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Smith HM, Ng HK, Moodie JE, Gadd DA, McCartney DL, Bernabeu E, Campbell A, Redmond P, Taylor A, Page D, Corley J, Harris SE, Tay D, Deary IJ, Evans KL, Robinson MR, Chambers JC, Loh M, Cox SR, Marioni RE, Hillary RF. Methylome-wide studies of six metabolic traits. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.29.24308103. [PMID: 38853823 PMCID: PMC11160850 DOI: 10.1101/2024.05.29.24308103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Exploring the molecular correlates of metabolic health measures may identify the shared and unique biological processes and pathways that they track. Here, we performed epigenome-wide association studies (EWASs) of six metabolic traits: body mass index (BMI), body fat percentage, waist-hip ratio (WHR), and blood-based measures of glucose, high-density lipoprotein (HDL) cholesterol, and total cholesterol. We considered blood-based DNA methylation (DNAm) from >750,000 CpG sites in over 17,000 volunteers from the Generation Scotland (GS) cohort. Linear regression analyses identified between 304 and 11,815 significant CpGs per trait at P<3.6×10-8, with 37 significant CpG sites across all six traits. Further, we performed a Bayesian EWAS that jointly models all CpGs simultaneously and conditionally on each other, as opposed to the marginal linear regression analyses. This identified between 3 and 27 CpGs with a posterior inclusion probability ≥ 0.95 across the six traits. Next, we used elastic net penalised regression to train epigenetic scores (EpiScores) of each trait in GS, which were then tested in the Lothian Birth Cohort 1936 (LBC1936; European ancestry) and Health for Life in Singapore (HELIOS; Indian-, Malay- and Chinese-ancestries). A maximum of 27.1% of the variance in BMI was explained by the BMI EpiScore in the subset of Malay-ancestry Singaporeans. Four metabolic EpiScores were associated with general cognitive function in LBC1936 in models adjusted for vascular risk factors (Standardised βrange: 0.08 - 0.12, PFDR < 0.05). EpiScores of metabolic health are applicable across ancestries and can reflect differences in brain health.
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Affiliation(s)
- Hannah M. Smith
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Hong Kiat Ng
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Joanna E. Moodie
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Danni A. Gadd
- 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
| | - Elena Bernabeu
- 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
| | - Paul Redmond
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Adele Taylor
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Danielle Page
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Janie Corley
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Sarah E. Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Darwin Tay
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
| | - Ian J. Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Kathryn L. Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Matthew R. Robinson
- Institute of Science and Technology Austria, Am Campus 1, 3400 Klosterneuburg, Austria
| | - John C. Chambers
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), Singapore
| | - Simon R. Cox
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Riccardo E. Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Robert F. Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
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Xing F, Han F, Wu Y, Lv B, Tian H, Wang W, Tian X, Xu C, Duan H, Zhang D, Wu Y. An epigenome-wide association study of waist circumference in Chinese monozygotic twins. Int J Obes (Lond) 2024:10.1038/s41366-024-01538-y. [PMID: 38773251 DOI: 10.1038/s41366-024-01538-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 05/05/2024] [Accepted: 05/09/2024] [Indexed: 05/23/2024]
Abstract
OBJECTIVES Central obesity poses significant health risks because it increases susceptibility to multiple chronic diseases. Epigenetic features such as DNA methylation may be associated with specific obesity traits, which could help us understand how genetic and environmental factors interact to influence the development of obesity. This study aims to identify DNA methylation sites associated with the waist circumference (WC) in Northern Han Chinese population, and to elucidate potential causal relationships. METHODS A total of 59 pairs of WC discordant monozygotic twins (ΔWC >0) were selected from the Qingdao Twin Registry in China. Generalized estimated equation model was employed to estimate the methylation levels of CpG sites on WC. Causal relationships between methylation and WC were assessed through the examination of family confounding factors using FAmiliaL CONfounding (ICE FALCON). Additionally, the findings of the epigenome-wide analysis were corroborated in the validation stage. RESULTS We identified 26 CpG sites with differential methylation reached false discovery rate (FDR) < 0.05 and 22 differentially methylated regions (slk-corrected p < 0.05) strongly linked to WC. These findings provided annotations for 26 genes, with notable emphasis on MMP17, ITGA11, COL23A1, TFPI, A2ML1-AS1, MRGPRE, C2orf82, and NINJ2. ICE FALCON analysis indicated the DNA methylation of ITGA11 and TFPI had a causal effect on WC and vice versa (p < 0.05). Subsequent validation analysis successfully replicated 10 (p < 0.05) out of the 26 identified sites. CONCLUSIONS Our research has ascertained an association between specific epigenetic variations and WC in the Northern Han Chinese population. These DNA methylation features can offer fresh insights into the epigenetic regulation of obesity and WC as well as hints to plausible biological mechanisms.
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Affiliation(s)
- Fangjie Xing
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Fulei Han
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Yan Wu
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Bosen Lv
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Huimin Tian
- Zhonglou District Center for Disease Control and Prevention, Changzhou, Jiangsu, China
| | - Weijing Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Xiaocao Tian
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - Chunsheng Xu
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - Haiping Duan
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong, China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China
| | - Yili Wu
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, Qingdao, China.
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Domínguez-Barragán J, Fernández-Sanlés A, Hernáez Á, Llauradó-Pont J, Marrugat J, Robinson O, Tzoulaki I, Elosua R, Lassale C. Blood DNA methylation signature of diet quality and association with cardiometabolic traits. Eur J Prev Cardiol 2024; 31:191-202. [PMID: 37793095 PMCID: PMC10809172 DOI: 10.1093/eurjpc/zwad317] [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: 05/30/2023] [Revised: 09/22/2023] [Accepted: 09/24/2023] [Indexed: 10/06/2023]
Abstract
AIMS Diet quality might influence cardiometabolic health through epigenetic changes, but this has been little investigated in adults. Our aims were to identify cytosine-phosphate-guanine (CpG) dinucleotides associated with diet quality by conducting an epigenome-wide association study (EWAS) based on blood DNA methylation (DNAm) and to assess how diet-related CpGs associate with inherited susceptibility to cardiometabolic traits: body mass index (BMI), systolic blood pressure (SBP), triglycerides, type 2 diabetes (T2D), and coronary heart disease (CHD). METHODS AND RESULTS Meta-EWAS including 5274 participants in four cohorts from Spain, the USA, and the UK. We derived three dietary scores (exposures) to measure adherence to a Mediterranean diet, to a healthy plant-based diet, and to the Dietary Approaches to Stop Hypertension. Blood DNAm (outcome) was assessed with the Infinium arrays Human Methylation 450K BeadChip and MethylationEPIC BeadChip. For each diet score, we performed linear EWAS adjusted for age, sex, blood cells, smoking and technical variables, and BMI in a second set of models. We also conducted Mendelian randomization analyses to assess the potential causal relationship between diet-related CpGs and cardiometabolic traits. We found 18 differentially methylated CpGs associated with dietary scores (P < 1.08 × 10-7; Bonferroni correction), of which 12 were previously associated with cardiometabolic traits. Enrichment analysis revealed overrepresentation of diet-associated genes in pathways involved in inflammation and cardiovascular disease. Mendelian randomization analyses suggested that genetically determined methylation levels corresponding to lower diet quality at cg02079413 (SNORA54), cg02107842 (MAST4), and cg23761815 (SLC29A3) were causally associated with higher BMI and at cg05399785 (WDR8) with greater SBP, and methylation levels associated with higher diet quality at cg00711496 (PRMT1) with lower BMI, T2D risk, and CHD risk and at cg0557921 (AHRR) with lower CHD risk. CONCLUSION Diet quality in adults was related to differential methylation in blood at 18 CpGs, some of which related to cardiometabolic health.
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Affiliation(s)
- Jorge Domínguez-Barragán
- Hospital del Mar Research Institute (IMIM), Programme of Epidemiology and Public Health, Dr Aiguader, 88, 08003 Barcelona, Spain
| | - Alba Fernández-Sanlés
- MRC Unit for Lifelong Health and Ageing, University College London, London WC1E 7HB, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol BS8 2BN, UK
| | - Álvaro Hernáez
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo 0463, Norway
- Blanquerna School of Health Sciences, Universitat Ramon Llull, 08025 Barcelona, Spain
- Consortium for Biomedical Research—Pathophysiology of Obesity and Nutrition (CIBEROBN), Instituto de Salud Carlos III, Monforte de Lemos 3-5, 08029 Madrid, Spain
| | - Joana Llauradó-Pont
- Barcelona Institute of Global Health (ISGlobal), Dr Aiguader 88, 08003, Barcelona, Spain
| | - Jaume Marrugat
- Hospital del Mar Research Institute (IMIM), Programme of Epidemiology and Public Health, Dr Aiguader, 88, 08003 Barcelona, Spain
- Consortium for Biomedical Research—Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain
| | - Oliver Robinson
- μedical Research Council Centre for Environment and Health, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Ioanna Tzoulaki
- Centre for Systems Biology, Biomedical Research Foundation of the Academy of Athens, 115 27 Athens, Greece
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, UK
| | - Roberto Elosua
- Hospital del Mar Research Institute (IMIM), Programme of Epidemiology and Public Health, Dr Aiguader, 88, 08003 Barcelona, Spain
- Consortium for Biomedical Research—Cardiovascular Diseases (CIBERCV), Instituto de Salud Carlos III, Madrid, Spain
- Faculty of Medicine, University of Vic—Central University of Catalunya, Ctra. de Roda, 70, 08500 Vic, Spain
| | - Camille Lassale
- Hospital del Mar Research Institute (IMIM), Programme of Epidemiology and Public Health, Dr Aiguader, 88, 08003 Barcelona, Spain
- Consortium for Biomedical Research—Pathophysiology of Obesity and Nutrition (CIBEROBN), Instituto de Salud Carlos III, Monforte de Lemos 3-5, 08029 Madrid, Spain
- Barcelona Institute of Global Health (ISGlobal), Dr Aiguader 88, 08003, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Dr Aiguader 88, 08003, Barcelona, Spain
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García-Álvarez NC, Riezu-Boj JI, Martínez JA, García-Calzón S, Milagro FI. A Predictive Tool Based on DNA Methylation Data for Personalized Weight Loss through Different Dietary Strategies: A Pilot Study. Nutrients 2023; 15:5023. [PMID: 38140282 PMCID: PMC10746100 DOI: 10.3390/nu15245023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Revised: 11/28/2023] [Accepted: 12/02/2023] [Indexed: 12/24/2023] Open
Abstract
BACKGROUND AND AIMS Obesity is a public health problem. The usual treatment is a reduction in calorie intake and an increase in energy expenditure, but not all individuals respond equally to these treatments. Epigenetics could be a factor that contributes to this heterogeneity. The aim of this research was to determine the association between DNA methylation at baseline and the percentage of BMI loss (%BMIL) after two dietary interventions, in order to design a prediction model to evaluate %BMIL based on methylation data. METHODS AND RESULTS Spanish participants with overweight or obesity (n = 306) were randomly assigned to two lifestyle interventions with hypocaloric diets: one moderately high in protein (MHP) and the other low in fat (LF) for 4 months (Obekit study; ClinicalTrials.gov ID: NCT02737267). Basal DNA methylation was analyzed in white blood cells using the Infinium MethylationEPIC array. After identifying those methylation sites associated with %BMIL (p < 0.05 and SD > 0.1), two weighted methylation sub-scores were constructed for each diet: 15 CpGs were used for the MHP diet and 11 CpGs for the LF diet. Afterwards, a total methylation score was made by subtracting the previous sub-scores. These data were used to design a prediction model for %BMIL through a linear mixed effect model with the interaction between diet and total score. CONCLUSION Overall, DNA methylation predicts the %BMIL of two 4-month hypocaloric diets and was able to determine which type of diet is the most appropriate for each individual. The results of this pioneer study confirm that epigenetic biomarkers may be further used for precision nutrition and the design of personalized dietary strategies against obesity.
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Affiliation(s)
- Nereyda Carolina García-Álvarez
- Center for Nutrition Research, Department of Nutrition, Food Science and Physiology, Faculty of Pharmacy and Nutrition, University of Navarra, 31008 Pamplona, Spain; (N.C.G.-Á.); (J.I.R.-B.); (J.A.M.); (S.G.-C.)
| | - José Ignacio Riezu-Boj
- Center for Nutrition Research, Department of Nutrition, Food Science and Physiology, Faculty of Pharmacy and Nutrition, University of Navarra, 31008 Pamplona, Spain; (N.C.G.-Á.); (J.I.R.-B.); (J.A.M.); (S.G.-C.)
- Navarra Institute for Health Research (IdiSNA), 31008 Pamplona, Spain
| | - J. Alfredo Martínez
- Center for Nutrition Research, Department of Nutrition, Food Science and Physiology, Faculty of Pharmacy and Nutrition, University of Navarra, 31008 Pamplona, Spain; (N.C.G.-Á.); (J.I.R.-B.); (J.A.M.); (S.G.-C.)
| | - Sonia García-Calzón
- Center for Nutrition Research, Department of Nutrition, Food Science and Physiology, Faculty of Pharmacy and Nutrition, University of Navarra, 31008 Pamplona, Spain; (N.C.G.-Á.); (J.I.R.-B.); (J.A.M.); (S.G.-C.)
- Navarra Institute for Health Research (IdiSNA), 31008 Pamplona, Spain
| | - Fermín I. Milagro
- Center for Nutrition Research, Department of Nutrition, Food Science and Physiology, Faculty of Pharmacy and Nutrition, University of Navarra, 31008 Pamplona, Spain; (N.C.G.-Á.); (J.I.R.-B.); (J.A.M.); (S.G.-C.)
- Navarra Institute for Health Research (IdiSNA), 31008 Pamplona, Spain
- Centro de Investigación Biomédica en Red de la Fisiopatología de la Obesidad y la Nutrición (CIBERobn), Carlos III Health Institute, 28029 Madrid, Spain
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Li X, Shao X, Kou M, Wang X, Ma H, Grundberg E, Bazzano LA, Smith SR, Bray GA, Sacks FM, Qi L. DNA Methylation at ABCG1 and Long-term Changes in Adiposity and Fat Distribution in Response to Dietary Interventions: The POUNDS Lost Trial. Diabetes Care 2023; 46:2201-2207. [PMID: 37770056 DOI: 10.2337/dc23-0748] [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: 04/26/2023] [Accepted: 09/07/2023] [Indexed: 10/03/2023]
Abstract
OBJECTIVE To examine whether participants with different levels of diabetes-related DNA methylation at ABCG1 might respond differently to dietary weight loss interventions with long-term changes in adiposity and body fat distribution. RESEARCH DESIGN AND METHODS The current study included overweight/obese participants from the POUNDS Lost trial. Blood levels of regional DNA methylation at ABCG1 were profiled by high-resolution methylC-capture sequencing at baseline among 673 participants, of whom 598 were followed up at 6 months and 543 at 2 years. Two-year changes in adiposity and computed tomography-measured body fat distribution were calculated. RESULTS Regional DNA methylation at ABCG1 showed significantly different associations with long-term changes in body weight and waist circumference at 6 months and 2 years in dietary interventions varying in protein intake (interaction P < 0.05 for all). Among participants assigned to an average-protein (15%) diet, lower baseline regional DNA methylation at ABCG1 was associated with greater reductions in body weight and waist circumference at 6 months and 2 years, whereas opposite associations were found among those assigned to a high-protein (25%) diet. Similar interaction patterns were also observed for body fat distribution, including visceral adipose tissue, subcutaneous adipose tissue, deep subcutaneous adipose tissue, and total adipose tissue at 6 months and 2 years (interaction P < 0.05 for all). CONCLUSIONS Baseline DNA methylation at ABCG1 interacted with dietary protein intake on long-term decreases in adiposity and body fat distribution. Participants with lower methylation at ABCG1 benefitted more in long-term reductions in body weight, waist circumference, and body fat distribution when consuming an average-protein diet.
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Affiliation(s)
- Xiang Li
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
| | - Xiaojian Shao
- Digital Technologies Research Centre, National Research Council Canada, Ottawa, Ontario, Canada
| | - Minghao Kou
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
| | - Xuan Wang
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
| | - Hao Ma
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
| | - Elin Grundberg
- Department of Pediatrics, Genomic Medicine Center, Children's Mercy Kansas City, Kansas City, MO
| | - Lydia A Bazzano
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
| | | | - George A Bray
- Pennington Biomedical Research Center, Louisiana State University, Baton Rouge, LA
| | - Frank M Sacks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
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Harris HA, Friedman C, Starling AP, Dabelea D, Johnson SL, Fuemmeler BF, Jima D, Murphy SK, Hoyo C, Jansen PW, Felix JF, Mulder RH. An epigenome-wide association study of child appetitive traits and DNA methylation. Appetite 2023; 191:107086. [PMID: 37844693 PMCID: PMC11156223 DOI: 10.1016/j.appet.2023.107086] [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: 06/19/2023] [Revised: 10/09/2023] [Accepted: 10/10/2023] [Indexed: 10/18/2023]
Abstract
The etiology of childhood appetitive traits is poorly understood. Early-life epigenetic processes may be involved in the developmental programming of appetite regulation in childhood. One such process is DNA methylation (DNAm), whereby a methyl group is added to a specific part of DNA, where a cytosine base is next to a guanine base, a CpG site. We meta-analyzed epigenome-wide association studies (EWASs) of cord blood DNAm and early-childhood appetitive traits. Data were from two independent cohorts: the Generation R Study (n = 1,086, Rotterdam, the Netherlands) and the Healthy Start study (n = 236, Colorado, USA). DNAm at autosomal methylation sites in cord blood was measured using the Illumina Infinium HumanMethylation450 BeadChip. Parents reported on their child's food responsiveness, emotional undereating, satiety responsiveness and food fussiness using the Children's Eating Behaviour Questionnaire at age 4-5 years. Multiple regression models were used to examine the association of DNAm (predictor) at the individual site- and regional-level (using DMRff) with each appetitive trait (outcome), adjusting for covariates. Bonferroni-correction was applied to adjust for multiple testing. There were no associations of DNAm and any appetitive trait when examining individual CpG-sites. However, when examining multiple CpGs jointly in so-called differentially methylated regions, we identified 45 associations of DNAm with food responsiveness, 7 associations of DNAm with emotional undereating, 13 associations of DNAm with satiety responsiveness, and 9 associations of DNAm with food fussiness. This study shows that DNAm in the newborn may partially explain variation in appetitive traits expressed in early childhood and provides preliminary support for early programming of child appetitive traits through DNAm. Investigating differential DNAm associated with appetitive traits could be an important first step in identifying biological pathways underlying the development of these behaviors.
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Affiliation(s)
- Holly A Harris
- Department of Child & Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands; The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Erasmus University Rotterdam, Department of Psychology, Education & Child Studies, Rotterdam, the Netherlands.
| | - Chloe Friedman
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| | - Anne P Starling
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
| | - Dana Dabelea
- Department of Epidemiology, Colorado School of Public Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA; Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| | - Susan L Johnson
- Department of Pediatrics, Section of Nutrition, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| | - Bernard F Fuemmeler
- Virginia Commonwealth University, Massey Comprehensive Cancer Center, Richmond, VA, USA.
| | - Dereje Jima
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA; Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, USA.
| | - Susan K Murphy
- Duke University Medical Center, Department of Obstetrics and Gynecology, Reproductive Sciences, Durham, NC, USA.
| | - Cathrine Hoyo
- Department of Biological Sciences, Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, USA.
| | - Pauline W Jansen
- Department of Child & Adolescent Psychiatry/Psychology, Erasmus MC, University Medical Center, Rotterdam, the Netherlands; The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Erasmus University Rotterdam, Department of Psychology, Education & Child Studies, Rotterdam, the Netherlands.
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
| | - Rosa H Mulder
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
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Keller M, Svensson SIA, Rohde-Zimmermann K, Kovacs P, Böttcher Y. Genetics and Epigenetics in Obesity: What Do We Know so Far? Curr Obes Rep 2023; 12:482-501. [PMID: 37819541 DOI: 10.1007/s13679-023-00526-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/07/2023] [Indexed: 10/13/2023]
Abstract
PURPOSE OF REVIEW Enormous progress has been made in understanding the genetic architecture of obesity and the correlation of epigenetic marks with obesity and related traits. This review highlights current research and its challenges in genetics and epigenetics of obesity. RECENT FINDINGS Recent progress in genetics of polygenic traits, particularly represented by genome-wide association studies, led to the discovery of hundreds of genetic variants associated with obesity, which allows constructing polygenic risk scores (PGS). In addition, epigenome-wide association studies helped identifying novel targets and methylation sites being important in the pathophysiology of obesity and which are essential for the generation of methylation risk scores (MRS). Despite their great potential for predicting the individual risk for obesity, the use of PGS and MRS remains challenging. Future research will likely discover more loci being involved in obesity, which will contribute to better understanding of the complex etiology of human obesity. The ultimate goal from a clinical perspective will be generating highly robust and accurate prediction scores allowing clinicians to predict obesity as well as individual responses to body weight loss-specific life-style interventions.
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Affiliation(s)
- Maria Keller
- Medical Department III-Endocrinology, Nephrology, Rheumatology, Medical Center, University of Leipzig, 04103, Leipzig, Germany
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig, University Hospital Leipzig, 04103, Leipzig, Germany
| | - Stina Ingrid Alice Svensson
- EpiGen, Department of Clinical Molecular Biology, Institute of Clinical Medicine, University of Oslo, 0316, Oslo, Norway
| | - Kerstin Rohde-Zimmermann
- Medical Department III-Endocrinology, Nephrology, Rheumatology, Medical Center, University of Leipzig, 04103, Leipzig, Germany
- Helmholtz Institute for Metabolic, Obesity and Vascular Research (HI-MAG) of the Helmholtz Center Munich at the University of Leipzig, University Hospital Leipzig, 04103, Leipzig, Germany
| | - Peter Kovacs
- Medical Department III-Endocrinology, Nephrology, Rheumatology, Medical Center, University of Leipzig, 04103, Leipzig, Germany
| | - Yvonne Böttcher
- EpiGen, Department of Clinical Molecular Biology, Institute of Clinical Medicine, University of Oslo, 0316, Oslo, Norway.
- EpiGen, Medical Division, Akershus University Hospital, 1478, Lørenskog, Norway.
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8
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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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9
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Ma H, Wang X, Liang Z, Li X, Heianza Y, He J, Chen W, Bazzano L, Qi L. BMI change during childhood, DNA methylation change at TXNIP, and glucose change during midlife. Obesity (Silver Spring) 2023; 31:2150-2158. [PMID: 37415079 PMCID: PMC10524171 DOI: 10.1002/oby.23806] [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: 01/18/2023] [Revised: 03/28/2023] [Accepted: 04/29/2023] [Indexed: 07/08/2023]
Abstract
OBJECTIVE This study investigated whether changes in DNA methylation (DNAm) at TXNIP are associated with glycemic changes and whether such an association differs with early-life adiposity changes. METHODS A total of 594 Bogalusa Heart Study participants who had blood DNAm measurements at two time points in midlife were included. Of them, 353 participants had at least four BMI measurements during childhood and adolescence. The incremental area under the curve was calculated as a measure of long-term trends of BMI during childhood and adolescence. RESULTS Increase in DNAm at TXNIP was significantly associated with decrease in fasting plasma glucose (FPG) independent of covariates (p < 0.001). The study found that the strength of this relationship was significantly modified by a trend of increasing BMI during childhood and adolescence (p-interaction = 0.003). Each 1% increase in DNAm at TXNIP was associated with a 2.90- (0.77) mg/dL decrease in FPG among participants with the highest tertile of BMI incremental area under the curve and a 0.96- (0.38) mg/dL decrease among those with the middle tertile, whereas no association was observed among participants with the lowest tertile. CONCLUSIONS These results indicate that changes in blood DNAm at TXNIP are significantly associated with changes in FPG in midlife, and this association was modified by BMI trends during childhood and adolescence.
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Affiliation(s)
- Hao Ma
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
| | - Xuan Wang
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
| | - Zhaoxia Liang
- Obstetrical Department, Women’s Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Xiang Li
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
| | - Yoriko Heianza
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
| | - Jiang He
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
| | - Wei Chen
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
| | - Lydia Bazzano
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
| | - Lu Qi
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
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10
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Xu B, Lv L, Chen X, Li X, Zhao X, Yang H, Feng W, Jiang X, Li J. Temporal relationships between BMI and obesity-related predictors of cardiometabolic and breast cancer risk in a longitudinal cohort. Sci Rep 2023; 13:12361. [PMID: 37524743 PMCID: PMC10390576 DOI: 10.1038/s41598-023-39387-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Accepted: 07/25/2023] [Indexed: 08/02/2023] Open
Abstract
Prospective inter-relationships among biomarkers were unexplored, which may provide mechanistic insights into diseases. We investigated the longitudinal associations of BMI change with trajectories of biomarkers related to cardiometabolic or breast cancer risk. A longitudinal study was conducted among 444 healthy women between 2019 to 2021. Cross‑lagged path analysis was used to examine the temporal relationships among BMI, cardiometabolic risk score (CRS), and obesity‑related proteins score (OPS) of breast cancer. Linear mixed-effect models were applied to investigate associations of time-varying BMI with biomarker-based risk score trajectories. Baseline BMI was associated with subsequent change of breast cancer predictors (P = 0.03), and baseline CRS were positively associated with OPS change (P < 0.001) but not vice versa. After fully adjustment of confounders, we found a 0.058 (95%CI = 0.009-0.107, P = 0.020) units increase of CRS and a 1.021 (95%CI = 0.041-1.995, P = 0.040) units increase of OPS as BMI increased 1 kg/m2 per year in postmenopausal women. OPS increased 0.784 (95%CI = 0.053-1.512, P = 0.035) units as CRS increased 1 unit per year. However, among premenopausal women, BMI only significantly affected CRS (β = 0.057, 95%CI = 0.007 to 0.107, P = 0.025). No significant change of OPS with time-varying CRS was found. Higher increase rates of BMI were associated with worse trajectories of biomarker-based risk of cardiometabolic and breast cancer. The longitudinal impact of CRS on OPS is unidirectional. Recommendations such as weight control for the reduction of cardiometabolic risk factors may benefit breast cancer prevention, especially in postmenopausal women.
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Affiliation(s)
- Bin Xu
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, 16#, Section 3, Renmin Nan Lu, Chengdu, 610041, Sichuan, People's Republic of China
| | - Liang Lv
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, 16#, Section 3, Renmin Nan Lu, Chengdu, 610041, Sichuan, People's Republic of China
| | - Xin Chen
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, 16#, Section 3, Renmin Nan Lu, Chengdu, 610041, Sichuan, People's Republic of China
| | - Xingyue Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, 16#, Section 3, Renmin Nan Lu, Chengdu, 610041, Sichuan, People's Republic of China
| | - Xunying Zhao
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, 16#, Section 3, Renmin Nan Lu, Chengdu, 610041, Sichuan, People's Republic of China
| | - Huifang Yang
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, 16#, Section 3, Renmin Nan Lu, Chengdu, 610041, Sichuan, People's Republic of China
| | - Wanting Feng
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, 16#, Section 3, Renmin Nan Lu, Chengdu, 610041, Sichuan, People's Republic of China
| | - Xia Jiang
- Department of Nutrition and Food Hygiene, West China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, China
| | - Jiayuan Li
- Department of Epidemiology and Biostatistics, Institute of Systems Epidemiology, and West China-PUMC C. C. Chen Institute of Health, West China School of Public Health and West China Fourth Hospital, Sichuan University, 16#, Section 3, Renmin Nan Lu, Chengdu, 610041, Sichuan, People's Republic of China.
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11
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Vineis P, Handakas E, Alfano R, Millett C, Fecht D, Chatzi L, Plusquin M, Nawrot T, Richiardi L, Barros H, Vrijheid M, Sassi F, Robinson O. The contribution to policies of an exposome-based approach to childhood obesity. EXPOSOME 2023; 3:osad006. [PMID: 37823001 PMCID: PMC7615122 DOI: 10.1093/exposome/osad006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 10/13/2023]
Abstract
Childhood obesity is an increasingly severe public health problem, with a prospective impact on health. We propose an exposome approach to identify actionable risk factors for this condition. Our assumption is that relationships between external exposures and outcomes such as rapid growth, overweight, or obesity in children can be better understood through a "meet-in-the-middle" model. This is based on a combination of external and internal exposome-based approaches, that is, the study of multiple exposures (in our case, dietary patterns) and molecular pathways (metabolomics and epigenetics). This may strengthen causal reasoning by identifying intermediate markers that are associated with both exposures and outcomes. Our biomarker-based studies in the STOP consortium suggest (in several ways, including mediation analysis) that branched-chain amino acids (BCAAs) could be mediators of the effect of dietary risk factors on childhood overweight/obesity. This is consistent with intervention and animal studies showing that higher intake of BCAAs has a positive impact on body composition, glycemia, and satiety. Concerning food, of particular concern is the trend of increasing intake of ultra-processed food (UPF), including among children. Several mechanisms have been proposed to explain the impact of UPF on obesity and overweight, including nutrient intake (particularly proteins), changes in appetite, or the role of additives. Research from the Avon Longitudinal Study of Parents and Children cohort has shown a relationship between UPF intake and trajectories in childhood adiposity, while UPF was related to lower blood levels of BCAAs. We suggest that an exposome-based approach can help strengthening causal reasoning and support policies. Intake of UPF in children should be restricted to prevent obesity.
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Affiliation(s)
- Paolo Vineis
- MRC Centre for Environment and Health, School of Public Health, Imperial College, London, UK
| | - Evangelos Handakas
- MRC Centre for Environment and Health, School of Public Health, Imperial College, London, UK
| | - Rossella Alfano
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
| | - Christopher Millett
- Public Health Policy Evaluation Unit, School of Public Heath, Imperial College London, London, UK
- NOVA National School of Public Health, Public Health Research Center, Comprehensive Health Research Center, CHRC,, NOVA University Lisbon, Lisbon, Portugal
| | - Daniela Fecht
- MRC Centre for Environment and Health, School of Public Health, Imperial College, London, UK
- NIHR Health Protection Research Unit in Chemical Radiation Threats and Hazards, School of Public Health, Imperial College London, London, UK
| | - Leda Chatzi
- Department of Population and Public Health Sciences, University of Southern California, Los Angeles, CA, USA
| | - Michelle Plusquin
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
| | - Tim Nawrot
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
| | - Lorenzo Richiardi
- Cancer Epidemiology Unit, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Henrique Barros
- Departamento de Ciências da Saúde Pública e Forenses e Educação Médica, Faculdade de Medicina, Universidade do Porto, Porto, Portugal
| | - Martine Vrijheid
- Institute for Global Health (ISGlobal), Barcelona, Spain
- Department of Medicine and Life Sciences, Universitat Pompeu Fabra (UPF), Barcelona, Spain
- Consorcio de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Franco Sassi
- Centre for Health Economics and Policy Innovation, Department of Economics and Public Policy, Imperial College Business School, London, UK
| | - Oliver Robinson
- MRC Centre for Environment and Health, School of Public Health, Imperial College, London, UK
- Mohn Centre for Children’s Health and Well-being, School of Public Health, Imperial College London, London, UK
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12
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Hahn J, Bressler J, Domingo-Relloso A, Chen MH, McCartney DL, Teumer A, van Dongen J, Kleber ME, Aïssi D, Swenson BR, Yao J, Zhao W, Huang J, Xia Y, Brown MR, Costeira R, de Geus EJC, Delgado GE, Dobson DA, Elliott P, Grabe HJ, Guo X, Harris SE, Huffman JE, Kardia SLR, Liu Y, Lorkowski S, Marioni RE, Nauck M, Ratliff SM, Sabater-Lleal M, Spector TD, Suchon P, Taylor KD, Thibord F, Trégouët DA, Wiggins KL, Willemsen G, Bell JT, Boomsma DI, Cole SA, Cox SR, Dehghan A, Greinacher A, Haack K, März W, Morange PE, Rotter JI, Sotoodehnia N, Tellez-Plaza M, Navas-Acien A, Smith JA, Johnson AD, Fornage M, Smith NL, Wolberg AS, Morrison AC, de Vries PS. DNA methylation analysis is used to identify novel genetic loci associated with circulating fibrinogen levels in blood. J Thromb Haemost 2023; 21:1135-1147. [PMID: 36716967 DOI: 10.1016/j.jtha.2023.01.015] [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: 07/25/2022] [Revised: 11/04/2022] [Accepted: 01/17/2023] [Indexed: 01/30/2023]
Abstract
BACKGROUND Fibrinogen plays an essential role in blood coagulation and inflammation. Circulating fibrinogen levels may be determined based on interindividual differences in DNA methylation at cytosine-phosphate-guanine (CpG) sites and vice versa. OBJECTIVES To perform an EWAS to examine an association between blood DNA methylation levels and circulating fibrinogen levels to better understand its biological and pathophysiological actions. METHODS We performed an epigenome-wide association study of circulating fibrinogen levels in 18 037 White, Black, American Indian, and Hispanic participants, representing 14 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium. Circulating leukocyte DNA methylation was measured using the Illumina 450K array in 12 904 participants and using the EPIC array in 5133 participants. In each study, an epigenome-wide association study of fibrinogen was performed using linear mixed models adjusted for potential confounders. Study-specific results were combined using array-specific meta-analysis, followed by cross-replication of epigenome-wide significant associations. We compared models with and without CRP adjustment to examine the role of inflammation. RESULTS We identified 208 and 87 significant CpG sites associated with fibrinogen levels from the 450K (p < 1.03 × 10-7) and EPIC arrays (p < 5.78 × 10-8), respectively. There were 78 associations from the 450K array that replicated in the EPIC array and 26 vice versa. After accounting for overlapping sites, there were 83 replicated CpG sites located in 61 loci, of which only 4 have been previously reported for fibrinogen. The examples of genes located near these CpG sites were SOCS3 and AIM2, which are involved in inflammatory pathways. The associations of all 83 replicated CpG sites were attenuated after CRP adjustment, although many remained significant. CONCLUSION We identified 83 CpG sites associated with circulating fibrinogen levels. These associations are partially driven by inflammatory pathways shared by both fibrinogen and CRP.
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Affiliation(s)
- Julie Hahn
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA.
| | - Jan Bressler
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Arce Domingo-Relloso
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA; Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institutes, Madrid, Spain; Department of Statistics and Operations Research, University of Valencia, Burjassot, Spain
| | - Ming-Huei Chen
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, Massachusetts, USA
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Alexander Teumer
- Department SHIP/Clinical-Epidemiological Research, Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany; DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany; Department of Population Medicine and Lifestyle Diseases Prevention, Medical University of Bialystok, Bialystok, Poland
| | - Jenny van Dongen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Marcus E Kleber
- Vth Department of Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany; SYNLAB MVZ Humangenetik Mannheim, Mannheim, Germany
| | - Dylan Aïssi
- Univ. Bordeaux, INSERM, Bordeaux Population Health Research Center, UMR 1219, Molecular Epidemiology of Vascular and Brain Disorders, Bordeaux, France
| | - Brenton R Swenson
- Cardiovascular Health Research Unit, School of Public Health, University of Washington, Seattle, Washington, USA
| | - Jie Yao
- Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA; Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Jian Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Yujing Xia
- Department of Twin Research and Genetic Epidemiology, St Thomas Hospital Campus, King's College London, London, United Kingdom
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Ricardo Costeira
- Department of Twin Research and Genetic Epidemiology, St Thomas Hospital Campus, King's College London, London, United Kingdom
| | - Eco J C de Geus
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Graciela E Delgado
- Vth Department of Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Dre'Von A Dobson
- Pathology and Laboratory Medicine and UNC Blood Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, MRC Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom; UK Dementia Research Institute, Imperial College London, London, United Kingdom; British Heart Foundation Centre for Research Excellence, Imperial College London, London, United Kingdom
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany; German Center for Neurodegenerative Diseases (DZNE), Site Rostock/Greifswald, Greifswald, Germany
| | - Xiuqing Guo
- Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Sarah E Harris
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC), VA Boston Healthcare System, Boston, Massachusetts, USA
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Yongmei Liu
- Medicine, Cardiology, Duke Molecular Physiology Institute, Durham, North Carolina, USA
| | - Stefan Lorkowski
- Institute of Nutritional Sciences, Friedrich Schiller University Jena, Jena, Germany; Competence Cluster for Nutrition and Cardiovascular Health (nutriCARD) Halle-Jena-Leipzig, Jena, Germany
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, United Kingdom
| | - Matthias Nauck
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, Greifswald, Germany; Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Scott M Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA
| | - Maria Sabater-Lleal
- Genomics of Complex Disease Unit, Sant Pau Biomedical Research Institute (IIB Sant Pau), Barcelona, Spain; Department of Medicine, Cardiovascular Medicine Unit, Karolinska Institutet, Stockholm, Sweden
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, St Thomas Hospital Campus, King's College London, London, United Kingdom
| | - Pierre Suchon
- Center for CardioVascular and Nutrition research (C2VN), INSERM 1263, INRAE 1260, Hematology Laboratory, La Timone University Hospital of Marseille, Aix-Marseille University, Marseille, France
| | - Kent D Taylor
- Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Florian Thibord
- Population Sciences Branch, National Heart, Lung, and Blood Institute, Framingham, Massachusetts, USA
| | - David-Alexandre Trégouët
- Univ. Bordeaux, INSERM, Bordeaux Population Health Research Center, UMR 1219, Molecular Epidemiology of Vascular and Brain Disorders, Bordeaux, France
| | - Kerri L Wiggins
- Department of Medicine, Division of General Internal Medicine, University of Washington, Seattle, Washington, USA
| | - Gonneke Willemsen
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Jordana T Bell
- Department of Twin Research and Genetic Epidemiology, St Thomas Hospital Campus, King's College London, London, United Kingdom
| | - Dorret I Boomsma
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands; Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Simon R Cox
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | - Andreas Greinacher
- Institute for Immunology and Transfusion Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Winfried März
- Vth Department of Medicine, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany; SYNLAB Academy, SYNLAB Holding Deutschland GmbH, Mannheim, Germany; Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria
| | - Pierre-Emmanuel Morange
- Cardiovascular and Nutrition Reserach Center (C2VN), INSERM, INRAE, Aix-Marseille University, Marseille, France
| | - Jerome I Rotter
- Pediatrics, Genomic Outcomes, The Institute for Translational Genomics and Population Sciences, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, California, USA
| | - Nona Sotoodehnia
- Department of Medicine, Division of Cardiology, University of Washington, Seattle, Washington, USA
| | - Maria Tellez-Plaza
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institutes, Madrid, Spain
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, New York, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, USA; Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - Andrew D Johnson
- Population Sciences Branch, Division of Intramural Research, National Heart, Lung and Blood Institute, Framingham, Massachusetts, USA
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA; Institute of Molecular Medicine, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Nicholas L Smith
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, Washington, USA; Kaiser Permanente Washington Health Research Institute, Kaiser Permanente Washington, Seattle, Washington, USA; Seattle Epidemiologic Research and Information Center, Department of Veterans Affairs Office of Research and Development, Seattle, Washington, USA
| | - Alisa S Wolberg
- Pathology and Laboratory Medicine and UNC Blood Research Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas, USA.
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13
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Tang H, Ling J, Meng H, Wu L, Zhu L, Zhu S. Temporal Relationship Between Insulin Resistance and Lipid Accumulation After Bariatric Surgery: a Multicenter Cohort Study. Obes Surg 2023:10.1007/s11695-023-06508-3. [PMID: 37060490 DOI: 10.1007/s11695-023-06508-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2022] [Revised: 06/12/2022] [Accepted: 06/15/2022] [Indexed: 04/16/2023]
Abstract
PURPOSE Insulin resistance (IR) is closely associated with lipid accumulation. Here, we investigated the temporal relationship between the two conditions after bariatric surgery. MATERIALS AND METHODS In total, 409 participants were enrolled from three bariatric centers in China from 2009 to 2018. We evaluated whether baseline IR (proxied by homeostasis model assessment of insulin resistance (HOMA-IR)) and lipid accumulation (proxied by visceral adiposity index (VAI) and lipid accumulation product (LAP)) were associated with follow-up IR and lipid accumulation (3 months postoperatively) using linear regression models. We then conducted a cross-lagged panel analysis model to simultaneously examine the bidirectional relationship between IR and lipid accumulation. RESULTS Multivariable linear regression analyses showed that baseline HOMA-IR was associated with follow-up VAI (β = 0.430, 95% CI: 0.082-0.778, p = 0.016) and LAP (β = 0.070, 95% CI: 0.010-0.130, p = 0.022). There was no relationship between baseline lipid accumulation and follow-up IR. Further cross-lagged panel analyses indicated that the path coefficient from baseline HOMA-IR to follow-up VAI (β2 = 0.145, p = 0.003) was significantly greater than the coefficient from baseline VAI to follow-up HOMA-IR (β1 = - 0.013, p = 0.777). Similarly, the path coefficient from baseline HOMA-IR to follow-up LAP (β2 = 0.141, p = 0.003) was significantly greater than the coefficient from baseline LAP to follow-up HOMA-IR (β1 = 0.041, p = 0.391). CONCLUSION Our study demonstrated a unidirectional relationship from HOMA-IR to VAI and LAP, suggesting that the change in IR may precede lipid accumulation after surgery.
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Affiliation(s)
- Haibo Tang
- Department of Metabolic and Bariatric Surgery, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Jiapu Ling
- Department of Metabolic and Bariatric Surgery, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Hua Meng
- Department of General Surgery, The China-Japan Friendship Hospital, Beijing, China
| | - Liangping Wu
- Department of Metabolic Surgery, The Jinshazhou Hospital of Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Liyong Zhu
- Department of Metabolic and Bariatric Surgery, The Third Xiangya Hospital of Central South University, Changsha, China
| | - Shaihong Zhu
- Department of Metabolic and Bariatric Surgery, The Third Xiangya Hospital of Central South University, Changsha, China.
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14
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Nie X, Mu G, Guo Y, Yang S, Wang X, Ye Z, Tan Q, Wang M, Zhou M, Ma J, Chen W. Associations of selenium exposure with blood lipids: Exploring mediating DNA methylation sites in general Chinese urban non-smokers. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 869:161815. [PMID: 36708841 DOI: 10.1016/j.scitotenv.2023.161815] [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: 10/31/2022] [Revised: 01/17/2023] [Accepted: 01/20/2023] [Indexed: 06/18/2023]
Abstract
Selenium (Se) is widely distributed in the total environment and people are commonly exposed to Se, while the potential effects and mechanisms of Se exposure on blood lipids have not been well established. This study aimed to assess the associations of urinary Se (SeU) with blood lipids and explore the potential mediating DNA methylation sites. We included 2844 non-smoke participants from the second follow-up (2017-2018) of the Wuhan-Zhuhai cohort (WHZH) in this study. SeU and blood lipids [i.e., total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL), and high-density lipoprotein cholesterol (HDL)] for all participants were determined. The associations of SeU with blood lipids were analyzed by generalized linear models. Then, we conducted the blood lipids related epigenome-wide association studies (EWAS) among 221 never smokers, and the mediation analysis was conducted to explore the potential mediating cytosine-phosphoguanine (CpG) sites in the above associations. In this study, the SeU concentration of the participants in this study was 1.40 (0.94, 2.08) μg/mmol Cr. The SeU was positively associated with TC and LDL, and not associated with TG and HDL. We found 131, 3, and 1 new CpG sites related to TC, HDL, and LDL, respectively. Mediation analyses found that the methylation of cg06964030 (within MIR1306) and cg15824094 (within PLCH2) significantly mediated the positive association between SeU and TC. In conclusion, high levels of Se exposure were associated with increased TC and LDL among non-smokers, and the methylation of MIR1306 and PLCH2 partly mediated Se-associated TC increase. These findings provide new insights into the effects and mechanisms of Se exposure on lipids metabolism and highlight the importance of controlling Se exposure and intake for preventing high blood lipids.
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Affiliation(s)
- Xiuquan Nie
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Ge Mu
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yanjun Guo
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Shijie Yang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Xing Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Zi Ye
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Qiyou Tan
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Mengyi Wang
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Min Zhou
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Jixuan Ma
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Weihong Chen
- Department of Occupational & Environmental Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China; Key Laboratory of Environment and Health, Ministry of Education & Ministry of Environmental Protection, and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
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15
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Shabalala S, Ghai M, Okpeku M. Analysis of Y-STR diversity and DNA methylation variation among Black and Indian males from KwaZulu-Natal, South Africa. Forensic Sci Int 2023; 348:111682. [PMID: 37094501 DOI: 10.1016/j.forsciint.2023.111682] [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: 02/10/2023] [Accepted: 04/05/2023] [Indexed: 04/26/2023]
Abstract
Y-chromosome short tandem repeats (Y-STRs) are essential in understanding genetic structure and diversity of human populations and, most importantly, in identification of male perpetrators in criminal investigations. DNA methylation differences have been reported in human populations and methylation pattern at the CpG sites found within or flanking the Y-STR sites could also aid in human identification. Studies based on DNA methylation (DNAm) at Y-STRs are currently limited. The current study aimed to analyze the Y-STR diversity in South African Black and Indian individuals living in KwaZulu-Natal, Durban, South Africa, with the Yfiler™ Plus Kit and to analyze DNAm patterns in Y-STR markers CpG sites. DNA from 247 stored saliva samples were isolated and quantified. Across the 27 Y-STR loci in the Yfiler™ Plus Kit, 253 alleles were observed in 113 South African Black and Indian males, 112 unique haplotypes were observed, and one haplotype appeared twice (two Black individuals). No statistically significant differences were observed in the genetic diversity between the two population groups (Fst = 0.028, p-value ≥ 0.05). The kit showed a high discrimination capacity (DC) of 0.9912 and an overall haplotype diversity (HD) = 0.9995 among the sampled population groups. DYS438 and DYS448 markers displayed 2 and 3 CpG sites, respectively. Based on the two-tailed Fisher's Exact test, there were no statistically significant differences in the DNAm levels at DYS438 CpGs of Black and Indian males (p > 0.05). The Yfiler™ Plus Kit can be considered highly discriminatory among South African Black and Indian males. Studies on the South African population using Yfiler™ Plus Kit are scarce. Hence, accumulating Y-STR data on the diverse South African population will enhance the representation of South Africa in STR databases. Knowing which Y-STR markers are significantly informative for South Africa is essential for developing Y-STR kits better suited for the different ethnic groups. And to the best of our knowledge, DNA methylation analysis in Y-STR for different ethnic groups has never been done before. Complementing Y-STR data with methylation knowledge could provide population-specific information for forensic identification.
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Affiliation(s)
- Sthabile Shabalala
- School of Life Sciences, University of KwaZulu-Natal, Private Bag X54001, Westville, Durban 4000, South Africa
| | - Meenu Ghai
- School of Life Sciences, University of KwaZulu-Natal, Private Bag X54001, Westville, Durban 4000, South Africa.
| | - Moses Okpeku
- School of Life Sciences, University of KwaZulu-Natal, Private Bag X54001, Westville, Durban 4000, South Africa
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16
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Do WL, Sun D, Meeks K, Dugué PA, Demerath E, Guan W, Li S, Chen W, Milne R, Adeyemo A, Agyemang C, Nassir R, Manson JE, Shadyab AH, Hou L, Horvath S, Assimes TL, Bhatti P, Jordahl KM, Baccarelli AA, Smith AK, Staimez LR, Stein AD, Whitsel EA, Narayan KV, Conneely KN. Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI. Am J Hum Genet 2023; 110:273-283. [PMID: 36649705 PMCID: PMC9943731 DOI: 10.1016/j.ajhg.2022.12.014] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 12/20/2022] [Indexed: 01/18/2023] Open
Abstract
This study sought to examine the association between DNA methylation and body mass index (BMI) and the potential of BMI-associated cytosine-phosphate-guanine (CpG) sites to provide information about metabolic health. We pooled summary statistics from six trans-ethnic epigenome-wide association studies (EWASs) of BMI representing nine cohorts (n = 17,034), replicated these findings in the Women's Health Initiative (WHI, n = 4,822), and developed an epigenetic prediction score of BMI. In the pooled EWASs, 1,265 CpG sites were associated with BMI (p < 1E-7) and 1,238 replicated in the WHI (FDR < 0.05). We performed several stratified analyses to examine whether these associations differed between individuals of European and African descent, as defined by self-reported race/ethnicity. We found that five CpG sites had a significant interaction with BMI by race/ethnicity. To examine the utility of the significant CpG sites in predicting BMI, we used elastic net regression to predict log-normalized BMI in the WHI (80% training/20% testing). This model found that 397 sites could explain 32% of the variance in BMI in the WHI test set. Individuals whose methylome-predicted BMI overestimated their BMI (high epigenetic BMI) had significantly higher glucose and triglycerides and lower HDL cholesterol and LDL cholesterol compared to accurately predicted BMI. Individuals whose methylome-predicted BMI underestimated their BMI (low epigenetic BMI) had significantly higher HDL cholesterol and lower glucose and triglycerides. This study confirmed 553 and identified 685 CpG sites associated with BMI. Participants with high epigenetic BMI had poorer metabolic health, suggesting that the overestimation may be driven in part by cardiometabolic derangements characteristic of metabolic syndrome.
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Affiliation(s)
- Whitney L. Do
- Laney Graduate School, Emory University, Atlanta, GA, USA
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China,Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Karlijn Meeks
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA,Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Pierre-Antoine Dugué
- Precision Medicine, School of Clinical Sciences At Monash Health, Monash University, Clayton, VIC, Australia,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia
| | - Ellen Demerath
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Weihua Guan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Shengxu Li
- Children’s Minnesota Research Institute, Childrens Minnesota, Minneapolis, MN, USA
| | - Wei Chen
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Roger Milne
- Precision Medicine, School of Clinical Sciences At Monash Health, Monash University, Clayton, VIC, Australia,Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia,Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Parkville, VIC 3051, Australia
| | - Abedowale Adeyemo
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Charles Agyemang
- Department of Public and Occupational Health, Amsterdam Public Health Research Institute, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Rami Nassir
- Department of Pathology, School of Medicine, Umm Al-Qura University, Mecca, Saudi Arabia
| | - JoAnn E. Manson
- Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Aladdin H. Shadyab
- Herbert Wertheim School of Public Health and Human Longevity Science, University of California, San Diego, La Jolla, CA, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Steve Horvath
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | | | - Parveen Bhatti
- Cancer Control Research, BC Cancer, Vancouver, BC, Canada
| | | | - Andrea A. Baccarelli
- Department of Environmental Health Sciences, Columbia University, New York, NY, USA
| | - Alicia K. Smith
- Department of Gynecology and Obstetrics, School of Medicine, Emory University, Atlanta, GA, USA
| | - Lisa R. Staimez
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Aryeh D. Stein
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Eric A. Whitsel
- Departments of Epidemiology and Medicine, University of North Carolina, Chapel Hill, NC, USA
| | - K.M. Venkat Narayan
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Karen N. Conneely
- Department of Human Genetics, School of Medicine, Emory University, Atlanta, GA, USA,Corresponding author
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17
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Alfano R, Zugna D, Barros H, Bustamante M, Chatzi L, Ghantous A, Herceg Z, Keski-Rahkonen P, de Kok TM, Nawrot TS, Relton CL, Robinson O, Roumeliotaki T, Scalbert A, Vrijheid M, Vineis P, Richiardi L, Plusquin M. Cord blood epigenome-wide meta-analysis in six European-based child cohorts identifies signatures linked to rapid weight growth. BMC Med 2023; 21:17. [PMID: 36627699 PMCID: PMC9831885 DOI: 10.1186/s12916-022-02685-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 11/29/2022] [Indexed: 01/12/2023] Open
Abstract
BACKGROUND Rapid postnatal growth may result from exposure in utero or early life to adverse conditions and has been associated with diseases later in life and, in particular, with childhood obesity. DNA methylation, interfacing early-life exposures and subsequent diseases, is a possible mechanism underlying early-life programming. METHODS Here, a meta-analysis of Illumina HumanMethylation 450K/EPIC-array associations of cord blood DNA methylation at single CpG sites and CpG genomic regions with rapid weight growth at 1 year of age (defined with reference to WHO growth charts) was conducted in six European-based child cohorts (ALSPAC, ENVIRONAGE, Generation XXI, INMA, Piccolipiù, and RHEA, N = 2003). The association of gestational age acceleration (calculated using the Bohlin epigenetic clock) with rapid weight growth was also explored via meta-analysis. Follow-up analyses of identified DNA methylation signals included prediction of rapid weight growth, mediation of the effect of conventional risk factors on rapid weight growth, integration with transcriptomics and metabolomics, association with overweight in childhood (between 4 and 8 years), and comparison with previous findings. RESULTS Forty-seven CpGs were associated with rapid weight growth at suggestive p-value <1e-05 and, among them, three CpGs (cg14459032, cg25953130 annotated to ARID5B, and cg00049440 annotated to KLF9) passed the genome-wide significance level (p-value <1.25e-07). Sixteen differentially methylated regions (DMRs) were identified as associated with rapid weight growth at false discovery rate (FDR)-adjusted/Siddak p-values < 0.01. Gestational age acceleration was associated with decreasing risk of rapid weight growth (p-value = 9.75e-04). Identified DNA methylation signals slightly increased the prediction of rapid weight growth in addition to conventional risk factors. Among the identified signals, three CpGs partially mediated the effect of gestational age on rapid weight growth. Both CpGs (N=3) and DMRs (N=3) were associated with differential expression of transcripts (N=10 and 7, respectively), including long non-coding RNAs. An AURKC DMR was associated with childhood overweight. We observed enrichment of CpGs previously reported associated with birthweight. CONCLUSIONS Our findings provide evidence of the association between cord blood DNA methylation and rapid weight growth and suggest links with prenatal exposures and association with childhood obesity providing opportunities for early prevention.
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Affiliation(s)
- Rossella Alfano
- Medical Research Council Centre for Environment and Health, Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| | - Daniela Zugna
- Department of Medical Sciences, University of Turin and CPO-Piemonte, Turin, Italy
| | - Henrique Barros
- Institute of Public Health, University of Porto, Porto, Portugal
| | - Mariona Bustamante
- ISGlobal, Institute of Global Health, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Leda Chatzi
- Department of Preventive Medicine, University of Southern California, Los Angeles, USA
| | - Akram Ghantous
- International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008, Lyon, France
| | - Zdenko Herceg
- International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008, Lyon, France
| | - Pekka Keski-Rahkonen
- International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008, Lyon, France
| | - Theo M de Kok
- Department of Toxicogenomics, Maastricht University, Maastricht, The Netherlands
| | - Tim S Nawrot
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium
| | - Caroline L Relton
- Μedical Research Council Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Oliver Robinson
- Medical Research Council Centre for Environment and Health, Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
- Mohn Centre for Children's Health and Well-being, The School of Public Health, Imperial College London, London, UK
| | - Theano Roumeliotaki
- Department of Social Medicine, Faculty of Medicine, University of Crete, Heraklion, Greece
| | - Augustin Scalbert
- International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008, Lyon, France
| | - Martine Vrijheid
- International Agency for Research on Cancer (IARC), 150 Cours Albert Thomas, 69008, Lyon, France
| | - Paolo Vineis
- Medical Research Council Centre for Environment and Health, Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
| | - Lorenzo Richiardi
- Department of Medical Sciences, University of Turin and CPO-Piemonte, Turin, Italy
| | - Michelle Plusquin
- Centre for Environmental Sciences, Hasselt University, Agoralaan Building D, 3590, Diepenbeek, Belgium.
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18
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Ghemrawi M, Tejero NF, Duncan G, McCord B. Pyrosequencing: Current forensic methodology and future applications-a review. Electrophoresis 2023; 44:298-312. [PMID: 36168852 DOI: 10.1002/elps.202200177] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 08/22/2022] [Accepted: 08/23/2022] [Indexed: 02/01/2023]
Abstract
The recent development of small, single-amplicon-based benchtop systems for pyrosequencing has opened up a host of novel procedures for applications in forensic science. Pyrosequencing is a sequencing by synthesis technique, based on chemiluminescent inorganic pyrophosphate detection. This review explains the pyrosequencing workflow and illustrates the step-by-step chemistry, followed by a description of the assay design and factors to keep in mind for an exemplary assay. Existing and potential forensic applications are highlighted using this technology. Current applications include identifying species, identifying bodily fluids, and determining smoking status. We also review progress in potential applications for the future, including research on distinguishing monozygotic twins, detecting alcohol and drug abuse, and other phenotypic characteristics such as diet and body mass index. Overall, the versatility of the pyrosequencing technologies renders it a useful tool in forensic genomics.
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Affiliation(s)
- Mirna Ghemrawi
- Department of Chemistry and Biochemistry, Florida International University, Miami, Florida, USA
| | - Nicole Fernandez Tejero
- Department of Chemistry and Biochemistry, Florida International University, Miami, Florida, USA
| | - George Duncan
- Halmos College of Natural Sciences and Oceanography, Nova Southeastern University, Dania Beach, Florida, USA
| | - Bruce McCord
- Department of Chemistry and Biochemistry, Florida International University, Miami, Florida, USA
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19
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Taylor JY, Huang Y, Zhao W, Wright ML, Wang Z, Hui Q, Potts‐Thompson S, Barcelona V, Prescott L, Yao Y, Crusto C, Kardia SLR, Smith JA, Sun YV. Epigenome-wide association study of BMI in Black populations from InterGEN and GENOA. Obesity (Silver Spring) 2023; 31:243-255. [PMID: 36479596 PMCID: PMC10107734 DOI: 10.1002/oby.23589] [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: 08/24/2021] [Revised: 08/09/2022] [Accepted: 08/22/2022] [Indexed: 12/12/2022]
Abstract
OBJECTIVE Obesity is a significant public health concern across the globe. Research investigating epigenetic mechanisms related to obesity and obesity-associated conditions has identified differences that may contribute to cellular dysregulation that accelerates the development of disease. However, few studies include Black women, who experience the highest incidence of obesity and early onset of cardiometabolic disorders. METHODS The association of BMI with epigenome-wide DNA methylation (DNAm) was examined using the 850K Illumina EPIC BeadChip in two Black populations (Intergenerational Impact of Genetic and Psychological Factors on Blood Pressure [InterGEN], n = 239; and The Genetic Epidemiology Network of Arteriopathy [GENOA] study, n = 961) using linear mixed-effects regression models adjusted for batch effects, cell type heterogeneity, population stratification, and confounding factors. RESULTS Cross-sectional analysis of the InterGEN discovery cohort identified 28 DNAm sites significantly associated with BMI, 24 of which had not been previously reported. Of these, 17 were replicated using the GENOA study. In addition, a meta-analysis, including both the InterGEN and GENOA cohorts, identified 658 DNAm sites associated with BMI with false discovery rate < 0.05. In a meta-analysis of Black women, we identified 628 DNAm sites significantly associated with BMI. Using a more stringent significance threshold of Bonferroni-corrected p value 0.05, 65 and 61 DNAm sites associated with BMI were identified from the combined sex and female-only meta-analyses, respectively. CONCLUSIONS This study suggests that BMI is associated with differences in DNAm among women that can be identified with DNA extracted from salivary (discovery) and peripheral blood (replication) samples among Black populations across two cohorts.
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Affiliation(s)
- Jacquelyn Y. Taylor
- Center for Research on People of ColorColumbia University School of NursingNew YorkNew YorkUSA
| | - Yunfeng Huang
- Department of EpidemiologyEmory University Rollins School of Public HealthAtlantaGeorgiaUSA
| | - Wei Zhao
- Department of Epidemiology, School of Public HealthUniversity of MichiganAnn ArborMichiganUSA
| | | | - Zeyuan Wang
- Department of EpidemiologyEmory University Rollins School of Public HealthAtlantaGeorgiaUSA
| | - Qin Hui
- Department of EpidemiologyEmory University Rollins School of Public HealthAtlantaGeorgiaUSA
| | | | - Veronica Barcelona
- Center for Research on People of ColorColumbia University School of NursingNew YorkNew YorkUSA
| | - Laura Prescott
- Center for Research on People of ColorColumbia University School of NursingNew YorkNew YorkUSA
| | - Yutong Yao
- Department of EpidemiologyEmory University Rollins School of Public HealthAtlantaGeorgiaUSA
| | - Cindy Crusto
- Department of PsychiatryYale School of MedicineNew HavenConnecticutUSA
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public HealthUniversity of MichiganAnn ArborMichiganUSA
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public HealthUniversity of MichiganAnn ArborMichiganUSA
- Survey Research CenterInstitute for Social Research, University of MichiganAnn ArborMichiganUSA
| | - Yan V. Sun
- Department of EpidemiologyEmory University Rollins School of Public HealthAtlantaGeorgiaUSA
- Atlanta VA Healthcare SystemDecaturGeorgiaUSA
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20
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Abstract
Nowadays, obesity is one of the largest public health problems worldwide. In the last few decades, there has been a marked increase in the obesity epidemic and its related comorbidities. Worldwide, more than 2.2 billion people (33%) are affected by overweight or obesity (712 million, 10%) and its associated metabolic complications. Although a high heritability of obesity has been estimated, the genetic variants conducted from genetic association studies only partially explain the variation of body mass index. This has led to a growing interest in understanding the potential role of epigenetics as a key regulator of gene-environment interactions on the development of obesity and its associated complications. Rapid advances in epigenetic research methods and reduced costs of epigenome-wide association studies have led to a great expansion of population-based studies. The field of epigenetics and metabolic diseases such as obesity has advanced rapidly in a short period of time. The main epigenetic mechanisms include DNA methylation, histone modifications, microRNA (miRNA)-mediated regulation and so on. DNA methylation is the most investigated epigenetic mechanism. Preliminary evidence from animal and human studies supports the effect of epigenetics on obesity. Studies of epigenome-wide association studies and genome-wide histone modifications from different biological specimens such as blood samples (newborn, children, adolescent, youth, woman, man, twin, race, and meta-analysis), adipose tissues, skeletal muscle cells, placenta, and saliva have reported the differential expression status of multiple genes before and after obesity interventions and have identified multiple candidate genes and biological markers. These findings may improve the understanding of the complex etiology of obesity and its related comorbidities, and help to predict an individual's risk of obesity at a young age and open possibilities for introducing targeted prevention and treatment strategies.
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Affiliation(s)
- Feng-Yao Wu
- Department of Comprehensive Internal Medicine, Affiliated Infectious Disease Hospital of Nanning (The Fourth People’s Hospital of Nanning), Guangxi Medical University, No. 1 Erli, Changgang Road, Nanning, 530023 Guangxi People’s Republic of China
| | - Rui-Xing Yin
- Department of Comprehensive Internal Medicine, Affiliated Infectious Disease Hospital of Nanning (The Fourth People’s Hospital of Nanning), Guangxi Medical University, No. 1 Erli, Changgang Road, Nanning, 530023 Guangxi People’s Republic of China
- Department of Cardiology, Institute of Cardiovascular Diseases, The First Affiliated Hospital, Guangxi Medical University, 6 Shuangyong Road, Nanning, 530021 Guangxi People’s Republic of China
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21
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Epigenetic clock: A promising biomarker and practical tool in aging. Ageing Res Rev 2022; 81:101743. [PMID: 36206857 DOI: 10.1016/j.arr.2022.101743] [Citation(s) in RCA: 31] [Impact Index Per Article: 15.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2022] [Revised: 09/13/2022] [Accepted: 09/30/2022] [Indexed: 01/31/2023]
Abstract
As a complicated process, aging is characterized by various changes at the cellular, subcellular and nuclear levels, one of which is epigenetic aging. With increasing awareness of the critical role that epigenetic alternations play in aging, DNA methylation patterns have been employed as a measure of biological age, currently referred to as the epigenetic clock. This review provides a comprehensive overview of the epigenetic clock as a biomarker of aging and a useful tool to manage healthy aging. In this burgeoning scientific field, various kinds of epigenetic clocks continue to emerge, including Horvath's clock, Hannum's clock, DNA PhenoAge, and DNA GrimAge. We hereby present the most classic epigenetic clocks, as well as their differences. Correlations of epigenetic age with morbidity, mortality and other factors suggest the potential of epigenetic clocks for risk prediction and identification in the context of aging. In particular, we summarize studies on promising age-reversing interventions, with epigenetic clocks employed as a practical tool in the efficacy evaluation. We also discuss how the lack of higher-quality information poses a major challenge, and offer some suggestions to address existing obstacles. Hopefully, our review will help provide an appropriate understanding of the epigenetic clocks, thereby enabling novel insights into the aging process and how it can be manipulated to promote healthy aging.
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22
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Wu Z, Chen L, Hong X, Si J, Cao W, Yu C, Huang T, Sun D, Liao C, Pang Y, Pang Z, Cong L, Wang H, Wu X, Liu Y, Guo Y, Chen Z, Lv J, Gao W, Li L. Temporal associations between leukocytes DNA methylation and blood lipids: a longitudinal study. Clin Epigenetics 2022; 14:132. [PMID: 36274151 PMCID: PMC9588246 DOI: 10.1186/s13148-022-01356-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 10/13/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND The associations between blood lipids and DNA methylation have been investigated in epigenome-wide association studies mainly among European ancestry populations. Several studies have explored the direction of the association using cross-sectional data, while evidence of longitudinal data is still lacking. RESULTS We tested the associations between peripheral blood leukocytes DNA methylation and four lipid measures from Illumina 450 K or EPIC arrays in 1084 participants from the Chinese National Twin Registry and replicated the result in 988 participants from the China Kadoorie Biobank. A total of 23 associations of 19 CpG sites were identified, with 4 CpG sites located in or adjacent to 3 genes (TMEM49, SNX5/SNORD17 and CCDC7) being novel. Among the validated associations, we conducted a cross-lagged analysis to explore the temporal sequence and found temporal associations of methylation levels of 2 CpG sites with triglyceride and 2 CpG sites with high-density lipoprotein-cholesterol (HDL-C) in all twins. In addition, methylation levels of cg11024682 located in SREBF1 at baseline were temporally associated with triglyceride at follow-up in only monozygotic twins. We then performed a mediation analysis with the longitudinal data and the result showed that the association between body mass index and HDL-C was partially mediated by the methylation level of cg06500161 (ABCG1), with a mediation proportion of 10.1%. CONCLUSIONS Our study indicated that the DNA methylation levels of ABCG1, AKAP1 and SREBF1 may be involved in lipid metabolism and provided evidence for elucidating the regulatory mechanism of lipid homeostasis.
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Affiliation(s)
- Zhiyu Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Lu Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Xuanming Hong
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Jiahui Si
- National Institute of Health Data Science at Peking University, Peking University, Beijing, 100191, China
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Chunxiao Liao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
| | - Zengchang Pang
- Qingdao Center for Disease Control and Prevention, Qingdao, 266033, China
| | - Liming Cong
- Zhejiang Center for Disease Control and Prevention, Hangzhou, 310051, China
| | - Hua Wang
- Jiangsu Center for Disease Control and Prevention, Nanjing, 210008, China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, 610041, China
| | - Yu Liu
- Heilongjiang Center for Disease Control and Prevention, Harbin, 150090, China
| | - Yu Guo
- Fuwai hospital Chinese Academy of Medical Sciences, Beijing, 100037, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China
- Key Laboratory of Molecular Cardiovascular Sciences (Peking University), Ministry of Education, Beijing, 100191, China
| | - Wenjing Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, 100191, China.
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China.
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23
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Titanji BK, Lee M, Wang Z, Chen J, Hui Q, Lo Re III V, So-Armah K, Justice AC, Xu K, Freiberg M, Gwinn M, Marconi VC, Sun YV. Epigenome-wide association study of biomarkers of liver function identifies albumin-associated DNA methylation sites among male veterans with HIV. Front Genet 2022; 13:1020871. [PMID: 36303554 PMCID: PMC9592923 DOI: 10.3389/fgene.2022.1020871] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2022] [Accepted: 09/22/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Liver disease (LD) is an important cause of morbidity and mortality for people with HIV (PWH). The molecular factors linked with LD in PWH are varied and incompletely characterized. We performed an epigenome-wide association study (EWAS) to identify associations between DNA methylation (DNAm) and biomarkers of liver function-aspartate transaminase, alanine transaminase, albumin, total bilirubin, platelet count, FIB-4 score, and APRI score-in male United States veterans with HIV. Methods: Blood samples and clinical data were obtained from 960 HIV-infected male PWH from the Veterans Aging Cohort Study. DNAm was assessed using the Illumina 450K or the EPIC 850K array in two mutually exclusive subsets. We performed a meta-analysis for each DNAm site measured by either platform. We also examined the associations between four measures of DNAm age acceleration (AA) and liver biomarkers. Results: Nine DNAm sites were positively associated with serum albumin in the meta-analysis of the EPIC and 450K EWAS after correcting for multiple testing. Four DNAm sites (cg16936953, cg18942579, cg01409343, and cg12054453), annotated within the TMEM49 and four of the remaining five sites (cg18181703, cg03546163, cg20995564, and cg23966214) annotated to SOCS3, FKBP5, ZEB2, and SAMD14 genes, respectively. The DNAm site, cg12992827, was not annotated to any known coding sequence. No significant associations were detected for the other six liver biomarkers. Higher PhenoAA was significantly associated with lower level of serum albumin (β = -0.007, p-value = 8.6 × 10-4, CI: -0.011116, -0.002884). Conclusion: We identified epigenetic associations of both individual DNAm sites and DNAm AA with liver function through serum albumin in men with HIV. Further replication analyses in independent cohorts are warranted to confirm the epigenetic mechanisms underlying liver function and LD in PWH.
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Affiliation(s)
- Boghuma K. Titanji
- Division of Infectious Disease, Emory School of Medicine, Atlanta, GA, United States
| | - Mitch Lee
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Zeyuan Wang
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Junyu Chen
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Qin Hui
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States
| | - Vincent Lo Re III
- Division of Infectious Diseases Department of Medicine and Center for Clinical Epidemiology and Biostatistics Perelman School of Medicine University of Pennsylvania, Philadelphia, PA, United States
| | - Kaku So-Armah
- Boston University Medical School, Boston, MA, United States
| | - Amy C. Justice
- Connecticut Veteran Health System, West Haven, CT, United States,Yale University School of Medicine, New Haven, CT, United States
| | - Ke Xu
- Connecticut Veteran Health System, West Haven, CT, United States,Yale University School of Medicine, New Haven, CT, United States
| | - Matthew Freiberg
- Cardiovascular Medicine Division and Tennessee Valley Healthcare System, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Marta Gwinn
- Centers for Disease Control and Prevention, Atlanta, GA, United States
| | - Vincent C. Marconi
- Division of Infectious Disease, Emory School of Medicine, Atlanta, GA, United States,Atlanta Veterans Affairs Health Care System, Decatur, GA, United States,Hubert Department of Global Health, Rollins School of Public Health, Atlanta, GA, United States,Emory Vaccine Center, Yerkes National Primate Research Center, Emory University, Atlanta, GA, United States
| | - Yan V. Sun
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, United States,Atlanta Veterans Affairs Health Care System, Decatur, GA, United States,*Correspondence: Yan V. Sun,
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24
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Zhang Y, Jia Z, Zhou Q, Zhang Y, Li D, Qi Y, Xu F. A bibliometric analysis of DNA methylation in cardiovascular diseases from 2001 to 2021. Medicine (Baltimore) 2022; 101:e30029. [PMID: 35984203 PMCID: PMC9388003 DOI: 10.1097/md.0000000000030029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
BACKGROUND DNA methylation is a dynamically reversible form of epigenetics. Dynamic regulation plays an important role in cardiovascular diseases (CVDs). However, there have been few bibliometric studies in this field. We aimed to visualize the research results and hotspots of DNA methylation in CVDs using a bibliometric analysis to provide a scientific direction for future research. METHODS Publications related to DNA methylation in CVDs from January 1, 2001, to September 15, 2021, were searched and confirmed from the Web of Science Core Collection. CiteSpace 5.7 and VOSviewer 1.6.15 were used for bibliometric and knowledge-map analyses. RESULTS A total of 2617 publications were included in 912 academic journals by 15,584 authors from 963 institutions from 85 countries/regions. Among them, the United States of America, China, and England were the top 3 countries contributing to the field of DNA methylation. Harvard University, Columbia University, and University of Cambridge were the top 3 contributing institutions in terms of publications and were closely linked. PLoS One was the most published and co-cited journal. Baccarelli Andrea A published the most content, while Barker DJP had the highest frequency of co-citations. The keyword cluster focused on the mechanism, methyl-containing substance, exposure/risk factor, and biomarker. In terms of research hotspots, references with strong bursts, which are still ongoing, recently included "epigenetic clock" (2017-2021), "obesity, smoking, aging, and DNA methylation" (2017-2021), and "biomarker and epigenome-wide association study" (2019-2021). CONCLUSIONS We used bibliometric and visual methods to identify research hotspots and trends in DNA methylation in CVDs. Epigenetic clocks, biomarkers, environmental exposure, and lifestyle may become the focus and frontier of future research.
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Affiliation(s)
- Yan Zhang
- Department of Cardiovascular, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Zijun Jia
- Department of Cardiovascular, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
- Graduate School, Beijing University of Chinese Medicine, Beijing, China
| | - Qingbing Zhou
- Department of Cardiovascular, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Ying Zhang
- Department of Cardiovascular, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Dandan Li
- Department of Cardiovascular, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yifei Qi
- Department of Cardiovascular, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Fengqin Xu
- Department of Cardiovascular, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
- *Correspondence: Fengqin Xu, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China (e-mail: )
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25
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Zheng Y, Joyce B, Hwang SJ, Ma J, Liu L, Allen N, Krefman A, Wang J, Gao T, Nannini D, Zhang H, Jacobs DR, Gross M, Fornage M, Lewis CE, Schreiner PJ, Sidney S, Chen D, Greenland P, Levy D, Hou L, Lloyd-Jones D. Association of Cardiovascular Health Through Young Adulthood With Genome-Wide DNA Methylation Patterns in Midlife: The CARDIA Study. Circulation 2022; 146:94-109. [PMID: 35652342 PMCID: PMC9348746 DOI: 10.1161/circulationaha.121.055484] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Cardiovascular health (CVH) from young adulthood is strongly associated with an individual's future risk of cardiovascular disease (CVD) and total mortality. Defining epigenomic biomarkers of lifelong CVH exposure and understanding their roles in CVD development may help develop preventive and therapeutic strategies for CVD. METHODS In 1085 CARDIA study (Coronary Artery Risk Development in Young Adults) participants, we defined a clinical cumulative CVH score that combines body mass index, blood pressure, total cholesterol, and fasting glucose measured longitudinally from young adulthood through middle age over 20 years (mean age, 25-45). Blood DNA methylation at >840 000 methylation markers was measured twice over 5 years (mean age, 40 and 45). Epigenome-wide association analyses on the cumulative CVH score were performed in CARDIA and compared in the FHS (Framingham Heart Study). We used penalized regression to build a methylation-based risk score to evaluate the risk of incident coronary artery calcification and clinical CVD events. RESULTS We identified 45 methylation markers associated with cumulative CVH at false discovery rate <0.01 (P=4.7E-7-5.8E-17) in CARDIA and replicated in FHS. These associations were more pronounced with methylation measured at an older age. CPT1A, ABCG1, and SREBF1 appeared as the most prominent genes. The 45 methylation markers were mostly located in transcriptionally active chromatin and involved lipid metabolism, insulin secretion, and cytokine production pathways. Three methylation markers located in genes SARS1, SOCS3, and LINC-PINT statistically mediated 20.4% of the total effect between CVH and risk of incident coronary artery calcification. The methylation risk score added information and significantly (P=0.004) improved the discrimination capacity of coronary artery calcification status versus CVH score alone and showed association with risk of incident coronary artery calcification 5 to 10 years later independent of cumulative CVH score (odds ratio, 1.87; P=9.66E-09). The methylation risk score was also associated with incident clinical CVD in FHS (hazard ratio, 1.28; P=1.22E-05). CONCLUSIONS Cumulative CVH from young adulthood contributes to midlife epigenetic programming over time. Our findings demonstrate the role of epigenetic markers in response to CVH changes and highlight the potential of epigenomic markers for precision CVD prevention, and earlier detection of subclinical CVD, as well.
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Affiliation(s)
- Yinan Zheng
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Brian Joyce
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Shih-Jen Hwang
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Jiantao Ma
- Tufts University Friedman School of Nutrition Science and Policy, Boston, Massachusetts, USA
| | - Lei Liu
- Division of Biostatistics, Washington University, St. Louis, Missouri, USA
| | - Norrina Allen
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Amy Krefman
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Jun Wang
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Tao Gao
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Drew Nannini
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Haixiang Zhang
- Center for Applied Mathematics, Tianjin University, Tianjin, China
| | - David R. Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Myron Gross
- Department of Laboratory Medicine and Pathology, Medical School, University of Minnesota, Minneapolis, Minnesota, USA
| | - Myriam Fornage
- Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Cora E. Lewis
- Department of Epidemiology, University of Alabama at Birmingham, Birmingham, Alabama, USA
- Division of Preventive Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Pamela J. Schreiner
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Stephen Sidney
- Division of Research, Kaiser Permanente Northern California, Oakland, California, USA
| | - Dongquan Chen
- Department of Medicine, School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Philip Greenland
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Lifang Hou
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Donald Lloyd-Jones
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
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26
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Yousefi PD, Suderman M, Langdon R, Whitehurst O, Davey Smith G, Relton CL. DNA methylation-based predictors of health: applications and statistical considerations. Nat Rev Genet 2022; 23:369-383. [PMID: 35304597 DOI: 10.1038/s41576-022-00465-w] [Citation(s) in RCA: 67] [Impact Index Per Article: 33.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/18/2022] [Indexed: 12/12/2022]
Abstract
DNA methylation data have become a valuable source of information for biomarker development, because, unlike static genetic risk estimates, DNA methylation varies dynamically in relation to diverse exogenous and endogenous factors, including environmental risk factors and complex disease pathology. Reliable methods for genome-wide measurement at scale have led to the proliferation of epigenome-wide association studies and subsequently to the development of DNA methylation-based predictors across a wide range of health-related applications, from the identification of risk factors or exposures, such as age and smoking, to early detection of disease or progression in cancer, cardiovascular and neurological disease. This Review evaluates the progress of existing DNA methylation-based predictors, including the contribution of machine learning techniques, and assesses the uptake of key statistical best practices needed to ensure their reliable performance, such as data-driven feature selection, elimination of data leakage in performance estimates and use of generalizable, adequately powered training samples.
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Affiliation(s)
- Paul D Yousefi
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Matthew Suderman
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Ryan Langdon
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Oliver Whitehurst
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - George Davey Smith
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK
| | - Caroline L Relton
- Medical Research Council Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Bristol, UK.
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27
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Wang YZ, Zhao W, Ammous F, Song Y, Du J, Shang L, Ratliff SM, Moore K, Kelly KM, Needham BL, Diez Roux AV, Liu Y, Butler KR, Kardia SLR, Mukherjee B, Zhou X, Smith JA. DNA Methylation Mediates the Association Between Individual and Neighborhood Social Disadvantage and Cardiovascular Risk Factors. Front Cardiovasc Med 2022; 9:848768. [PMID: 35665255 PMCID: PMC9162507 DOI: 10.3389/fcvm.2022.848768] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 04/29/2022] [Indexed: 12/14/2022] Open
Abstract
Low socioeconomic status (SES) and living in a disadvantaged neighborhood are associated with poor cardiovascular health. Multiple lines of evidence have linked DNA methylation to both cardiovascular risk factors and social disadvantage indicators. However, limited research has investigated the role of DNA methylation in mediating the associations of individual- and neighborhood-level disadvantage with multiple cardiovascular risk factors in large, multi-ethnic, population-based cohorts. We examined whether disadvantage at the individual level (childhood and adult SES) and neighborhood level (summary neighborhood SES as assessed by Census data and social environment as assessed by perceptions of aesthetic quality, safety, and social cohesion) were associated with 11 cardiovascular risk factors including measures of obesity, diabetes, lipids, and hypertension in 1,154 participants from the Multi-Ethnic Study of Atherosclerosis (MESA). For significant associations, we conducted epigenome-wide mediation analysis to identify methylation sites mediating the relationship between individual/neighborhood disadvantage and cardiovascular risk factors using the JT-Comp method that assesses sparse mediation effects under a composite null hypothesis. In models adjusting for age, sex, race/ethnicity, smoking, medication use, and genetic principal components of ancestry, epigenetic mediation was detected for the associations of adult SES with body mass index (BMI), insulin, and high-density lipoprotein cholesterol (HDL-C), as well as for the association between neighborhood socioeconomic disadvantage and HDL-C at FDR q < 0.05. The 410 CpG mediators identified for the SES-BMI association were enriched for CpGs associated with gene expression (expression quantitative trait methylation loci, or eQTMs), and corresponding genes were enriched in antigen processing and presentation pathways. For cardiovascular risk factors other than BMI, most of the epigenetic mediators lost significance after controlling for BMI. However, 43 methylation sites showed evidence of mediating the neighborhood socioeconomic disadvantage and HDL-C association after BMI adjustment. The identified mediators were enriched for eQTMs, and corresponding genes were enriched in inflammatory and apoptotic pathways. Our findings support the hypothesis that DNA methylation acts as a mediator between individual- and neighborhood-level disadvantage and cardiovascular risk factors, and shed light on the potential underlying epigenetic pathways. Future studies are needed to fully elucidate the biological mechanisms that link social disadvantage to poor cardiovascular health.
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Affiliation(s)
- Yi Zhe Wang
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Farah Ammous
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Yanyi Song
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Jiacong Du
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Lulu Shang
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Scott M. Ratliff
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Kari Moore
- Urban Health Collaborative, Drexel University, Philadelphia, PA, United States
| | - Kristen M. Kelly
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Belinda L. Needham
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Ana V. Diez Roux
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, United States
| | - Yongmei Liu
- Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, NC, United States
| | - Kenneth R. Butler
- Department of Medicine, Division of Geriatrics, University of Mississippi Medical Center, Jackson, MS, United States
| | - Sharon L. R. Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Bhramar Mukherjee
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Xiang Zhou
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, MI, United States
| | - Jennifer A. Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, United States
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, United States
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28
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Deng K, Shuai M, Zhang Z, Jiang Z, Fu Y, Shen L, Zheng JS, Chen YM. Temporal relationship among adiposity, gut microbiota, and insulin resistance in a longitudinal human cohort. BMC Med 2022; 20:171. [PMID: 35585555 PMCID: PMC9118787 DOI: 10.1186/s12916-022-02376-3] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Accepted: 04/12/2022] [Indexed: 12/18/2022] Open
Abstract
BACKGROUND The temporal relationship between adiposity and gut microbiota was unexplored. Whether some gut microbes lie in the pathways from adiposity to insulin resistance is less clear. Our study aims to reveal the temporal relationship between adiposity and gut microbiota and investigate whether gut microbiota may mediate the association of adiposity with insulin resistance in a longitudinal human cohort study. METHODS We obtained repeated-measured gut shotgun metagenomic and anthropometric data from 426 Chinese participants over ~3 years of follow-up. Cross-lagged path analysis was used to examine the temporal relationship between BMI and gut microbial features. The associations between the gut microbes and insulin resistance-related phenotypes were examined using a linear mixed-effect model. We examined the mediation effect of gut microbes on the association between adiposity and insulin resistance-related phenotypes. Replication was performed in the HMP cohort. RESULTS Baseline BMI was prospectively associated with levels of ten gut microbial species. Among them, results of four species (Adlercreutzia equolifaciens, Parabacteroides unclassified, Lachnospiraceae bacterium 3 1 57FAA CT1, Lachnospiraceae bacterium 7 1 58FAA) were replicated in the independent HMP cohort. Lachnospiraceae bacterium 3 1 57FAA CT1 was inversely associated with HOMA-IR and fasting insulin. Lachnospiraceae bacterium 3 1 57FAA CT1 mediated the association of overweight/obesity with HOMA-IR (FDR<0.05). Furthermore, Lachnospiraceae bacterium 3 1 57FAA CT1 was positively associated with the butyrate-producing pathway PWY-5022 (p < 0.001). CONCLUSIONS Our study identified one potentially beneficial microbe Lachnospiraceae bacterium 3 1 57FAA CT1, which might mediate the effect of adiposity on insulin resistance. The identified microbes are helpful for the discovery of novel therapeutic targets, as to mitigate the impact of adiposity on insulin resistance.
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Affiliation(s)
- Kui Deng
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.,Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China.,Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Rd, Cloud Town, Hangzhou, China
| | - Menglei Shuai
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Rd, Cloud Town, Hangzhou, China
| | - Zheqing Zhang
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.,Department of Nutrition and Food Hygiene, Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Southern Medical University, Guangzhou, China
| | - Zengliang Jiang
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Rd, Cloud Town, Hangzhou, China.,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Yuanqing Fu
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Rd, Cloud Town, Hangzhou, China.,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Luqi Shen
- Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Rd, Cloud Town, Hangzhou, China.,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China
| | - Ju-Sheng Zheng
- Institute of Basic Medical Sciences, Westlake Institute for Advanced Study, Hangzhou, China. .,Key Laboratory of Growth Regulation and Translational Research of Zhejiang Province, School of Life Sciences, Westlake University, 18 Shilongshan Rd, Cloud Town, Hangzhou, China. .,Westlake Intelligent Biomarker Discovery Lab, Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, China.
| | - Yu-Ming Chen
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Epidemiology, School of Public Health, Sun Yat-sen University, Guangzhou, China.
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Mayer F, Becker J, Reinauer C, Böhme P, Eickhoff SB, Koop B, Gündüz T, Blum J, Wagner W, Ritz-Timme S. Altered DNA methylation at age-associated CpG sites in children with growth disorders: impact on age estimation? Int J Legal Med 2022; 136:987-996. [PMID: 35551445 PMCID: PMC9170667 DOI: 10.1007/s00414-022-02826-w] [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: 11/29/2021] [Accepted: 04/07/2022] [Indexed: 11/09/2022]
Abstract
Age estimation based on DNA methylation (DNAm) can be applied to children, adolescents and adults, but many CG dinucleotides (CpGs) exhibit different kinetics of age-associated DNAm across these age ranges. Furthermore, it is still unclear how growth disorders impact epigenetic age predictions, and this may be particularly relevant for a forensic application. In this study, we analyzed buccal mucosa samples from 95 healthy children and 104 children with different growth disorders. DNAm was analysed by pyrosequencing for 22 CpGs in the genes PDE4C, ELOVL2, RPA2, EDARADD and DDO. The relationship between DNAm and age in healthy children was tested by Spearman’s rank correlation. Differences in DNAm between the groups “healthy children” and the (sub-)groups of children with growth disorders were tested by ANCOVA. Models for age estimation were trained (1) based on the data from 11 CpGs with a close correlation between DNAm and age (R ≥ 0.75) and (2) on five CpGs that also did not present significant differences in DNAm between healthy and diseased children. Statistical analysis revealed significant differences between the healthy group and the group with growth disorders (11 CpGs), the subgroup with a short stature (12 CpGs) and the non-short stature subgroup (three CpGs). The results are in line with the assumption of an epigenetic regulation of height-influencing genes. Age predictors trained on 11 CpGs with high correlations between DNAm and age revealed higher mean absolute errors (MAEs) in the group of growth disorders (mean MAE 2.21 years versus MAE 1.79 in the healthy group) as well as in the short stature (sub-)groups; furthermore, there was a clear tendency for overestimation of ages in all growth disorder groups (mean age deviations: total growth disorder group 1.85 years, short stature group 1.99 years). Age estimates on samples from children with growth disorders were more precise when using a model containing only the five CpGs that did not present significant differences in DNAm between healthy and diseased children (mean age deviations: total growth disorder group 1.45 years, short stature group 1.66 years). The results suggest that CpGs in genes involved in processes relevant for growth and development should be avoided in age prediction models for children since they may be sensitive for alterations in the DNAm pattern in cases of growth disorders.
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Affiliation(s)
- F Mayer
- Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Düsseldorf, Germany.
| | - J Becker
- Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Düsseldorf, Germany
| | - C Reinauer
- Department of General Paediatrics, University Hospital Düsseldorf, 40225, Düsseldorf, Germany
| | - P Böhme
- Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Düsseldorf, Germany
| | - S B Eickhoff
- Institute for Systems Neuroscience, University Hospital Düsseldorf, 40225, Düsseldorf, Germany.,Institute of Neuroscience and Medicine, Brain and Behaviour (INM-7), Research Centre Jülich, 52428, Jülich, Germany
| | - B Koop
- Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Düsseldorf, Germany
| | - T Gündüz
- Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Düsseldorf, Germany
| | - J Blum
- Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Düsseldorf, Germany
| | - W Wagner
- Helmholtz Institute for Biomedical Engineering, Stem Cell Biology and Cellular Engineering, RWTH Aachen University Medical School, 52074, Aachen, Germany
| | - S Ritz-Timme
- Institute of Legal Medicine, University Hospital Düsseldorf, 40225, Düsseldorf, Germany
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30
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Ko YK, Kim H, Lee Y, Lee YS, Gim JA. DNA Methylation Patterns According to Fatty Liver Index and Longitudinal Changes from the Korean Genome and Epidemiology Study (KoGES). Curr Issues Mol Biol 2022; 44:1149-1168. [PMID: 35723298 PMCID: PMC8947460 DOI: 10.3390/cimb44030075] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 02/23/2022] [Accepted: 02/25/2022] [Indexed: 11/16/2022] Open
Abstract
The role of differentially methylated regions (DMRs) in nonalcoholic fatty liver disease (NAFLD) is unclear. This study aimed to identify the role of DMR in NAFLD development and progression using the Korean Genome and Epidemiology Study (KoGES) cohort. We used laboratory evaluations and Illumina Methylation 450 k DNA methylation microarray data from KoGES. The correlation between fatty liver index (FLI) and genomic CpG sites was analyzed in 322 subjects. Longitudinal changes over 8 years were confirmed in 33 subjects. To identify CpG sites and genes related to FLI, we obtained enrichment terms for 6765 genes. DMRs were identified for both high (n = 128) and low (n = 194) groups on the basis of FLI 30 in 142 men and 180 women. To confirm longitudinal changes in 33 subjects, the ratio of follow-up and baseline investigation values was obtained. Correlations and group comparisons were performed for the 8 year change values. PITPNM3, RXFP3, and THRB were hypermethylated in the increased FLI groups, whereas SLC9A2 and FOXI3 were hypermethylated in the decreased FLI groups. DMRs describing NAFLD were determined, and functions related to inflammation were identified. Factors related to longitudinal changes are suggested, and blood circulation-related functions appear to be important in the management of NAFLD.
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Affiliation(s)
- Young Kyung Ko
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Internal Medicine, Korea University Guro Hospital, Seoul 08308, Korea;
| | - Hayeon Kim
- Department of Pathology, Korea University College of Medicine, Seoul 08308, Korea;
| | - Yoonseok Lee
- Department of Internal Medicine, Korea University College of Medicine, Seoul 08308, Korea;
| | - Young-Sun Lee
- Department of Internal Medicine, Korea University College of Medicine, Seoul 08308, Korea;
- Correspondence: (Y.-S.L.); (J.-A.G.); Tel.: +82-2-2626-3013 (Y.-S.L.); +82-2-2626-2362 (J.-A.G.)
| | - Jeong-An Gim
- Medical Science Research Center, College of Medicine, Korea University Guro Hospital, Seoul 08308, Korea
- Correspondence: (Y.-S.L.); (J.-A.G.); Tel.: +82-2-2626-3013 (Y.-S.L.); +82-2-2626-2362 (J.-A.G.)
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31
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Alfano R, Robinson O, Handakas E, Nawrot TS, Vineis P, Plusquin M. Perspectives and challenges of epigenetic determinants of childhood obesity: A systematic review. Obes Rev 2022; 23 Suppl 1:e13389. [PMID: 34816569 DOI: 10.1111/obr.13389] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 10/11/2021] [Indexed: 12/20/2022]
Abstract
The tremendous increase in childhood obesity prevalence over the last few decades cannot merely be explained by genetics and evolutionary changes in the genome, implying that gene-environment interactions, such as epigenetic modifications, likely play a major role. This systematic review aims to summarize the evidence of the association between epigenetics and childhood obesity. A literature search was performed via PubMed and Scopus engines using a combination of terms related to epigenetics and pediatric obesity. Articles studying the association between epigenetic mechanisms (including DNA methylation and hydroxymethylation, non-coding RNAs, and chromatin and histones modification) and obesity and/or overweight (or any related anthropometric parameters) in children (0-18 years) were included. The risk of bias was assessed with a modified Newcastle-Ottawa scale for non-randomized studies. One hundred twenty-one studies explored epigenetic changes related to childhood obesity. DNA methylation was the most widely investigated mechanism (N = 101 studies), followed by non-coding RNAs (N = 19 studies) with evidence suggestive of an association with childhood obesity for DNA methylation of specific genes and microRNAs (miRNAs). One study, focusing on histones modification, was identified. Heterogeneity of findings may have hindered more insights into the epigenetic changes related to childhood obesity. Gaps and challenges that future research should face are herein described.
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Affiliation(s)
- Rossella Alfano
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK.,Medical Research Council-Health Protection Agency Centre for Environment and Health, Imperial College London, London, UK.,Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
| | - Oliver Robinson
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK.,Medical Research Council-Health Protection Agency Centre for Environment and Health, Imperial College London, London, UK
| | - Evangelos Handakas
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK.,Medical Research Council-Health Protection Agency Centre for Environment and Health, Imperial College London, London, UK
| | - Tim S Nawrot
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
| | - Paolo Vineis
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK.,Medical Research Council-Health Protection Agency Centre for Environment and Health, Imperial College London, London, UK.,Unit of Molecular and Genetic Epidemiology, Human Genetic Foundation (HuGeF), Turin, Italy
| | - Michelle Plusquin
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
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Chen Y, Kassam I, Lau SH, Kooner JS, Wilson R, Peters A, Winkelmann J, Chambers JC, Chow VT, Khor CC, van Dam RM, Teo YY, Loh M, Sim X. Impact of BMI and waist circumference on epigenome-wide DNA methylation and identification of epigenetic biomarkers in blood: an EWAS in multi-ethnic Asian individuals. Clin Epigenetics 2021; 13:195. [PMID: 34670603 PMCID: PMC8527674 DOI: 10.1186/s13148-021-01162-x] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2021] [Accepted: 08/29/2021] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND The prevalence of obesity and its related chronic diseases have been increasing especially in Asian countries. Obesity-related genetic variants have been identified, but these explain little of the variation in BMI. Recent studies reported associations between DNA methylation and obesity, mostly in non-Asian populations. METHODS We performed an epigenome-wide association study (EWAS) on general adiposity (body mass index, BMI) and abdominal adiposity (waist circumference, WC) in 409 multi-ethnic Asian individuals and replicated BMI and waist-associated DNA methylation CpGs identified in other populations. The cross-lagged panel model and Mendelian randomization were used to assess the temporal relationship between methylation and BMI. The temporal relationship between the identified CpGs and inflammation and metabolic markers was also examined. RESULTS EWAS identified 116 DNA methylation CpGs independently associated with BMI and eight independently associated with WC at false discovery rate PFDR < 0.05 in 409 Asian samples. We replicated 110 BMI-associated CpGs previously reported in Europeans and identified six novel BMI-associated CpGs and two novel WC-associated CpGs. We observed high consistency in association direction of effect compared to studies in other populations. Causal relationship analyses indicated that BMI was more likely to be the cause of DNA methylation alteration, rather than the consequence. The causal analyses using BMI-associated methylation risk score also suggested that higher levels of the inflammation marker IL-6 were likely the consequence of methylation change. CONCLUSION Our study provides evidence of an association between obesity and DNA methylation in multi-ethnic Asians and suggests that obesity can drive methylation change. The results also suggested possible causal influence that obesity-related methylation changes might have on inflammation and lipoprotein levels.
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Affiliation(s)
- Yuqing Chen
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, #10-01, Tahir Foundation Building, Singapore, 117549, Singapore
| | - Irfahan Kassam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, #10-01, Tahir Foundation Building, Singapore, 117549, Singapore
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - Suk Hiang Lau
- Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Jaspal S Kooner
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Middlesex, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
- National Heart and Lung Institute, Imperial College London, London, UK
| | - Rory Wilson
- Research Unit Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, 85764, Neuherberg, Bavaria, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Cardiovascular Research, Partner Site Munich Heart Alliance, Munich, Germany
| | - Juliane Winkelmann
- Institute of Neurogenomics, Helmholtz Zentrum München, Munich, Germany
- Institute of Human Genetics, Technical University of Munich, Klinikum rechts der Isar, Munich, Germany
- Lehrstuhl Für Neurogenetik, Technische Universität München, Munich, Germany
- Munich Cluster for Systems Neurology, Munich, Germany
| | - John C Chambers
- Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Middlesex, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
- Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, Level 18, Lee Kong Chian Clinical Science Building, Singapore, 308232, Singapore
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
| | - Vincent T Chow
- National University Health System Infectious Diseases Translational Research Program, Department of Microbiology and Immunology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - Chiea Chuen Khor
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
| | - Rob M van Dam
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, #10-01, Tahir Foundation Building, Singapore, 117549, Singapore
- Department of Nutrition and Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yik-Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, #10-01, Tahir Foundation Building, Singapore, 117549, Singapore
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
| | - Marie Loh
- Lee Kong Chian School of Medicine, Nanyang Technological University, 11 Mandalay Road, Level 18, Lee Kong Chian Clinical Science Building, Singapore, 308232, Singapore.
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK.
- National Skin Centre, Singapore, Singapore.
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, 12 Science Drive 2, #10-01, Tahir Foundation Building, Singapore, 117549, Singapore.
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33
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Do WL, Gohar J, McCullough LE, Galaviz KI, Conneely KN, Narayan KMV. Examining the association between adiposity and DNA methylation: A systematic review and meta-analysis. Obes Rev 2021; 22:e13319. [PMID: 34278703 DOI: 10.1111/obr.13319] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2021] [Revised: 05/26/2021] [Accepted: 06/22/2021] [Indexed: 12/13/2022]
Abstract
Obesity is associated with widespread differential DNA methylation (DNAm) patterns, though there have been limited overlap in the obesity-associated cytosine-guanine nucleotide pair (CpG) sites that have been identified in the literature. We systematically searched four databases for studies published until January 2020. Eligible studies included cross-sectional, longitudinal, or intervention studies examining adiposity and genome-wide DNAm in non-pregnant adults aged 18-75 in all tissue types. Study design and results were extracted in the descriptive review. Blood-based DNAm results in body mass index (BMI) and waist circumference (WC) were meta-analyzed using weighted sum of Z-score meta-analysis. Of the 10,548 studies identified, 46 studies were included in the systematic review with 18 and nine studies included in the meta-analysis of BMI and WC, respectively. In the blood, 77 and four CpG sites were significant in three or more studies of BMI and WC, respectively. Using a genome-wide threshold for significance, 52 blood-based CpG sites were significantly associated with BMI. These sites have previously been associated with many obesity-related diseases including type 2 diabetes, cardiovascular disease, Crohn's disease, and depression. Our study shows that DNAm at 52 CpG sites represent potential mediators of obesity-associated chronic diseases and may be novel intervention or therapeutic targets to protect against obesity-associated chronic diseases.
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Affiliation(s)
- Whitney L Do
- Nutrition and Health Sciences Program, Laney Graduate School, Emory University, Atlanta, Georgia, USA
| | - Jazib Gohar
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Lauren E McCullough
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Karla I Galaviz
- Department of Applied Health Science, School of Public Health, Indiana University Bloomington, Bloomington, Indiana, USA
| | - Karen N Conneely
- Department of Human Genetics, School of Medicine, Emory University, Atlanta, Georgia, USA
| | - K M Venkat Narayan
- Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
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Fragoso-Bargas N, Opsahl JO, Kiryushchenko N, Böttcher Y, Lee-Ødegård S, Qvigstad E, Richardsen KR, Waage CW, Sletner L, Jenum AK, Prasad RB, Groop LC, Moen GH, Birkeland KI, Sommer C. Cohort profile: Epigenetics in Pregnancy (EPIPREG) - population-based sample of European and South Asian pregnant women with epigenome-wide DNA methylation (850k) in peripheral blood leukocytes. PLoS One 2021; 16:e0256158. [PMID: 34388220 PMCID: PMC8362992 DOI: 10.1371/journal.pone.0256158] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 08/01/2021] [Indexed: 11/26/2022] Open
Abstract
Pregnancy is a valuable model to study the association between DNA methylation and several cardiometabolic traits, due to its direct potential to influence mother's and child's health. Epigenetics in Pregnancy (EPIPREG) is a population-based sample with the aim to study associations between DNA-methylation in pregnancy and cardiometabolic traits in South Asian and European pregnant women and their offspring. This cohort profile paper aims to present our sample with genetic and epigenetic data and invite researchers with similar cohorts to collaborative projects, such as replication of ours or their results and meta-analysis. In EPIPREG we have quantified epigenome-wide DNA methylation in maternal peripheral blood leukocytes in gestational week 28±1 in Europeans (n = 312) and South Asians (n = 168) that participated in the population-based cohort STORK Groruddalen, in Norway. DNA methylation was measured with Infinium MethylationEPIC BeadChip (850k sites), with technical validation of four CpG sites using bisulphite pyrosequencing in a subset (n = 30). The sample is well characterized with few missing data on e.g. genotype, universal screening for gestational diabetes, objectively measured physical activity, bioelectrical impedance, anthropometrics, biochemical measurements, and a biobank with maternal serum and plasma, urine, placenta tissue. In the offspring, we have repeated ultrasounds during pregnancy, cord blood, and anthropometrics up to 4 years of age. We have quantified DNA methylation in peripheral blood leukocytes in nearly all eligible women from the STORK Groruddalen study, to minimize the risk of selection bias. Genetic principal components distinctly separated Europeans and South Asian women, which fully corresponded with the self-reported ethnicity. Technical validation of 4 CpG sites from the methylation bead chip showed good agreement with bisulfite pyrosequencing. We plan to study associations between DNA methylation and cardiometabolic traits and outcomes.
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Affiliation(s)
- Nicolas Fragoso-Bargas
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Julia O. Opsahl
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Nadezhda Kiryushchenko
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Department of Bioscience, University of Oslo, Oslo, Norway
| | - Yvonne Böttcher
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Clinical Molecular Biology, Akershus University Hospital, Lørenskog, Norway
- Helmholtz-Institute for Metabolic, Adiposity and Vascular Research, Leipzig, Germany
| | | | - Elisabeth Qvigstad
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Kåre Rønn Richardsen
- Faculty of Health Sciences, Department of Physiotherapy, Oslo Metropolitan University, Oslo, Norway
| | - Christin W. Waage
- Faculty of Health Sciences, Department of Physiotherapy, Oslo Metropolitan University, Oslo, Norway
- Department of General Practice, General Practice Research Unit (AFE), Institute of Health and Society, University of Oslo, Oslo, Norway
| | - Line Sletner
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Pediatric and Adolescents Medicine, Akershus University Hospital, Lørenskog, Norway
| | - Anne Karen Jenum
- Department of General Practice, General Practice Research Unit (AFE), Institute of Health and Society, University of Oslo, Oslo, Norway
| | | | | | - Gunn-Helen Moen
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- The University of Queensland Diamantina Institute, The University of Queensland, Woolloongabba, QLD, Australia
- Department of Public Health and Nursing, K.G. Jebsen Center for Genetic Epidemiology, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
- Population Health Science, Bristol Medical School, University of Bristol, Bristol, United Kingdom
| | - Kåre I. Birkeland
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Christine Sommer
- Department of Endocrinology, Morbid Obesity and Preventive Medicine, Oslo University Hospital, Oslo, Norway
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35
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Oblak L, van der Zaag J, Higgins-Chen AT, Levine ME, Boks MP. A systematic review of biological, social and environmental factors associated with epigenetic clock acceleration. Ageing Res Rev 2021; 69:101348. [PMID: 33930583 DOI: 10.1016/j.arr.2021.101348] [Citation(s) in RCA: 179] [Impact Index Per Article: 59.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 04/01/2021] [Accepted: 04/21/2021] [Indexed: 02/06/2023]
Abstract
Aging involves a diverse set of biological changes accumulating over time that leads to increased risk of morbidity and mortality. Epigenetic clocks are now widely used to quantify biological aging, in order to investigate determinants that modify the rate of aging and to predict age-related outcomes. Numerous biological, social and environmental factors have been investigated for their relationship to epigenetic clock acceleration and deceleration. The aim of this review was to synthesize general trends concerning the associations between human epigenetic clocks and these investigated factors. We conducted a systematic review of all available literature and included 156 publications across 4 resource databases. We compiled a list of all presently existing blood-based epigenetic clocks. Subsequently, we created an extensive dataset of over 1300 study findings in which epigenetic clocks were utilized in blood tissue of human subjects to assess the relationship between these clocks and numeral environmental exposures and human traits. Statistical analysis was possible on 57 such relationships, measured across 4 different epigenetic clocks (Hannum, Horvath, Levine and GrimAge). We found that the Horvath, Hannum, Levine and GrimAge epigenetic clocks tend to agree in direction of effects, but vary in size. Body mass index, HIV infection, and male sex were significantly associated with acceleration of one or more epigenetic clocks. Acceleration of epigenetic clocks was also significantly related to mortality, cardiovascular disease, cancer and diabetes. Our findings provide a graphical and numerical synopsis of the past decade of epigenetic age estimation research and indicate areas where further attention could be focused in the coming years.
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36
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Qin X, Karlsson IK, Wang Y, Li X, Pedersen N, Reynolds CA, Hägg S. The epigenetic etiology of cardiovascular disease in a longitudinal Swedish twin study. Clin Epigenetics 2021; 13:129. [PMID: 34167563 PMCID: PMC8223329 DOI: 10.1186/s13148-021-01113-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 06/14/2021] [Indexed: 02/02/2023] Open
Abstract
BACKGROUND Studies on DNA methylation have the potential to discover mechanisms of cardiovascular disease (CVD) risk. However, the role of DNA methylation in CVD etiology remains unclear. RESULTS We performed an epigenome-wide association study (EWAS) on CVD in a longitudinal sample of Swedish twins (535 individuals). We selected CpGs reaching the Bonferroni-corrected significance level (2 [Formula: see text] 10-7) or the top-ranked 20 CpGs with the lowest P values if they did not reach this significance level in EWAS analysis associated with non-stroke CVD, overall stroke, and ischemic stroke, respectively. We further applied a bivariate autoregressive latent trajectory model with structured residuals (ALT-SR) to evaluate the cross-lagged effect between DNA methylation of these CpGs and cardiometabolic traits (blood lipids, blood pressure, and body mass index). Furthermore, mediation analysis was performed to evaluate whether the cross-lagged effects had causal impacts on CVD. In the EWAS models, none of the CpGs we selected reached the Bonferroni-corrected significance level. The ALT-SR model showed that DNA methylation levels were more likely to predict the subsequent level of cardiometabolic traits rather than the other way around (numbers of significant cross-lagged paths of methylation → trait/trait → methylation were 84/4, 45/6, 66/1 for the identified three CpG sets, respectively). Finally, we demonstrated significant indirect effects from DNA methylation on CVD mediated by cardiometabolic traits. CONCLUSIONS We present evidence for a directional association from DNA methylation on cardiometabolic traits and CVD, rather than the opposite, highlighting the role of epigenetics in CVD development.
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Affiliation(s)
- Xueying Qin
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 17177, Stockholm, Sweden.
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, 38# Xueyuan Road, Beijing, 100191, China.
| | - Ida K Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 17177, Stockholm, Sweden
- Institute of Gerontology and Aging Research Network - Jönköping (ARN-J), School of Health and Welfare, Jönköping University, Jönköping, Sweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 17177, Stockholm, Sweden
| | - Xia Li
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 17177, Stockholm, Sweden
| | - Nancy Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 17177, Stockholm, Sweden
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | | | - Sara Hägg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels väg 12A, 17177, Stockholm, Sweden
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Pescador-Tapia A, Silva-Martínez GA, Fragoso-Bargas N, Rodríguez-Ríos D, Esteller M, Moran S, Zaina S, Lund G. Distinct Associations of BMI and Fatty Acids With DNA Methylation in Fasting and Postprandial States in Men. Front Genet 2021; 12:665769. [PMID: 34025721 PMCID: PMC8138173 DOI: 10.3389/fgene.2021.665769] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 03/23/2021] [Indexed: 12/15/2022] Open
Abstract
We have previously shown that blood global DNA methylation (DNAm) differs between postprandial state (PS) and fasting state (FS) and is associated with BMI and polyunsaturated fatty acid (PUFA) (negatively and positively, respectively) in 12 metabolically healthy adult Mexican men (AMM cohort) equally distributed among conventional BMI classes. Here, we detailed those associations at CpG dinucleotide level by exploiting the Infinium methylation EPIC array (Illumina). We sought differentially methylated CpG (dmCpG) that were (1) associated with BMI (BMI-dmCpG) and/or fatty acids (FA) (FA-dmCpG) in FS or PS and (2) different across FS and PS within a BMI class. BMI-dmCpG and FA-dmCpG were more numerous in FS compared to PS and largely prandial state-specific. For saturated and monounsaturated FA, dmCpG overlap was higher across than within the respective saturation group. Several BMI- and FA-dmCpG mapped to genes involved in metabolic disease and in some cases matched published experimental data sets. Notably, SETDB1 and MTHFS promoter dmCpG could explain the previously observed associations between global DNAm, PUFA content, and BMI in FS. Surprisingly, overlap between BMI-dmCpG and FA-dmCpG was limited and the respective dmCpG were differentially distributed across functional genomic elements. BMI-dmCpG showed the highest overlap with dmCpG of the saturated FA palmitate, monounsaturated C20:1 and PUFA C20:2. Of these, selected promoter BMI-dmCpG showed opposite associations with palmitate compared to C20:1 and C20:2. As for the comparison between FS and PS within BMI classes, dmCpG were strikingly more abundant and variably methylated in overweight relative to normoweight or obese subjects (∼70–139-fold, respectively). Overweight-associated dmCpG-hosting genes were significantly enriched in targets for E47, SREBP1, and RREB1 transcription factors, which are known players in obesity and lipid homeostasis, but none overlapped with BMI-dmCpG. We show for the first time that the association of BMI and FA with methylation of disease-related genes is distinct in FS and PS and that limited overlap exists between BMI- and FA-dmCpG within and across prandial states. Our study also identifies a transcriptional regulation circuitry in overweight that might contribute to adaptation to that condition or to transition to obesity. Further work is necessary to define the pathophysiological implications of these findings.
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Affiliation(s)
| | - Guillermo A Silva-Martínez
- Department of Genetic Engineering, CINVESTAV Irapuato Unit, Irapuato, Mexico.,Celaya Technological Institute, Celaya, Mexico
| | | | | | - Manel Esteller
- Josep Carreras Leukemia Research Institute (IJC), Barcelona, Spain.,Centro de Investigación Biomédica en Red Cancer (CIBERONC), Madrid, Spain.,Institució Catalana de Recerca i Estudis Avançats (ICREA), Barcelona, Spain.,Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona (UB), Barcelona, Spain
| | | | - Silvio Zaina
- Department of Medical Sciences, Division of Health Sciences, Leon Campus, University of Guanajuato, Leon, Mexico
| | - Gertrud Lund
- Department of Genetic Engineering, CINVESTAV Irapuato Unit, Irapuato, Mexico
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Fischer MA, Vondriska TM. Clinical epigenomics for cardiovascular disease: Diagnostics and therapies. J Mol Cell Cardiol 2021; 154:97-105. [PMID: 33561434 PMCID: PMC8330446 DOI: 10.1016/j.yjmcc.2021.01.011] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Revised: 01/05/2021] [Accepted: 01/10/2021] [Indexed: 12/28/2022]
Abstract
The study of epigenomics has advanced in recent years to span the regulation of a single genetic locus to the structure and orientation of entire chromosomes within the nucleus. In this review, we focus on the challenges and opportunities of clinical epigenomics in cardiovascular disease. As an integrator of genetic and environmental inputs, and because of advances in measurement techniques that are highly reproducible and provide sequence information, the epigenome is a rich source of potential biosignatures of cardiovascular health and disease. Most of the studies to date have focused on the latter, and herein we discuss observations on epigenomic changes in human cardiovascular disease, examining the role of protein modifiers of chromatin, noncoding RNAs and DNA modification. We provide an overview of cardiovascular epigenomics, discussing the challenges of data sovereignty, data analysis, doctor-patient ethics and innovations necessary to implement precision health.
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Affiliation(s)
- Matthew A Fischer
- Department of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine at UCLA, USA.
| | - Thomas M Vondriska
- Department of Anesthesiology & Perioperative Medicine, David Geffen School of Medicine at UCLA, USA
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39
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Lv BM, Quan Y, Zhang HY. Causal Inference in Microbiome Medicine: Principles and Applications. Trends Microbiol 2021; 29:736-746. [PMID: 33895062 DOI: 10.1016/j.tim.2021.03.015] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2020] [Revised: 03/25/2021] [Accepted: 03/26/2021] [Indexed: 12/12/2022]
Abstract
Microorganisms that colonize the mammalian skin and cavity play critical roles in various physiological functions of the host. Numerous studies have revealed strong associations between the microbiota and multiple diseases. However, association does not mean causation. To clarify the mechanisms underlying microbiota-mediated diseases, research is moving from associative analyses to causation studies. In this article, we first introduce the principles of the computational methods for causal inference, and then discuss the applications of these methods in microbiome medicine. Furthermore, we examine the reliability of theoretically inferred causality by the interventionist framework. Finally, we show the potential of confirmed causality in microbiota-targeted therapy, especially in personalized dietary intervention. We conclude that a comprehensive understanding of the causal relationships between diets, microbiota, host targets, and diseases is critical to future microbiome medicine.
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Affiliation(s)
- Bo-Min Lv
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, P. R. China
| | - Yuan Quan
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, P. R. China
| | - Hong-Yu Zhang
- Hubei Key Laboratory of Agricultural Bioinformatics, College of Informatics, Huazhong Agricultural University, Wuhan 430070, P. R. China.
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40
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Vehmeijer FOL, Küpers LK, Sharp GC, Salas LA, Lent S, Jima DD, Tindula G, Reese S, Qi C, Gruzieva O, Page C, Rezwan FI, Melton PE, Nohr E, Escaramís G, Rzehak P, Heiskala A, Gong T, Tuominen ST, Gao L, Ross JP, Starling AP, Holloway JW, Yousefi P, Aasvang GM, Beilin LJ, Bergström A, Binder E, Chatzi L, Corpeleijn E, Czamara D, Eskenazi B, Ewart S, Ferre N, Grote V, Gruszfeld D, Håberg SE, Hoyo C, Huen K, Karlsson R, Kull I, Langhendries JP, Lepeule J, Magnus MC, Maguire RL, Molloy PL, Monnereau C, Mori TA, Oken E, Räikkönen K, Rifas-Shiman S, Ruiz-Arenas C, Sebert S, Ullemar V, Verduci E, Vonk JM, Xu CJ, Yang IV, Zhang H, Zhang W, Karmaus W, Dabelea D, Muhlhausler BS, Breton CV, Lahti J, Almqvist C, Jarvelin MR, Koletzko B, Vrijheid M, Sørensen TIA, Huang RC, Arshad SH, Nystad W, Melén E, Koppelman GH, London SJ, Holland N, Bustamante M, Murphy SK, Hivert MF, Baccarelli A, Relton CL, Snieder H, Jaddoe VWV, Felix JF. DNA methylation and body mass index from birth to adolescence: meta-analyses of epigenome-wide association studies. Genome Med 2020; 12:105. [PMID: 33239103 PMCID: PMC7687793 DOI: 10.1186/s13073-020-00810-w] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2020] [Accepted: 11/12/2020] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND DNA methylation has been shown to be associated with adiposity in adulthood. However, whether similar DNA methylation patterns are associated with childhood and adolescent body mass index (BMI) is largely unknown. More insight into this relationship at younger ages may have implications for future prevention of obesity and its related traits. METHODS We examined whether DNA methylation in cord blood and whole blood in childhood and adolescence was associated with BMI in the age range from 2 to 18 years using both cross-sectional and longitudinal models. We performed meta-analyses of epigenome-wide association studies including up to 4133 children from 23 studies. We examined the overlap of findings reported in previous studies in children and adults with those in our analyses and calculated enrichment. RESULTS DNA methylation at three CpGs (cg05937453, cg25212453, and cg10040131), each in a different age range, was associated with BMI at Bonferroni significance, P < 1.06 × 10-7, with a 0.96 standard deviation score (SDS) (standard error (SE) 0.17), 0.32 SDS (SE 0.06), and 0.32 BMI SDS (SE 0.06) higher BMI per 10% increase in methylation, respectively. DNA methylation at nine additional CpGs in the cross-sectional childhood model was associated with BMI at false discovery rate significance. The strength of the associations of DNA methylation at the 187 CpGs previously identified to be associated with adult BMI, increased with advancing age across childhood and adolescence in our analyses. In addition, correlation coefficients between effect estimates for those CpGs in adults and in children and adolescents also increased. Among the top findings for each age range, we observed increasing enrichment for the CpGs that were previously identified in adults (birth Penrichment = 1; childhood Penrichment = 2.00 × 10-4; adolescence Penrichment = 2.10 × 10-7). CONCLUSIONS There were only minimal associations of DNA methylation with childhood and adolescent BMI. With the advancing age of the participants across childhood and adolescence, we observed increasing overlap with altered DNA methylation loci reported in association with adult BMI. These findings may be compatible with the hypothesis that DNA methylation differences are mostly a consequence rather than a cause of obesity.
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Affiliation(s)
- Florianne O L Vehmeijer
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Room Na-2918, Erasmus MC, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Leanne K Küpers
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
| | - Gemma C Sharp
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Lucas A Salas
- Geisel School of Medicine at Dartmouth, Lebanon, NH, USA
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Samantha Lent
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Dereje D Jima
- Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, USA
| | - Gwen Tindula
- Children's Environmental Health Laboratory, Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Sarah Reese
- Department of Health and Human Services, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Cancan Qi
- University of Groningen, University Medical Center Groningen, Department of Pediatric Pulmonology and Pediatric Allergy, Beatrix Children's Hospital, Groningen, The Netherlands
- University Medical Center Groningen GRIAC Research Institute, University of Groningen, Groningen, the Netherlands
| | - Olena Gruzieva
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Centre for Occupational and Environmental Medicine, Region Stockholm, Stockholm, Sweden
| | - Christian Page
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
- Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, Norway
| | - Faisal I Rezwan
- School of Water, Energy and Environment, Cranfield University, Cranfield, Bedfordshire, UK
- Human Development and Health, Faculty of Medicine, Southampton General Hospital, University of Southampton, Southampton, UK
| | - Philip E Melton
- School of Pharmacy and Biomedical Sciences, Curtin University, Bentley, Western Australia, Australia
- School of Biomedical Sciences, The University of Western Australia, Crawley, Western Austalia, Australia
| | - Ellen Nohr
- Centre for Women's, Family and Child Health, University of South-Eastern Norway, Kongsberg, Norway
- Institute of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Geòrgia Escaramís
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
- Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain
- Research group on Statistics, Econometrics and Health (GRECS), University of Girona, Girona, Spain
| | - Peter Rzehak
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Anni Heiskala
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Tong Gong
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Samuli T Tuominen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Lu Gao
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jason P Ross
- CSIRO Health and Biosecurity, North Ryde, New South Wales, Australia
| | - Anne P Starling
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - John W Holloway
- Human Development and Health, Faculty of Medicine, Southampton General Hospital, University of Southampton, Southampton, UK
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
| | - Paul Yousefi
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Gunn Marit Aasvang
- Department of Air Pollution and Noise, Norwegian Institute of Public Health, Oslo, Norway
| | | | - Anna Bergström
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Centre for Occupational and Environmental Medicine, Region Stockholm, Stockholm, Sweden
| | - Elisabeth Binder
- Department of Translational Research in Psychiatry, Max-Planck-Institute of Psychiatry, Munich, Germany
- Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA
| | - Leda Chatzi
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Eva Corpeleijn
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
| | - Darina Czamara
- Department of Translational Research in Psychiatry, Max-Planck-Institute of Psychiatry, Munich, Germany
| | - Brenda Eskenazi
- Center for Environmental Research and Children's Health, School of Public Health, University of California, Berkeley, CA, USA
| | - Susan Ewart
- College of Veterinary Medicine, Michigan State University, East Lansing, MI, USA
| | - Natalia Ferre
- Pediatrics, Nutrition and Development Research Unit, Universitat Rovira i Virgili, IISPV, Reus, Spain
| | - Veit Grote
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Dariusz Gruszfeld
- Neonatal Department, Children's Memorial Health Institute, Warsaw, Poland
| | - Siri E Håberg
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Cathrine Hoyo
- Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, USA
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
| | - Karen Huen
- Children's Environmental Health Laboratory, Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Robert Karlsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Inger Kull
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
- Sachs' Children and Youth Hospital, Södersjukhuset, Stockholm, Sweden
| | | | - Johanna Lepeule
- Université Grenoble Alpes, Inserm, CNRS, Team of Environmental Epidemiology Applied to Reproduction and Respiratory Health, IAB, Grenoble, France
| | - Maria C Magnus
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Rachel L Maguire
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, USA
- Department of Obstetrics and Gynecology, Duke University Medical Center, Raleigh, NC, USA
| | - Peter L Molloy
- CSIRO Health and Biosecurity, North Ryde, New South Wales, Australia
| | - Claire Monnereau
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Room Na-2918, Erasmus MC, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Trevor A Mori
- Medical School, University of Western Australia, Perth, Australia
| | - Emily Oken
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Katri Räikkönen
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Sheryl Rifas-Shiman
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Carlos Ruiz-Arenas
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Sylvain Sebert
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
| | - Vilhelmina Ullemar
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Elvira Verduci
- Department of Pediatrics, San Paolo Hospital, University of Milan, Milan, Italy
| | - Judith M Vonk
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
- University Medical Center Groningen GRIAC Research Institute, University of Groningen, Groningen, the Netherlands
| | - Cheng-Jian Xu
- University of Groningen, University Medical Center Groningen, Department of Pediatric Pulmonology and Pediatric Allergy, Beatrix Children's Hospital, Groningen, The Netherlands
- University Medical Center Groningen GRIAC Research Institute, University of Groningen, Groningen, the Netherlands
- Department of Gastroenterology, Hepatology and Endocrinology, CiiM, Centre for Individualised Infection Medicine, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
- TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Ivana V Yang
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado School of Medicine, Aurora, CO, USA
- Center for Genes, Environment and Health, National Jewish Health, Denver, CO, USA
| | - Hongmei Zhang
- Division of Epidemiology, Biostatistics, and Environmental Health, University of Memphis, Memphis, TN, USA
| | - Weiming Zhang
- Department of Biostatistics and Informatics, Colorado School of Public Health, Aurora, CO, USA
| | - Wilfried Karmaus
- Division of Epidemiology, Biostatistics, and Environmental Health, University of Memphis, Memphis, TN, USA
| | - Dana Dabelea
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
- Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
- Department of Pediatrics, School of Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | | | - Carrie V Breton
- Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jari Lahti
- Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland
- Turku Institute for Advanced Studies, University of Turku, Turku, Finland
| | - Catarina Almqvist
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Pediatric Allergy and Pulmonology Unit at Astrid Lindgren Children's Hospital, Karolinska University Hospital, Stockholm, Sweden
| | - Marjo-Riitta Jarvelin
- Center for Life Course Health Research, University of Oulu, Oulu, Finland
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
- Unit of Primary Health Care, Oulu University Hospital, OYS, Oulu, Finland
- Department of Life Sciences, College of Health and Life Sciences, Brunel University London, London, UK
| | - Berthold Koletzko
- Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany
| | - Martine Vrijheid
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Thorkild I A Sørensen
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
- Department of Public Health, Section of Epidemiology, and The Novo Nordisk Foundation Center for Basic Metabolic Research, Section on Metabolic Genetics, Faculty of Medical and Health Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Rae-Chi Huang
- Telethon Kids Institute, University of Western Australia, Perth, Australia
| | - Syed Hasan Arshad
- Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK
- David Hide Asthma and Allergy Research Centre, Isle of Wight, UK
| | - Wenche Nystad
- Department of Chronic Diseases and Ageing, Norwegian Institute of Public Health, Oslo, Norway
| | - Erik Melén
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
- Sachs' Children and Youth Hospital, Södersjukhuset, Stockholm, Sweden
| | - Gerard H Koppelman
- University of Groningen, University Medical Center Groningen, Department of Pediatric Pulmonology and Pediatric Allergy, Beatrix Children's Hospital, Groningen, The Netherlands
- University Medical Center Groningen GRIAC Research Institute, University of Groningen, Groningen, the Netherlands
| | - Stephanie J London
- Department of Health and Human Services, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA
| | - Nina Holland
- Children's Environmental Health Laboratory, Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA
| | - Mariona Bustamante
- ISGlobal, Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Susan K Murphy
- Department of Obstetrics and Gynecology, Duke University Medical Center, Raleigh, NC, USA
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Medical School, Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Universite de Sherbrooke, Sherbrooke, QC, Canada
| | - Andrea Baccarelli
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Caroline L Relton
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK
| | - Harold Snieder
- University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands
| | - Vincent W V Jaddoe
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Room Na-2918, Erasmus MC, PO Box 2040, 3000 CA, Rotterdam, the Netherlands
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands
| | - Janine F Felix
- The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Room Na-2918, Erasmus MC, PO Box 2040, 3000 CA, Rotterdam, the Netherlands.
- Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
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41
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Xiao Y, Liu D, Cline MA, Gilbert ER. Chronic stress, epigenetics, and adipose tissue metabolism in the obese state. Nutr Metab (Lond) 2020; 17:88. [PMID: 33088334 PMCID: PMC7574417 DOI: 10.1186/s12986-020-00513-4] [Citation(s) in RCA: 33] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Accepted: 10/08/2020] [Indexed: 12/11/2022] Open
Abstract
In obesity, endocrine and metabolic perturbations, including those induced by chronic activation of the hypothalamus-pituitary-adrenal axis, are associated with the accumulation of adipose tissue and inflammation. Such changes are attributable to a combination of genetic and epigenetic factors that are influenced by the environment and exacerbated by chronic activation of the hypothalamus-pituitary-adrenal axis. Stress exposure at different life stages can alter adipose tissue metabolism directly through epigenetic modification or indirectly through the manipulation of hypothalamic appetite regulation, and thereby contribute to endocrine changes that further disrupt whole-body energy balance. This review synthesizes current knowledge, with an emphasis on human clinical trials, to describe metabolic changes in adipose tissue and associated endocrine, genetic and epigenetic changes in the obese state. In particular, we discuss epigenetic changes induced by stress exposure and their contribution to appetite and adipocyte dysfunction, which collectively promote the pathogenesis of obesity. Such knowledge is critical for providing future directions of metabolism research and targets for treating metabolic disorders.
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Affiliation(s)
- Yang Xiao
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA USA
| | - Dongmin Liu
- Department of Human Nutrition, Foods, and Exercise, Virginia Polytechnic Institute and State University, Blacksburg, VA USA
| | - Mark A Cline
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA USA.,School of Neuroscience, Virginia Polytechnic Institute and State University, Blacksburg, VA USA
| | - Elizabeth R Gilbert
- Department of Animal and Poultry Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA USA.,School of Neuroscience, Virginia Polytechnic Institute and State University, Blacksburg, VA USA
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Afarideh M, Thaler R, Khani F, Tang H, Jordan KL, Conley SM, Saadiq IM, Obeidat Y, Pawar AS, Eirin A, Zhu XY, Lerman A, van Wijnen AJ, Lerman LO. Global epigenetic alterations of mesenchymal stem cells in obesity: the role of vitamin C reprogramming. Epigenetics 2020; 16:705-717. [PMID: 32893712 DOI: 10.1080/15592294.2020.1819663] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
Obesity promotes dysfunction and impairs the reparative capacity of mesenchymal stem/stromal cells (MSCs), and alters their transcription, protein content, and paracrine function. Whether these adverse effects are mediated by chromatin-modifying epigenetic changes remains unclear. We tested the hypothesis that obesity imposes global DNA hydroxymethylation and histone tri-methylation alterations in obese swine abdominal adipose tissue-derived MSCs compared to lean pig MSCs. MSCs from female lean (n = 7) and high-fat-diet fed obese (n = 7) domestic pigs were assessed using global epigenetic assays, before and after in-vitro co-incubation with the epigenetic modulator vitamin-C (VIT-C) (50 μg/ml). Dot blotting was used to measure across the whole genome 5-hydroxyemthycytosine (5hmC) residues, and Western blotting to quantify in genomic histone-3 protein tri-methylated lysine-4 (H3K4me3), lysine-9 (H3K9me3), and lysine-27 (H3K27me3) residues. MSC migration and proliferation were studied in-vitro. Obese MSCs displayed reduced global 5hmC and H3K4m3 levels, but comparable H3K9me3 and H3K27me3, compared to lean MSCs. Global 5hmC, H3K4me3, and HK9me3 marks correlated with MSC migration and reduced proliferation, as well as clinical and metabolic characteristics of obesity. Co-incubation of obese MSCs with VIT-C enhanced 5hmC marks, and reduced their global levels of H3K9me3 and H3K27me3. Contrarily, VIT-C did not affect 5hmC, and decreased H3K4me3 in lean MSCs. Obesity induces global genomic epigenetic alterations in swine MSCs, involving primarily genomic transcriptional repression, which are associated with MSC function and clinical features of obesity. Some of these alterations might be reversible using the epigenetic modulator VIT-C, suggesting epigenetic modifications as therapeutic targets in obesity.
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Affiliation(s)
- Mohsen Afarideh
- Division of Nephrology and Hypertension, Mayo Clinic Rochester, MN, USA
| | - Roman Thaler
- Department of Orthopedic Surgery, and Department of Biochemistry, and Molecular Biology, Mayo Clinic, Rochester, MN, USA
| | - Farzaneh Khani
- Department of Orthopedic Surgery, and Department of Biochemistry, and Molecular Biology, Mayo Clinic, Rochester, MN, USA
| | - Hui Tang
- Division of Nephrology and Hypertension, Mayo Clinic Rochester, MN, USA
| | - Kyra L Jordan
- Division of Nephrology and Hypertension, Mayo Clinic Rochester, MN, USA
| | - Sabena M Conley
- Division of Nephrology and Hypertension, Mayo Clinic Rochester, MN, USA
| | - Ishran M Saadiq
- Division of Nephrology and Hypertension, Mayo Clinic Rochester, MN, USA
| | - Yasin Obeidat
- Division of Nephrology and Hypertension, Mayo Clinic Rochester, MN, USA
| | - Aditya S Pawar
- Division of Nephrology and Hypertension, Mayo Clinic Rochester, MN, USA
| | - Alfonso Eirin
- Division of Nephrology and Hypertension, Mayo Clinic Rochester, MN, USA
| | - Xiang-Yang Zhu
- Division of Nephrology and Hypertension, Mayo Clinic Rochester, MN, USA
| | - Amir Lerman
- Department of Cardiovascular Diseases, Mayo Clinic, Rochester, MN, USA
| | - Andre J van Wijnen
- Department of Orthopedic Surgery, and Department of Biochemistry, and Molecular Biology, Mayo Clinic, Rochester, MN, USA
| | - Lilach O Lerman
- Division of Nephrology and Hypertension, Mayo Clinic Rochester, MN, USA
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Ma Z, Zhang J, Kang X, Xu C, Sun C, Tao L, Zheng D, Han Y, Li Q, Guo X, Yang X. Hyperuricemia precedes non-alcoholic fatty liver disease with abdominal obesity moderating this unidirectional relationship: Three longitudinal analyses. Atherosclerosis 2020; 311:44-51. [PMID: 32937242 DOI: 10.1016/j.atherosclerosis.2020.08.006] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2020] [Revised: 07/29/2020] [Accepted: 08/21/2020] [Indexed: 12/13/2022]
Abstract
BACKGROUND AND AIMS The temporal relationship between hyperuricemia and non-alcoholic fatty liver disease (NAFLD) is debatable. This study aimed to explore whether there exists a bidirectional or temporal relationship between them. METHODS A total of 11,585 participants were recruited from the Beijing Health Management Cohort during the period 2012-2016. We evaluated whether hyperuricemia was associated with NAFLD development (part I) and whether NAFLD was associated with hyperuricemia incidence (part II) using a logistic regression model. Further, the cross-lagged panel analysis model was used to simultaneously examine the bidirectional relationship between hepatic steatosis and serum uric acid (SUA) (part III). Subgroup and interaction analyses were also performed to assess whether other variables moderated those relationships. RESULTS In part I, multiple logistic regression indicated that baseline hyperuricemia was associated with the development of NAFLD (OR = 1.5970, p < 0.0001). In part II, multiple logistic regression showed that baseline NAFLD was not correlated with hyperuricemia incidence (OR = 0.8600, p = 0.1976). In part III, cross-lagged panel analyses indicated that the standard regression coefficient of baseline SUA to follow-up hepatic steatosis (0.1516) was significantly greater than the coefficient from the baseline hepatic steatosis to follow-up SUA (-0.0044) with p < 0.0001 for the difference. This indicated a unidirectional relationship from baseline SUA to follow-up hepatic steatosis, suggesting hyperuricemia may precede NAFLD; and this relationship was not affected by age, sex, dyslipidemia, metabolism syndrome, diabetes but was moderated by abdominal obesity. CONCLUSIONS This study demonstrated a unidirectional relationship from hyperuricemia to NAFLD incidence, and suggested that lowering SUA levels in hyperuricemia patients may prevent subsequent NAFLD.
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Affiliation(s)
- Zhimin Ma
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Jingbo Zhang
- Department of Information, Beijing Physical Examination Center, Beijing, China
| | - Xiaoping Kang
- Rehabilitation Center, Beijing Xiaotangshan Hospital, Beijing, China
| | - Chaonan Xu
- Medical Engineering Department, Peking University Third Hospital, Beijing, China
| | - Ce Sun
- Department of Clinical Epidemiology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Lixin Tao
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Deqiang Zheng
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Yumei Han
- Department of Information, Beijing Physical Examination Center, Beijing, China
| | - Qiang Li
- Department of Information, Beijing Physical Examination Center, Beijing, China
| | - Xiuhua Guo
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Xinghua Yang
- School of Public Health, Capital Medical University, Beijing, China; Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China.
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44
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Williams R. Circulation Research
“In This Issue” Anthology. Circ Res 2020. [DOI: 10.1161/res.0000000000000406] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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45
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Deng J, Guo M, Li G, Xiao J. Gene therapy for cardiovascular diseases in China: basic research. Gene Ther 2020; 27:360-369. [PMID: 32341485 DOI: 10.1038/s41434-020-0148-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2020] [Revised: 03/26/2020] [Accepted: 04/02/2020] [Indexed: 12/14/2022]
Abstract
Cardiovascular disease has become a major disease affecting health in the whole world. Gene therapy, delivering foreign normal genes into target cells to repair damages caused by defects and abnormal genes, shows broad prospects in treating different kinds of cardiovascular diseases. China has achieved great progress of basic gene therapy researches and pathogenesis of cardiovascular diseases in recent years. This review will summarize the latest research about gene therapy of proteins, epigenetics, including noncoding RNAs and genome-editing technology in myocardial infarction, cardiac ischemia-reperfusion injury, atherosclerosis, muscle atrophy, and so on in China. We wish to highlight some important findings about the essential roles of basic gene therapy in this field, which might be helpful for searching potential therapeutic targets for cardiovascular disease.
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Affiliation(s)
- Jiali Deng
- Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, School of Life Science, Shanghai University, Shanghai, 200444, China
| | - Mengying Guo
- Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, School of Life Science, Shanghai University, Shanghai, 200444, China.,School of Medicine, Shanghai University, Shanghai, 200444, China
| | - Guoping Li
- Cardiovascular Division of the Massachusetts, General Hospital and Harvard Medical School, Boston, MA, 02215, USA
| | - Junjie Xiao
- Cardiac Regeneration and Ageing Lab, Institute of Cardiovascular Sciences, School of Life Science, Shanghai University, Shanghai, 200444, China. .,School of Medicine, Shanghai University, Shanghai, 200444, China.
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