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Walker RM, Chong M, Perrot N, Pigeyre M, Gadd DA, Stolicyn A, Shi L, Campbell A, Shen X, Whalley HC, Nevado-Holgado A, McIntosh AM, Heitmeier S, Rangarajan S, O'Donnell M, Smith EE, Yusuf S, Whiteley WN, Paré G. The circulating proteome and brain health: Mendelian randomisation and cross-sectional analyses. Transl Psychiatry 2024; 14:204. [PMID: 38762535 PMCID: PMC11102511 DOI: 10.1038/s41398-024-02915-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/18/2023] [Revised: 04/17/2024] [Accepted: 04/23/2024] [Indexed: 05/20/2024] Open
Abstract
Decline in cognitive function is the most feared aspect of ageing. Poorer midlife cognitive function is associated with increased dementia and stroke risk. The mechanisms underlying variation in cognitive function are uncertain. Here, we assessed associations between 1160 proteins' plasma levels and two measures of cognitive function, the digit symbol substitution test (DSST) and the Montreal Cognitive Assessment in 1198 PURE-MIND participants. We identified five DSST performance-associated proteins (NCAN, BCAN, CA14, MOG, CDCP1), with NCAN and CDCP1 showing replicated association in an independent cohort, GS (N = 1053). MRI-assessed structural brain phenotypes partially mediated (8-19%) associations between NCAN, BCAN, and MOG, and DSST performance. Mendelian randomisation analyses suggested higher CA14 levels might cause larger hippocampal volume and increased stroke risk, whilst higher CDCP1 levels might increase intracranial aneurysm risk. Our findings highlight candidates for further study and the potential for drug repurposing to reduce the risk of stroke and cognitive decline.
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Affiliation(s)
- Rosie M Walker
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada.
- School of Psychology, University of Exeter, Perry Road, Exeter, UK.
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK.
| | - Michael Chong
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Pathology and Molecular Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada
| | - Nicolas Perrot
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
| | - Marie Pigeyre
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Medicine, Michael G DeGroote School of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada
| | - Danni A Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Aleks Stolicyn
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Liu Shi
- Department of Psychiatry, University of Oxford, Oxford, UK
- Nxera Pharma UK Limited, Cambridge, UK
| | - Archie Campbell
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Xueyi Shen
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | - Heather C Whalley
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | | | - Andrew M McIntosh
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
| | | | - Sumathy Rangarajan
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
| | - Martin O'Donnell
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Health Research Board Clinical Research Facility, University of Galway, Galway, Ireland
| | - Eric E Smith
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Clinical Neurosciences and Hotchkiss Brain Institute, Cumming School of Medicine, Calgary, AB, Canada
- University of Calgary, Calgary, AB, Canada
- Department of Clinical Neurosciences, University of Calgary, Calgary, AB, Canada
| | - Salim Yusuf
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Department of Medicine, Michael G DeGroote School of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada
| | - William N Whiteley
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada
- Centre for Clinical Brain Sciences, The University of Edinburgh, Edinburgh, UK
- MRC Centre for Population Health, University of Oxford, Oxford, UK
| | - Guillaume Paré
- Population Health Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada.
- Department of Pathology and Molecular Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada.
- Thrombosis and Atherosclerosis Research Institute, Hamilton Health Sciences and McMaster University, Hamilton, ON, Canada.
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2
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Hillary RF, Ng HK, McCartney DL, Elliott HR, Walker RM, Campbell A, Huang F, Direk K, Welsh P, Sattar N, Corley J, Hayward C, McIntosh AM, Sudlow C, Evans KL, Cox SR, Chambers JC, Loh M, Relton CL, Marioni RE, Yousefi PD, Suderman M. Blood-based epigenome-wide analyses of chronic low-grade inflammation across diverse population cohorts. CELL GENOMICS 2024; 4:100544. [PMID: 38692281 PMCID: PMC11099341 DOI: 10.1016/j.xgen.2024.100544] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 02/09/2024] [Accepted: 04/03/2024] [Indexed: 05/03/2024]
Abstract
Chronic inflammation is a hallmark of age-related disease states. The effectiveness of inflammatory proteins including C-reactive protein (CRP) in assessing long-term inflammation is hindered by their phasic nature. DNA methylation (DNAm) signatures of CRP may act as more reliable markers of chronic inflammation. We show that inter-individual differences in DNAm capture 50% of the variance in circulating CRP (N = 17,936, Generation Scotland). We develop a series of DNAm predictors of CRP using state-of-the-art algorithms. An elastic-net-regression-based predictor outperformed competing methods and explained 18% of phenotypic variance in the Lothian Birth Cohort of 1936 (LBC1936) cohort, doubling that of existing DNAm predictors. DNAm predictors performed comparably in four additional test cohorts (Avon Longitudinal Study of Parents and Children, Health for Life in Singapore, Southall and Brent Revisited, and LBC1921), including for individuals of diverse genetic ancestry and different age groups. The best-performing predictor surpassed assay-measured CRP and a genetic score in its associations with 26 health outcomes. Our findings forge new avenues for assessing chronic low-grade inflammation in diverse populations.
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Affiliation(s)
- Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Hong Kiat Ng
- Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Sciences Building, Singapore 308232, Singapore
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Hannah R Elliott
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 1UD, UK
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK; School of Psychology, University of Exeter, Exeter EX4 4QG, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Felicia Huang
- MRC Unit for Lifelong Health and Ageing, University College London, London WC1E 7HB, UK
| | - Kenan Direk
- Imperial Clinical Trials Unit, School of Public Health, Imperial College London, London SW7 2AZ, UK
| | - Paul Welsh
- School of Cardiovascular and Metabolic Health, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow G12 8TA, UK
| | - Naveed Sattar
- School of Cardiovascular and Metabolic Health, BHF Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow G12 8TA, UK
| | - Janie Corley
- Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Caroline Hayward
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK; Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Andrew M McIntosh
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK; Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh EH10 5HF, UK
| | - Cathie Sudlow
- Centre for Clinical Brain Sciences, Edinburgh Imaging and UK Dementia Research Institute, University of Edinburgh, Edinburgh EH16 4SB, UK; British Heart Foundation Data Science Centre, Health Data Research UK, London NW1 2BE, UK; Health Data Research UK, London NW1 2BE, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Simon R Cox
- Lothian Birth Cohort Studies, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - John C Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Sciences Building, Singapore 308232, Singapore; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, London W2 1PG, UK
| | - Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Clinical Sciences Building, Singapore 308232, Singapore; Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, St Mary's Campus, London W2 1PG, UK; National Skin Centre, Singapore 308205, Singapore; Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore 138672, Singapore
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 1UD, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU, UK.
| | - Paul D Yousefi
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 1UD, UK.
| | - Matthew Suderman
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol BS8 2BN, UK; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 1UD, UK.
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3
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Davyson E, Shen X, Huider F, Adams M, Borges K, McCartney D, Barker L, Van Dongen J, Boomsma D, Weihs A, Grabe H, Kühn L, Teumer A, Völzke H, Zhu T, Kaprio J, Ollikainen M, David FS, Meinert S, Stein F, Forstner AJ, Dannlowski U, Kircher T, Tapuc A, Czamara D, Binder EB, Brückl T, Kwong A, Yousefi P, Wong C, Arseneault L, Fisher HL, Mill J, Cox S, Redmond P, Russ TC, van den Oord E, Aberg KA, Penninx B, Marioni RE, Wray NR, McIntosh AM. Antidepressant Exposure and DNA Methylation: Insights from a Methylome-Wide Association Study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.01.24306640. [PMID: 38746357 PMCID: PMC11092700 DOI: 10.1101/2024.05.01.24306640] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Importance Understanding antidepressant mechanisms could help design more effective and tolerated treatments. Objective Identify DNA methylation (DNAm) changes associated with antidepressant exposure. Design Case-control methylome-wide association studies (MWAS) of antidepressant exposure were performed from blood samples collected between 2006-2011 in Generation Scotland (GS). The summary statistics were tested for enrichment in specific tissues, gene ontologies and an independent MWAS in the Netherlands Study of Depression and Anxiety (NESDA). A methylation profile score (MPS) was derived and tested for its association with antidepressant exposure in eight independent cohorts, alongside prospective data from GS. Setting Cohorts; GS, NESDA, FTC, SHIP-Trend, FOR2107, LBC1936, MARS-UniDep, ALSPAC, E-Risk, and NTR. Participants Participants with DNAm data and self-report/prescription derived antidepressant exposure. Main Outcomes and Measures Whole-blood DNAm levels were assayed by the EPIC/450K Illumina array (9 studies, N exposed = 661, N unexposed = 9,575) alongside MBD-Seq in NESDA (N exposed = 398, N unexposed = 414). Antidepressant exposure was measured by self- report and/or antidepressant prescriptions. Results The self-report MWAS (N = 16,536, N exposed = 1,508, mean age = 48, 59% female) and the prescription-derived MWAS (N = 7,951, N exposed = 861, mean age = 47, 59% female), found hypermethylation at seven and four DNAm sites (p < 9.42x10 -8 ), respectively. The top locus was cg26277237 ( KANK1, p self-report = 9.3x10 -13 , p prescription = 6.1x10 -3 ). The self-report MWAS found a differentially methylated region, mapping to DGUOK-AS1 ( p adj = 5.0x10 -3 ) alongside significant enrichment for genes expressed in the amygdala, the "synaptic vesicle membrane" gene ontology and the top 1% of CpGs from the NESDA MWAS (OR = 1.39, p < 0.042). The MPS was associated with antidepressant exposure in meta-analysed data from external cohorts (N studies = 9, N = 10,236, N exposed = 661, f3 = 0.196, p < 1x10 -4 ). Conclusions and Relevance Antidepressant exposure is associated with changes in DNAm across different cohorts. Further investigation into these changes could inform on new targets for antidepressant treatments. 3 Key Points Question: Is antidepressant exposure associated with differential whole blood DNA methylation?Findings: In this methylome-wide association study of 16,536 adults across Scotland, antidepressant exposure was significantly associated with hypermethylation at CpGs mapping to KANK1 and DGUOK-AS1. A methylation profile score trained on this sample was significantly associated with antidepressant exposure (pooled f3 [95%CI]=0.196 [0.105, 0.288], p < 1x10 -4 ) in a meta-analysis of external datasets. Meaning: Antidepressant exposure is associated with hypermethylation at KANK1 and DGUOK-AS1 , which have roles in mitochondrial metabolism and neurite outgrowth. If replicated in future studies, targeting these genes could inform the design of more effective and better tolerated treatments for depression.
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4
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Welsh P, Kimenai DM, Shah ASV, Gadd DA, Marioni RE, Woodward M, Sudlow CLM, Campbell A, Cleland JGF, Pellicori P, Hayward C, Mills NL, Sattar N. Multiple Cardiac Biomarkers to Improve Prediction of Cardiovascular Events: Findings from the Generation Scotland Scottish Family Health Study. Clin Chem 2024; 70:403-413. [PMID: 38069915 DOI: 10.1093/clinchem/hvad205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Accepted: 10/27/2023] [Indexed: 01/04/2024]
Abstract
BACKGROUND Many studies have investigated whether single cardiac biomarkers improve cardiovascular risk prediction for primary prevention but whether a combined approach could further improve risk prediction is unclear. We aimed to test a sex-specific, combined cardiac biomarker approach for cardiovascular risk prediction. METHODS In the Generation Scotland Scottish Family Health Study, N-terminal pro-B-type natriuretic peptide (NT-proBNP), growth differentiation factor-15 (GDF-15), cardiac troponin I (cTnI), cardiac troponin T (cTnT), and C-reactive protein (CRP) were measured in stored serum using automated immunoassays. Sex-specific Cox models that included SCORE2 risk factors evaluated addition of single and combined biomarkers for prediction of major adverse cardiovascular events (MACE). Combined biomarker models were compared to a baseline model that included SCORE2 risk factors. RESULTS The study population comprised 18 383 individuals (58.9% women, median age of 48 years [25th-75th percentile, 35-58 years]). During the median follow up of 11.6 (25th-75th percentile, 10.8-13.0) years, MACE occurred in 942 (5.1%) individuals. The greatest increase in discrimination with addition of individual biomarkers to the base model was for women GDF-15 and for men NT-proBNP (change in c-index: + 0.010 for women and +0.005 for men). For women, combined biomarker models that included GDF-15 and NT-proBNP (+0.012) or GDF-15 and cTnI (+0.013), but not CRP or cTnT, further improved discrimination. For men, combined biomarker models that included NT-proBNP and GDF-15 (+0.007), NT-proBNP and cTnI (+0.006), or NT-proBNP and CRP (+0.008), but not cTnT, further improved discrimination. CONCLUSIONS A combined biomarker approach, particularly the use of GDF-15, NT-proBNP and cTnI, further refined cardiovascular risk estimates.
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Affiliation(s)
- Paul Welsh
- School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow, United Kingdom
| | - Dorien M Kimenai
- BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom
| | - Anoop S V Shah
- Department of Non-Communicable Disease Epidemiology, London School of Hygiene & Tropical Medicine, London, United Kingdom
| | - Danni A Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark Woodward
- The George Institute for Global Health, School of Public Health, Imperial College London, London, United Kingdom
- The George Institute for Global Health, University of New South Wales, Sydney, New South Wales, Australia
| | - Cathie L M Sudlow
- British Heart Foundation Data Science Centre, Health Data Research UK, London, United Kingdom
- Usher Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - John G F Cleland
- School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow, United Kingdom
| | - Pierpaolo Pellicori
- School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow, United Kingdom
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Nicholas L Mills
- BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom
- Usher Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Naveed Sattar
- School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow, United Kingdom
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5
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Chybowska AD, Gadd DA, Cheng Y, Bernabeu E, Campbell A, Walker RM, McIntosh AM, Wrobel N, Murphy L, Welsh P, Sattar N, Price JF, McCartney DL, Evans KL, Marioni RE. Epigenetic Contributions to Clinical Risk Prediction of Cardiovascular Disease. CIRCULATION. GENOMIC AND PRECISION MEDICINE 2024; 17:e004265. [PMID: 38288591 PMCID: PMC10876178 DOI: 10.1161/circgen.123.004265] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2023] [Accepted: 11/30/2023] [Indexed: 02/21/2024]
Abstract
BACKGROUND Cardiovascular disease (CVD) is among the leading causes of death worldwide. The discovery of new omics biomarkers could help to improve risk stratification algorithms and expand our understanding of molecular pathways contributing to the disease. Here, ASSIGN-a cardiovascular risk prediction tool recommended for use in Scotland-was examined in tandem with epigenetic and proteomic features in risk prediction models in ≥12 657 participants from the Generation Scotland cohort. METHODS Previously generated DNA methylation-derived epigenetic scores (EpiScores) for 109 protein levels were considered, in addition to both measured levels and an EpiScore for cTnI (cardiac troponin I). The associations between individual protein EpiScores and the CVD risk were examined using Cox regression (ncases≥1274; ncontrols≥11 383) and visualized in a tailored R application. Splitting the cohort into independent training (n=6880) and test (n=3659) subsets, a composite CVD EpiScore was then developed. RESULTS Sixty-five protein EpiScores were associated with incident CVD independently of ASSIGN and the measured concentration of cTnI (P<0.05), over a follow-up of up to 16 years of electronic health record linkage. The most significant EpiScores were for proteins involved in metabolic, immune response, and tissue development/regeneration pathways. A composite CVD EpiScore (based on 45 protein EpiScores) was a significant predictor of CVD risk independent of ASSIGN and the concentration of cTnI (hazard ratio, 1.32; P=3.7×10-3; 0.3% increase in C-statistic). CONCLUSIONS EpiScores for circulating protein levels are associated with CVD risk independent of traditional risk factors and may increase our understanding of the etiology of the disease.
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Affiliation(s)
- Aleksandra D Chybowska
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer (A.D.C., D.A.G., Y.C., E.B., A.C., D.L.M., K.L.E., R.E.M.), The University of Edinburgh, United Kingdom
| | - Danni A Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer (A.D.C., D.A.G., Y.C., E.B., A.C., D.L.M., K.L.E., R.E.M.), The University of Edinburgh, United Kingdom
| | - Yipeng Cheng
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer (A.D.C., D.A.G., Y.C., E.B., A.C., D.L.M., K.L.E., R.E.M.), The University of Edinburgh, United Kingdom
| | - Elena Bernabeu
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer (A.D.C., D.A.G., Y.C., E.B., A.C., D.L.M., K.L.E., R.E.M.), The University of Edinburgh, United Kingdom
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer (A.D.C., D.A.G., Y.C., E.B., A.C., D.L.M., K.L.E., R.E.M.), The University of Edinburgh, United Kingdom
| | - Rosie M Walker
- School of Psychology, University of Exeter, United Kingdom (R.M.W.)
| | - Andrew M McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital (A.M.M.), The University of Edinburgh, United Kingdom
| | - Nicola Wrobel
- Edinburgh Clinical Research Facility, Western General Hospital (N.W., L.M.), The University of Edinburgh, United Kingdom
| | - Lee Murphy
- Edinburgh Clinical Research Facility, Western General Hospital (N.W., L.M.), The University of Edinburgh, United Kingdom
| | - Paul Welsh
- Institute of Cardiovascular and Medical Sciences, British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, United Kingdom (P.W., N.S.)
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, United Kingdom (P.W., N.S.)
| | - Jackie F Price
- Usher Institute, Old Medical School (J.F.P.), The University of Edinburgh, United Kingdom
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer (A.D.C., D.A.G., Y.C., E.B., A.C., D.L.M., K.L.E., R.E.M.), The University of Edinburgh, United Kingdom
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer (A.D.C., D.A.G., Y.C., E.B., A.C., D.L.M., K.L.E., R.E.M.), The University of Edinburgh, United Kingdom
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer (A.D.C., D.A.G., Y.C., E.B., A.C., D.L.M., K.L.E., R.E.M.), The University of Edinburgh, United Kingdom
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6
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Hoang TT, Lee Y, McCartney DL, Kersten ETG, Page CM, Hulls PM, Lee M, Walker RM, Breeze CE, Bennett BD, Burkholder AB, Ward J, Brantsæter AL, Caspersen IH, Motsinger-Reif AA, Richards M, White JD, Zhao S, Richmond RC, Magnus MC, Koppelman GH, Evans KL, Marioni RE, Håberg SE, London SJ. Comprehensive evaluation of smoking exposures and their interactions on DNA methylation. EBioMedicine 2024; 100:104956. [PMID: 38199042 PMCID: PMC10825325 DOI: 10.1016/j.ebiom.2023.104956] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 12/19/2023] [Accepted: 12/20/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND Smoking impacts DNA methylation, but data are lacking on smoking-related differential methylation by sex or dietary intake, recent smoking cessation (<1 year), persistence of differential methylation from in utero smoking exposure, and effects of environmental tobacco smoke (ETS). METHODS We meta-analysed data from up to 15,014 adults across 5 cohorts with DNA methylation measured in blood using Illumina's EPIC array for current smoking (2560 exposed), quit < 1 year (500 exposed), in utero (286 exposed), and ETS exposure (676 exposed). We also evaluated the interaction of current smoking with sex or diet (fibre, folate, and vitamin C). FINDINGS Using false discovery rate (FDR < 0.05), 65,857 CpGs were differentially methylated in relation to current smoking, 4025 with recent quitting, 594 with in utero exposure, and 6 with ETS. Most current smoking CpGs attenuated within a year of quitting. CpGs related to in utero exposure in adults were enriched for those previously observed in newborns. Differential methylation by current smoking at 4-71 CpGs may be modified by sex or dietary intake. Nearly half (35-50%) of differentially methylated CpGs on the 450 K array were associated with blood gene expression. Current smoking and in utero smoking CpGs implicated 3049 and 1067 druggable targets, including chemotherapy drugs. INTERPRETATION Many smoking-related methylation sites were identified with Illumina's EPIC array. Most signals revert to levels observed in never smokers within a year of cessation. Many in utero smoking CpGs persist into adulthood. Smoking-related druggable targets may provide insights into cancer treatment response and shared mechanisms across smoking-related diseases. FUNDING Intramural Research Program of the National Institutes of Health, Norwegian Ministry of Health and Care Services and the Ministry of Education and Research, Chief Scientist Office of the Scottish Government Health Directorates and the Scottish Funding Council, Medical Research Council UK and the Wellcome Trust.
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Affiliation(s)
- Thanh T Hoang
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA; Department of Pediatrics, Division of Hematology-Oncology, Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA; Dan L. Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX, USA; Cancer and Hematology Center, Texas Children's Hospital, Houston, TX, USA
| | - Yunsung Lee
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Elin T G Kersten
- University of Groningen, University Medical Center Groningen, Beatrix Children's Hospital, Dept. of Pediatric Pulmonology and Pediatric Allergy, Groningen, the Netherlands; University of Groningen, University Medical Center Groningen, GRIAC Research Institute, Groningen, the Netherlands
| | - Christian M Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway; Department of Physical Health and Ageing, Division for Physical and Mental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Paige M Hulls
- Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN, UK; MRC Integrative Epidemiology Unit at University of Bristol, BS8 2BN, UK
| | - Mikyeong Lee
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh EH4 2XU, UK; Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK; School of Psychology, University of Exeter, Perry Road, Exeter, UK
| | - Charles E Breeze
- UCL Cancer Institute, University College London, Paul O'Gorman Building, London, UK; Altius Institute for Biomedical Sciences, Seattle, WA, USA
| | - Brian D Bennett
- Department of Health and Human Services, Integrative Bioinformatics Support Group, National Institutes of Health, Research Triangle Park, NC, USA
| | - Adam B Burkholder
- Department of Health and Human Services, Office of Environmental Science Cyberinfrastructure, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - James Ward
- Department of Health and Human Services, Integrative Bioinformatics Support Group, National Institutes of Health, Research Triangle Park, NC, USA
| | - Anne Lise Brantsæter
- Department of Food Safety, Division of Climate and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Ida H Caspersen
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Alison A Motsinger-Reif
- Department of Health and Human Services, Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | | | - Julie D White
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA; GenOmics and Translational Research Center, Analytics Practice Area, RTI International, Research Triangle Park, NC, USA
| | - Shanshan Zhao
- Department of Health and Human Services, Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Rebecca C Richmond
- Population Health Sciences, Bristol Medical School, University of Bristol, BS8 2BN, UK; MRC Integrative Epidemiology Unit at University of Bristol, BS8 2BN, UK
| | - Maria C Magnus
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Gerard H Koppelman
- University of Groningen, University Medical Center Groningen, Beatrix Children's Hospital, Dept. of Pediatric Pulmonology and Pediatric Allergy, Groningen, the Netherlands; University of Groningen, University Medical Center Groningen, GRIAC Research Institute, Groningen, the Netherlands
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh EH4 2XU, UK
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Stephanie J London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA.
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7
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Fejzo M, Rocha N, Cimino I, Lockhart SM, Petry CJ, Kay RG, Burling K, Barker P, George AL, Yasara N, Premawardhena A, Gong S, Cook E, Rimmington D, Rainbow K, Withers DJ, Cortessis V, Mullin PM, MacGibbon KW, Jin E, Kam A, Campbell A, Polasek O, Tzoneva G, Gribble FM, Yeo GSH, Lam BYH, Saudek V, Hughes IA, Ong KK, Perry JRB, Sutton Cole A, Baumgarten M, Welsh P, Sattar N, Smith GCS, Charnock-Jones DS, Coll AP, Meek CL, Mettananda S, Hayward C, Mancuso N, O'Rahilly S. GDF15 linked to maternal risk of nausea and vomiting during pregnancy. Nature 2024; 625:760-767. [PMID: 38092039 PMCID: PMC10808057 DOI: 10.1038/s41586-023-06921-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2023] [Accepted: 11/30/2023] [Indexed: 01/19/2024]
Abstract
GDF15, a hormone acting on the brainstem, has been implicated in the nausea and vomiting of pregnancy, including its most severe form, hyperemesis gravidarum (HG), but a full mechanistic understanding is lacking1-4. Here we report that fetal production of GDF15 and maternal sensitivity to it both contribute substantially to the risk of HG. We confirmed that higher GDF15 levels in maternal blood are associated with vomiting in pregnancy and HG. Using mass spectrometry to detect a naturally labelled GDF15 variant, we demonstrate that the vast majority of GDF15 in the maternal plasma is derived from the feto-placental unit. By studying carriers of rare and common genetic variants, we found that low levels of GDF15 in the non-pregnant state increase the risk of developing HG. Conversely, women with β-thalassaemia, a condition in which GDF15 levels are chronically high5, report very low levels of nausea and vomiting of pregnancy. In mice, the acute food intake response to a bolus of GDF15 is influenced bi-directionally by prior levels of circulating GDF15 in a manner suggesting that this system is susceptible to desensitization. Our findings support a putative causal role for fetally derived GDF15 in the nausea and vomiting of human pregnancy, with maternal sensitivity, at least partly determined by prepregnancy exposure to the hormone, being a major influence on its severity. They also suggest mechanism-based approaches to the treatment and prevention of HG.
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Affiliation(s)
- M Fejzo
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - N Rocha
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - I Cimino
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - S M Lockhart
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - C J Petry
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - R G Kay
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Peptidomics and Proteomics Core Facility, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - K Burling
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Core Biochemical Assay Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - P Barker
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Core Biochemical Assay Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - A L George
- Peptidomics and Proteomics Core Facility, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - N Yasara
- Department of Paediatrics, Faculty of Medicine, University of Kelaniya, Thalagolla Road, Ragama, Sri Lanka
| | - A Premawardhena
- Adolescent and Adult Thalassaemia Care Center (University Medical Unit), North Colombo Teaching Hospital, Kadawatha, Sri Lanka
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - S Gong
- Department of Obstetrics and Gynaecology, University of Cambridge, NIHR Cambridge Biomedical Research Centre, Cambridge, UK
- Centre for Trophoblast Research (CTR), Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - E Cook
- Department of Obstetrics and Gynaecology, University of Cambridge, NIHR Cambridge Biomedical Research Centre, Cambridge, UK
| | - D Rimmington
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - K Rainbow
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - D J Withers
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - V Cortessis
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - P M Mullin
- Department of Obstetrics and Gynaecology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - K W MacGibbon
- Hyperemesis Education and Research Foundation, Clackamas, OR, USA
| | - E Jin
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - A Kam
- Department of Obstetrics and Gynaecology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - A Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - O Polasek
- Faculty of Medicine, University of Split, Split, Croatia
| | - G Tzoneva
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - F M Gribble
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - G S H Yeo
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - B Y H Lam
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - V Saudek
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - I A Hughes
- Department of Paediatrics, University of Cambridge, Cambridge, UK
| | - K K Ong
- Department of Paediatrics, University of Cambridge, Cambridge, UK
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - J R B Perry
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- MRC Epidemiology Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - A Sutton Cole
- Department of Obstetrics and Gynaecology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - M Baumgarten
- Department of Obstetrics and Gynaecology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - P Welsh
- School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - N Sattar
- School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - G C S Smith
- Department of Obstetrics and Gynaecology, University of Cambridge, NIHR Cambridge Biomedical Research Centre, Cambridge, UK
- Centre for Trophoblast Research (CTR), Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - D S Charnock-Jones
- Department of Obstetrics and Gynaecology, University of Cambridge, NIHR Cambridge Biomedical Research Centre, Cambridge, UK
- Centre for Trophoblast Research (CTR), Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - A P Coll
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - C L Meek
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - S Mettananda
- Department of Paediatrics, Faculty of Medicine, University of Kelaniya, Thalagolla Road, Ragama, Sri Lanka
- University Paediatrics Unit, Colombo North Teaching Hospital, Ragama, Sri Lanka
| | - C Hayward
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - N Mancuso
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Quantitative and Computational Biology, University of Southern California, California, CA, USA
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, California, CA, USA
| | - S O'Rahilly
- Medical Research Council (MRC) Metabolic Diseases Unit, Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
- NIHR Cambridge Biomedical Research Centre, Cambridge, UK.
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8
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Casey A, Davidson E, Grover C, Tobin R, Grivas A, Zhang H, Schrempf P, O’Neil AQ, Lee L, Walsh M, Pellie F, Ferguson K, Cvoro V, Wu H, Whalley H, Mair G, Whiteley W, Alex B. Understanding the performance and reliability of NLP tools: a comparison of four NLP tools predicting stroke phenotypes in radiology reports. Front Digit Health 2023; 5:1184919. [PMID: 37840686 PMCID: PMC10569314 DOI: 10.3389/fdgth.2023.1184919] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Accepted: 09/06/2023] [Indexed: 10/17/2023] Open
Abstract
Background Natural language processing (NLP) has the potential to automate the reading of radiology reports, but there is a need to demonstrate that NLP methods are adaptable and reliable for use in real-world clinical applications. Methods We tested the F1 score, precision, and recall to compare NLP tools on a cohort from a study on delirium using images and radiology reports from NHS Fife and a population-based cohort (Generation Scotland) that spans multiple National Health Service health boards. We compared four off-the-shelf rule-based and neural NLP tools (namely, EdIE-R, ALARM+, ESPRESSO, and Sem-EHR) and reported on their performance for three cerebrovascular phenotypes, namely, ischaemic stroke, small vessel disease (SVD), and atrophy. Clinical experts from the EdIE-R team defined phenotypes using labelling techniques developed in the development of EdIE-R, in conjunction with an expert researcher who read underlying images. Results EdIE-R obtained the highest F1 score in both cohorts for ischaemic stroke, ≥93%, followed by ALARM+, ≥87%. The F1 score of ESPRESSO was ≥74%, whilst that of Sem-EHR is ≥66%, although ESPRESSO had the highest precision in both cohorts, 90% and 98%. For F1 scores for SVD, EdIE-R scored ≥98% and ALARM+ ≥90%. ESPRESSO scored lowest with ≥77% and Sem-EHR ≥81%. In NHS Fife, F1 scores for atrophy by EdIE-R and ALARM+ were 99%, dropping in Generation Scotland to 96% for EdIE-R and 91% for ALARM+. Sem-EHR performed lowest for atrophy at 89% in NHS Fife and 73% in Generation Scotland. When comparing NLP tool output with brain image reads using F1 scores, ALARM+ scored 80%, outperforming EdIE-R at 66% in ischaemic stroke. For SVD, EdIE-R performed best, scoring 84%, with Sem-EHR 82%. For atrophy, EdIE-R and both ALARM+ versions were comparable at 80%. Conclusions The four NLP tools show varying F1 (and precision/recall) scores across all three phenotypes, although more apparent for ischaemic stroke. If NLP tools are to be used in clinical settings, this cannot be performed "out of the box." It is essential to understand the context of their development to assess whether they are suitable for the task at hand or whether further training, re-training, or modification is required to adapt tools to the target task.
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Affiliation(s)
- Arlene Casey
- Advanced Care Research Centre, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Emma Davidson
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Claire Grover
- School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Richard Tobin
- School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Andreas Grivas
- School of Informatics, University of Edinburgh, Edinburgh, United Kingdom
| | - Huayu Zhang
- Advanced Care Research Centre, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Patrick Schrempf
- Canon Medical Research Europe Ltd., AI Research, Edinburgh, United Kingdom
- School of Computer Science, University of St Andrews, St Andrews, United Kingdom
| | - Alison Q. O’Neil
- Canon Medical Research Europe Ltd., AI Research, Edinburgh, United Kingdom
- School of Engineering, University of Edinburgh, Edinburgh, United Kingdom
| | - Liam Lee
- Medical School, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael Walsh
- Intensive Care Department, University Hospitals Bristol and Weston, Bristol, United Kingdom
| | - Freya Pellie
- National Horizons Centre, Teesside University, Darlington, United Kingdom
- School of Health and Life Sciences, Teesside University, Middlesbrough, United Kingdom
| | - Karen Ferguson
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Vera Cvoro
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Department of Geriatric Medicine, NHS Fife, Fife, United Kingdom
| | - Honghan Wu
- Institute of Health Informatics, University College London, London, United Kingdom
- Alan Turing Institute, London, United Kingdom
| | - Heather Whalley
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Generation Scotland, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Grant Mair
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Neuroradiology, Department of Clinical Neurosciences, NHS Lothian, Edinburgh, United Kingdom
| | - William Whiteley
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Neuroradiology, Department of Clinical Neurosciences, NHS Lothian, Edinburgh, United Kingdom
| | - Beatrice Alex
- Edinburgh Futures Institute, University of Edinburgh, Edinburgh, United Kingdom
- School of Literatures, Languages and Cultures, University of Edinburgh, Edinburgh, United Kingdom
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9
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Hatton AA, Hillary RF, Bernabeu E, McCartney DL, Marioni RE, McRae AF. Blood-based genome-wide DNA methylation correlations across body-fat- and adiposity-related biochemical traits. Am J Hum Genet 2023; 110:1564-1573. [PMID: 37652023 PMCID: PMC10502853 DOI: 10.1016/j.ajhg.2023.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Revised: 08/04/2023] [Accepted: 08/03/2023] [Indexed: 09/02/2023] Open
Abstract
The recent increase in obesity levels across many countries is likely to be driven by nongenetic factors. The epigenetic modification DNA methylation (DNAm) may help to explore this, as it is sensitive to both genetic and environmental exposures. While the relationship between DNAm and body-fat traits has been extensively studied, there is limited literature on the shared associations of DNAm variation across such traits. Akin to genetic correlation estimates, here, we introduce an approach to evaluate the similarities in DNAm associations between traits: DNAm correlations. As DNAm can be both a cause and consequence of complex traits, DNAm correlations have the potential to provide insights into trait relationships above that currently obtained from genetic and phenotypic correlations. Utilizing 7,519 unrelated individuals from Generation Scotland with DNAm from the EPIC array, we calculated DNAm correlations between body-fat- and adiposity-related traits by using the bivariate OREML framework in the OSCA software. For each trait, we also estimated the shared contribution of DNAm between sexes. We identified strong, positive DNAm correlations between each of the body-fat traits (BMI, body-fat percentage, and waist-to-hip ratio, ranging from 0.96 to 1.00), finding larger associations than those identified by genetic and phenotypic correlations. We identified a significant deviation from 1 in the DNAm correlations for BMI between males and females, with sex-specific DNAm changes associated with BMI identified at eight DNAm probes. Employing genome-wide DNAm correlations to evaluate the similarities in the associations of DNAm with complex traits has provided insight into obesity-related traits beyond that provided by genetic correlations.
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Affiliation(s)
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Elena Bernabeu
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Allan F McRae
- Institute for Molecular Bioscience, Brisbane, Australia.
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10
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Hillary RF, McCartney DL, Smith HM, Bernabeu E, Gadd DA, Chybowska AD, Cheng Y, Murphy L, Wrobel N, Campbell A, Walker RM, Hayward C, Evans KL, McIntosh AM, Marioni RE. Blood-based epigenome-wide analyses of 19 common disease states: A longitudinal, population-based linked cohort study of 18,413 Scottish individuals. PLoS Med 2023; 20:e1004247. [PMID: 37410739 PMCID: PMC10325072 DOI: 10.1371/journal.pmed.1004247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 05/25/2023] [Indexed: 07/08/2023] Open
Abstract
BACKGROUND DNA methylation is a dynamic epigenetic mechanism that occurs at cytosine-phosphate-guanine dinucleotide (CpG) sites. Epigenome-wide association studies (EWAS) investigate the strength of association between methylation at individual CpG sites and health outcomes. Although blood methylation may act as a peripheral marker of common disease states, previous EWAS have typically focused only on individual conditions and have had limited power to discover disease-associated loci. This study examined the association of blood DNA methylation with the prevalence of 14 disease states and the incidence of 19 disease states in a single population of over 18,000 Scottish individuals. METHODS AND FINDINGS DNA methylation was assayed at 752,722 CpG sites in whole-blood samples from 18,413 volunteers in the family-structured, population-based cohort study Generation Scotland (age range 18 to 99 years). EWAS tested for cross-sectional associations between baseline CpG methylation and 14 prevalent disease states, and for longitudinal associations between baseline CpG methylation and 19 incident disease states. Prevalent cases were self-reported on health questionnaires at the baseline. Incident cases were identified using linkage to Scottish primary (Read 2) and secondary (ICD-10) care records, and the censoring date was set to October 2020. The mean time-to-diagnosis ranged from 5.0 years (for chronic pain) to 11.7 years (for Coronavirus Disease 2019 (COVID-19) hospitalisation). The 19 disease states considered in this study were selected if they were present on the World Health Organisation's 10 leading causes of death and disease burden or included in baseline self-report questionnaires. EWAS models were adjusted for age at methylation typing, sex, estimated white blood cell composition, population structure, and 5 common lifestyle risk factors. A structured literature review was also conducted to identify existing EWAS for all 19 disease states tested. The MEDLINE, Embase, Web of Science, and preprint servers were searched to retrieve relevant articles indexed as of March 27, 2023. Fifty-four of approximately 2,000 indexed articles met our inclusion criteria: assayed blood-based DNA methylation, had >20 individuals in each comparison group, and examined one of the 19 conditions considered. First, we assessed whether the associations identified in our study were reported in previous studies. We identified 69 associations between CpGs and the prevalence of 4 conditions, of which 58 were newly described. The conditions were breast cancer, chronic kidney disease, ischemic heart disease, and type 2 diabetes mellitus. We also uncovered 64 CpGs that associated with the incidence of 2 disease states (COPD and type 2 diabetes), of which 56 were not reported in the surveyed literature. Second, we assessed replication across existing studies, which was defined as the reporting of at least 1 common site in >2 studies that examined the same condition. Only 6/19 disease states had evidence of such replication. The limitations of this study include the nonconsideration of medication data and a potential lack of generalizability to individuals that are not of Scottish and European ancestry. CONCLUSIONS We discovered over 100 associations between blood methylation sites and common disease states, independently of major confounding risk factors, and a need for greater standardisation among EWAS on human disease.
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Affiliation(s)
- Robert F. Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Daniel L. McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Hannah M. Smith
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Elena Bernabeu
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Danni A. Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Aleksandra D. Chybowska
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Yipeng Cheng
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Lee Murphy
- Edinburgh Clinical Research Facility, University of Edinburgh, Edinburgh, United Kingdom
| | - Nicola Wrobel
- Edinburgh Clinical Research Facility, University of Edinburgh, Edinburgh, United Kingdom
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Rosie M. Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
- School of Psychology, University of Exeter, Exeter, United Kingdom
| | - Caroline Hayward
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Kathryn L. Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew M. McIntosh
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, United Kingdom
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
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11
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Sherwood K, Ward JC, Soriano I, Martin L, Campbell A, Rahbari R, Kafetzopoulos I, Sproul D, Green A, Sampson JR, Donaldson A, Ong KR, Heinimann K, Nielsen M, Thomas H, Latchford A, Palles C, Tomlinson I. Germline de novo mutations in families with Mendelian cancer syndromes caused by defects in DNA repair. Nat Commun 2023; 14:3636. [PMID: 37336879 PMCID: PMC10279637 DOI: 10.1038/s41467-023-39248-0] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/20/2022] [Accepted: 05/31/2023] [Indexed: 06/21/2023] Open
Abstract
DNA repair defects underlie many cancer syndromes. We tested whether de novo germline mutations (DNMs) are increased in families with germline defects in polymerase proofreading or base excision repair. A parent with a single germline POLE or POLD1 mutation, or biallelic MUTYH mutations, had 3-4 fold increased DNMs over sex-matched controls. POLE had the largest effect. The DNMs carried mutational signatures of the appropriate DNA repair deficiency. No DNM increase occurred in offspring of MUTYH heterozygous parents. Parental DNA repair defects caused about 20-150 DNMs per child, additional to the ~60 found in controls, but almost all extra DNMs occurred in non-coding regions. No increase in post-zygotic mutations was detected, excepting a child with bi-allelic MUTYH mutations who was excluded from the main analysis; she had received chemotherapy and may have undergone oligoclonal haematopoiesis. Inherited DNA repair defects associated with base pair-level mutations increase DNMs, but phenotypic consequences appear unlikely.
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Affiliation(s)
- Kitty Sherwood
- Cancer Research UK Edinburgh Centre and MRC Human Genetics Unit, Institute of Genomics and Cancer, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Joseph C Ward
- Dept of Oncology, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford, OX3 7DQ, UK
| | - Ignacio Soriano
- Dept of Oncology, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford, OX3 7DQ, UK
| | - Lynn Martin
- Institute of Cancer and Genomic Sciences, University of Birmingham Medical School, Vincent Drive, Edgbaston, Birmingham, B15 2JJ, UK
| | - Archie Campbell
- Centre for Genetics and Experimental Medicine, Institute of Genetics and Cancer, Western General Hospital, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Raheleh Rahbari
- Wellcome Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Ioannis Kafetzopoulos
- Cancer Research UK Edinburgh Centre and MRC Human Genetics Unit, Institute of Genomics and Cancer, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Duncan Sproul
- Cancer Research UK Edinburgh Centre and MRC Human Genetics Unit, Institute of Genomics and Cancer, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Andrew Green
- Department of Clinical Genetics, Children's Health Ireland and School of Medicine University College, Dublin, Ireland
| | - Julian R Sampson
- Institute of Medical Genetics, Division of Cancer and Genetics, Cardiff University School of Medicine, Cardiff, UK
| | - Alan Donaldson
- Bristol Regional Clinical Genetics Service, St Michael's Hospital, Southwell Street, Bristol, BS2 8EG, UK
| | - Kai-Ren Ong
- West Midlands Regional Genetics Service, Birmingham Women's and Children's NHS Foundation Trust, Birmingham, UK
| | - Karl Heinimann
- Institute for Medical Genetics and Pathology, University Hospital Basel, Basel, BS, Switzerland
| | - Maartje Nielsen
- Department of Clinical Genetics, Leiden University Medical Centre, 2333 ZA, Leiden, the Netherlands
| | - Huw Thomas
- St Mark's Hospital, Watford Road, Harrow, HA1 3UJ, UK
| | | | - Claire Palles
- Institute of Cancer and Genomic Sciences, University of Birmingham Medical School, Vincent Drive, Edgbaston, Birmingham, B15 2JJ, UK.
| | - Ian Tomlinson
- Dept of Oncology, University of Oxford, Old Road Campus Research Building, Roosevelt Drive, Oxford, OX3 7DQ, UK.
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12
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Fejzo M, Rocha N, Cimino I, Lockhart SM, Petry C, Kay RG, Burling K, Barker P, George AL, Yasara N, Premawardhena A, Gong S, Cook E, Rainbow K, Withers DJ, Cortessis V, Mullin PM, MacGibbon KW, Jin E, Kam A, Campbell A, Polasek O, Tzoneva G, Gribble FM, Yeo G, Lam B, Saudek V, Hughes IA, Ong KK, Perry J, Sutton Cole A, Baumgarten M, Welsh P, Sattar N, Smith G, Charnock Jones DS, Coll AP, Meek CL, Mettananda S, Hayward C, Mancuso N, O'Rahilly S. Fetally-encoded GDF15 and maternal GDF15 sensitivity are major determinants of nausea and vomiting in human pregnancy. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.06.02.542661. [PMID: 37398065 PMCID: PMC10312505 DOI: 10.1101/2023.06.02.542661] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Human pregnancy is frequently accompanied by nausea and vomiting that may become severe and life-threatening, as in hyperemesis gravidarum (HG), the cause of which is unknown. Growth Differentiation Factor-15 (GDF15), a hormone known to act on the hindbrain to cause emesis, is highly expressed in the placenta and its levels in maternal blood rise rapidly in pregnancy. Variants in the maternal GDF15 gene are associated with HG. Here we report that fetal production of GDF15, and maternal sensitivity to it, both contribute substantially to the risk of HG. We found that the great majority of GDF15 in maternal circulation is derived from the feto-placental unit and that higher GDF15 levels in maternal blood are associated with vomiting and are further elevated in patients with HG. Conversely, we found that lower levels of GDF15 in the non-pregnant state predispose women to HG. A rare C211G variant in GDF15 which strongly predisposes mothers to HG, particularly when the fetus is wild-type, was found to markedly impair cellular secretion of GDF15 and associate with low circulating levels of GDF15 in the non-pregnant state. Consistent with this, two common GDF15 haplotypes which predispose to HG were associated with lower circulating levels outside pregnancy. The administration of a long-acting form of GDF15 to wild-type mice markedly reduced subsequent responses to an acute dose, establishing that desensitisation is a feature of this system. GDF15 levels are known to be highly and chronically elevated in patients with beta thalassemia. In women with this disorder, reports of symptoms of nausea or vomiting in pregnancy were strikingly diminished. Our findings support a causal role for fetal derived GDF15 in the nausea and vomiting of human pregnancy, with maternal sensitivity, at least partly determined by pre-pregnancy exposure to GDF15, being a major influence on its severity. They also suggest mechanism-based approaches to the treatment and prevention of HG.
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Affiliation(s)
- M Fejzo
- Department of Obstetrics and Gynaecology, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - N Rocha
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - I Cimino
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - S M Lockhart
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - C Petry
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - R G Kay
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Peptidomics and Proteomics Core Facility, Level 4, Wellcome-MRC Institute of Metabolic Science, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, United Kingdom
| | - K Burling
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Core Biochemical Assay Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK
| | - P Barker
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- Core Biochemical Assay Laboratory, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, UK
| | - A L George
- Peptidomics and Proteomics Core Facility, Level 4, Wellcome-MRC Institute of Metabolic Science, Cambridge University Hospitals NHS Foundation Trust, Cambridge CB2 0QQ, United Kingdom
| | - N Yasara
- Department of Paediatrics, Faculty of Medicine, University of Kelaniya, Thalagolla Road, Ragama, 11010, Sri Lanka
| | - A Premawardhena
- Adolescent and Adult Thalassaemia Care Center (University Medical Unit), North Colombo Teaching Hospital, Kadawatha, Sri Lanka
- Department of Medicine, Faculty of Medicine, University of Kelaniya, Ragama, Sri Lanka
| | - S Gong
- Department of Obstetrics and Gynaecology, University of Cambridge, NIHR Cambridge Biomedical Research Centre, Cambridge, UK
- Centre for Trophoblast Research (CTR), Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - E Cook
- Department of Obstetrics and Gynaecology, University of Cambridge, NIHR Cambridge Biomedical Research Centre, Cambridge, UK
| | - K Rainbow
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - D J Withers
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - V Cortessis
- Department of Obstetrics and Gynaecology, Keck School of Medicine, University of Southern California, Los Angeles, CA
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
| | - P M Mullin
- Department of Obstetrics and Gynaecology, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - K W MacGibbon
- Hyperemesis Education and Research Foundation, Clackamas, OR
| | - E Jin
- Department of Obstetrics and Gynaecology, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - A Kam
- Department of Obstetrics and Gynaecology, Keck School of Medicine, University of Southern California, Los Angeles, CA
| | - A Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - O Polasek
- Faculty of Medicine, University of Split, Split, Croatia
| | - G Tzoneva
- Regeneron Genetics Center, Tarrytown, NY, USA
| | - F M Gribble
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Gsh Yeo
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Byh Lam
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - V Saudek
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - I A Hughes
- Department of Paediatrics, Cambridge University Hospitals NHS Foundation Trust, University of Cambridge, Cambridge, UK
| | - K K Ong
- Department of Paediatrics, Cambridge University Hospitals NHS Foundation Trust, University of Cambridge, Cambridge, UK
- MRC Epidemiology Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - Jrb Perry
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- MRC Epidemiology Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - A Sutton Cole
- Department of Obstetrics and Gynaecology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - M Baumgarten
- Department of Obstetrics and Gynaecology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - P Welsh
- School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - N Sattar
- School of Cardiovascular and Metabolic Health, University of Glasgow, Glasgow, UK
| | - Gcs Smith
- Department of Obstetrics and Gynaecology, University of Cambridge, NIHR Cambridge Biomedical Research Centre, Cambridge, UK
- Centre for Trophoblast Research (CTR), Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - D S Charnock Jones
- Department of Obstetrics and Gynaecology, University of Cambridge, NIHR Cambridge Biomedical Research Centre, Cambridge, UK
- Centre for Trophoblast Research (CTR), Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
| | - A P Coll
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - C L Meek
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
| | - S Mettananda
- Department of Paediatrics, Faculty of Medicine, University of Kelaniya, Thalagolla Road, Ragama, 11010, Sri Lanka
- University Paediatrics Unit, Colombo North Teaching Hospital, Ragama, Sri Lanka
| | - C Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh EH4 2XU,16, UK
| | - N Mancuso
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California
- Department of Quantitative and Computational Biology, University of Southern California
- Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California
| | - S O'Rahilly
- Medical Research Council (MRC) Metabolic Diseases Unit, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK.
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13
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Iakovliev A, McGurnaghan SJ, Hayward C, Colombo M, Lipschutz D, Spiliopoulou A, Colhoun HM, McKeigue PM. Genome-wide aggregated trans-effects on risk of type 1 diabetes: A test of the "omnigenic" sparse effector hypothesis of complex trait genetics. Am J Hum Genet 2023; 110:913-926. [PMID: 37164005 PMCID: PMC10257008 DOI: 10.1016/j.ajhg.2023.04.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 04/12/2023] [Indexed: 05/12/2023] Open
Abstract
The "omnigenic" hypothesis postulates that the polygenic effects of common SNPs on a typical complex trait are mediated through trans-effects on expression of a relatively sparse set of effector ("core") genes. We tested this hypothesis in a study of 4,964 cases of type 1 diabetes (T1D) and 7,497 controls by using summary statistics to calculate aggregated (excluding the HLA region) trans-scores for gene expression in blood. From associations of T1D with aggregated trans-scores, nine putative core genes were identified, of which three-STAT1, CTLA4 and FOXP3-are genes in which variants cause monogenic forms of autoimmune diabetes. Seven of these genes affect the activity of regulatory T cells, and two are involved in immune responses to microbial lipids. Four T1D-associated genomic regions could be identified as master regulators via trans-effects on gene expression. These results support the sparse effector hypothesis and reshape our understanding of the genetic architecture of T1D.
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Affiliation(s)
- Andrii Iakovliev
- Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, Scotland
| | - Stuart J McGurnaghan
- Institute of Genetics and Cancer, College of Medicine and Veterinary Medicine, University of Edinburgh, Western General Hospital Campus, Crewe Road, Edinburgh EH4 2XUC, Scotland
| | - Caroline Hayward
- Institute of Genetics and Cancer, College of Medicine and Veterinary Medicine, University of Edinburgh, Western General Hospital Campus, Crewe Road, Edinburgh EH4 2XUC, Scotland
| | - Marco Colombo
- University of Leipzig, Medical Faculty, University Hospital for Children and Adolescents, Center for Pediatric Research, Leipzig, Germany
| | - Debby Lipschutz
- Institute of Genetics and Cancer, College of Medicine and Veterinary Medicine, University of Edinburgh, Western General Hospital Campus, Crewe Road, Edinburgh EH4 2XUC, Scotland
| | - Athina Spiliopoulou
- Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, Scotland
| | - Helen M Colhoun
- Institute of Genetics and Cancer, College of Medicine and Veterinary Medicine, University of Edinburgh, Western General Hospital Campus, Crewe Road, Edinburgh EH4 2XUC, Scotland
| | - Paul M McKeigue
- Usher Institute, College of Medicine and Veterinary Medicine, University of Edinburgh, Teviot Place, Edinburgh EH8 9AG, Scotland.
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14
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Packer RJ, Shrine N, Hall R, Melbourne CA, Thompson R, Williams AT, Paynton ML, Guyatt AL, Allen RJ, Lee PH, John C, Campbell A, Hayward C, de Vries M, Vonk JM, Davitte J, Hessel E, Michalovich D, Betts JC, Sayers I, Yeo A, Hall IP, Tobin MD, Wain LV. Genome-wide association study of chronic sputum production implicates loci involved in mucus production and infection. Eur Respir J 2023; 61:2201667. [PMID: 37263751 PMCID: PMC10284065 DOI: 10.1183/13993003.01667-2022] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 02/17/2023] [Indexed: 06/03/2023]
Abstract
BACKGROUND Chronic sputum production impacts on quality of life and is a feature of many respiratory diseases. Identification of the genetic variants associated with chronic sputum production in a disease agnostic sample could improve understanding of its causes and identify new molecular targets for treatment. METHODS We conducted a genome-wide association study (GWAS) of chronic sputum production in UK Biobank. Signals meeting genome-wide significance (p<5×10-8) were investigated in additional independent studies, were fine-mapped and putative causal genes identified by gene expression analysis. GWASs of respiratory traits were interrogated to identify whether the signals were driven by existing respiratory disease among the cases and variants were further investigated for wider pleiotropic effects using phenome-wide association studies (PheWASs). RESULTS From a GWAS of 9714 cases and 48 471 controls, we identified six novel genome-wide significant signals for chronic sputum production including signals in the human leukocyte antigen (HLA) locus, chromosome 11 mucin locus (containing MUC2, MUC5AC and MUC5B) and FUT2 locus. The four common variant associations were supported by independent studies with a combined sample size of up to 2203 cases and 17 627 controls. The mucin locus signal had previously been reported for association with moderate-to-severe asthma. The HLA signal was fine-mapped to an amino acid change of threonine to arginine (frequency 36.8%) in HLA-DRB1 (HLA-DRB1*03:147). The signal near FUT2 was associated with expression of several genes including FUT2, for which the direction of effect was tissue dependent. Our PheWAS identified a wide range of associations including blood cell traits, liver biomarkers, infections, gastrointestinal and thyroid-associated diseases, and respiratory disease. CONCLUSIONS Novel signals at the FUT2 and mucin loci suggest that mucin fucosylation may be a driver of chronic sputum production even in the absence of diagnosed respiratory disease and provide genetic support for this pathway as a target for therapeutic intervention.
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Affiliation(s)
- Richard J Packer
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Nick Shrine
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Robert Hall
- Centre for Respiratory Research, NIHR Nottingham Biomedical Research Centre, School of Medicine, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | - Carl A Melbourne
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Rebecca Thompson
- Centre for Respiratory Research, NIHR Nottingham Biomedical Research Centre, School of Medicine, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | - Alex T Williams
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Megan L Paynton
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Anna L Guyatt
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Richard J Allen
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Paul H Lee
- Department of Population Health Sciences, University of Leicester, Leicester, UK
| | - Catherine John
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Maaike de Vries
- University of Groningen, University Medical Center Groningen, Department of Epidemiology and Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, The Netherlands
| | - Judith M Vonk
- University of Groningen, University Medical Center Groningen, Department of Epidemiology and Groningen Research Institute for Asthma and COPD (GRIAC), Groningen, The Netherlands
| | | | | | | | | | - Ian Sayers
- Centre for Respiratory Research, NIHR Nottingham Biomedical Research Centre, School of Medicine, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | | | - Ian P Hall
- Centre for Respiratory Research, NIHR Nottingham Biomedical Research Centre, School of Medicine, Biodiscovery Institute, University of Nottingham, Nottingham, UK
| | - Martin D Tobin
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Leicester, UK
| | - Louise V Wain
- Department of Population Health Sciences, University of Leicester, Leicester, UK
- Leicester NIHR Biomedical Research Centre, Glenfield Hospital, Leicester, UK
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15
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Gao C, Amador C, Walker RM, Campbell A, Madden RA, Adams MJ, Bai X, Liu Y, Li M, Hayward C, Porteous DJ, Shen X, Evans KL, Haley CS, McIntosh AM, Navarro P, Zeng Y. Phenome-wide analyses identify an association between the parent-of-origin effects dependent methylome and the rate of aging in humans. Genome Biol 2023; 24:117. [PMID: 37189164 PMCID: PMC10184337 DOI: 10.1186/s13059-023-02953-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 04/26/2023] [Indexed: 05/17/2023] Open
Abstract
BACKGROUND The variation in the rate at which humans age may be rooted in early events acting through the genomic regions that are influenced by such events and subsequently are related to health phenotypes in later life. The parent-of-origin-effect (POE)-regulated methylome includes regions enriched for genetically controlled imprinting effects (the typical type of POE) and regions influenced by environmental effects associated with parents (the atypical POE). This part of the methylome is heavily influenced by early events, making it a potential route connecting early exposures, the epigenome, and aging. We aim to test the association of POE-CpGs with early and later exposures and subsequently with health-related phenotypes and adult aging. RESULTS We perform a phenome-wide association analysis for the POE-influenced methylome using GS:SFHS (Ndiscovery = 5087, Nreplication = 4450). We identify and replicate 92 POE-CpG-phenotype associations. Most of the associations are contributed by the POE-CpGs belonging to the atypical class where the most strongly enriched associations are with aging (DNAmTL acceleration), intelligence, and parental (maternal) smoking exposure phenotypes. A proportion of the atypical POE-CpGs form co-methylation networks (modules) which are associated with these phenotypes, with one of the aging-associated modules displaying increased within-module methylation connectivity with age. The atypical POE-CpGs also display high levels of methylation heterogeneity, fast information loss with age, and a strong correlation with CpGs contained within epigenetic clocks. CONCLUSIONS These results identify the association between the atypical POE-influenced methylome and aging and provide new evidence for the "early development of origin" hypothesis for aging in humans.
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Affiliation(s)
- Chenhao Gao
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Carmen Amador
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Rosie M Walker
- Centre for Clinical Brain Sciences, Chancellor's Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- School of Psychology, University of Exeter, Perry Road, Exeter, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | | | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Xiaomeng Bai
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Ying Liu
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Miaoxin Li
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Xueyi Shen
- Division of Psychiatry, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Chris S Haley
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | | | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
- Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK.
| | - Yanni Zeng
- 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.
- Guangdong Province Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China.
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16
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Baskozos G, Hébert HL, Pascal MM, Themistocleous AC, Macfarlane GJ, Wynick D, Bennett DL, Smith BH. Epidemiology of neuropathic pain: an analysis of prevalence and associated factors in UK Biobank. Pain Rep 2023; 8:e1066. [PMID: 37090682 PMCID: PMC7614463 DOI: 10.1097/pr9.0000000000001066] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 11/14/2022] [Accepted: 12/13/2022] [Indexed: 02/12/2023] Open
Abstract
Supplemental Digital Content is Available in the Text. An analysis of UK Biobank participants who completed a detailed pain questionnaire identified factors associated with neuropathic pain (NeuP) vs no chronic pain and non-NeuP and estimated the prevalence of NeuP. Introduction: Previous epidemiological studies of neuropathic pain have reported a range of prevalences and factors associated with the disorder. Objectives: This study aimed to verify these characteristics in a large UK cohort. Methods: A cross-sectional analysis was conducted of 148,828 UK Biobank participants who completed a detailed questionnaire on chronic pain. The Douleur Neuropathique en Quatre Questions (DN4) was used to distinguish between neuropathic pain (NeuP) and non-neuropathic pain (non-NeuP) in participants with pain of at least 3 months' duration. Participants were also identified with less than 3 months' pain or without pain (NoCP). Multivariable regression was used to identify factors associated with NeuP compared with non-NeuP and NoCP, respectively. Results: Chronic pain was present in 76,095 participants (51.1%). The overall prevalence of NeuP was 9.2%. Neuropathic pain was significantly associated with worse health-related quality of life, having a manual or personal service type occupation, and younger age compared with NoCP. As expected, NeuP was associated with diabetes and neuropathy, but also other pains (pelvic, postsurgical, and migraine) and musculoskeletal disorders (rheumatoid arthritis, osteoarthritis, and fibromyalgia). In addition, NeuP was associated with pain in the limbs and greater pain intensity and higher body mass index compared with non-NeuP. Female sex was associated with NeuP when compared with NoCP, whereas male sex was associated with NeuP when compared with non-NeuP. Conclusion: This is the largest epidemiological study of neuropathic pain to date. The results confirm that the disorder is common in a population of middle- to older-aged people with mixed aetiologies and is associated with a higher health impact than non-neuropathic pain.
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Affiliation(s)
- Georgios Baskozos
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Harry L. Hébert
- Chronic Pain Research Group, Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, United Kingdom
| | - Mathilde M.V. Pascal
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Andreas C. Themistocleous
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Gary J. Macfarlane
- Epidemiology Group and Aberdeen Centre for Arthritis and Musculoskeletal Health, School of Medicine, Medical Sciences, and Nutrition, University of Aberdeen, Aberdeen, United Kingdom
| | - David Wynick
- Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - David L.H. Bennett
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, United Kingdom
| | - Blair H. Smith
- Chronic Pain Research Group, Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, United Kingdom
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17
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Hébert HL, Veluchamy A, Baskozos G, Fardo F, Van Ryckeghem D, Pearson ER, Colvin LA, Crombez G, Bennett DLH, Meng W, Palmer CNA, Smith BH. Development and external validation of multivariable risk models to predict incident and resolved neuropathic pain: a DOLORisk Dundee study. J Neurol 2023; 270:1076-1094. [PMID: 36355188 PMCID: PMC9886655 DOI: 10.1007/s00415-022-11478-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2022] [Revised: 11/03/2022] [Accepted: 11/04/2022] [Indexed: 11/12/2022]
Abstract
Neuropathic pain is difficult to treat, and an understanding of the risk factors for its onset and resolution is warranted. This study aimed to develop and externally validate two clinical risk models to predict onset and resolution of chronic neuropathic pain. Participants of Generation Scotland: Scottish Family Health Study (GS; general Scottish population; n = 20,221) and Genetic of Diabetes Audit and Research in Tayside Scotland (GoDARTS; n = 5236) were sent a questionnaire on neuropathic pain and followed- -up 18 months later. Chronic neuropathic pain was defined using DN4 scores (≥ 3/7) and pain for 3 months or more. The models were developed in GS using logistic regression with backward elimination based on the Akaike information criterion. External validation was conducted in GoDARTS and assessed model discrimination (ROC and Precision-Recall curves), calibration and clinical utility (decision curve analysis [DCA]). Analysis revealed incidences of neuropathic pain onset (6.0% in GS [236/3903] and 10.7% in GoDARTS [61/571]) and resolution (42.6% in GS [230/540] and 23.7% in GoDARTS [56/236]). Psychosocial and lifestyle factors were included in both onset and resolved prediction models. In GoDARTS, these models showed adequate discrimination (ROC = 0.636 and 0.699), but there was evidence of miscalibration (Intercept = - 0.511 and - 0.424; slope = 0.623 and 0.999). The DCA indicated that the models would provide clinical benefit over a range of possible risk thresholds. To our knowledge, these are the first externally validated risk models for neuropathic pain. The findings are of interest to patients and clinicians in the community, who may take preventative or remedial measures.
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Affiliation(s)
- Harry L Hébert
- Chronic Pain Research Group, Division of Population Health and Genomics, Mackenzie Building, Ninewells Hospital and Medical School, University of Dundee, Kirsty Semple Way, Dundee, DD2 4BF, UK
| | - Abirami Veluchamy
- Chronic Pain Research Group, Division of Population Health and Genomics, Mackenzie Building, Ninewells Hospital and Medical School, University of Dundee, Kirsty Semple Way, Dundee, DD2 4BF, UK
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Georgios Baskozos
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Francesca Fardo
- Danish Pain Research Center, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Dimitri Van Ryckeghem
- Department of Experimental-Clinical and Health Psychology, Faculty of Psychology and Educational Sciences, Ghent University, Ghent, Belgium
- Section Experimental Health Psychology, Clinical Psychological Science, Departments, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
| | - Ewan R Pearson
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Lesley A Colvin
- Chronic Pain Research Group, Division of Population Health and Genomics, Mackenzie Building, Ninewells Hospital and Medical School, University of Dundee, Kirsty Semple Way, Dundee, DD2 4BF, UK
| | - Geert Crombez
- Department of Experimental-Clinical and Health Psychology, Faculty of Psychology and Educational Sciences, Ghent University, Ghent, Belgium
| | - David L H Bennett
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Weihua Meng
- Chronic Pain Research Group, Division of Population Health and Genomics, Mackenzie Building, Ninewells Hospital and Medical School, University of Dundee, Kirsty Semple Way, Dundee, DD2 4BF, UK
| | - Colin N A Palmer
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Blair H Smith
- Chronic Pain Research Group, Division of Population Health and Genomics, Mackenzie Building, Ninewells Hospital and Medical School, University of Dundee, Kirsty Semple Way, Dundee, DD2 4BF, UK.
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18
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Gao C, Amador C, Walker RM, Campbell A, Madden RA, Adams MJ, Bai X, Liu Y, Li M, Hayward C, Porteous DJ, Shen X, Evans KL, Haley CS, McIntosh AM, Navarro P, Zeng Y. Phenome-wide analysis identifies parent-of-origin effects on the human methylome associated with changes in the rate of aging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.18.524653. [PMID: 36711749 PMCID: PMC9882261 DOI: 10.1101/2023.01.18.524653] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
Variation in the rate at which humans age may be rooted in early life events acting through genomic regions that are influenced by such events and subsequently are related to health phenotypes in later life. The parent-of-origin-effect (POE)-regulated methylome includes regions either enriched for genetically controlled imprinting effects (the typical type of POE) or atypical POE introduced by environmental effects associated with parents. This part of the methylome is heavily influenced by early life events, making it a potential route connecting early environmental exposures, the epigenome and the rate of aging. Here, we aim to test the association of POE-influenced methylation of CpG dinucleotides (POE-CpG sites) with early and later environmental exposures and subsequently with health-related phenotypes and adult aging phenotypes. We do this by performing phenome-wide association analyses of the POE-influenced methylome using a large family-based population cohort (GS:SFHS, Ndiscovery=5,087, Nreplication=4,450). At the single CpG level, 92 associations of POE-CpGs with phenotypic variation were identified and replicated. Most of the associations were contributed by POE-CpGs belonging to the atypical class and the most strongly enriched associations were with aging (DNAmTL acceleration), intelligence and parental (maternal) smoking exposure phenotypes. We further found that a proportion of the atypical-POE-CpGs formed co-methylation networks (modules) which are associated with these phenotypes, with one of the aging-associated modules displaying increased internal module connectivity (strength of methylation correlation across constituent CpGs) with age. Atypical POE-CpGs also displayed high levels of methylation heterogeneity and epigenetic drift (i.e. information loss with age) and a strong correlation with CpGs contained within epigenetic clocks. These results identified associations between the atypical-POE-influenced methylome and aging and provided new evidence for the "early development of origin" hypothesis for aging in humans.
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Affiliation(s)
- Chenhao Gao
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
| | - Carmen Amador
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Rosie M. Walker
- Centre for Clinical Brain Sciences, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- School of Psychology, University of Exeter, Perry Road, Exeter, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Rebecca A Madden
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark J. Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Xiaomeng Bai
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
| | - Ying Liu
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
| | - Miaoxin Li
- Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - David J. Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Xueyi Shen
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Kathryn L. Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Chris S. Haley
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK
| | - Andrew M. McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Yanni Zeng
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
- Guangdong Province Translational Forensic Medicine Engineering Technology Research Center Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
- Guangdong Province Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
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19
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Welsh P, Kimenai DM, Marioni RE, Hayward C, Campbell A, Porteous D, Mills NL, O’Rahilly S, Sattar N. Reference ranges for GDF-15, and risk factors associated with GDF-15, in a large general population cohort. Clin Chem Lab Med 2022; 60:1820-1829. [PMID: 35976089 PMCID: PMC9524804 DOI: 10.1515/cclm-2022-0135] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 08/01/2022] [Indexed: 11/15/2022]
Abstract
OBJECTIVES Growth differentiation factor (GDF)-15 is attracting interest as a biomarker in several areas of medicine. We aimed to evaluate the reference range for GDF-15 in a general population, and to explore demographics, classical cardiovascular disease risk factors, and other cardiac biomarkers associated with GDF-15. METHODS GDF-15 was measured in serum from 19,462 individuals in the Generation Scotland Scottish Family Health Study. Associations of cardiometabolic risk factors with GDF-15 were tested using adjusted linear regression. Among 18,507 participants with no heart disease, heart failure, or stroke, and not pregnant, reference ranges (median and 97.5th centiles) were derived by decade age bands and sex. RESULTS Among males in the reference range population, median (97.5th centile) GDF-15 concentration at age <30 years was 537 (1,135) pg/mL, rising to 931 (2,492) pg/mL at 50-59 years, and 2,152 (5,972) pg/mL at ≥80 years. In females, median GDF-15 at age <30 years was 628 (2,195) pg/mL, 881 (2,323) pg/mL at 50-59 years, and 1847 (6,830) pg/mL at ≥80 years. Among those known to be pregnant, median GDF-15 was 19,311 pg/mL. After adjustment, GDF-15 was higher in participants with adverse cardiovascular risk factors, including current smoking (+26.1%), those with previous heart disease (+12.7%), stroke (+17.1%), heart failure (+25.3%), and particularly diabetes (+60.2%). GDF-15 had positive associations with cardiac biomarkers cardiac troponin I, cardiac troponin T, and N-terminal pro B-type natriuretic peptide (NT-proBNP). CONCLUSIONS These data define reference ranges for GDF-15 for comparison in future studies, and identify potentially confounding risk factors and mediators to be considered in interpreting GDF-15 concentrations.
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Affiliation(s)
- Paul Welsh
- School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow, UK
| | - Dorien M. Kimenai
- BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
| | - Riccardo E. Marioni
- Institute of Genetics and Cancer (IGC), University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- MRC Human Genetics Unit (HGU), University of Edinburgh, Edinburgh, UK
| | - Archie Campbell
- Institute of Genetics and Cancer (IGC), University of Edinburgh, Edinburgh, UK
| | - David Porteous
- Institute of Genetics and Cancer (IGC), University of Edinburgh, Edinburgh, UK
| | - Nicholas L. Mills
- BHF Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, UK
- Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Stephen O’Rahilly
- MRC Metabolic Diseases Unit, Wellcome – MRC Institute of Metabolic Science, University of Cambridge, Cambridge, UK
- NIHR Cambridge Biomedical Research Centre, Cambridge, UK
| | - Naveed Sattar
- School of Cardiovascular & Metabolic Health, University of Glasgow, Glasgow, UK
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20
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Epigenetic and Proteomic Biomarkers of Elevated Alcohol Use Predict Epigenetic Aging and Cell-Type variation Better Than Self-Report. Genes (Basel) 2022; 13:genes13101888. [PMID: 36292773 PMCID: PMC9601579 DOI: 10.3390/genes13101888] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 10/12/2022] [Accepted: 10/15/2022] [Indexed: 11/17/2022] Open
Abstract
Excessive alcohol consumption (EAC) has a generally accepted effect on morbidity and mortality, outcomes thought to be reflected in measures of epigenetic aging (EA). As the association of self-reported EAC with EA has not been consistent with these expectations, underscoring the need for readily employable non-self-report tools for accurately assessing and monitoring the contribution of EAC to accelerated EA, newly developed alcohol consumption DNA methylation indices, such as the Alcohol T Score (ATS) and Methyl DetectR (MDR), may be helpful. To test that hypothesis, we used these new indices along with the carbohydrate deficient transferrin (CDT), concurrent as well as past self-reports of EAC, and well-established measures of cigarette smoking to examine the relationship of EAC to both accelerated EA and immune cell counts in a cohort of 437 young Black American adults. We found that MDR, CDT, and ATS were intercorrelated, even after controlling for gender and cotinine effects. Correlations between EA and self-reported EAC were low or non-significant, replicating prior research, whereas correlations with non-self-report indices were significant and more substantial. Comparing non-self-report indices showed that the ATS predicted more than four times as much variance in EA, CDT4 cells and B-cells as for both the MDR and CDT, and better predicted indices of accelerated EA. We conclude that each of the non-self-report indices have differing predictive capacities with respect to key alcohol-related health outcomes, and that the ATS may be particularly useful for clinicians seeking to understand and prevent accelerated EA. The results also underscore the likelihood of substantial underestimates of problematic use when self-report is used and a reduction in correlations with EA and variance in cell-types.
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21
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Higham J, Kerr L, Zhang Q, Walker RM, Harris SE, Howard DM, Hawkins EL, Sandu AL, Steele JD, Waiter GD, Murray AD, Evans KL, McIntosh AM, Visscher PM, Deary IJ, Cox SR, Sproul D. Local CpG density affects the trajectory and variance of age-associated DNA methylation changes. Genome Biol 2022; 23:216. [PMID: 36253871 PMCID: PMC9575273 DOI: 10.1186/s13059-022-02787-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 10/05/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND DNA methylation is an epigenetic mark associated with the repression of gene promoters. Its pattern in the genome is disrupted with age and these changes can be used to statistically predict age with epigenetic clocks. Altered rates of aging inferred from these clocks are observed in human disease. However, the molecular mechanisms underpinning age-associated DNA methylation changes remain unknown. Local DNA sequence can program steady-state DNA methylation levels, but how it influences age-associated methylation changes is unknown. RESULTS We analyze longitudinal human DNA methylation trajectories at 345,895 CpGs from 600 individuals aged between 67 and 80 to understand the factors responsible for age-associated epigenetic changes at individual CpGs. We show that changes in methylation with age occur at 182,760 loci largely independently of variation in cell type proportions. These changes are especially apparent at 8322 low CpG density loci. Using SNP data from the same individuals, we demonstrate that methylation trajectories are affected by local sequence polymorphisms at 1487 low CpG density loci. More generally, we find that low CpG density regions are particularly prone to change and do so variably between individuals in people aged over 65. This differs from the behavior of these regions in younger individuals where they predominantly lose methylation. CONCLUSIONS Our results, which we reproduce in two independent groups of individuals, demonstrate that local DNA sequence influences age-associated DNA methylation changes in humans in vivo. We suggest that this occurs because interactions between CpGs reinforce maintenance of methylation patterns in CpG dense regions.
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Affiliation(s)
- Jonathan Higham
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Lyndsay Kerr
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Qian Zhang
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
- Present address: Wellcome Sanger Institute, Hinxton, Cambridgeshire, UK
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
- Present address: School of Psychology, University of Exeter, Edinburgh, UK
| | - Sarah E Harris
- Department of Psychology, Lothian Birth Cohorts Group, University of Edinburgh, Edinburgh, UK
| | - David M Howard
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Emma L Hawkins
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Anca-Larisa Sandu
- Aberdeen Biomedical Imaging Centre, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
| | - J Douglas Steele
- Division of Imaging Science and Technology, Medical School, University of Dundee, Dundee, UK
| | - Gordon D Waiter
- Aberdeen Biomedical Imaging Centre, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
| | - Alison D Murray
- Aberdeen Biomedical Imaging Centre, Institute of Medical Sciences, University of Aberdeen, Aberdeen, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Peter M Visscher
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD, Australia
| | - Ian J Deary
- Department of Psychology, Lothian Birth Cohorts Group, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Department of Psychology, Lothian Birth Cohorts Group, University of Edinburgh, Edinburgh, UK
| | - Duncan Sproul
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
- CRUK Edinburgh Centre, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
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22
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Tesfaye R, Huguet G, Schmilovich Z, Renne T, Loum MA, Douard E, Saci Z, Jean-Louis M, Martineau JL, Whelan R, Desrivieres S, Heinz A, Schumann G, Hayward C, Elsabbagh M, Jacquemont S. Investigating the contributions of circadian pathway and insomnia risk genes to autism and sleep disturbances. Transl Psychiatry 2022; 12:424. [PMID: 36192372 PMCID: PMC9529939 DOI: 10.1038/s41398-022-02188-2] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Revised: 09/08/2022] [Accepted: 09/14/2022] [Indexed: 12/12/2022] Open
Abstract
Sleep disturbance is prevalent in youth with Autism Spectrum Disorder (ASD). Researchers have posited that circadian dysfunction may contribute to sleep problems or exacerbate ASD symptomatology. However, there is limited genetic evidence of this. It is also unclear how insomnia risk genes identified through GWAS in general populations are related to ASD and common sleep problems like insomnia traits in ASD. We investigated the contribution of copy number variants (CNVs) encompassing circadian pathway genes and insomnia risk genes to ASD risk as well as sleep disturbances in children with ASD. We studied 5860 ASD probands and 2092 unaffected siblings from the Simons Simplex Collection (SSC) and MSSNG database, as well as 7509 individuals from two unselected populations (IMAGEN and Generation Scotland). Sleep duration and insomnia symptoms were parent reported for SSC probands. We identified 335 and 616 rare CNVs encompassing circadian and insomnia risk genes respectively. Deletions and duplications with circadian genes were overrepresented in ASD probands compared to siblings and unselected controls. For insomnia-risk genes, deletions (not duplications) were associated with ASD in both cohorts. Results remained significant after adjusting for cognitive ability. CNVs containing circadian pathway and insomnia risk genes showed a stronger association with ASD, compared to CNVs containing other genes. Circadian genes did not influence sleep duration or insomnia traits in ASD. Insomnia risk genes intolerant to haploinsufficiency increased risk for insomnia when duplicated. CNVs encompassing circadian and insomnia risk genes increase ASD liability with little to no observable impacts on sleep disturbances.
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Affiliation(s)
- Rackeb Tesfaye
- McGill University, Neurology and Neurosurgery, Montreal Neurological Institute, Azrieli Centre for Autism Research, Montreal, Canada.
| | - Guillaume Huguet
- UHC Sainte-Justine Research Center, Université de Montréal, Montreal, Canada
| | | | - Thomas Renne
- UHC Sainte-Justine Research Center, Université de Montréal, Montreal, Canada
| | - Mor Absa Loum
- UHC Sainte-Justine Research Center, Université de Montréal, Montreal, Canada
| | - Elise Douard
- UHC Sainte-Justine Research Center, Université de Montréal, Montreal, Canada
| | - Zohra Saci
- UHC Sainte-Justine Research Center, Université de Montréal, Montreal, Canada
| | | | - Jean Luc Martineau
- Institut National de la Santé et de la Recherche Médicale, INSERM U A10 "Trajectoires développementales en psychiatrie", Université Paris-Saclay, Paris-Saclay, CNRS, Centre Borelli, Gif-sur-Yvette, France
| | - Rob Whelan
- Global Brain Health Institute and School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivieres
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, United Kingdom
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Gunter Schumann
- Centre for Population Neuroscience and Precision Medicine (PONS), Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, United Kingdom
- PONS Research Group, Dept of Psychiatry and Psychotherapy, Campus Charite Mitte, Humboldt University, Berlin and Leibniz Institute for Neurobiology, Magdeburg, Germany, and Institute for Science and Technology of Brain-inspired Intelligence (ISTBI), Fudan University, Shanghai, People's Republic of China
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, United Kingdom
- Generation Scotland, Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, United Kingdom
| | - Mayada Elsabbagh
- McGill University, Neurology and Neurosurgery, Montreal Neurological Institute, Azrieli Centre for Autism Research, Montreal, Canada
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23
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Welsh P, Campbell RT, Mooney L, Kimenai DM, Hayward C, Campbell A, Porteous D, Mills NL, Lang NN, Petrie MC, Januzzi JL, McMurray JJ, Sattar N. Reference Ranges for NT-proBNP (N-Terminal Pro-B-Type Natriuretic Peptide) and Risk Factors for Higher NT-proBNP Concentrations in a Large General Population Cohort. Circ Heart Fail 2022; 15:e009427. [PMID: 36098049 PMCID: PMC9561238 DOI: 10.1161/circheartfailure.121.009427] [Citation(s) in RCA: 25] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 07/11/2022] [Indexed: 11/25/2022]
Abstract
BACKGROUND Demographic differences in expected NT-proBNP (N-terminal pro-B-type natriuretic peptide) concentration are not well established. We aimed to establish reference ranges for NT-proBNP and explore the determinants of moderately elevated NT-proBNP under the universal definition of heart failure criteria. METHODS This is a cross-sectional study. NT-proBNP was measured in serum from 18 356 individuals without previous cardiovascular disease in the Generation Scotland Scottish Family Health Study. Age- and sex-stratified medians and 97.5th centiles were generated. Sex stratified risk factors for moderately elevated NT-proBNP (≥125 pg/mL) were investigated. RESULTS In males, median (97.5th centile) NT-proBNP concentration at age <30 years was 21 (104) pg/mL, rising to 38 (195) pg/ml at 50 to 59 years, and 281 (6792) pg/mL at ≥80 years. In females, median NT-proBNP at age <30 years was 51 (196) pg/mL, 66 (299) pg/mL at 50 to 59 years, and 240 (2704) pg/mL at ≥80 years. At age <30 years, 9.8% of females and 1.4% of males had elevated NT-proBNP, rising to 76.5% and 81.0%, respectively, at age ≥80 years. After adjusting for risk factors, an NT-proBNP ≥125 pg/mL was more common in females than males (OR, 9.48 [95% CI, 5.60-16.1]). Older age and smoking were more strongly associated with elevated NT-proBNP in males than in females (Psex interaction <0.001, 0.07, respectively). Diabetes was inversely associated with odds of elevated NT-proBNP in females only (Psex interaction=0.007). CONCLUSIONS An NT-proBNP ≥125 pg/mL is common in females without classical cardiovascular risk factors as well as older people. If NT-proBNP becomes widely used for screening in the general population, interpretation of NT-proBNP levels will require that age and sex-specific thresholds are used to identify patients with potential pathophysiology.
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Affiliation(s)
- Paul Welsh
- School of Cardiovascular and Metabolic Health, University of Glasgow, United Kingdom (P.W., R.T.C., L.M., N.N.L., M.C.P., J.J.V.M., N.S.)
| | - Ross T. Campbell
- School of Cardiovascular and Metabolic Health, University of Glasgow, United Kingdom (P.W., R.T.C., L.M., N.N.L., M.C.P., J.J.V.M., N.S.)
| | - Leanne Mooney
- School of Cardiovascular and Metabolic Health, University of Glasgow, United Kingdom (P.W., R.T.C., L.M., N.N.L., M.C.P., J.J.V.M., N.S.)
| | - Dorien M. Kimenai
- British Heart Foundation Centre for Cardiovascular Science (D.M.K., N.L.M.), University of Edinburgh, United Kingdom
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit (C.H.), University of Edinburgh, United Kingdom
| | - Archie Campbell
- Institute of Genetics and Cancer (A.C., D.P.), University of Edinburgh, United Kingdom
| | - David Porteous
- Institute of Genetics and Cancer (A.C., D.P.), University of Edinburgh, United Kingdom
| | - Nicholas L. Mills
- British Heart Foundation Centre for Cardiovascular Science (D.M.K., N.L.M.), University of Edinburgh, United Kingdom
- Usher Institute (N.L.M.), University of Edinburgh, United Kingdom
| | - Ninian N. Lang
- School of Cardiovascular and Metabolic Health, University of Glasgow, United Kingdom (P.W., R.T.C., L.M., N.N.L., M.C.P., J.J.V.M., N.S.)
| | - Mark C. Petrie
- School of Cardiovascular and Metabolic Health, University of Glasgow, United Kingdom (P.W., R.T.C., L.M., N.N.L., M.C.P., J.J.V.M., N.S.)
| | - James L. Januzzi
- Cardiology Division, Massachusetts General Hospital, Boston (J.L.J.)
- Harvard Medical School, Boston, MA (J.L.J.)
| | - John J.V. McMurray
- School of Cardiovascular and Metabolic Health, University of Glasgow, United Kingdom (P.W., R.T.C., L.M., N.N.L., M.C.P., J.J.V.M., N.S.)
| | - Naveed Sattar
- School of Cardiovascular and Metabolic Health, University of Glasgow, United Kingdom (P.W., R.T.C., L.M., N.N.L., M.C.P., J.J.V.M., N.S.)
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24
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Barbu MC, Harris M, Shen X, Aleks S, Green C, Amador C, Walker R, Morris S, Adams M, Sandu A, McNeil C, Waiter G, Evans K, Campbell A, Wardlaw J, Steele D, Murray A, Porteous D, McIntosh A, Whalley H. Epigenome-wide association study of global cortical volumes in generation Scotland: Scottish family health study. Epigenetics 2022; 17:1143-1158. [PMID: 34738878 PMCID: PMC9542280 DOI: 10.1080/15592294.2021.1997404] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Revised: 10/18/2021] [Accepted: 10/21/2021] [Indexed: 01/22/2023] Open
Abstract
A complex interplay of genetic and environmental risk factors influence global brain structural alterations associated with brain health and disease. Epigenome-wide association studies (EWAS) of global brain imaging phenotypes have the potential to reveal the mechanisms of brain health and disease and can lead to better predictive analytics through the development of risk scores.We perform an EWAS of global brain volumes in Generation Scotland using peripherally measured whole blood DNA methylation (DNAm) from two assessments, (i) at baseline recruitment, ~6 years prior to MRI assessment (N = 672) and (ii) concurrent with MRI assessment (N=565). Four CpGs at baseline were associated with global cerebral white matter, total grey matter, and whole-brain volume (Bonferroni p≤7.41×10-8, βrange = -1.46x10-6 to 9.59 × 10-7). These CpGs were annotated to genes implicated in brain-related traits, including psychiatric disorders, development, and ageing. We did not find significant associations in the meta-analysis of the EWAS of the two sets concurrent with imaging at the corrected level.These findings reveal global brain structural changes associated with DNAm measured ~6 years previously, indicating a potential role of early DNAm modifications in brain structure. Although concurrent DNAm was not associated with global brain structure, the nominally significant findings identified here present a rationale for future investigation of associations between DNA methylation and structural brain phenotypes in larger population-based samples.
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Affiliation(s)
- Miruna Carmen Barbu
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Mat Harris
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Xueyi Shen
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Stolicyn Aleks
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Claire Green
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Carmen Amador
- Mrc Human Genetics Unit, Institute of Genetics and Cancer, the University of Edinburgh, UK
| | - Rosie Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, the University of Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, UK
| | - Stewart Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, the University of Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, UK
| | - Mark Adams
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Anca Sandu
- Aberdeen Biomedical Imaging Centre, The Institute of Medical Sciences, University of Aberdeen, UK
| | - Christopher McNeil
- Aberdeen Biomedical Imaging Centre, The Institute of Medical Sciences, University of Aberdeen, UK
| | - Gordon Waiter
- Aberdeen Biomedical Imaging Centre, The Institute of Medical Sciences, University of Aberdeen, UK
| | - Kathryn Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, the University of Edinburgh, UK
- Centre for Clinical Brain Sciences, The University of Edinburgh, UK
| | - Archie Campbell
- Mrc Human Genetics Unit, Institute of Genetics and Cancer, the University of Edinburgh, UK
| | - Joanna Wardlaw
- Centre for Clinical Brain Sciences, The University of Edinburgh, UK
| | - Douglas Steele
- Imaging Science and Technology, School of Medicine, University of Dundee, DundeeUK
| | - Alison Murray
- Aberdeen Biomedical Imaging Centre, The Institute of Medical Sciences, University of Aberdeen, UK
| | - David Porteous
- Mrc Human Genetics Unit, Institute of Genetics and Cancer, the University of Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, UK
| | - Andrew McIntosh
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, School of Philosophy, Psychology and Language Sciences, The University of Edinburgh, UK
| | - Heather Whalley
- Division of Psychiatry, The University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
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25
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Green MJ, Maddock J, Di Gessa G, Wielgoszewska B, Parsons S, Griffith GJ, Croft J, Stevenson AJ, Huggins CF, Booth C, Wels J, Silverwood RJ, Patalay P, Hughes AD, Chaturvedi N, Howe LD, Fitzsimons E, Katikireddi SV, Ploubidis GB. The UK Coronavirus Job Retention Scheme and smoking, alcohol consumption and vaping during the COVID-19 pandemic: evidence from eight longitudinal population surveys. BMC Med 2022; 20:345. [PMID: 36127702 PMCID: PMC9489267 DOI: 10.1186/s12916-022-02511-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 08/02/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Employment disruptions can impact smoking and alcohol consumption. During the COVID-19 pandemic, many countries implemented furlough schemes to prevent job loss. We examine how furlough was associated with smoking, vaping and alcohol consumption in the UK. METHODS Data from 27,841 participants in eight UK adult longitudinal surveys were analysed. Participants self-reported employment status and current smoking, current vaping and alcohol consumption (>4 days/week or 5+ drinks per typical occasion) both before and during the early stages of the pandemic (April-July 2020). Risk ratios were estimated within each study using modified Poisson regression, adjusting for a range of potential confounders, including pre-pandemic behaviour. Findings were synthesised using random effects meta-analysis. RESULTS Compared to stable employment and after adjustment for pre-pandemic characteristics, furlough was not associated with smoking (ARR = 1.05; 95% CI: 0.95-1.16; I2: 10%), vaping (ARR = 0.89; 95% CI: 0.74-1.08; I2: 0%) or drinking (ARR = 1.03; 95% CI: 0.94-1.13; I2: 48%). There were similar findings for no longer being employed, and stable unemployment, though this varied by sex: stable unemployment was associated with smoking for women (ARR = 1.35; 95% CI: 1.00-1.82; I2: 47%) but not men (0.84; 95% CI: 0.67-1.05; I2: 0%). No longer being employed was associated with vaping among women (ARR = 2.74; 95% CI: 1.59-4.72; I2: 0%) but not men (ARR = 1.25; 95% CI: 0.83-1.87; I2: 0%). CONCLUSIONS We found no clear evidence of furlough or unemployment having adverse impacts on smoking, vaping or drinking behaviours during the early stages of the COVID-19 pandemic in the UK. Differences in risk compared to those who remained employed were largely explained by pre-pandemic characteristics.
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Affiliation(s)
- Michael J Green
- MRC/CSO Social & Public Health Sciences Unit, University of Glasgow, Glasgow, UK.
| | - Jane Maddock
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Giorgio Di Gessa
- Institute of Epidemiology and Health Care, University College London, London, UK
| | - Bożena Wielgoszewska
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK
| | - Sam Parsons
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK
| | - Gareth J Griffith
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Jazz Croft
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Charlotte F Huggins
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, UK
| | - Charlotte Booth
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK
| | - Jacques Wels
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Richard J Silverwood
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK
| | - Praveetha Patalay
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK.,Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK
| | - Alun D Hughes
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Nishi Chaturvedi
- MRC Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Laura D Howe
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Emla Fitzsimons
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK
| | | | - George B Ploubidis
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, London, UK
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26
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Hillary RF, McCartney DL, McRae AF, Campbell A, Walker RM, Hayward C, Horvath S, Porteous DJ, Evans KL, Marioni RE. Identification of influential probe types in epigenetic predictions of human traits: implications for microarray design. Clin Epigenetics 2022; 14:100. [PMID: 35948928 PMCID: PMC9367152 DOI: 10.1186/s13148-022-01320-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Accepted: 07/29/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND CpG methylation levels can help to explain inter-individual differences in phenotypic traits. Few studies have explored whether identifying probe subsets based on their biological and statistical properties can maximise predictions whilst minimising array content. Variance component analyses and penalised regression (epigenetic predictors) were used to test the influence of (i) the number of probes considered, (ii) mean probe variability and (iii) methylation QTL status on the variance captured in eighteen traits by blood DNA methylation. Training and test samples comprised ≤ 4450 and ≤ 2578 unrelated individuals from Generation Scotland, respectively. RESULTS As the number of probes under consideration decreased, so too did the estimates from variance components and prediction analyses. Methylation QTL status and mean probe variability did not influence variance components. However, relative effect sizes were 15% larger for epigenetic predictors based on probes with known or reported methylation QTLs compared to probes without reported methylation QTLs. Relative effect sizes were 45% larger for predictors based on probes with mean Beta-values between 10 and 90% compared to those based on hypo- or hypermethylated probes (Beta-value ≤ 10% or ≥ 90%). CONCLUSIONS Arrays with fewer probes could reduce costs, leading to increased sample sizes for analyses. Our results show that reducing array content can restrict prediction metrics and careful attention must be given to the biological and distribution properties of CpG probes in array content selection.
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Affiliation(s)
- Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK.
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, 4072, Australia
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK.,Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh, EH16 4SB, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, 90095-7088, USA.,Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, 90095-1772, USA
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Crewe Road South, Edinburgh, EH4 2XU, UK
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27
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Kimenai DM, Pirondini L, Gregson J, Prieto D, Pocock SJ, Perel P, Hamilton T, Welsh P, Campbell A, Porteous DJ, Hayward C, Sattar N, Mills NL, Shah ASV. Socioeconomic Deprivation: An Important, Largely Unrecognized Risk Factor in Primary Prevention of Cardiovascular Disease. Circulation 2022; 146:240-248. [PMID: 35748241 PMCID: PMC9287096 DOI: 10.1161/circulationaha.122.060042] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/03/2022]
Abstract
Background: Socioeconomic deprivation is associated with higher cardiovascular morbidity and mortality. Whether deprivation status should be incorporated in more cardiovascular risk estimation scores remains unclear. This study evaluates how socioeconomic deprivation status affects the performance of 3 primary prevention cardiovascular risk scores. Methods: The Generation Scotland Scottish Family Health Study was used to evaluate the performance of 3 cardiovascular risk scores with (ASSIGN [Assessing cardiovascular risk using SIGN (Scottish Intercollegiate Guidelines Network) guidelines to ASSIGN preventive treatment]) and without (SCORE2 [Systematic Coronary Risk Evaluation 2 algorithm], Pooled Cohort Equations) socioeconomic deprivation as a covariate in the risk prediction model. Deprivation was defined by Scottish Index of Multiple Deprivation score. The predicted 10-year risk was evaluated against the observed event rate for the cardiovascular outcome of each risk score. The comparison was made across 3 groups defined by the deprivation index score consisting of group 1 defined as most deprived, group 3 defined as least deprived, and group 2, which consisted of individuals in the middle deprivation categories. Results: The study population consisted of 15 506 individuals (60.0% female, median age of 51). Across the population, 1808 (12%) individuals were assigned to group 1 (most deprived), 8119 (52%) to group 2, and 4708 (30%) to group 3 (least deprived), and 871 (6%) individuals had a missing deprivation score. Risk scores based on models that did not include deprivation status significantly under predicted risk in the most deprived (6.43% observed versus 4.63% predicted for SCORE2 [P=0.001] and 6.69% observed versus 4.66% predicted for Pooled Cohort Equations [P<0.001]). Both risk scores also significantly overpredicted the risk in the least deprived group (3.97% observed versus 4.72% predicted for SCORE2 [P=0.007] and 4.22% observed versus 4.85% predicted for Pooled Cohort Equations [P=0.028]). In contrast, no significant difference was demonstrated in the observed versus predicted risk when using the ASSIGN risk score, which included socioeconomic deprivation status in the risk model. Conclusions: Socioeconomic status is a largely unrecognized risk factor in primary prevention of cardiovascular disease. Risk scores that exclude socioeconomic deprivation as a covariate under- and overestimate the risk in the most and least deprived individuals, respectively. This study highlights the importance of incorporating socioeconomic deprivation status in risk estimation systems to ultimately reduce inequalities in health care provision for cardiovascular disease.
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Affiliation(s)
- Dorien M Kimenai
- British Heart Foundation Centre for Cardiovascular Science (D. M.K., T.H., N.L.M.), University of Edinburgh, United Kingdom
| | - Leah Pirondini
- Department of Medical Statistics (L.P., J.G., S.J.P.), London School of Hygiene & Tropical Medicine, United Kingdom
| | - John Gregson
- Department of Medical Statistics (L.P., J.G., S.J.P.), London School of Hygiene & Tropical Medicine, United Kingdom
| | - David Prieto
- Department of Non-communicable Disease Epidemiology (D.P., P.P., A.S.V.S.), London School of Hygiene & Tropical Medicine, United Kingdom
| | - Stuart J Pocock
- Department of Medical Statistics (L.P., J.G., S.J.P.), London School of Hygiene & Tropical Medicine, United Kingdom
| | - Pablo Perel
- Department of Non-communicable Disease Epidemiology (D.P., P.P., A.S.V.S.), London School of Hygiene & Tropical Medicine, United Kingdom
| | - Tilly Hamilton
- British Heart Foundation Centre for Cardiovascular Science (D. M.K., T.H., N.L.M.), University of Edinburgh, United Kingdom
| | - Paul Welsh
- Institute of Cardiovascular & Medical Sciences, University of Glasgow, United Kingdom (P.W., N.S.)
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine (A.C., D.J.P.), University of Edinburgh, United Kingdom
| | - David J Porteous
- Centre for Genomic and Experimental Medicine (A.C., D.J.P.), University of Edinburgh, United Kingdom
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit (C.H.), University of Edinburgh, United Kingdom
| | - Naveed Sattar
- Institute of Cardiovascular & Medical Sciences, University of Glasgow, United Kingdom (P.W., N.S.)
| | - Nicholas L Mills
- British Heart Foundation Centre for Cardiovascular Science (D. M.K., T.H., N.L.M.), University of Edinburgh, United Kingdom.,Institute of Genetics and Cancer, Usher Institute (N.L.M.), University of Edinburgh, United Kingdom
| | - Anoop S V Shah
- Department of Non-communicable Disease Epidemiology (D.P., P.P., A.S.V.S.), London School of Hygiene & Tropical Medicine, United Kingdom
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28
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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] [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
| | -
- 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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29
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Shen X, Caramaschi D, Adams MJ, Walker RM, Min JL, Kwong A, Hemani G, Barbu MC, Whalley HC, Harris SE, Deary IJ, Morris SW, Cox SR, Relton CL, Marioni RE, Evans KL, McIntosh AM. DNA methylome-wide association study of genetic risk for depression implicates antigen processing and immune responses. Genome Med 2022; 14:36. [PMID: 35354486 PMCID: PMC8969265 DOI: 10.1186/s13073-022-01039-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2021] [Accepted: 03/14/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Depression is a disabling and highly prevalent condition where genetic and epigenetic, such as DNA methylation (DNAm), differences contribute to disease risk. DNA methylation is influenced by genetic variation but the association between polygenic risk of depression and DNA methylation is unknown. METHODS We investigated the association between polygenic risk scores (PRS) for depression and DNAm by conducting a methylome-wide association study (MWAS) in Generation Scotland (N = 8898, mean age = 49.8 years) with replication in the Lothian Birth Cohorts of 1921 and 1936 and adults in the Avon Longitudinal Study of Parents and Children (ALSPAC) (Ncombined = 2049, mean age = 79.1, 69.6 and 47.2 years, respectively). We also conducted a replication MWAS in the ALSPAC children (N = 423, mean age = 17.1 years). Gene ontology analysis was conducted for the cytosine-guanine dinucleotide (CpG) probes significantly associated with depression PRS, followed by Mendelian randomisation (MR) analysis to infer the causal relationship between depression and DNAm. RESULTS Widespread associations (NCpG = 71, pBonferroni < 0.05, p < 6.3 × 10-8) were found between PRS constructed using genetic risk variants for depression and DNAm in CpG probes that localised to genes involved in immune responses and neural development. The effect sizes for the significant associations were highly correlated between the discovery and replication samples in adults (r = 0.79) and in adolescents (r = 0.82). Gene Ontology analysis showed that significant CpG probes are enriched in immunological processes in the human leukocyte antigen system. Additional MWAS was conducted for each lead genetic risk variant. Over 47.9% of the independent genetic risk variants included in the PRS showed associations with DNAm in CpG probes located in both the same (cis) and distal (trans) locations to the genetic loci (pBonferroni < 0.045). Subsequent MR analysis showed that there are a greater number of causal effects found from DNAm to depression than vice versa (DNAm to depression: pFDR ranged from 0.024 to 7.45 × 10-30; depression to DNAm: pFDR ranged from 0.028 to 0.003). CONCLUSIONS PRS for depression, especially those constructed from genome-wide significant genetic risk variants, showed methylome-wide differences associated with immune responses. Findings from MR analysis provided evidence for causal effect of DNAm to depression.
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Affiliation(s)
- Xueyi Shen
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh, EH10 5HF, UK.
| | - Doretta Caramaschi
- College of Life and Environmental Sciences, Psychology, University of Exeter, Exeter, UK
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh, EH10 5HF, UK
| | - Rosie M Walker
- Centre for Clinical Brain Sciences, Chancellor's Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, UK
| | - Josine L Min
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Alex Kwong
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh, EH10 5HF, UK
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Gibran Hemani
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Miruna C Barbu
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh, EH10 5HF, UK
| | - Heather C Whalley
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh, EH10 5HF, UK
| | - Sarah E Harris
- Lothian Birth Cohorts group, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Lothian Birth Cohorts group, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Stewart W Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Lothian Birth Cohorts group, Department of Psychology, The University of Edinburgh, Edinburgh, UK
| | - Caroline L Relton
- Medical Research Council Integrative Epidemiology Unit, Bristol Medical School, Population Health Sciences, University of Bristol, Bristol, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Morningside Park, Edinburgh, EH10 5HF, UK.
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30
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Lohoff FW, Clarke TK, Kaminsky ZA, Walker RM, Bermingham ML, Jung J, Morris SW, Rosoff D, Campbell A, Barbu M, Charlet K, Adams M, Lee J, Howard DM, O'Connell EM, Whalley H, Porteous DJ, McIntosh AM, Evans KL. Epigenome-wide association study of alcohol consumption in N = 8161 individuals and relevance to alcohol use disorder pathophysiology: identification of the cystine/glutamate transporter SLC7A11 as a top target. Mol Psychiatry 2022; 27:1754-1764. [PMID: 34857913 PMCID: PMC9095480 DOI: 10.1038/s41380-021-01378-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2021] [Revised: 09/22/2021] [Accepted: 10/25/2021] [Indexed: 12/23/2022]
Abstract
Alcohol misuse is common in many societies worldwide and is associated with extensive morbidity and mortality, often leading to alcohol use disorders (AUD) and alcohol-related end-organ damage. The underlying mechanisms contributing to the development of AUD are largely unknown; however, growing evidence suggests that alcohol consumption is strongly associated with alterations in DNA methylation. Identification of alcohol-associated methylomic variation might provide novel insights into pathophysiology and novel treatment targets for AUD. Here we performed the largest single-cohort epigenome-wide association study (EWAS) of alcohol consumption to date (N = 8161) and cross-validated findings in AUD populations with relevant endophenotypes, as well as alcohol-related animal models. Results showed 2504 CpGs significantly associated with alcohol consumption (Bonferroni p value < 6.8 × 10-8) with the five leading probes located in SLC7A11 (p = 7.75 × 10-108), JDP2 (p = 1.44 × 10-56), GAS5 (p = 2.71 × 10-47), TRA2B (p = 3.54 × 10-42), and SLC43A1 (p = 1.18 × 10-40). Genes annotated to associated CpG sites are implicated in liver and brain function, the cellular response to alcohol and alcohol-associated diseases, including hypertension and Alzheimer's disease. Two-sample Mendelian randomization confirmed the causal relationship of consumption on AUD risk (inverse variance weighted (IVW) p = 5.37 × 10-09). A methylation-based predictor of alcohol consumption was able to discriminate AUD cases in two independent cohorts (p = 6.32 × 10-38 and p = 5.41 × 10-14). The top EWAS probe cg06690548, located in the cystine/glutamate transporter SLC7A11, was replicated in an independent cohort of AUD and control participants (N = 615) and showed strong hypomethylation in AUD (p < 10-17). Decreased CpG methylation at this probe was consistently associated with clinical measures including increased heavy drinking days (p < 10-4), increased liver function enzymes (GGT (p = 1.03 × 10-21), ALT (p = 1.29 × 10-6), and AST (p = 1.97 × 10-8)) in individuals with AUD. Postmortem brain analyses documented increased SLC7A11 expression in the frontal cortex of individuals with AUD and animal models showed marked increased expression in liver, suggesting a mechanism by which alcohol leads to hypomethylation-induced overexpression of SLC7A11. Taken together, our EWAS discovery sample and subsequent validation of the top probe in AUD suggest a strong role of abnormal glutamate signaling mediated by methylomic variation in SLC7A11. Our data are intriguing given the prominent role of glutamate signaling in brain and liver and might provide an important target for therapeutic intervention.
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Affiliation(s)
- Falk W Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA.
| | - Toni-Kim Clarke
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Zachary A Kaminsky
- Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, ON, Canada
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Mairead L Bermingham
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Jeesun Jung
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Stewart W Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Daniel Rosoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Miruna Barbu
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Katrin Charlet
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Mark Adams
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Jisoo Lee
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - David M Howard
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Emma M O'Connell
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Heather Whalley
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Royal Edinburgh Hospital, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
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McCartney DL, Hillary RF, Conole ELS, Banos DT, Gadd DA, Walker RM, Nangle C, Flaig R, Campbell A, Murray AD, Maniega SM, Valdés-Hernández MDC, Harris MA, Bastin ME, Wardlaw JM, Harris SE, Porteous DJ, Tucker-Drob EM, McIntosh AM, Evans KL, Deary IJ, Cox SR, Robinson MR, Marioni RE. Blood-based epigenome-wide analyses of cognitive abilities. Genome Biol 2022; 23:26. [PMID: 35039062 PMCID: PMC8762878 DOI: 10.1186/s13059-021-02596-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Accepted: 12/29/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Blood-based markers of cognitive functioning might provide an accessible way to track neurodegeneration years prior to clinical manifestation of cognitive impairment and dementia. RESULTS Using blood-based epigenome-wide analyses of general cognitive function, we show that individual differences in DNA methylation (DNAm) explain 35.0% of the variance in general cognitive function (g). A DNAm predictor explains ~4% of the variance, independently of a polygenic score, in two external cohorts. It also associates with circulating levels of neurology- and inflammation-related proteins, global brain imaging metrics, and regional cortical volumes. CONCLUSIONS As sample sizes increase, the ability to assess cognitive function from DNAm data may be informative in settings where cognitive testing is unreliable or unavailable.
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Affiliation(s)
- Daniel L. McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Robert F. Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Eleanor L. S. Conole
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB UK
| | - Daniel Trejo Banos
- Department of Quantitative Biomedicine, University of Zurich, Zurich, Switzerland
- Biomedical Informatics, University Hospital of Zurich, Zurich, Switzerland
| | - Danni A. Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Rosie M. Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB UK
| | - Cliff Nangle
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Robin Flaig
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Alison D. Murray
- Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, Scotland, UK
| | - Susana Muñoz Maniega
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB UK
| | - María del C. Valdés-Hernández
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB UK
| | - Mathew A. Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - Mark E. Bastin
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB UK
| | - Joanna M. Wardlaw
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, EH16 4SB UK
| | - Sarah E. Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - David J. Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Elliot M. Tucker-Drob
- Department of Psychology, University of Texas, Austin, TX USA
- Population Research Center and Center on Aging and Population Sciences, University of Texas, Austin, TX USA
| | - Andrew M. McIntosh
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Kathryn L. Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
| | - Ian J. Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | - Simon R. Cox
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ UK
| | | | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU UK
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Oppong RF, Boutin T, Campbell A, McIntosh AM, Porteous D, Hayward C, Haley CS, Navarro P, Knott S. SNP and Haplotype Regional Heritability Mapping (SNHap-RHM): Joint Mapping of Common and Rare Variation Affecting Complex Traits. Front Genet 2022; 12:791712. [PMID: 35069690 PMCID: PMC8770330 DOI: 10.3389/fgene.2021.791712] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 12/14/2021] [Indexed: 11/13/2022] Open
Abstract
We describe a genome-wide analytical approach, SNP and Haplotype Regional Heritability Mapping (SNHap-RHM), that provides regional estimates of the heritability across locally defined regions in the genome. This approach utilises relationship matrices that are based on sharing of SNP and haplotype alleles at local haplotype blocks delimited by recombination boundaries in the genome. We implemented the approach on simulated data and show that the haplotype-based regional GRMs capture variation that is complementary to that captured by SNP-based regional GRMs, and thus justifying the fitting of the two GRMs jointly in a single analysis (SNHap-RHM). SNHap-RHM captures regions in the genome contributing to the phenotypic variation that existing genome-wide analysis methods may fail to capture. We further demonstrate that there are real benefits to be gained from this approach by applying it to real data from about 20,000 individuals from the Generation Scotland: Scottish Family Health Study. We analysed height and major depressive disorder (MDD). We identified seven genomic regions that are genome-wide significant for height, and three regions significant at a suggestive threshold (p-value < 1 × 10-5) for MDD. These significant regions have genes mapped to within 400 kb of them. The genes mapped for height have been reported to be associated with height in humans. Similarly, those mapped for MDD have been reported to be associated with major depressive disorder and other psychiatry phenotypes. The results show that SNHap-RHM presents an exciting new opportunity to analyse complex traits by allowing the joint mapping of novel genomic regions tagged by either SNPs or haplotypes, potentially leading to the recovery of some of the "missing" heritability.
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Affiliation(s)
- Richard F. Oppong
- Longitudinal Studies Section, Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD, United States
- Institute of Evolutionary Biology, School of Biological Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Thibaud Boutin
- MRC Human Genetics Unit, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew M. McIntosh
- Division of Psychiatry, The University of Edinburgh, Edinburgh, United Kingdom
| | - David Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom
| | - Chris S. Haley
- MRC Human Genetics Unit, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom
- The Roslin Institute and Royal (Dick) School of Veterinary Studies, The University of Edinburgh, Edinburgh, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Cancer, The University of Edinburgh, Edinburgh, United Kingdom
| | - Sara Knott
- Institute of Evolutionary Biology, School of Biological Sciences, The University of Edinburgh, Edinburgh, United Kingdom
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Di Gessa G, Maddock J, Green MJ, Thompson EJ, McElroy E, Davies HL, Mundy J, Stevenson AJ, Kwong ASF, Griffith GJ, Katikireddi SV, Niedzwiedz CL, Ploubidis GB, Fitzsimons E, Henderson M, Silverwood RJ, Chaturvedi N, Breen G, Steves CJ, Steptoe A, Porteous DJ, Patalay P. Pre-pandemic mental health and disruptions to healthcare, economic and housing outcomes during the COVID-19 pandemic: evidence from 12 UK longitudinal studies. Br J Psychiatry 2022; 220:21-30. [PMID: 35045893 DOI: 10.1192/bjp.2021.132] [Citation(s) in RCA: 19] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
BACKGROUND The COVID-19 pandemic has disrupted lives and livelihoods, and people already experiencing mental ill health may have been especially vulnerable. AIMS Quantify mental health inequalities in disruptions to healthcare, economic activity and housing. METHOD We examined data from 59 482 participants in 12 UK longitudinal studies with data collected before and during the COVID-19 pandemic. Within each study, we estimated the association between psychological distress assessed pre-pandemic and disruptions since the start of the pandemic to healthcare (medication access, procedures or appointments), economic activity (employment, income or working hours) and housing (change of address or household composition). Estimates were pooled across studies. RESULTS Across the analysed data-sets, 28% to 77% of participants experienced at least one disruption, with 2.3-33.2% experiencing disruptions in two or more domains. We found 1 s.d. higher pre-pandemic psychological distress was associated with (a) increased odds of any healthcare disruptions (odds ratio (OR) 1.30, 95% CI 1.20-1.40), with fully adjusted odds ratios ranging from 1.24 (95% CI 1.09-1.41) for disruption to procedures to 1.33 (95% CI 1.20-1.49) for disruptions to prescriptions or medication access; (b) loss of employment (odds ratio 1.13, 95% CI 1.06-1.21) and income (OR 1.12, 95% CI 1.06 -1.19), and reductions in working hours/furlough (odds ratio 1.05, 95% CI 1.00-1.09) and (c) increased likelihood of experiencing a disruption in at least two domains (OR 1.25, 95% CI 1.18-1.32) or in one domain (OR 1.11, 95% CI 1.07-1.16), relative to no disruption. There were no associations with housing disruptions (OR 1.00, 95% CI 0.97-1.03). CONCLUSIONS People experiencing psychological distress pre-pandemic were more likely to experience healthcare and economic disruptions, and clusters of disruptions across multiple domains during the pandemic. Failing to address these disruptions risks further widening mental health inequalities.
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Affiliation(s)
- Giorgio Di Gessa
- Institute of Epidemiology and Health Care, University College London, UK
| | - Jane Maddock
- MRC Unit for Lifelong Health and Ageing, University College London, UK
| | - Michael J Green
- MRC/CSO Social & Public Health Sciences Unit, University of Glasgow, UK
| | - Ellen J Thompson
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, UK
| | - Eoin McElroy
- Department of Neuroscience, Psychology and Behaviour, University of Leicester, UK
| | - Helena L Davies
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK
| | - Jessica Mundy
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, University of Edinburgh, UK
| | - Alex S F Kwong
- Division of Psychiatry, University of Edinburgh, UK; and MRC Integrative Epidemiology Unit, University of Bristol, UK
| | | | | | | | - George B Ploubidis
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, UK
| | - Emla Fitzsimons
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, UK
| | - Morag Henderson
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, UK
| | - Richard J Silverwood
- Centre for Longitudinal Studies, UCL Social Research Institute, University College London, UK
| | - Nish Chaturvedi
- MRC Unit for Lifelong Health and Ageing, University College London, UK
| | - Gerome Breen
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, UK; and Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London, UK
| | - Claire J Steves
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, UK
| | - Andrew Steptoe
- Institute of Epidemiology and Health Care, University College London, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, University of Edinburgh, UK
| | - Praveetha Patalay
- MRC Unit for Lifelong Health and Ageing, University College London, UK; and Centre for Longitudinal Studies, UCL Social Research Institute, University College London, UK
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35
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Zeng Y, Amador C, Gao C, Walker RM, Morris SW, Campbell A, Frkatović A, Madden RA, Adams MJ, He S, Bretherick AD, Hayward C, Porteous DJ, Wilson JF, Evans KL, McIntosh AM, Navarro P, Haley CS. Lifestyle and Genetic Factors Modify Parent-of-Origin Effects on the Human Methylome. EBioMedicine 2021; 74:103730. [PMID: 34883445 PMCID: PMC8654798 DOI: 10.1016/j.ebiom.2021.103730] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2021] [Revised: 11/19/2021] [Accepted: 11/19/2021] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND parent-of-origin effects (POE) play important roles in complex disease and thus understanding their regulation and associated molecular and phenotypic variation are warranted. Previous studies mainly focused on the detection of genomic regions or phenotypes regulated by POE. Understanding whether POE may be modified by environmental or genetic exposures is important for understanding of the source of POE-associated variation, but only a few case studies addressing modifiable POE exist. METHODS in order to understand this high order of POE regulation, we screened 101 genetic and environmental factors such as 'predicted mRNA expression levels' of DNA methylation/imprinting machinery genes and environmental exposures. POE-mQTL-modifier interaction models were proposed to test the potential of these factors to modify POE at DNA methylation using data from Generation Scotland: The Scottish Family Health Study(N=2315). FINDINGS a set of vulnerable/modifiable POE-CpGs were identified (modifiable-POE-regulated CpGs, N=3). Four factors, 'lifetime smoking status' and 'predicted mRNA expression levels' of TET2, SIRT1 and KDM1A, were found to significantly modify the POE on the three CpGs in both discovery and replication datasets. We further identified plasma protein and health-related phenotypes associated with the methylation level of one of the identified CpGs. INTERPRETATION the modifiable POE identified here revealed an important yet indirect path through which genetic background and environmental exposures introduce their effect on DNA methylation, motivating future comprehensive evaluation of the role of these modifiers in complex diseases. FUNDING NSFC (81971270),H2020-MSCA-ITN(721815), Wellcome (204979/Z/16/Z,104036/Z/14/Z), MRC (MC_UU_00007/10, MC_PC_U127592696), CSO (CZD/16/6,CZB/4/276, CZB/4/710), SFC (HR03006), EUROSPAN (LSHG-CT-2006-018947), BBSRC (BBS/E/D/30002276), SYSU, Arthritis Research UK, NHLBI, NIH.
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Affiliation(s)
- Yanni Zeng
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China; Guangdong Province Translational Forensic Medicine Engineering Technology Research Center, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China; Guangdong Province Key Laboratory of Brain Function and Disease, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China.
| | - Carmen Amador
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Chenhao Gao
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou 510080, China
| | - Rosie M Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK; Centre for Clinical Brain Sciences, Chancellor's Building, The University of Edinburgh, Edinburgh, UK
| | - Stewart W Morris
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Azra Frkatović
- Genos Glycoscience Research Laboratory, Borongajska cesta 83h, 10000 Zagreb, Croatia
| | - Rebecca A Madden
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Mark J Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Shuai He
- Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, 510060, China
| | - Andrew D Bretherick
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - James F Wilson
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK; Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK.
| | - Chris S Haley
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK; Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, UK.
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Antoniades A, Papaioannou M, Malatras A, Papagregoriou G, Müller H, Holub P, Deltas C, Schizas CN. Integration of Biobanks in National eHealth Ecosystems Facilitating Long-Term Longitudinal Clinical-Omics Studies and Citizens' Engagement in Research Through eHealthBioR. Front Digit Health 2021; 3:628646. [PMID: 34713101 PMCID: PMC8521893 DOI: 10.3389/fdgth.2021.628646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2020] [Accepted: 05/11/2021] [Indexed: 11/13/2022] Open
Abstract
Biobanks have long existed to support research activities with BBMRI-ERIC formed as a European research infrastructure supporting the coordination for biobanking with 20 country members and one international organization. Although the benefits of biobanks to the research community are well-established, the direct benefit to citizens is limited to the generic benefit of promoting future research. Furthermore, the advent of General Data Protection Regulation (GDPR) legislation raised a series of challenges for scientific research especially related to biobanking associate activities and longitudinal research studies. Electronic health record (EHR) registries have long existed in healthcare providers. In some countries, even at the national level, these record the state of the health of citizens through time for the purposes of healthcare and data portability between different providers. The potential of EHRs in research is great and has been demonstrated in many projects that have transformed EHR data into retrospective medical history information on participating subjects directly from their physician's collected records; many key challenges, however, remain. In this paper, we present a citizen-centric framework called eHealthBioR, which would enable biobanks to link to EHR systems, thus enabling not just retrospective but also lifelong prospective longitudinal studies of participating citizens. It will also ensure strict adherence to legal and ethical requirements, enabling greater control that encourages participation. Citizens would benefit from the real and direct control of their data and samples, utilizing technology, to empower them to make informed decisions about providing consent and practicing their rights related to the use of their data, as well as by having access to knowledge and data generated from samples they provided to biobanks. This is expected to motivate patient engagement in future research and even leads to participatory design methodologies with citizen/patient-centric designed studies. The development of platforms based on the eHealthBioR framework would need to overcome significant challenges. However, it would shift the burden of addressing these to experts in the field while providing solutions enabling in the long term the lower monetary and time cost of longitudinal studies coupled with the option of lifelong monitoring through EHRs.
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Affiliation(s)
- Athos Antoniades
- eHealth Lab, Department of Computer Science, University of Cyprus, Nicosia, Cyprus
| | - Maria Papaioannou
- eHealth Lab, Department of Computer Science, University of Cyprus, Nicosia, Cyprus
| | - Apostolos Malatras
- biobank.cy Center of Excellence in Biobanking and Biomedical Research, University of Cyprus, Nicosia, Cyprus
| | - Gregory Papagregoriou
- biobank.cy Center of Excellence in Biobanking and Biomedical Research, University of Cyprus, Nicosia, Cyprus
| | - Heimo Müller
- Institute of Pathology, Medical University of Graz, Graz, Austria.,Biobanking and Biomolecular Resources Research Infrastructure - European Research Infrastructure Consortium, Biobanks and Biomolecular Resources Research Infrastructure Consortium, Graz, Austria
| | - Petr Holub
- Biobanking and Biomolecular Resources Research Infrastructure - European Research Infrastructure Consortium, Biobanks and Biomolecular Resources Research Infrastructure Consortium, Graz, Austria
| | - Constantinos Deltas
- biobank.cy Center of Excellence in Biobanking and Biomedical Research, University of Cyprus, Nicosia, Cyprus
| | - Christos N Schizas
- eHealth Lab, Department of Computer Science, University of Cyprus, Nicosia, Cyprus
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Daniels H, Jones KH, Heys S, Ford DV. Exploring the Use of Genomic and Routinely Collected Data: Narrative Literature Review and Interview Study. J Med Internet Res 2021; 23:e15739. [PMID: 34559060 PMCID: PMC8501405 DOI: 10.2196/15739] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2019] [Revised: 10/01/2020] [Accepted: 07/15/2021] [Indexed: 11/13/2022] Open
Abstract
Background Advancing the use of genomic data with routinely collected health data holds great promise for health care and research. Increasing the use of these data is a high priority to understand and address the causes of disease. Objective This study aims to provide an outline of the use of genomic data alongside routinely collected data in health research to date. As this field prepares to move forward, it is important to take stock of the current state of play in order to highlight new avenues for development, identify challenges, and ensure that adequate data governance models are in place for safe and socially acceptable progress. Methods We conducted a literature review to draw information from past studies that have used genomic and routinely collected data and conducted interviews with individuals who use these data for health research. We collected data on the following: the rationale of using genomic data in conjunction with routinely collected data, types of genomic and routinely collected data used, data sources, project approvals, governance and access models, and challenges encountered. Results The main purpose of using genomic and routinely collected data was to conduct genome-wide and phenome-wide association studies. Routine data sources included electronic health records, disease and death registries, health insurance systems, and deprivation indices. The types of genomic data included polygenic risk scores, single nucleotide polymorphisms, and measures of genetic activity, and biobanks generally provided these data. Although the literature search showed that biobanks released data to researchers, the case studies revealed a growing tendency for use within a data safe haven. Challenges of working with these data revolved around data collection, data storage, technical, and data privacy issues. Conclusions Using genomic and routinely collected data holds great promise for progressing health research. Several challenges are involved, particularly in terms of privacy. Overcoming these barriers will ensure that the use of these data to progress health research can be exploited to its full potential.
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Affiliation(s)
- Helen Daniels
- Population Data Science, Swansea University, Swansea, United Kingdom
| | | | - Sharon Heys
- Population Data Science, Swansea University, Swansea, United Kingdom
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Amador C, Zeng Y, Barber M, Walker RM, Campbell A, McIntosh AM, Evans KL, Porteous DJ, Hayward C, Wilson JF, Navarro P, Haley CS. Genome-wide methylation data improves dissection of the effect of smoking on body mass index. PLoS Genet 2021; 17:e1009750. [PMID: 34499657 PMCID: PMC8428545 DOI: 10.1371/journal.pgen.1009750] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2021] [Accepted: 07/28/2021] [Indexed: 11/18/2022] Open
Abstract
Variation in obesity-related traits has a genetic basis with heritabilities between 40 and 70%. While the global obesity pandemic is usually associated with environmental changes related to lifestyle and socioeconomic changes, most genetic studies do not include all relevant environmental covariates, so the genetic contribution to variation in obesity-related traits cannot be accurately assessed. Some studies have described interactions between a few individual genes linked to obesity and environmental variables but there is no agreement on their total contribution to differences between individuals. Here we compared self-reported smoking data and a methylation-based proxy to explore the effect of smoking and genome-by-smoking interactions on obesity related traits from a genome-wide perspective to estimate the amount of variance they explain. Our results indicate that exploiting omic measures can improve models for complex traits such as obesity and can be used as a substitute for, or jointly with, environmental records to better understand causes of disease.
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Affiliation(s)
- Carmen Amador
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Yanni Zeng
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, China
| | - Michael Barber
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Rosie M. Walker
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, Chancellor’s Building, 49 Little France Crescent, Edinburgh BioQuarter, Edinburgh, United Kingdom
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Andrew M. McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, United Kingdom
| | - Kathryn L. Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - David J. Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - James F. Wilson
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Global Health Research, Usher Institute, University of Edinburgh, Edinburgh, United Kingdom
| | - Pau Navarro
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Chris S. Haley
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
- Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Edinburgh, United Kingdom
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Barbu MC, Shen X, Walker RM, Howard DM, Evans KL, Whalley HC, Porteous DJ, Morris SW, Deary IJ, Zeng Y, Marioni RE, Clarke TK, McIntosh AM. Epigenetic prediction of major depressive disorder. Mol Psychiatry 2021; 26:5112-5123. [PMID: 32523041 PMCID: PMC8589651 DOI: 10.1038/s41380-020-0808-3] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2019] [Revised: 05/21/2020] [Accepted: 06/01/2020] [Indexed: 11/09/2022]
Abstract
Variation in DNA methylation (DNAm) is associated with lifestyle factors such as smoking and body mass index (BMI) but there has been little research exploring its ability to identify individuals with major depressive disorder (MDD). Using penalised regression on genome-wide CpG methylation, we tested whether DNAm risk scores (MRS), trained on 1223 MDD cases and 1824 controls, could discriminate between cases (n = 363) and controls (n = 1417) in an independent sample, comparing their predictive accuracy to polygenic risk scores (PRS). The MRS explained 1.75% of the variance in MDD (β = 0.338, p = 1.17 × 10-7) and remained associated after adjustment for lifestyle factors (β = 0.219, p = 0.001, R2 = 0.68%). When modelled alongside PRS (β = 0.384, p = 4.69 × 10-9) the MRS remained associated with MDD (β = 0.327, p = 5.66 × 10-7). The MRS was also associated with incident cases of MDD who were well at recruitment but went on to develop MDD at a later assessment (β = 0.193, p = 0.016, R2 = 0.52%). Heritability analyses found additive genetic effects explained 22% of variance in the MRS, with a further 19% explained by pedigree-associated genetic effects and 16% by the shared couple environment. Smoking status was also strongly associated with MRS (β = 0.440, p ≤ 2 × 10-16). After removing smokers from the training set, the MRS strongly associated with BMI (β = 0.053, p = 0.021). We tested the association of MRS with 61 behavioural phenotypes and found that whilst PRS were associated with psychosocial and mental health phenotypes, MRS were more strongly associated with lifestyle and sociodemographic factors. DNAm-based risk scores of MDD significantly discriminated MDD cases from controls in an independent dataset and may represent an archive of exposures to lifestyle factors that are relevant to the prediction of MDD.
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Affiliation(s)
- Miruna C Barbu
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Xueyi Shen
- Division of Psychiatry, Centre for Clinical Brain Sciences, 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
- Centre for Cognitive Ageing and Cognitive Epidemiology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - David M Howard
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Social Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - Heather C Whalley
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, School of Philosophy, Psychology and Language Sciences, 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
- Centre for Cognitive Ageing and Cognitive Epidemiology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - Yanni Zeng
- Faculty of Forensic Medicine, Zhongshan School of Medicine, Sun Yat-Sen University, 74 Zhongshan 2nd Road, Guangzhou, 510080, China
- Guangdong Province Translational Forensic Medicine Engineering Technology Research Center Zhongshan School of Medicine, Sun Yat-Sen University, 74 Zhongshan 2nd Road, Guangzhou, China
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK
| | - Toni-Kim Clarke
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.
- Centre for Cognitive Ageing and Cognitive Epidemiology, School of Philosophy, Psychology and Language Sciences, University of Edinburgh, Edinburgh, UK.
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40
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Demichev V, Tober-Lau P, Lemke O, Nazarenko T, Thibeault C, Whitwell H, Röhl A, Freiwald A, Szyrwiel L, Ludwig D, Correia-Melo C, Aulakh SK, Helbig ET, Stubbemann P, Lippert LJ, Grüning NM, Blyuss O, Vernardis S, White M, Messner CB, Joannidis M, Sonnweber T, Klein SJ, Pizzini A, Wohlfarter Y, Sahanic S, Hilbe R, Schaefer B, Wagner S, Mittermaier M, Machleidt F, Garcia C, Ruwwe-Glösenkamp C, Lingscheid T, Bosquillon de Jarcy L, Stegemann MS, Pfeiffer M, Jürgens L, Denker S, Zickler D, Enghard P, Zelezniak A, Campbell A, Hayward C, Porteous DJ, Marioni RE, Uhrig A, Müller-Redetzky H, Zoller H, Löffler-Ragg J, Keller MA, Tancevski I, Timms JF, Zaikin A, Hippenstiel S, Ramharter M, Witzenrath M, Suttorp N, Lilley K, Mülleder M, Sander LE, Ralser M, Kurth F. A time-resolved proteomic and prognostic map of COVID-19. Cell Syst 2021; 12:780-794.e7. [PMID: 34139154 PMCID: PMC8201874 DOI: 10.1016/j.cels.2021.05.005] [Citation(s) in RCA: 92] [Impact Index Per Article: 30.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2020] [Revised: 03/24/2021] [Accepted: 05/07/2021] [Indexed: 12/14/2022]
Abstract
COVID-19 is highly variable in its clinical presentation, ranging from asymptomatic infection to severe organ damage and death. We characterized the time-dependent progression of the disease in 139 COVID-19 inpatients by measuring 86 accredited diagnostic parameters, such as blood cell counts and enzyme activities, as well as untargeted plasma proteomes at 687 sampling points. We report an initial spike in a systemic inflammatory response, which is gradually alleviated and followed by a protein signature indicative of tissue repair, metabolic reconstitution, and immunomodulation. We identify prognostic marker signatures for devising risk-adapted treatment strategies and use machine learning to classify therapeutic needs. We show that the machine learning models based on the proteome are transferable to an independent cohort. Our study presents a map linking routinely used clinical diagnostic parameters to plasma proteomes and their dynamics in an infectious disease.
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Affiliation(s)
- Vadim Demichev
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany; The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, UK; The University of Cambridge, Department of Biochemistry and Cambridge Centre for Proteomics, Cambridge CB21GA, UK
| | - Pinkus Tober-Lau
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Oliver Lemke
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | - Tatiana Nazarenko
- University College London, Department of Mathematics, London WC1E 6BT, UK; University College London, Department of Women's Cancer, EGA Institute for Women'S Health, London WC1E 6BT, UK
| | - Charlotte Thibeault
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Harry Whitwell
- National Phenome Centre and Imperial Clinical Phenotyping Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW72AZ, UK; Lobachevsky University, Department of Applied Mathematics, Nizhny Novgorod 603105, Russia; Imperial College London, Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, London SW7 2AZ, UK
| | - Annika Röhl
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | - Anja Freiwald
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | - Lukasz Szyrwiel
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, UK
| | - Daniela Ludwig
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | - Clara Correia-Melo
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, UK
| | - Simran Kaur Aulakh
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, UK
| | - Elisa T Helbig
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Paula Stubbemann
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Lena J Lippert
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Nana-Maria Grüning
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany
| | - Oleg Blyuss
- Lobachevsky University, Department of Applied Mathematics, Nizhny Novgorod 603105, Russia; University of Hertfordshire, School of Physics, Astronomy and Mathematics, Hatfield AL10 9AB, UK; Sechenov First Moscow State Medical University, Department of Paediatrics and Paediatric Infectious Diseases, Moscow 119435, Russia
| | - Spyros Vernardis
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, UK
| | - Matthew White
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, UK
| | - Christoph B Messner
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany; The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, UK
| | - Michael Joannidis
- Medical University Innsbruck, Division of Intensive Care and Emergency Medicine, Department of Internal Medicine, 6020 Innsbruck, Austria
| | - Thomas Sonnweber
- Medical University of Innsbruck, Department of Internal Medicine II, 6020 Innsbruck, Austria
| | - Sebastian J Klein
- Medical University Innsbruck, Division of Intensive Care and Emergency Medicine, Department of Internal Medicine, 6020 Innsbruck, Austria
| | - Alex Pizzini
- Medical University of Innsbruck, Department of Internal Medicine II, 6020 Innsbruck, Austria
| | - Yvonne Wohlfarter
- Medical University of Innsbruck, Institute of Human Genetics, 6020 Innsbruck, Austria
| | - Sabina Sahanic
- Medical University of Innsbruck, Department of Internal Medicine II, 6020 Innsbruck, Austria
| | - Richard Hilbe
- Medical University of Innsbruck, Department of Internal Medicine II, 6020 Innsbruck, Austria
| | - Benedikt Schaefer
- Medical University of Innsbruck, Christian Doppler Laboratory for Iron and Phosphate Biology, Department of Internal Medicine I, 6020 Innsbruck, Austria
| | - Sonja Wagner
- Medical University of Innsbruck, Christian Doppler Laboratory for Iron and Phosphate Biology, Department of Internal Medicine I, 6020 Innsbruck, Austria
| | - Mirja Mittermaier
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany; Berlin Institute of Health, 10178 Berlin, Germany
| | - Felix Machleidt
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Carmen Garcia
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Christoph Ruwwe-Glösenkamp
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Tilman Lingscheid
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Laure Bosquillon de Jarcy
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Miriam S Stegemann
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Moritz Pfeiffer
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Linda Jürgens
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Sophy Denker
- Charité Universitätsmedizin Berlin, Medical Department of Hematology, Oncology & Tumor Immunology, Virchow Campus & Molekulares Krebsforschungszentrum, 13353 Berlin, Germany; Berlin Institute of Health, 10178 Berlin, Germany
| | - Daniel Zickler
- Charité Universitätsmedizin Berlin, Department of Nephrology and Internal Intensive Care Medicine, 10117 Berlin, Germany
| | - Philipp Enghard
- Charité Universitätsmedizin Berlin, Department of Nephrology and Internal Intensive Care Medicine, 10117 Berlin, Germany
| | - Aleksej Zelezniak
- The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, UK; Chalmers Tekniska Högskola, Department of Biology and Biological Engineering, SE-412 96 Gothenburg, Sweden
| | - Archie Campbell
- University of Edinburgh, Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, Edinburgh EH4 2XU, UK; University of Edinburgh, Usher Institute, Edinburgh EH16 4UX, UK
| | - Caroline Hayward
- University of Edinburgh, MRC Human Genetics Unit, Institute of Genetics and Cancer, Edinburgh EH4 2XU, UK
| | - David J Porteous
- University of Edinburgh, Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, Edinburgh EH4 2XU, UK; University of Edinburgh, Usher Institute, Edinburgh EH16 4UX, UK
| | - Riccardo E Marioni
- University of Edinburgh, Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, Edinburgh EH4 2XU, UK
| | - Alexander Uhrig
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Holger Müller-Redetzky
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany
| | - Heinz Zoller
- Medical University of Innsbruck, Christian Doppler Laboratory for Iron and Phosphate Biology, Department of Internal Medicine I, 6020 Innsbruck, Austria
| | - Judith Löffler-Ragg
- Medical University of Innsbruck, Department of Internal Medicine II, 6020 Innsbruck, Austria
| | - Markus A Keller
- Medical University of Innsbruck, Institute of Human Genetics, 6020 Innsbruck, Austria
| | - Ivan Tancevski
- Medical University of Innsbruck, Department of Internal Medicine II, 6020 Innsbruck, Austria
| | - John F Timms
- University College London, Department of Women's Cancer, EGA Institute for Women'S Health, London WC1E 6BT, UK
| | - Alexey Zaikin
- University College London, Department of Mathematics, London WC1E 6BT, UK; University College London, Department of Women's Cancer, EGA Institute for Women'S Health, London WC1E 6BT, UK; Lobachevsky University, Laboratory of Systems Medicine of Healthy Ageing, Nizhny Novgorod 603105, Russia
| | - Stefan Hippenstiel
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany; German Centre for Lung Research, 35392 Gießen, Germany
| | - Michael Ramharter
- Bernhard Nocht Institute for Tropical Medicine, Department of Tropical Medicine, and University Medical Center Hamburg-Eppendorf, Department of Medicine, 20359 Hamburg, Germany
| | - Martin Witzenrath
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany; German Centre for Lung Research, 35392 Gießen, Germany
| | - Norbert Suttorp
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany; German Centre for Lung Research, 35392 Gießen, Germany
| | - Kathryn Lilley
- The University of Cambridge, Department of Biochemistry and Cambridge Centre for Proteomics, Cambridge CB21GA, UK
| | - Michael Mülleder
- Charité - Universitätsmedizin Berlin, Core Facility - High-Throughput Mass Spectrometry, 10117 Berlin, Germany
| | - Leif Erik Sander
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany; German Centre for Lung Research, 35392 Gießen, Germany
| | - Markus Ralser
- Charité Universitätsmedizin Berlin, Department of Biochemistry, 10117 Berlin, Germany; The Francis Crick Institute, Molecular Biology of Metabolism Laboratory, London NW11AT, UK.
| | - Florian Kurth
- Charité Universitätsmedizin Berlin, Department of Infectious Diseases and Respiratory Medicine, 10117 Berlin, Germany; Bernhard Nocht Institute for Tropical Medicine, Department of Tropical Medicine, and University Medical Center Hamburg-Eppendorf, Department of Medicine, 20359 Hamburg, Germany
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Meng W, Chan BW, Harris C, Freidin MB, Hebert HL, Adams MJ, Campbell A, Hayward C, Zheng H, Zhang X, Colvin LA, Hales TG, Palmer CNA, Williams FMK, McIntosh A, Smith BH. A genome-wide association study finds genetic variants associated with neck or shoulder pain in UK Biobank. Hum Mol Genet 2021; 29:1396-1404. [PMID: 32246137 PMCID: PMC7254846 DOI: 10.1093/hmg/ddaa058] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Revised: 03/25/2020] [Accepted: 03/26/2020] [Indexed: 12/19/2022] Open
Abstract
Background Common types of musculoskeletal conditions include pain in the neck and shoulder areas. This study seeks to identify the genetic variants associated with neck or shoulder pain based on a genome-wide association approach using 203 309 subjects from the UK Biobank cohort and look for replication evidence from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and TwinsUK. Methods A genome-wide association study was performed adjusting for age, sex, BMI and nine population principal components. Significant and independent genetic variants were then sent to GS:SFHS and TwinsUK for replication. Results We identified three genetic loci that were associated with neck or shoulder pain in the UK Biobank samples. The most significant locus was in an intergenic region in chromosome 17, rs12453010, having P = 1.66 × 10−11. The second most significant locus was located in the FOXP2 gene in chromosome 7 with P = 2.38 × 10−10 for rs34291892. The third locus was located in the LINC01572 gene in chromosome 16 with P = 4.50 × 10−8 for rs62053992. In the replication stage, among four significant and independent genetic variants, rs2049604 in the FOXP2 gene and rs62053992 in the LINC01572 gene were weakly replicated in GS:SFHS (P = 0.0240 and P = 0.0202, respectively). Conclusions We have identified three loci associated with neck or shoulder pain in the UK Biobank cohort, two of which were weakly supported in a replication cohort. Further evidence is needed to confirm their roles in neck or shoulder pain.
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Affiliation(s)
- Weihua Meng
- Division of Population Health and Genomics, Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, DD2 4BF, UK
| | - Brian W Chan
- Division of Population Health and Genomics, Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, DD2 4BF, UK
| | - Cameron Harris
- Division of Population Health and Genomics, Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, DD2 4BF, UK
| | - Maxim B Freidin
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, SE1 7EH, UK
| | - Harry L Hebert
- Division of Population Health and Genomics, Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, DD2 4BF, UK
| | - Mark J Adams
- Division of Psychiatry, Edinburgh Medical School, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, EH4 2XU, UK
| | - Hua Zheng
- Department of Anaesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xianwei Zhang
- Department of Anaesthesiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Lesley A Colvin
- Division of Population Health and Genomics, Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, DD2 4BF, UK
| | - Tim G Hales
- Institute for Academic Anaesthesia, Division of Systems Medicine, School of Medicine, Ninewells Hospital, University of Dundee, Dundee, UK
| | - Colin N A Palmer
- Division of Population Health and Genomics, Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, DD2 4BF, UK
| | - Frances M K Williams
- Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences, King's College London, London, SE1 7EH, UK
| | - Andrew McIntosh
- Division of Psychiatry, Edinburgh Medical School, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Blair H Smith
- Division of Population Health and Genomics, Medical Research Institute, Ninewells Hospital and School of Medicine, University of Dundee, Dundee, DD2 4BF, UK
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42
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Clarke TK, Adams MJ, Howard DM, Xia C, Davies G, Hayward C, Campbell A, Padmanabhan S, Smith BH, Murray A, Porteous D, Deary IJ, McIntosh AM. Genetic and shared couple environmental contributions to smoking and alcohol use in the UK population. Mol Psychiatry 2021; 26:4344-4354. [PMID: 31767999 PMCID: PMC8550945 DOI: 10.1038/s41380-019-0607-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/20/2019] [Revised: 11/07/2019] [Accepted: 11/13/2019] [Indexed: 11/22/2022]
Abstract
Alcohol use and smoking are leading causes of death and disability worldwide. Both genetic and environmental factors have been shown to influence individual differences in the use of these substances. In the present study we tested whether genetic factors, modelled alongside common family environment, explained phenotypic variance in alcohol use and smoking behaviour in the Generation Scotland (GS) family sample of up to 19,377 individuals. SNP and pedigree-associated effects combined explained between 18 and 41% of the variance in substance use. Shared couple effects explained a significant amount of variance across all substance use traits, particularly alcohol intake, for which 38% of the phenotypic variance was explained. We tested whether the within-couple substance use associations were due to assortative mating by testing the association between partner polygenic risk scores in 34,987 couple pairs from the UK Biobank (UKB). No significant association between partner polygenic risk scores were observed. Associations between an individual's alcohol PRS (b = 0.05, S.E. = 0.006, p < 2 × 10-16) and smoking status PRS (b = 0.05, S.E. = 0.005, p < 2 × 10-16) were found with their partner's phenotype. In support of this, G carriers of a functional ADH1B polymorphism (rs1229984), known to be associated with greater alcohol intake, were found to consume less alcohol if they had a partner who carried an A allele at this SNP. Together these results show that the shared couple environment contributes significantly to patterns of substance use. It is unclear whether this is due to shared environmental factors, assortative mating, or indirect genetic effects. Future studies would benefit from longitudinal data and larger sample sizes to assess this further.
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Affiliation(s)
- Toni-Kim Clarke
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK.
| | - Mark J Adams
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - David M Howard
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
| | - Charley Xia
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Gail Davies
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Archie Campbell
- Usher Institute for Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Sandosh Padmanabhan
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, UK
| | - Blair H Smith
- Division of Population and Health Genomics, University of Dundee, Dundee, UK
| | - Alison Murray
- The Institute of Medical Sciences, Aberdeen Biomedical Imaging Centre, University of Aberdeen, Aberdeen, UK
| | - David Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
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43
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Fawns-Ritchie C, Altschul DM, Campbell A, Huggins C, Nangle C, Dawson R, Edwards R, Flaig R, Hartley L, Levein C, McCartney DL, Bell D, Douglas E, Deary IJ, Hayward C, Marioni RE, McIntosh AM, Sudlow C, Porteous DJ. CovidLife: a resource to understand mental health, well-being and behaviour during the COVID-19 pandemic in the UK. Wellcome Open Res 2021; 6:176. [PMID: 38406227 PMCID: PMC10884595 DOI: 10.12688/wellcomeopenres.16987.1] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/28/2021] [Indexed: 02/27/2024] Open
Abstract
CovidLife is a longitudinal observational study designed to investigate the impact of the COVID-19 pandemic on mental health, well-being and behaviour in adults living in the UK. In total, 18,518 participants (mean age = 56.43, SD = 14.35) completed the first CovidLife questionnaire (CovidLife1) between April and June 2020. To date, participants have completed two follow-up assessments. CovidLife2 took place between July and August 2020 (n = 11,319), and CovidLife3 took place in February 2021 (n = 10,386). A range of social and psychological measures were administered at each wave including assessments of anxiety, depression, well-being, loneliness and isolation. Information on sociodemographic, health, and economic circumstances was also collected. Questions also assessed information on COVID-19 infections and symptoms, compliance to COVID-19 restrictions, and opinions on the UK and Scottish Governments' handling of the pandemic. CovidLife includes a subsample of 4,847 participants from the Generation Scotland cohort (N~24,000, collected 2006-2011); a well-characterised cohort of families in Scotland with pre-pandemic data on mental health, physical health, lifestyle, and socioeconomic factors, along with biochemical and genomic data derived from biological samples. These participants also consented to their study data being linked to Scottish health records. CovidLife and Generation Scotland data can be accessed and used by external researchers following approval from the Generation Scotland Access Committee. CovidLife can be used to investigate mental health, well-being and behaviour during COVID-19; how these vary according to sociodemographic, health and economic circumstances; and how these change over time. The Generation Scotland subsample with pre-pandemic data and linkage to health records can be used to investigate the predictors of health and well-being during COVID-19 and the future health consequences of the COVID-19 pandemic.
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Affiliation(s)
- Chloe Fawns-Ritchie
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Drew M. Altschul
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - Charlotte Huggins
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Clifford Nangle
- Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - Rebecca Dawson
- Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - Rachel Edwards
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Robin Flaig
- Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - Louise Hartley
- Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - Christie Levein
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Daniel L. McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - David Bell
- Division of Economics, Stirling Management School, University of Stirling, Stirling, FK9 4LA, UK
| | - Elaine Douglas
- Faculty of Social Sciences, University of Stirling, Stirling, FK9 4LA, UK
| | - Ian J. Deary
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Andrew M. McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Cathie Sudlow
- Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - David J. Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
- Centre for Medical Informatics, Usher Institute, University of Edinburgh, Edinburgh, EH16 4UX, UK
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44
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Lohoff FW, Roy A, Jung J, Longley M, Rosoff DB, Luo A, O'Connell E, Sorcher JL, Sun H, Schwandt M, Hodgkinson CA, Goldman D, Momenan R, McIntosh AM, Adams MJ, Walker RM, Evans KL, Porteous D, Smith AK, Lee J, Muench C, Charlet K, Clarke TK, Kaminsky ZA. Epigenome-wide association study and multi-tissue replication of individuals with alcohol use disorder: evidence for abnormal glucocorticoid signaling pathway gene regulation. Mol Psychiatry 2021; 26:2224-2237. [PMID: 32398718 PMCID: PMC7658001 DOI: 10.1038/s41380-020-0734-4] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 03/13/2020] [Accepted: 04/14/2020] [Indexed: 12/12/2022]
Abstract
Alcohol use disorder (AUD) is a chronic debilitating disorder with limited treatment options and poorly defined pathophysiology. There are substantial genetic and epigenetic components; however, the underlying mechanisms contributing to AUD remain largely unknown. We conducted the largest DNA methylation epigenome-wide association study (EWAS) analyses currently available for AUD (total N = 625) and employed a top hit replication (N = 4798) using a cross-tissue/cross-phenotypic approach with the goal of identifying novel epigenetic targets relevant to AUD. Results show that a network of differentially methylated regions in glucocorticoid signaling and inflammation-related genes were associated with alcohol use behaviors. A top probe consistently associated across all cohorts was located in the long non-coding RNA growth arrest specific five gene (GAS5) (p < 10-24). GAS5 has been implicated in regulating transcriptional activity of the glucocorticoid receptor and has multiple functions related to apoptosis, immune function and various cancers. Endophenotypic analyses using peripheral cortisol levels and neuroimaging paradigms showed that methylomic variation in GAS5 network-related probes were associated with stress phenotypes. Postmortem brain analyses documented increased GAS5 expression in the amygdala of individuals with AUD. Our data suggest that alcohol use is associated with differential methylation in the glucocorticoid system that might influence stress and inflammatory reactivity and subsequently risk for AUD.
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Affiliation(s)
- Falk W Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA.
| | - Arunima Roy
- Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
| | - Jeesun Jung
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Martha Longley
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Daniel B Rosoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Audrey Luo
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Emma O'Connell
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Jill L Sorcher
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Hui Sun
- Office of the Clinical Director, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Melanie Schwandt
- Office of the Clinical Director, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Colin A Hodgkinson
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - David Goldman
- Laboratory of Neurogenetics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Reza Momenan
- Clinical Neuroimaging Research Core, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Andrew M McIntosh
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Mark J Adams
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Rosie M Walker
- Medical Genetic Section, Centre for Genomic and Experimental Medicine, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Medical Genetic Section, Centre for Genomic and Experimental Medicine, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - David Porteous
- Medical Genetic Section, Centre for Genomic and Experimental Medicine, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Alicia K Smith
- Department of Gynecology and Obstetrics, Emory University, Atlanta, Georgia, USA
- Department of Psychiatry & Behavioral Sciences, Emory University, Atlanta, GA, USA
| | - Jisoo Lee
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Christine Muench
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Katrin Charlet
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Toni-Kim Clarke
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Zachary A Kaminsky
- Royal's Institute of Mental Health Research, University of Ottawa, Ottawa, Canada
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45
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Carress H, Lawson DJ, Elhaik E. Population genetic considerations for using biobanks as international resources in the pandemic era and beyond. BMC Genomics 2021; 22:351. [PMID: 34001009 PMCID: PMC8127217 DOI: 10.1186/s12864-021-07618-x] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 04/14/2021] [Indexed: 12/11/2022] Open
Abstract
The past years have seen the rise of genomic biobanks and mega-scale meta-analysis of genomic data, which promises to reveal the genetic underpinnings of health and disease. However, the over-representation of Europeans in genomic studies not only limits the global understanding of disease risk but also inhibits viable research into the genomic differences between carriers and patients. Whilst the community has agreed that more diverse samples are required, it is not enough to blindly increase diversity; the diversity must be quantified, compared and annotated to lead to insight. Genetic annotations from separate biobanks need to be comparable and computable and to operate without access to raw data due to privacy concerns. Comparability is key both for regular research and to allow international comparison in response to pandemics. Here, we evaluate the appropriateness of the most common genomic tools used to depict population structure in a standardized and comparable manner. The end goal is to reduce the effects of confounding and learn from genuine variation in genetic effects on phenotypes across populations, which will improve the value of biobanks (locally and internationally), increase the accuracy of association analyses and inform developmental efforts.
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Affiliation(s)
- Hannah Carress
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK
| | - Daniel John Lawson
- School of Mathematics and Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Eran Elhaik
- Department of Animal and Plant Sciences, University of Sheffield, Sheffield, UK. .,Department of Biology, Lund University, Lund, Sweden.
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46
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Hébert HL, Veluchamy A, Baskozos G, Fardo F, Van Ryckeghem DML, Pascal MMV, Jones C, Milburn K, Pearson ER, Crombez G, Bennett DLH, Meng W, Palmer CNA, Smith BH. Cohort profile: DOLORisk Dundee: a longitudinal study of chronic neuropathic pain. BMJ Open 2021; 11:e042887. [PMID: 33952538 PMCID: PMC8103377 DOI: 10.1136/bmjopen-2020-042887] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Revised: 12/09/2020] [Accepted: 04/11/2021] [Indexed: 02/07/2023] Open
Abstract
PURPOSE Neuropathic pain is a common disorder of the somatosensory system that affects 7%-10% of the general population. The disorder places a large social and economic burden on patients as well as healthcare services. However, not everyone with a relevant underlying aetiology develops corresponding pain. DOLORisk Dundee, a European Union-funded cohort, part of the multicentre DOLORisk consortium, was set up to increase current understanding of this variation in onset. In particular, the cohort will allow exploration of psychosocial, clinical and genetic predictors of neuropathic pain onset. PARTICIPANTS DOLORisk Dundee has been constructed by rephenotyping two pre-existing Scottish population cohorts for neuropathic pain using a standardised 'core' study protocol: Genetics of Diabetes Audit and Research in Tayside Scotland (GoDARTS) (n=5236) consisting of predominantly type 2 diabetics from the Tayside region, and Generation Scotland: Scottish Family Health Study (GS:SFHS; n=20 221). Rephenotyping was conducted in two phases: a baseline postal survey and a combined postal and online follow-up survey. DOLORisk Dundee consists of 9155 participants (GoDARTS=1915; GS:SFHS=7240) who responded to the baseline survey, of which 6338 (69.2%; GoDARTS=1046; GS:SFHS=5292) also responded to the follow-up survey (18 months later). FINDINGS TO DATE At baseline, the proportion of those with chronic neuropathic pain (Douleur Neuropathique en 4 Questions questionnaire score ≥3, duration ≥3 months) was 30.5% in GoDARTS and 14.2% in Generation Scotland. Electronic record linkage enables large scale genetic association studies to be conducted and risk models have been constructed for neuropathic pain. FUTURE PLANS The cohort is being maintained by an access committee, through which collaborations are encouraged. Details of how to do this will be available on the study website (http://dolorisk.eu/). Further follow-up surveys of the cohort are planned and funding applications are being prepared to this effect. This will be conducted in harmony with similar pain rephenotyping of UK Biobank.
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Affiliation(s)
- Harry L Hébert
- Chronic Pain Research Group, Division of Population Health and Genomics, Mackenzie Building, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Abirami Veluchamy
- Chronic Pain Research Group, Division of Population Health and Genomics, Mackenzie Building, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Georgios Baskozos
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Francesca Fardo
- Danish Pain Research Center, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark
| | - Dimitri M L Van Ryckeghem
- Department of Experimental-Clinical and Health Psychology, Faculty of Psychology and Educational Sciences, Ghent University, Gent, Belgium
- Section Experimental Health Psychology, Clinical Psychological Science, Departments, Faculty of Psychology and Neuroscience, Maastricht University, Maastricht, Netherlands
- Institute of Health and Behaviour, INSIDE, University of Luxembourg, Luxembourg, Luxembourg
| | - Mathilde M V Pascal
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Claire Jones
- Health Informatics Centre, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Keith Milburn
- Health Informatics Centre, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Ewan R Pearson
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Geert Crombez
- Department of Experimental-Clinical and Health Psychology, Faculty of Psychology and Educational Sciences, Ghent University, Gent, Belgium
| | - David L H Bennett
- Neural Injury Group, Nuffield Department of Clinical Neuroscience, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Weihua Meng
- Chronic Pain Research Group, Division of Population Health and Genomics, Mackenzie Building, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Colin N A Palmer
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, Division of Population Health and Genomics, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
| | - Blair H Smith
- Chronic Pain Research Group, Division of Population Health and Genomics, Mackenzie Building, Ninewells Hospital and Medical School, University of Dundee, Dundee, UK
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47
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Gadd DA, Stevenson AJ, Hillary RF, McCartney DL, Wrobel N, McCafferty S, Murphy L, Russ TC, Harris SE, Redmond P, Taylor AM, Smith C, Rose J, Millar T, Spires-Jones TL, Cox SR, Marioni RE. Epigenetic predictors of lifestyle traits applied to the blood and brain. Brain Commun 2021; 3:fcab082. [PMID: 34041477 PMCID: PMC8134833 DOI: 10.1093/braincomms/fcab082] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Revised: 02/02/2021] [Accepted: 03/04/2021] [Indexed: 11/14/2022] Open
Abstract
Modifiable lifestyle factors influence the risk of developing many neurological diseases. These factors have been extensively linked with blood-based genome-wide DNA methylation, but it is unclear if the signatures from blood translate to the target tissue of interest-the brain. To investigate this, we apply blood-derived epigenetic predictors of four lifestyle traits to genome-wide DNA methylation from five post-mortem brain regions and the last blood sample prior to death in 14 individuals in the Lothian Birth Cohort 1936. Using these matched samples, we found that correlations between blood and brain DNA methylation scores for smoking, high-density lipoprotein cholesterol, alcohol and body mass index were highly variable across brain regions. Smoking scores in the dorsolateral prefrontal cortex had the strongest correlations with smoking scores in blood (r = 0.5, n = 14, P = 0.07) and smoking behaviour (r = 0.56, n = 9, P = 0.12). This was also the brain region which exhibited the largest correlations for DNA methylation at site cg05575921 - the single strongest correlate of smoking in blood-in relation to blood (r = 0.61, n = 14, P = 0.02) and smoking behaviour (r = -0.65, n = 9, P = 0.06). This suggested a particular vulnerability to smoking-related differential methylation in this region. Our work contributes to understanding how lifestyle factors affect the brain and suggest that lifestyle-related DNA methylation is likely to be both brain region dependent and in many cases poorly proxied for by blood. Though these pilot data provide a rarely-available opportunity for the comparison of methylation patterns across multiple brain regions and the blood, due to the limited sample size available our results must be considered as preliminary and should therefore be used as a basis for further investigation.
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Affiliation(s)
- Danni A Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh 2XU, UK
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh 2XU, UK
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh 2XU, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh 2XU, UK
| | - Nicola Wrobel
- Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Sarah McCafferty
- Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Lee Murphy
- Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, Edinburgh EH4 2XU, UK
| | - Tom C Russ
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh EH8 9JZ, UK
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Sarah E Harris
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Paul Redmond
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Adele M Taylor
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Colin Smith
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Jamie Rose
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Tracey Millar
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Tara L Spires-Jones
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Simon R Cox
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh EH8 9JZ, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh 2XU, UK
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48
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Adams MJ, Hill WD, Howard DM, Dashti HS, Davis KAS, Campbell A, Clarke TK, Deary IJ, Hayward C, Porteous D, Hotopf M, McIntosh AM. Factors associated with sharing e-mail information and mental health survey participation in large population cohorts. Int J Epidemiol 2021; 49:410-421. [PMID: 31263887 PMCID: PMC7266553 DOI: 10.1093/ije/dyz134] [Citation(s) in RCA: 49] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 06/17/2019] [Indexed: 11/12/2022] Open
Abstract
BACKGROUND People who opt to participate in scientific studies tend to be healthier, wealthier and more educated than the broader population. Although selection bias does not always pose a problem for analysing the relationships between exposures and diseases or other outcomes, it can lead to biased effect size estimates. Biased estimates may weaken the utility of genetic findings because the goal is often to make inferences in a new sample (such as in polygenic risk score analysis). METHODS We used data from UK Biobank, Generation Scotland and Partners Biobank and conducted phenotypic and genome-wide association analyses on two phenotypes that reflected mental health data availability: (i) whether participants were contactable by e-mail for follow-up; and (ii) whether participants responded to follow-up surveys of mental health. RESULTS In UK Biobank, we identified nine genetic loci associated (P <5 × 10-8) with e-mail contact and 25 loci associated with mental health survey completion. Both phenotypes were positively genetically correlated with higher educational attainment and better health and negatively genetically correlated with psychological distress and schizophrenia. One single nucleotide polymorphism association replicated along with the overall direction of effect of all association results. CONCLUSIONS Re-contact availability and follow-up participation can act as further genetic filters for data on mental health phenotypes.
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Affiliation(s)
- Mark J Adams
- Division of Psychiatry, Royal Edinburgh Hospital, Edinburgh, UK
| | - W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK.,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - David M Howard
- Division of Psychiatry, Royal Edinburgh Hospital, Edinburgh, UK.,Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Hassan S Dashti
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Katrina A S Davis
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,South London and Maudsley NHS Foundation Trust, London, UK.,NIHR Biomedical Research Centre, London, UK
| | - Archie Campbell
- Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, Edinburgh, UK.,Usher Institute for Population Health Sciences and Informatics, Edinburgh, UK
| | - Toni-Kim Clarke
- Division of Psychiatry, Royal Edinburgh Hospital, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK.,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - David Porteous
- Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK.,Centre for Genomic and Experimental Medicine, Institute of Genetics & Molecular Medicine, Edinburgh, UK
| | - Matthew Hotopf
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.,South London and Maudsley NHS Foundation Trust, London, UK.,NIHR Biomedical Research Centre, London, UK
| | - Andrew M McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, Edinburgh, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, Edinburgh, UK
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49
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Pairo-Castineira E, Clohisey S, Klaric L, Bretherick AD, Rawlik K, Pasko D, Walker S, Parkinson N, Fourman MH, Russell CD, Furniss J, Richmond A, Gountouna E, Wrobel N, Harrison D, Wang B, Wu Y, Meynert A, Griffiths F, Oosthuyzen W, Kousathanas A, Moutsianas L, Yang Z, Zhai R, Zheng C, Grimes G, Beale R, Millar J, Shih B, Keating S, Zechner M, Haley C, Porteous DJ, Hayward C, Yang J, Knight J, Summers C, Shankar-Hari M, Klenerman P, Turtle L, Ho A, Moore SC, Hinds C, Horby P, Nichol A, Maslove D, Ling L, McAuley D, Montgomery H, Walsh T, Pereira AC, Renieri A, Shen X, Ponting CP, Fawkes A, Tenesa A, Caulfield M, Scott R, Rowan K, Murphy L, Openshaw PJM, Semple MG, Law A, Vitart V, Wilson JF, Baillie JK. Genetic mechanisms of critical illness in COVID-19. Nature 2021; 591:92-98. [PMID: 33307546 DOI: 10.1038/s41586-020-03065-y] [Citation(s) in RCA: 810] [Impact Index Per Article: 270.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2020] [Accepted: 11/30/2020] [Indexed: 02/06/2023]
Abstract
Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 × 10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice.
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Affiliation(s)
- Erola Pairo-Castineira
- Roslin Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Sara Clohisey
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Lucija Klaric
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Andrew D Bretherick
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Konrad Rawlik
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | | | | | - Nick Parkinson
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | | | - Clark D Russell
- Roslin Institute, University of Edinburgh, Edinburgh, UK
- Centre for Inflammation Research, The Queen's Medical Research Institute, University of Edinburgh, Edinburgh, UK
| | - James Furniss
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Anne Richmond
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Elvina Gountouna
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Nicola Wrobel
- Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - David Harrison
- Intensive Care National Audit & Research Centre, London, UK
| | - Bo Wang
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Yang Wu
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
| | - Alison Meynert
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | | | | | | | | | - Zhijian Yang
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Ranran Zhai
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Chenqing Zheng
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
| | - Graeme Grimes
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | | | | | - Barbara Shih
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Sean Keating
- Intensive Care Unit, Royal Infirmary of Edinburgh, Edinburgh, UK
| | - Marie Zechner
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Chris Haley
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - David J Porteous
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Jian Yang
- School of Life Sciences, Westlake University, Hangzhou, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Julian Knight
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | | | - Manu Shankar-Hari
- Department of Intensive Care Medicine, Guy's and St Thomas' NHS Foundation Trust, London, UK
- School of Immunology and Microbial Sciences, King's College London, London, UK
| | - Paul Klenerman
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Lance Turtle
- NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
| | - Antonia Ho
- MRC-University of Glasgow Centre for Virus Research, Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, UK
| | - Shona C Moore
- NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
| | - Charles Hinds
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Peter Horby
- Centre for Tropical Medicine and Global Health, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Alistair Nichol
- Clinical Research Centre at St Vincent's University Hospital, University College Dublin, Dublin, Ireland
- Australian and New Zealand Intensive Care Research Centre, Monash University, Melbourne, Victoria, Australia
- Intensive Care Unit, Alfred Hospital, Melbourne, Victoria, Australia
| | - David Maslove
- Department of Critical Care Medicine, Queen's University and Kingston Health Sciences Centre, Kingston, Ontario, Canada
| | - Lowell Ling
- Department of Anaesthesia and Intensive Care, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Danny McAuley
- Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, UK
- Department of Intensive Care Medicine, Royal Victoria Hospital, Belfast, UK
| | - Hugh Montgomery
- UCL Centre for Human Health and Performance, University College London, London, UK
| | - Timothy Walsh
- Intensive Care Unit, Royal Infirmary of Edinburgh, Edinburgh, UK
| | - Alexandre C Pereira
- Faculty of Medicine, University of São Paulo, São Paulo, Brazil
- Heart Institute, University of São Paulo, São Paulo, Brazil
| | - Alessandra Renieri
- Medical Genetics, University of Siena, Siena, Italy
- Genetica Medica, Azienda Ospedaliero-Universitaria Senese, Siena, Italy
| | - Xia Shen
- Biostatistics Group, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Chris P Ponting
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - Angie Fawkes
- Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - Albert Tenesa
- Roslin Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK
| | - Mark Caulfield
- Genomics England, London, UK
- William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Richard Scott
- Genomics England, London, UK
- Great Ormond Street Hospital for Children NHS Foundation Trust, London, UK
| | - Kathy Rowan
- Intensive Care National Audit & Research Centre, London, UK
| | - Lee Murphy
- Edinburgh Clinical Research Facility, Western General Hospital, University of Edinburgh, Edinburgh, UK
| | - Peter J M Openshaw
- National Heart and Lung Institute, Imperial College London, London, UK
- Imperial College Healthcare NHS Trust London, London, UK
| | - Malcolm G Semple
- NIHR Health Protection Research Unit for Emerging and Zoonotic Infections, Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool, UK
- Respiratory Medicine, Alder Hey Children's Hospital, Institute in The Park, University of Liverpool, Liverpool, UK
| | - Andrew Law
- Roslin Institute, University of Edinburgh, Edinburgh, UK
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
| | - James F Wilson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK
| | - J Kenneth Baillie
- Roslin Institute, University of Edinburgh, Edinburgh, UK.
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh, UK.
- Intensive Care Unit, Royal Infirmary of Edinburgh, Edinburgh, UK.
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Dance C, Jaquiery M, Eagleman D, Porteous D, Zeman A, Simner J. What is the relationship between Aphantasia, Synaesthesia and Autism? Conscious Cogn 2021; 89:103087. [DOI: 10.1016/j.concog.2021.103087] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 01/01/2021] [Accepted: 01/17/2021] [Indexed: 12/31/2022]
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