.6% of the variation in alcohol intake, roughly half of what had been reported previously, and interestingly explained a larger 9.8% of Alcohol Use Disorders Identification Test (AUDIT) score, a scale of alcohol use disorder. Explanatory capacity in participants from the offspring generation of ARIES measured during adolescence was much lower. However, DNAm-Alc explained 14.3% of the variation in replication using the Head and Neck 5000 (HN5000) clinical cohort that had higher average alcohol consumption. To investigate whether this relationship was being driven by genetic and/or earlier environment confounding, we examined how earlier versus concurrent DNAm-Alc measures predicted AUDIT scores. In both ARIES parental and offspring generations, we observed associations between AUDIT and concurrent, but not earlier DNAm-Alc, suggesting independence from genetic and stable environmental contributions. CONCLUSIONS The stronger relationship between DNAm-Alcs and AUDIT in parents at midlife compared to adolescents despite similar levels of consumption suggests that DNAm-Alc likely reflects long-term patterns of alcohol abuse. Such biomarkers may have potential applications for biomonitoring and risk prediction, especially in cases where reporting bias is a concern.
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Affiliation(s)
- Paul Darius Yousefi
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK.
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
| | - Rebecca Richmond
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Ryan Langdon
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Andrew Ness
- National Institute of Health Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
- Bristol Dental School, University of Bristol, Bristol, UK
| | - Chunyu Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Daniel Levy
- The Framingham Heart Study, Framingham, MA, USA
- The Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Bethesda, MD, USA
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Luisa Zuccolo
- MRC Integrative Epidemiology Unit, University of Bristol, Oakfield House, Oakfield Grove, Bristol, BS82BN, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
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47
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Odintsova VV, Hagenbeek FA, Suderman M, Caramaschi D, van Beijsterveldt CEM, Kallsen NA, Ehli EA, Davies GE, Sukhikh GT, Fanos V, Relton C, Bartels M, Boomsma DI, van Dongen J. DNA Methylation Signatures of Breastfeeding in Buccal Cells Collected in Mid-Childhood. Nutrients 2019; 11:E2804. [PMID: 31744183 PMCID: PMC6893543 DOI: 10.3390/nu11112804] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Revised: 11/12/2019] [Accepted: 11/12/2019] [Indexed: 12/11/2022] Open
Abstract
Breastfeeding has long-term benefits for children that may be mediated via the epigenome. This pathway has been hypothesized, but the number of empirical studies in humans is small and mostly done by using peripheral blood as the DNA source. We performed an epigenome-wide association study (EWAS) in buccal cells collected around age nine (mean = 9.5) from 1006 twins recruited by the Netherlands Twin Register (NTR). An age-stratified analysis examined if effects attenuate with age (median split at 10 years; n<10 = 517, mean age = 7.9; n>10 = 489, mean age = 11.2). We performed replication analyses in two independent cohorts from the NTR (buccal cells) and the Avon Longitudinal Study of Parents and Children (ALSPAC) (peripheral blood), and we tested loci previously associated with breastfeeding in epigenetic studies. Genome-wide DNA methylation was assessed with the Illumina Infinium MethylationEPIC BeadChip (Illumina, San Diego, CA, USA) in the NTR and with the HumanMethylation450 Bead Chip in the ALSPAC. The duration of breastfeeding was dichotomized ('never' vs. 'ever'). In the total sample, no robustly associated epigenome-wide significant CpGs were identified (α = 6.34 × 10-8). In the sub-group of children younger than 10 years, four significant CpGs were associated with breastfeeding after adjusting for child and maternal characteristics. In children older than 10 years, methylation differences at these CpGs were smaller and non-significant. The findings did not replicate in the NTR sample (n = 98; mean age = 7.5 years), and no nearby sites were associated with breastfeeding in the ALSPAC study (n = 938; mean age = 7.4). Of the CpG sites previously reported in the literature, three were associated with breastfeeding in children younger than 10 years, thus showing that these CpGs are associated with breastfeeding in buccal and blood cells. Our study is the first to show that breastfeeding is associated with epigenetic variation in buccal cells in children. Further studies are needed to investigate if methylation differences at these loci are caused by breastfeeding or by other unmeasured confounders, as well as what mechanism drives changes in associations with age.
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Affiliation(s)
- Veronika V. Odintsova
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands (D.I.B.)
- Amsterdam Public Health Research Institute, 1081 BT Amsterdam, The Netherlands
- Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Moscow 101000, Russia
| | - Fiona A. Hagenbeek
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands (D.I.B.)
- Amsterdam Public Health Research Institute, 1081 BT Amsterdam, The Netherlands
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, Bristol Medical School, Population Health Science, University of Bristol, Bristol BS8 1TH, UK
| | - Doretta Caramaschi
- MRC Integrative Epidemiology Unit, Bristol Medical School, Population Health Science, University of Bristol, Bristol BS8 1TH, UK
| | | | - Noah A. Kallsen
- Avera Institute for Human Genetics, Sioux Falls, SD 57101, USA
| | - Erik A. Ehli
- Avera Institute for Human Genetics, Sioux Falls, SD 57101, USA
| | | | - Gennady T. Sukhikh
- Kulakov National Medical Research Center for Obstetrics, Gynecology and Perinatology, Moscow 101000, Russia
| | - Vassilios Fanos
- Neonatal Intensive Care Unit, Department of Surgical Sciences, AOU and University of Cagliari, 09121 Cagliari, Italy
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, Bristol Medical School, Population Health Science, University of Bristol, Bristol BS8 1TH, UK
| | - Meike Bartels
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands (D.I.B.)
- Amsterdam Public Health Research Institute, 1081 BT Amsterdam, The Netherlands
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands (D.I.B.)
- Amsterdam Public Health Research Institute, 1081 BT Amsterdam, The Netherlands
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, 1081 BT Amsterdam, The Netherlands (D.I.B.)
- Amsterdam Public Health Research Institute, 1081 BT Amsterdam, The Netherlands
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48
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Mills HL, Heron J, Relton C, Suderman M, Tilling K. Methods for Dealing With Missing Covariate Data in Epigenome-Wide Association Studies. Am J Epidemiol 2019; 188:2021-2030. [PMID: 31504104 PMCID: PMC6825836 DOI: 10.1093/aje/kwz186] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2018] [Revised: 08/09/2019] [Accepted: 08/13/2019] [Indexed: 12/15/2022] Open
Abstract
Multiple imputation (MI) is a well-established method for dealing with missing data. MI is computationally intensive when imputing missing covariates with high-dimensional outcome data (e.g., DNA methylation data in epigenome-wide association studies (EWAS)), because every outcome variable must be included in the imputation model to avoid biasing associations towards the null. Instead, EWAS analyses are reduced to only complete cases, limiting statistical power and potentially causing bias. We used simulations to compare 5 MI methods for high-dimensional data under 2 missingness mechanisms. All imputation methods had increased power over complete-case (C-C) analyses. Imputing missing values separately for each variable was computationally inefficient, but dividing sites at random into evenly sized bins improved efficiency and gave low bias. Methods imputing solely using subsets of sites identified by the C-C analysis suffered from bias towards the null. However, if these subsets were added into random bins of sites, this bias was reduced. The optimal methods were applied to an EWAS with missingness in covariates. All methods identified additional sites over the C-C analysis, and many of these sites had been replicated in other studies. These methods are also applicable to other high-dimensional data sets, including the rapidly expanding area of "-omics" studies.
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Affiliation(s)
- Harriet L Mills
- Correspondence to Dr. Harriet L. Mills, MRC Integrative Epidemiology Unit, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol BS8 2BN, United Kingdom (e-mail: )
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49
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Mesirow MSC, Roberts S, Cecil CAM, Maughan B, Jacka FN, Relton C, Barker ED. Serum cholesterol, MTHFR methylation, and symptoms of depression in children. Dev Psychol 2019; 55:2575-2586. [PMID: 31621343 DOI: 10.1037/dev0000831] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Abstract
Depression is associated with dietary factors and epigenetics. Serum cholesterol, which is prone to dietary influences, has been linked to symptoms of depression. This relationship may be (in part) due to altered epigenetic regulation of Methylenetetrahydrofolate Reductase (MTHFR). MTHFR codes for the MTHFR enzyme, which has diverse metabolic functions, and has recently been linked individually with diet, serum cholesterol levels and depressive symptoms. In 514 mother-child pairs, we examined prospective relationships between maternal (pregnancy) and child (7 years) serum cholesterol, MTHFR DNA methylation (DNAm; birth, 7 years), and development of depression symptoms from 8-15 years. After adjusting for potential confounding, we had three main findings. First, higher prenatal cholesterol associated (at a small effect size) with higher MTHFR DNAm at birth. Second, there was small effect size continuity for MTHFR DNAm between birth and age 7. Third, higher age 7 MTHFR DNAm associated with higher initial symptoms of depression symptoms at age 8, again at a small effect size. Overall, our findings provide preliminary evidence for a relationship between prenatal cholesterol, MTHFR DNAm, and symptoms of depression in children. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
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Affiliation(s)
| | - Susanna Roberts
- Department of Psychology, Institute of Psychiatry, Psychology, and Neuroscience
| | - Charlotte A M Cecil
- Department of Psychology, Institute of Psychiatry, Psychology, and Neuroscience
| | | | | | | | - Edward D Barker
- Department of Psychology, Institute of Psychiatry, Psychology, and Neuroscience
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50
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Russell AE, Heron J, Gunnell D, Ford T, Hemani G, Joinson C, Moran P, Relton C, Suderman M, Mars B. Pathways between early-life adversity and adolescent self-harm: the mediating role of inflammation in the Avon Longitudinal Study of Parents and Children. J Child Psychol Psychiatry 2019; 60:1094-1103. [PMID: 31486089 PMCID: PMC6771906 DOI: 10.1111/jcpp.13100] [Citation(s) in RCA: 28] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/25/2019] [Indexed: 12/18/2022]
Abstract
BACKGROUND Adverse childhood experiences (ACEs) such as physical and emotional abuse are strongly associated with self-harm, but mechanisms underlying this relationship are unclear. Inflammation has been linked to both the experience of ACEs and self-harm or suicide in prior research. This is the first study to examine whether inflammatory markers mediate the association between exposure to ACEs and self-harm. METHODS Participants were 4,308 young people from the Avon Longitudinal Study of Parents and Children (ALSPAC), a population-based birth cohort in the United Kingdom. A structural equation modelling approach was used to fit a mediation model with the number of ACEs experienced between ages 0 and 9 years old (yo), levels of the inflammatory markers interleukin-6 and C-reactive protein measured at 9.5 yo, and self-harm reported at 16 yo. RESULTS The mean number of ACEs young people experienced was 1.41 (SE 0.03). Higher ACE scores were associated with an increased risk of self-harm at 16 yo (direct effect relative risk (RR) per additional ACE 1.11, 95% CI 1.05, 1.18, p < 0.001). We did not find evidence of an indirect effect of ACEs on self-harm via inflammation (RR 1.00, 95% CI 1.00, 1.01, p = 0.38). CONCLUSIONS Young people who have been exposed to ACEs are a group at high risk of self-harm. The association between ACEs and self-harm does not appear to be mediated by an inflammatory process in childhood, as indexed by peripheral levels of circulating inflammatory markers measured in childhood. Further research is needed to identify alternative psychological and biological mechanisms underlying this relationship.
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Affiliation(s)
- Abigail Emma Russell
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Jon Heron
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - David Gunnell
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK.,NIHR Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, University of Bristol, Bristol, UK
| | - Tamsin Ford
- College of Medicine and Health, University of Exeter, Exeter, UK
| | - Gibran Hemani
- MRC Integrative Epidemiology Unit, University of Bristol Medical School, Bristol, UK.,Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Carol Joinson
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Paul Moran
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK.,NIHR Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, University of Bristol, Bristol, UK
| | - Caroline Relton
- MRC Integrative Epidemiology Unit, University of Bristol Medical School, Bristol, UK.,Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit, University of Bristol Medical School, Bristol, UK.,Population Health Sciences, University of Bristol Medical School, Bristol, UK
| | - Becky Mars
- Centre for Academic Mental Health, Population Health Sciences, University of Bristol Medical School, Bristol, UK.,NIHR Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust, University of Bristol, Bristol, UK
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