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Zhen-Duan J, Canenguez KM, Wilson AE, Gu Y, Valluri HG, Chavez AD, Argentieri MA, Schachter AB, Wu H, Baccarelli AA, Daviglus ML, Wassertheil-Smoller S, Warner ET, Shields AE. Religion, spirituality, and DNA methylation in HPA-axis genes among Hispanic/Latino adults. Epigenomics 2024:1-12. [PMID: 39707707 DOI: 10.1080/17501911.2024.2442293] [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: 06/21/2024] [Accepted: 12/10/2024] [Indexed: 12/23/2024] Open
Abstract
AIM Investigate associations between religion and spirituality (R&S) and DNA methylation of four HPA-axis genes (i.e. 14 CpG sites) among 992 adults from the Hispanic Community Health Study/Study of Latinos cohorts. METHODS We assessed 1) the association between R&S measures and mean percent methylation overall and stratified by nativity status (US-born or immigrant) and 2) if interactions between R&S and methylation differed by nativity status. RESULTS Among individuals with the FKBP5 CC genotype, increased spirituality scores were associated with significantly lower methylation levels among immigrants, compared to US-born participants. Organizational religiosity (e.g. service attendance) was associated with increased FKBP5 (CC genotype) methylation among immigrants. CONCLUSION R&S may influence HPA-axis functioning differently based on nativity status; a finding that could offer insight into mechanisms leading to health disparities.
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Affiliation(s)
- Jenny Zhen-Duan
- Disparities Research Unit, Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - Katia M Canenguez
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
- Harvard/MGH Center on Genomics, Vulnerable Populations, and Health Disparities, Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Anna E Wilson
- Disparities Research Unit, Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Health Policy Research Center, Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Yue Gu
- Harvard/MGH Center on Genomics, Vulnerable Populations, and Health Disparities, Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Harshitha G Valluri
- Department of Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY, USA
| | - Alejandra D Chavez
- Disparities Research Unit, Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - M Austin Argentieri
- Harvard/MGH Center on Genomics, Vulnerable Populations, and Health Disparities, Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Anna Boonin Schachter
- Harvard/MGH Center on Genomics, Vulnerable Populations, and Health Disparities, Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Haotian Wu
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - Andrea A Baccarelli
- Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, MA, USA
| | - Martha L Daviglus
- Institute for Minority Health Research, Department of Medicine, University of Illinois Chicago, Chicago, IL, USA
| | | | - Erica T Warner
- Harvard/MGH Center on Genomics, Vulnerable Populations, and Health Disparities, Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Alexandra E Shields
- Harvard/MGH Center on Genomics, Vulnerable Populations, and Health Disparities, Mongan Institute, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Mongan Institute, Clinical Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA
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Navarro-Rios D, Panduro A, Roman S, Ramos-Lopez O. CD36 polymorphism, sugary drinks, and sedentarism are associated with hypertriglyceridemic waist phenotype. INT J VITAM NUTR RES 2024; 94:37-44. [PMID: 36274589 DOI: 10.1024/0300-9831/a000771] [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] [Indexed: 10/29/2023]
Abstract
Background: The hypertriglyceridemic waist (HTGW) phenotype is characterized by concomitant increases in waist circumference (WC) and blood triglyceride levels (TG), which have been identified as a predictor of metabolic disorders. This study aimed to analyze associations between food consumption, exercise, and the CD36 gene rs1761667 G>A polymorphism with the HTGW phenotype in adult Mexicans. Methods: This cross-sectional study included a total of 255 participants (both genders, between 18-64 years of age). The HTGW phenotype was defined as WC >88 cm in women, WC >102 cm in men, and TG >150 mg/dL. Body composition was analyzed by electrical bioimpedance. Dietary intakes (macro and micronutrients) were evaluated through a validated 64-item food frequency questionnaire and a 24-h recall. Physical exercise was subjectively recorded asking the participants if they regularly performed some systematic exercise or sport of moderate intensity at least 150-300 minutes a week. Biochemical tests were determined by an automated system. A Taqman real-time assay was used to detect the rs1761667 (G>A) polymorphism of the CD36 gene. A multivariate logistic regression model was performed to analyze the variables potentially associated with the HTGW phenotype (adjusted for age, energy intake, and total fat mass). Results: Overall, 21.6% of the population presented the HTGW phenotype; compared to the HTGW-, also, they were older, had more body fat, higher glucose, cholesterol and insulin levels, and high blood pressure. Female sex (OR=2.92, 95% CI: 1.12-7.60, p=0.028), body mass index (OR=1.19, 95% CI: 1.07-1.32, p=0.001), total cholesterol (OR=1.01, 95% CI:1.00-1.02, p=0.039), daily consumption of sugary drinks (OR=6.94, 95% CI: 1.80-26.8, p=0.005), and the CD36 AG genotype (OR=3.81, 95% CI: 1.08-13.4, p=0.037) were positively associated with the HTGW phenotype, while performing exercise played a protective role (OR=0.23, 95% CI: 0.08-0.62, p=0.004). Overall, the model predicted the HTGW phenotype in 47% (R2=0.47, p≤0.001). Conclusion: The CD36 AG genotype, daily consumption of sugary drinks and sedentarism are risk factors for the HTGW phenotype in Mexicans.
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Affiliation(s)
- Dayanara Navarro-Rios
- Medicine and Psychology School, Autonomous University of Baja California, Tijuana, Baja California, Mexico
| | - Arturo Panduro
- Department of Genomic Medicine in Hepatology, Civil Hospital of Guadalajara, Fray Antonio Alcalde, Guadalajara, Jalisco, Mexico
- Health Sciences Center, University of Guadalajara, Jalisco, Mexico
| | - Sonia Roman
- Department of Genomic Medicine in Hepatology, Civil Hospital of Guadalajara, Fray Antonio Alcalde, Guadalajara, Jalisco, Mexico
- Health Sciences Center, University of Guadalajara, Jalisco, Mexico
| | - Omar Ramos-Lopez
- Medicine and Psychology School, Autonomous University of Baja California, Tijuana, Baja California, Mexico
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Villablanca A, Dugger BN, Nuthikattu S, Chauhan J, Cheung S, Chuah CN, Garrison SL, Milenkovic D, Norman JE, Oliveira LC, Smith BP, Brown SD. How cy pres promotes transdisciplinary convergence science: an academic health center for women's cardiovascular and brain health. J Clin Transl Sci 2024; 8:e16. [PMID: 38384925 PMCID: PMC10880003 DOI: 10.1017/cts.2023.705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Revised: 11/15/2023] [Accepted: 12/15/2023] [Indexed: 02/23/2024] Open
Abstract
Cardiovascular disease (CVD) is largely preventable, and the leading cause of death for men and women. Though women have increased life expectancy compared to men, there are marked sex disparities in prevalence and risk of CVD-associated mortality and dementia. Yet, the basis for these and female-male differences is not completely understood. It is increasingly recognized that heart and brain health represent a lifetime of exposures to shared risk factors (including obesity, hyperlipidemia, diabetes, and hypertension) that compromise cerebrovascular health. We describe the process and resources for establishing a new research Center for Women's Cardiovascular and Brain Health at the University of California, Davis as a model for: (1) use of the cy pres principle for funding science to improve health; (2) transdisciplinary collaboration to leapfrog progress in a convergence science approach that acknowledges and addresses social determinants of health; and (3) training the next generation of diverse researchers. This may serve as a blueprint for future Centers in academic health institutions, as the cy pres mechanism for funding research is a unique mechanism to leverage residual legal settlement funds to catalyze the pace of scientific discovery, maximize innovation, and promote health equity in addressing society's most vexing health problems.
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Affiliation(s)
- Amparo Villablanca
- Department of Internal Medicine, University of California, Davis, CA, USA
| | - Brittany N. Dugger
- Department of Pathology and Laboratory Medicine, University of California, Davis, CA, USA
| | | | - Joohi Chauhan
- Department of Pathology and Laboratory Medicine, University of California, Davis, CA, USA
- Department of Computer Engineering, University of California, Davis, CA, USA
| | - Samson Cheung
- Department of Computer Engineering, University of California, Davis, CA, USA
| | - Chen-Nee Chuah
- Department of Computer Engineering, University of California, Davis, CA, USA
| | - Siedah L. Garrison
- Department of Internal Medicine, University of California, Davis, CA, USA
| | | | - Jennifer E. Norman
- Department of Internal Medicine, University of California, Davis, CA, USA
| | - Luca Cerny Oliveira
- Department of Computer Engineering, University of California, Davis, CA, USA
| | - Bridgette P. Smith
- Department of Internal Medicine, University of California, Davis, CA, USA
| | - Susan D. Brown
- Department of Internal Medicine, University of California, Davis, CA, USA
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Ding Y, Deng Q, Yang M, Niu H, Wang Z, Xia S. Clinical Classification of Obesity and Implications for Metabolic Dysfunction-Associated Fatty Liver Disease and Treatment. Diabetes Metab Syndr Obes 2023; 16:3303-3329. [PMID: 37905232 PMCID: PMC10613411 DOI: 10.2147/dmso.s431251] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Accepted: 10/10/2023] [Indexed: 11/02/2023] Open
Abstract
Obesity,and metabolic dysfunction-associated fatty liver disease (MAFLD) have reached epidemic proportions globally. Obesity and MAFLD frequently coexist and act synergistically to increase the risk of adverse clinical outcomes (both hepatic and extrahepatic). Type 2 diabetes mellitus (T2DM) is the most important risk factor for rapid progression of steatohepatitis and advanced fibrosis. Conversely, the later stages of MAFLD are associated with an increased risk of T2DM incident. According to the proposed criteria, MAFLD is diagnosed in patients with liver steatosis and in at least one in three: overweight or obese, T2DM, or signs of metabolic dysregulation if they are of normal weight. However, the clinical classification and correlation between obesity and MAFLD is more complex than expected. In addition, treatment for obesity and MAFLD are associated with a reduced risk of T2DM, suggesting that liver-based treatments could reduce the risk of developing T2DM. This review describes the clinical classification of obesity and MAFLD, discusses the clinical features of various types of obesity and MAFLD, emphasizes the role of visceral obesity and insulin resistance (IR) in the development of MAFLD,and summarizes the existing treatments for obesity and MAFLD that reduce the risk of developing T2DM.
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Affiliation(s)
- Yuping Ding
- Department of Gastroenterology and Hepatology, Characteristic Medical Center of the Chinese People’s Armed Police Force, Tianjin, 300162, People’s Republic of China
- Tianjin Key Laboratory of Hepatopancreatic Fibrosis and Molecular Diagnosis & Treatment, Tianjin, 300162, People’s Republic of China
| | - Quanjun Deng
- Department of Gastroenterology and Hepatology, Characteristic Medical Center of the Chinese People’s Armed Police Force, Tianjin, 300162, People’s Republic of China
- Tianjin Key Laboratory of Hepatopancreatic Fibrosis and Molecular Diagnosis & Treatment, Tianjin, 300162, People’s Republic of China
| | - Mei Yang
- Department of Gastroenterology and Hepatology, Characteristic Medical Center of the Chinese People’s Armed Police Force, Tianjin, 300162, People’s Republic of China
- Tianjin Key Laboratory of Hepatopancreatic Fibrosis and Molecular Diagnosis & Treatment, Tianjin, 300162, People’s Republic of China
| | - Haiyan Niu
- Department of Gastroenterology and Hepatology, Characteristic Medical Center of the Chinese People’s Armed Police Force, Tianjin, 300162, People’s Republic of China
- Tianjin Key Laboratory of Hepatopancreatic Fibrosis and Molecular Diagnosis & Treatment, Tianjin, 300162, People’s Republic of China
| | - Zuoyu Wang
- Department of Gastroenterology and Hepatology, Characteristic Medical Center of the Chinese People’s Armed Police Force, Tianjin, 300162, People’s Republic of China
- Tianjin Key Laboratory of Hepatopancreatic Fibrosis and Molecular Diagnosis & Treatment, Tianjin, 300162, People’s Republic of China
| | - Shihai Xia
- Department of Gastroenterology and Hepatology, Characteristic Medical Center of the Chinese People’s Armed Police Force, Tianjin, 300162, People’s Republic of China
- Tianjin Key Laboratory of Hepatopancreatic Fibrosis and Molecular Diagnosis & Treatment, Tianjin, 300162, People’s Republic of China
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Giri AK, Prasad G, Parekatt V, Rajashekar D, Tandon N, Bharadwaj D. Epigenome-wide methylation study identified two novel CpGs associated with T2DM risk and a network of co-methylated CpGs capable of patient's classifications. Hum Mol Genet 2023; 32:2576-2586. [PMID: 37184252 DOI: 10.1093/hmg/ddad084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2022] [Revised: 04/24/2023] [Accepted: 05/11/2023] [Indexed: 05/16/2023] Open
Abstract
Prevention of Type 2 diabetes mellitus (T2DM) pandemic needs markers that can precisely predict the disease risk in an individual. Alterations in DNA methylations due to exposure towards environmental risk factors are widely sought markers for T2DM risk prediction. To identify such individual DNA methylation signatures and their effect on disease risk, we performed an epigenome-wide association study (EWAS) in 844 Indian individuals of Indo-European origin. We identified and validated methylation alterations at two novel CpG sites in MIR1287 (cg01178710) and EDN2-SCMH1 (cg04673737) genes associated with T2DM risk at the epigenome-wide-significance-level (P < 1.2 × 10-7). Further, we also replicated the association of two known CpG sites in TXNIP, and CPT1A in the Indian population. With 535 EWAS significant CpGs (P < 1.2 × 10-7) identified in the discovery phase samples, we created a co-methylation network using weighted correlation network analysis and identified four modules among the CpGs. We observed that methylation of one of the module associates with T2DM risk factors (e.g. BMI, insulin and C-peptide) and can be used as markers to segregate T2DM patients with good glycemic control (e.g. low HbA1c) and dyslipidemia (low HDL and high TG) from the other patients. Additionally, an intronic SNP (rs6503650) in the JUP gene, a member of the same module, associated with methylation at all the 14 hub CpG sites of that module as methQTL. Our network-assisted EWAS is the first to systematically explore DNA methylation variations conferring risks to T2DM in Indians and use the identified risk CpG sites for patient segregation with different clinical outcomes. These findings can be useful for better stratification of patients to improve the clinical management and treatment effects.
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Affiliation(s)
- Anil K Giri
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi 110025, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Gauri Prasad
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi 110025, India
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
| | - Vaisak Parekatt
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi 110025, India
| | - Donaka Rajashekar
- Genomics and Molecular Medicine Unit, CSIR-Institute of Genomics and Integrative Biology, New Delhi 110025, India
| | - Nikhil Tandon
- Department of Endocrinology and Metabolism, All India Institute of Medical Sciences, New Delhi 110029, India
| | - Dwaipayan Bharadwaj
- Academy of Scientific and Innovative Research (AcSIR), Ghaziabad 201002, India
- Systems Genomics Laboratory, School of Biotechnology, Jawaharlal Nehru University, New Delhi 110067, India
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Hong X, Miao K, Cao W, Lv J, Yu C, Huang T, Sun D, Liao C, Pang Y, Pang Z, Yu M, Wang H, Wu X, Liu Y, Gao W, Li L. Association Between DNA Methylation and Blood Pressure: A 5-Year Longitudinal Twin Study. Hypertension 2023; 80:169-181. [PMID: 36345830 DOI: 10.1161/hypertensionaha.122.19953] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Abstract
BACKGROUND Previous EWASs (Epigenome-Wide Association Studies) have reported hundreds of blood pressure (BP) associated 5'-cytosine-phosphate-guanine-3' (CpG) sites. However, their results were inconsistent. Longitudinal observations on the temporal relationship between DNA methylation and BP are lacking. METHODS A candidate CpG site association study for BP was conducted on 1072 twins in the Chinese National Twin Registry. PubMed and EMBASE were searched for candidate CpG sites. Cross-lagged models were used to assess the temporal relationship between BP and DNA methylation in 308 twins who completed 2 surveys in 2013 and 2018. Then, the significant cross-lagged associations were validated by adopting the Inference About Causation From Examination of Familial Confounding approach. Finally, to evaluate the cumulative effects of DNA methylation on the progression of hypertension, we established methylation risk scores based on BP-associated CpG sites and performed Markov multistate models. RESULTS 16 and 20 CpG sites were validated to be associated with systolic BP and diastolic BP, respectively. In the cross-lagged analysis, we detected that methylation of 2 CpG sites could predict subsequent systolic BP, and systolic BP predicted methylation at another 3 CpG sites. For diastolic BP, methylation at 3 CpG sites had significant cross-lagged effects for predicting diastolic BP levels, while the prediction from the opposite direction was observed at one site. Among these, 3 associations were validated in the Inference About Causation From Examination of Familial Confounding analysis. Using the Markov multistate model, we observed that methylation risk scores were associated with the development of hypertension. CONCLUSIONS Our findings suggest the significance of DNA methylation in the development of hypertension.
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Affiliation(s)
- Xuanming Hong
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Ke Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Chunxiao Liao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Zengchang Pang
- Qingdao Center for Disease Control and Prevention, China (Z.P.)
| | - Min Yu
- Zhejiang Center for Disease Control and Prevention, Hangzhou, China (M.Y.)
| | - Hua Wang
- Jiangsu Center for Disease Control and Prevention, Nanjing, China (H.W.)
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, China (X.W.)
| | - Yu Liu
- Heilongjiang Center for Disease Control and Prevention, Harbin, China (Y.L.)
| | - Wenjing Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, China (X.H., K.M., W.C., J.L., C.Y., T.H., D.S., C.L., Y.P., W.G., L.L.)
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Epigenetics and Gut Microbiota Crosstalk: A potential Factor in Pathogenesis of Cardiovascular Disorders. BIOENGINEERING (BASEL, SWITZERLAND) 2022; 9:bioengineering9120798. [PMID: 36551003 PMCID: PMC9774431 DOI: 10.3390/bioengineering9120798] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 12/09/2022] [Accepted: 12/12/2022] [Indexed: 12/15/2022]
Abstract
Cardiovascular diseases (CVD) are the leading cause of mortality, morbidity, and "sudden death" globally. Environmental and lifestyle factors play important roles in CVD susceptibility, but the link between environmental factors and genetics is not fully established. Epigenetic influence during CVDs is becoming more evident as its direct involvement has been reported. The discovery of epigenetic mechanisms, such as DNA methylation and histone modification, suggested that external factors could alter gene expression to modulate human health. These external factors also influence our gut microbiota (GM), which participates in multiple metabolic processes in our body. Evidence suggests a high association of GM with CVDs. Although the exact mechanism remains unclear, the influence of GM over the epigenetic mechanisms could be one potential pathway in CVD etiology. Both epigenetics and GM are dynamic processes and vary with age and environment. Changes in the composition of GM have been found to underlie the pathogenesis of metabolic diseases via modulating epigenetic changes in the form of DNA methylation, histone modifications, and regulation of non-coding RNAs. Several metabolites produced by the GM, including short-chain fatty acids, folates, biotin, and trimethylamine-N-oxide, have the potential to regulate epigenetics, apart from playing a vital role in normal physiological processes. The role of GM and epigenetics in CVDs are promising areas of research, and important insights in the field of early diagnosis and therapeutic approaches might appear soon.
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Hong X, Wu Z, Cao W, Lv J, Yu C, Huang T, Sun D, Liao C, Pang Y, Pang Z, Cong L, Wang H, Wu X, Liu Y, Gao W, Li L. Longitudinal Association of DNA Methylation With Type 2 Diabetes and Glycemic Traits: A 5-Year Cross-Lagged Twin Study. Diabetes 2022; 71:2804-2817. [PMID: 36170668 DOI: 10.2337/db22-0513] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 09/20/2022] [Indexed: 01/11/2023]
Abstract
Investigators of previous cross-sectional epigenome-wide association studies (EWAS) in adults have reported hundreds of 5'-cytosine-phosphate-guanine-3' (CpG) sites associated with type 2 diabetes mellitus (T2DM) and glycemic traits. However, the results from EWAS have been inconsistent, and longitudinal observations of these associations are scarce. Furthermore, few studies have investigated whether DNA methylation (DNAm) could be modified by smoking, drinking, and glycemic traits, which have broad impacts on genome-wide DNAm and result in altering the risk of T2DM. Twin studies provide a valuable tool for epigenetic studies, as twins are naturally matched for genetic information. In this study, we conducted a systematic literature search in PubMed and Embase for EWAS, and 214, 33, and 117 candidate CpG sites were selected for T2DM, HbA1c, and fasting blood glucose (FBG). Based on 1,070 twins from the Chinese National Twin Registry, 67, 17, and 16 CpG sites from previous studies were validated for T2DM, HbA1c, and FBG. Longitudinal review and blood sampling for phenotypic information and DNAm were conducted twice in 2013 and 2018 for 308 twins. A cross-lagged analysis was performed to examine the temporal relationship between DNAm and T2DM or glycemic traits in the longitudinal data. A total of 11 significant paths from T2DM to subsequent DNAm and 15 paths from DNAm to subsequent T2DM were detected, suggesting both directions of associations. For glycemic traits, we detected 17 cross-lagged associations from baseline glycemic traits to subsequent DNAm, and none were from the other cross-lagged direction, indicating that CpG sites may be the consequences, not the causes, of glycemic traits. Finally, a longitudinal mediation analysis was performed to explore the mediation effects of DNAm on the associations of smoking, drinking, and glycemic traits with T2DM. No significant mediations of DNAm in the associations linking smoking and drinking with T2DM were found. In contrast, our study suggested a potential role of DNAm of cg19693031, cg00574958, and cg04816311 in mediating the effect of altered glycemic traits on T2DM.
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Affiliation(s)
- Xuanming Hong
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zhiyu Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Chunxiao Liao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Zengchang Pang
- Qingdao Center for Disease Control and Prevention, Qingdao, China
| | - Liming Cong
- Zhejiang Center for Disease Control and Prevention, Hangzhou, China
| | - Hua Wang
- Jiangsu Center for Disease Control and Prevention, Nanjing, China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Yu Liu
- Heilongjiang Center for Disease Control and Prevention, Harbin, China
| | - Wenjing Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
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Domingo-Relloso A, Makhani K, Riffo-Campos AL, Tellez-Plaza M, Klein KO, Subedi P, Zhao J, Moon KA, Bozack AK, Haack K, Goessler W, Umans JG, Best LG, Zhang Y, Herreros-Martinez M, Glabonjat RA, Schilling K, Galvez-Fernandez M, Kent JW, Sanchez TR, Taylor KD, Craig Johnson W, Durda P, Tracy RP, Rotter JI, Rich SS, Berg DVD, Kasela S, Lappalainen T, Vasan RS, Joehanes R, Howard BV, Levy D, Lohman K, Liu Y, Daniele Fallin M, Cole SA, Mann KK, Navas-Acien A. Arsenic Exposure, Blood DNA Methylation, and Cardiovascular Disease. Circ Res 2022; 131:e51-e69. [PMID: 35658476 PMCID: PMC10203287 DOI: 10.1161/circresaha.122.320991] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2022] [Accepted: 05/18/2022] [Indexed: 02/03/2023]
Abstract
BACKGROUND Epigenetic dysregulation has been proposed as a key mechanism for arsenic-related cardiovascular disease (CVD). We evaluated differentially methylated positions (DMPs) as potential mediators on the association between arsenic and CVD. METHODS Blood DNA methylation was measured in 2321 participants (mean age 56.2, 58.6% women) of the Strong Heart Study, a prospective cohort of American Indians. Urinary arsenic species were measured using high-performance liquid chromatography coupled to inductively coupled plasma mass spectrometry. We identified DMPs that are potential mediators between arsenic and CVD. In a cross-species analysis, we compared those DMPs with differential liver DNA methylation following early-life arsenic exposure in the apoE knockout (apoE-/-) mouse model of atherosclerosis. RESULTS A total of 20 and 13 DMPs were potential mediators for CVD incidence and mortality, respectively, several of them annotated to genes related to diabetes. Eleven of these DMPs were similarly associated with incident CVD in 3 diverse prospective cohorts (Framingham Heart Study, Women's Health Initiative, and Multi-Ethnic Study of Atherosclerosis). In the mouse model, differentially methylated regions in 20 of those genes and DMPs in 10 genes were associated with arsenic. CONCLUSIONS Differential DNA methylation might be part of the biological link between arsenic and CVD. The gene functions suggest that diabetes might represent a relevant mechanism for arsenic-related cardiovascular risk in populations with a high burden of diabetes.
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Affiliation(s)
- Arce Domingo-Relloso
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
- Department of Statistics and Operations Research, University of Valencia, Spain
| | - Kiran Makhani
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
| | - Angela L. Riffo-Campos
- Millennium Nucleus on Sociomedicine (SocioMed) and Vicerrectoría Académica, Universidad de La Frontera, Temuco, Chile
- Department of Computer Science, ETSE, University of Valencia, Valencia, Spain
| | - Maria Tellez-Plaza
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| | - Kathleen Oros Klein
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
| | - Pooja Subedi
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
| | - Jinying Zhao
- Department of Epidemiology, College of Public Health and Health Professions and College of Medicine, University of Florida, Gainesville, FL, USA
| | - Katherine A. Moon
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Anne K. Bozack
- Department of Environmental Health Sciences, School of Public Health, University of California, Berkeley, USA
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Walter Goessler
- Institute of Chemistry - Analytical Chemistry for Health and Environment, University of Graz, Austria
| | | | - Lyle G. Best
- Missouri Breaks Industries and Research Inc., Eagle Butte, SD, USA
| | - Ying Zhang
- Department of Biostatistics and Epidemiology, The University of Oklahoma Health Sciences Center, OK, USA
| | | | - Ronald A. Glabonjat
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Kathrin Schilling
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Marta Galvez-Fernandez
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
- Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| | - Jack W. Kent
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Tiffany R Sanchez
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - W. Craig Johnson
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - Peter Durda
- Department of Pathology Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
| | - Russell P. Tracy
- Department of Pathology Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington, VT, USA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - David Van Den Berg
- Department of Population and Public Health Sciences, Keck School of Medicine of USC, University of Southern California, Los Angeles, CA, USA
| | - Silva Kasela
- New York Genome Center, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
| | - Tuuli Lappalainen
- New York Genome Center, New York, NY, USA
- Department of Systems Biology, Columbia University, New York, NY, USA
| | - Ramachandran S Vasan
- National Heart, Lung, and Blood Institute’s and Boston University’s Framingham Heart Study, Framingham, MA; Sections of Preventive Medicine and Epidemiology and Cardiovascular Medicine, Department of Medicine, department of Epidemiology, Boston University Schools of medicine and Public health, Boston, MA, USA
| | - Roby Joehanes
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
- Framingham Heart Study, Framingham, MA
| | | | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD
- Framingham Heart Study, Framingham, MA
| | - Kurt Lohman
- Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | - Yongmei Liu
- Department of Medicine, Duke University Medical Center, Durham, NC, USA
| | - M Daniele Fallin
- Departments of Mental Health and Epidemiology, Johns Hopkins University, Baltimore, MD, USA
| | - Shelley A. Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Koren K. Mann
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Department of Pharmacology and Therapeutics, McGill University, Montreal, Canada
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
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10
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de Cuevillas B, Alvarez-Alvarez I, Riezu-Boj JI, Navas-Carretero S, Martinez JA. The hypertriglyceridemic-waist phenotype as a valuable and integrative mirror of metabolic syndrome traits. Sci Rep 2021; 11:21859. [PMID: 34750510 PMCID: PMC8575863 DOI: 10.1038/s41598-021-01343-x] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2020] [Accepted: 10/27/2021] [Indexed: 12/28/2022] Open
Abstract
Rates of non-communicable diseases (NCDs), such as obesity, diabetes, cardiovascular events and cancer, continue to rise worldwide, which require objective instruments for preventive and management actions. Diverse anthropometric and biochemical markers have been used to qualitatively evaluate degrees of disease, metabolic traits and evolution of nutritional status. The aim of this study was to integrate and assess the interactions between an anthropometric measurement, such as waist circumference (WC), and biochemical data, such as the triglyceride glucose index (TyG), in order to individually characterize metabolic syndrome (MetS) features considering the hypertriglyceridemic waist phenotype as a marker. An ancillary cross-sectional study was conducted using anthropometric measurements, such as weight, height, waist and hip circumferences, as well as fasting biochemical data of 314 participants. Different indices based on WC (WC, WC*TG and WC*TyG) were estimated to compute MetS components and accompanying comorbidities. ROC curves were fitted to define the strength of the analyses and the validity of the relationships. Associations were confirmed between anthropometric, biochemical and combined indices with some chronic disease manifestations, including hyperglycemia, hypertension and dyslipidemia. Both WC*TG and WC*TyG indices showed similar performance in diagnosing MetS (area under the ROC curve = 0.81). Interestingly, when participants were categorized according to a reference value of the WC*TyG index (842.7 cm*mg/dl), our results evidenced that subjects classified over this limit presented statistically higher prevalence of MetS and accompanying individual components with clinical relevance for interventions. These results revealed that WC*TyG mirrors the hypertriglyceridemic phenotype, which suggests may serve as a good indicator to define the metabolic syndrome phenotype and a suitable, sensitive, and simple proxy to complement others. A reference point was proposed with a good clinical performance and maximized sensitivity and specificity values.
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Affiliation(s)
- Begoña de Cuevillas
- Department of Nutrition, Food Sciences and Physiology, Center for Nutrition Research, University of Navarra, Calle Irunlarrea 1, 31008, Pamplona, Spain
| | - Ismael Alvarez-Alvarez
- Department of Nutrition, Food Sciences and Physiology, Center for Nutrition Research, University of Navarra, Calle Irunlarrea 1, 31008, Pamplona, Spain
| | - Jose I Riezu-Boj
- Department of Nutrition, Food Sciences and Physiology, Center for Nutrition Research, University of Navarra, Calle Irunlarrea 1, 31008, Pamplona, Spain
- IdisNA Health Research Institute of Navarra, Pamplona, Spain
| | - Santiago Navas-Carretero
- Department of Nutrition, Food Sciences and Physiology, Center for Nutrition Research, University of Navarra, Calle Irunlarrea 1, 31008, Pamplona, Spain.
- IdisNA Health Research Institute of Navarra, Pamplona, Spain.
- CIBER Physiopathology of Obesity and Nutrition (CIBEROBN), Institute of Health Carlos III, 28029, Madrid, Spain.
| | - J Alfredo Martinez
- Department of Nutrition, Food Sciences and Physiology, Center for Nutrition Research, University of Navarra, Calle Irunlarrea 1, 31008, Pamplona, Spain
- IdisNA Health Research Institute of Navarra, Pamplona, Spain
- CIBER Physiopathology of Obesity and Nutrition (CIBEROBN), Institute of Health Carlos III, 28029, Madrid, Spain
- Precision Nutrition Program, Cardiometabolic IMDEA Food, 28049, Madrid, Spain
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11
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Wei S, Tao J, Xu J, Chen X, Wang Z, Zhang N, Zuo L, Jia Z, Chen H, Sun H, Yan Y, Zhang M, Lv H, Kong F, Duan L, Ma Y, Liao M, Xu L, Feng R, Liu G, Project TEWAS, Jiang Y. Ten Years of EWAS. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2021; 8:e2100727. [PMID: 34382344 PMCID: PMC8529436 DOI: 10.1002/advs.202100727] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/22/2021] [Revised: 05/11/2021] [Indexed: 06/13/2023]
Abstract
Epigenome-wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next-generation, and third-generation sequencing technologies have prepared a high-quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.
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Affiliation(s)
- Siyu Wei
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
| | - Junxian Tao
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
| | - Jing Xu
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
| | - Xingyu Chen
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Zhaoyang Wang
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Nan Zhang
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Lijiao Zuo
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Zhe Jia
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Haiyan Chen
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Hongmei Sun
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Yubo Yan
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Mingming Zhang
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Hongchao Lv
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
| | - Fanwu Kong
- The EWAS ProjectHarbinChina
- Department of NephrologyThe Second Affiliated HospitalHarbin Medical UniversityHarbin150001China
| | - Lian Duan
- The EWAS ProjectHarbinChina
- The First Affiliated Hospital of Wenzhou Medical UniversityWenzhou325000China
| | - Ye Ma
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
| | - Mingzhi Liao
- The EWAS ProjectHarbinChina
- College of Life SciencesNorthwest A&F UniversityYanglingShanxi712100China
| | - Liangde Xu
- The EWAS ProjectHarbinChina
- School of Biomedical EngineeringWenzhou Medical UniversityWenzhou325035China
| | - Rennan Feng
- The EWAS ProjectHarbinChina
- Department of Nutrition and Food HygienePublic Health CollegeHarbin Medical UniversityHarbin150081China
| | - Guiyou Liu
- The EWAS ProjectHarbinChina
- Beijing Institute for Brain DisordersCapital Medical UniversityBeijing100069China
| | | | - Yongshuai Jiang
- College of Bioinformatics Science and TechnologyHarbin Medical UniversityHarbin150081China
- The EWAS ProjectHarbinChina
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12
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Mamtani M, Jaisinghani MT, Jaiswal SG, Pipal KV, Patel AA, Kulkarni H. Genetic association of anthropometric traits with type 2 diabetes in ethnically endogamous Sindhi families. PLoS One 2021; 16:e0257390. [PMID: 34506595 PMCID: PMC8432747 DOI: 10.1371/journal.pone.0257390] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2021] [Accepted: 08/31/2021] [Indexed: 12/20/2022] Open
Abstract
Background Ethnically endogamous populations can shed light on the genetics of type 2 diabetes. Such studies are lacking in India. We conducted this study to determine the genetic and environmental contributions of anthropometric traits to type 2 diabetes risk in the Sindhi families in central India. Methods We conducted a family study in Indian Sindhi families with at least one case of type 2 diabetes. Variance components methods were used to quantify the genetic association of 18 anthropometric traits with eight type 2 diabetes related traits. Univariate and bivariate polygenic models were used to determine the heritability, genetic and environmental correlation of anthropometric traits with type 2 diabetes related traits. Results We included 1,152 individuals from 112 phenotyped families. The ascertainment-bias corrected prevalence of type 2 diabetes was 35%. Waist circumference, hip circumference and the biceps, triceps, subscapular and medial calf skinfold thicknesses were polygenically and significantly associated with type 2 diabetes. The range of heritability of the anthropometric traits and type 2 diabetes related traits was 0.27–0.73 and 0.00–0.39, respectively. Heritability of type 2 diabetes as a discrete trait was 0.35. Heritability curves demonstrated a substantial local influence of type 2 diabetes related traits. Bivariate trait analyses showed that biceps and abdominal skinfold thickness and all waist-containing indexes were strongly genetically correlated with type 2 diabetes. Conclusions In this first study of Sindhi families, we found evidence for genetic and environmental concordance of anthropometric traits with type 2 diabetes. Future studies need to probe into the genetics of type 2 diabetes in this population.
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Affiliation(s)
- Manju Mamtani
- Lata Medical Research Foundation, Nagpur, India
- M&H Research, LLC, San Antonio, Texas, United States of America
- * E-mail:
| | | | | | | | | | - Hemant Kulkarni
- Lata Medical Research Foundation, Nagpur, India
- M&H Research, LLC, San Antonio, Texas, United States of America
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13
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Jones AC, Irvin MR, Claas SA, Arnett DK. Lipid Phenotypes and DNA Methylation: a Review of the Literature. Curr Atheroscler Rep 2021; 23:71. [PMID: 34468868 DOI: 10.1007/s11883-021-00965-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/11/2021] [Indexed: 12/17/2022]
Abstract
PURPOSE OF REVIEW Epigenetic modifications via DNA methylation have previously been linked to blood lipid levels, dyslipidemias, and atherosclerosis. The purpose of this review is to discuss current literature on the role of DNA methylation on lipid traits and their associated pathologies. RECENT FINDINGS Candidate gene and epigenome-wide approaches have identified differential methylation of genes associated with lipid traits (particularly CPT1A, ABCG1, SREBF1), and novel approaches are being implemented to further characterize these relationships. Moreover, studies on environmental factors have shown that methylation variations at lipid-related genes are associated with diet and pollution exposure. Further investigation is needed to elucidate the directionality of the associations between the environment, lipid traits, and epigenome. Future studies should also seek to increase the diversity of cohorts, as European and Asian ancestry populations are the predominant study populations in the current literature.
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Affiliation(s)
- Alana C Jones
- Medical Scientist Training Program, University of Alabama-Birmingham, Birmingham, AL, USA.,Department of Epidemiology, School of Public Health, University of Alabama-Birmingham, Birmingham, AL, USA
| | - Marguerite R Irvin
- Department of Epidemiology, School of Public Health, University of Alabama-Birmingham, Birmingham, AL, USA
| | - Steven A Claas
- Department of Epidemiology, College of Public Health, University of Kentucky, 111 Washington Ave, Lexington, KY, 40508, USA
| | - Donna K Arnett
- Department of Epidemiology, College of Public Health, University of Kentucky, 111 Washington Ave, Lexington, KY, 40508, USA.
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14
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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: 2.0] [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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15
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Rohner M, Heiz R, Feldhaus S, Bornstein SR. Hepatic-Metabolite-Based Intermittent Fasting Enables a Sustained Reduction in Insulin Resistance in Type 2 Diabetes and Metabolic Syndrome. Horm Metab Res 2021; 53:529-540. [PMID: 34192792 PMCID: PMC8360708 DOI: 10.1055/a-1510-8896] [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] [Received: 02/09/2021] [Accepted: 05/12/2021] [Indexed: 11/03/2022]
Abstract
Insulin resistance is the hallmark of Type 2 Diabetes and is still an unmet medical need. Insulin resistance lies at the crossroads of non-alcoholic fatty liver disease, obesity, weight loss and exercise resistance, heart disease, stroke, depression, and brain health. Insulin resistance is purely nutrition related, with a typical molecular disease food intake pattern. The insulin resistant state is accessible by TyG as the appropriate surrogate marker, which is found to lead the personalized molecular hepatic nutrition system for highly efficient insulin resistance remission. Treating insulin resistance with a molecular nutrition-centered approach shifts the treatment paradigm of Type 2 Diabetes from management to cure. This allows remission within five months, with a high efficiency rate of 85%. With molecular intermittent fasting a very efficient treatment for prediabetes and metabolic syndrome is possible, improving the non-alcoholic fatty liver disease (NAFL) state and enabling the body to lose weight in a sustainable manner.
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Affiliation(s)
| | - Robert Heiz
- Zentrum für Komplementärmedizin AG, Uster,
Switzerland
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16
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Womersley JS, Nothling J, Toikumo S, Malan-Müller S, van den Heuvel LL, McGregor NW, Seedat S, Hemmings SMJ. Childhood trauma, the stress response and metabolic syndrome: A focus on DNA methylation. Eur J Neurosci 2021; 55:2253-2296. [PMID: 34169602 DOI: 10.1111/ejn.15370] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2020] [Revised: 05/13/2021] [Accepted: 06/12/2021] [Indexed: 12/12/2022]
Abstract
Childhood trauma (CT) is well established as a potent risk factor for the development of mental disorders. However, the potential of adverse early experiences to exert chronic and profound effects on physical health, including aberrant metabolic phenotypes, has only been more recently explored. Among these consequences is metabolic syndrome (MetS), which is characterised by at least three of five related cardiometabolic traits: hypertension, insulin resistance/hyperglycaemia, raised triglycerides, low high-density lipoprotein and central obesity. The deleterious effects of CT on health outcomes may be partially attributable to dysregulation of the hypothalamic-pituitary-adrenal (HPA) axis, which coordinates the response to stress, and the consequent fostering of a pro-inflammatory environment. Epigenetic tags, such as DNA methylation, which are sensitive to environmental influences provide a means whereby the effects of CT can be biologically embedded and persist into adulthood to affect health and well-being. The methylome regulates the transcription of genes involved in the stress response, metabolism and inflammation. This narrative review examines the evidence for DNA methylation in CT and MetS in order to identify shared neuroendocrine and immune correlates that may mediate the increased risk of MetS following CT exposure. Our review specifically highlights differential methylation of FKBP5, the gene that encodes FK506-binding protein 51 and has pleiotropic effects on stress responding, inflammation and energy metabolism, as a central candidate to understand the molecular aetiology underlying CT-associated MetS risk.
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Affiliation(s)
- Jacqueline S Womersley
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Jani Nothling
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.,Gender and Health Research Unit, South African Medical Research Council, Cape Town, South Africa
| | - Sylvanus Toikumo
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Stefanie Malan-Müller
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Leigh L van den Heuvel
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Nathaniel W McGregor
- Systems Genetics Working Group, Department of Genetics, Faculty of Agriculture, Stellenbosch University, Stellenbosch, South Africa
| | - Soraya Seedat
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Sîan M J Hemmings
- Department of Psychiatry, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa.,South African Medical Research Council/Stellenbosch University Genomics of Brain Disorders Research Unit, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
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17
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Wan JY, Goodman DL, Willems EL, Freedland AR, Norden-Krichmar TM, Santorico SA, Edwards KL. Genome-wide association analysis of metabolic syndrome quantitative traits in the GENNID multiethnic family study. Diabetol Metab Syndr 2021; 13:59. [PMID: 34074324 PMCID: PMC8170963 DOI: 10.1186/s13098-021-00670-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/19/2021] [Accepted: 04/28/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND To identify genetic associations of quantitative metabolic syndrome (MetS) traits and characterize heterogeneity across ethnic groups. METHODS Data was collected from GENetics of Noninsulin dependent Diabetes Mellitus (GENNID), a multiethnic resource of Type 2 diabetic families and included 1520 subjects in 259 African-American, European-American, Japanese-Americans, and Mexican-American families. We focused on eight MetS traits: weight, waist circumference, systolic and diastolic blood pressure, high-density lipoprotein, triglycerides, fasting glucose, and insulin. Using genotyped and imputed data from Illumina's Multiethnic array, we conducted genome-wide association analyses with linear mixed models for all ethnicities, except for the smaller Japanese-American group, where we used additive genetic models with gene-dropping. RESULTS Findings included ethnic-specific genetic associations and heterogeneity across ethnicities. Most significant associations were outside our candidate linkage regions and were coincident within a gene or intergenic region, with two exceptions in European-American families: (a) within previously identified linkage region on chromosome 2, two significant GLI2-TFCP2L1 associations with weight, and (b) one chromosome 11 variant near CADM1-LINC00900 with pleiotropic blood pressure effects. CONCLUSIONS This multiethnic family study found genetic heterogeneity and coincident associations (with one case of pleiotropy), highlighting the importance of including diverse populations in genetic research and illustrating the complex genetic architecture underlying MetS.
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Affiliation(s)
- Jia Y Wan
- Department of Epidemiology and Biostatistics, Program in Public Health, University of California, 635 E. Peltason Dr, Mail Code: 7550, Irvine, CA, 92697, USA
| | - Deborah L Goodman
- Department of Epidemiology and Biostatistics, Program in Public Health, University of California, 635 E. Peltason Dr, Mail Code: 7550, Irvine, CA, 92697, USA
| | - Emileigh L Willems
- Department of Mathematical and Statistical Sciences, University of Colorado, Denver, CO, USA
| | - Alexis R Freedland
- Department of Epidemiology and Biostatistics, Program in Public Health, University of California, 635 E. Peltason Dr, Mail Code: 7550, Irvine, CA, 92697, USA
| | - Trina M Norden-Krichmar
- Department of Epidemiology and Biostatistics, Program in Public Health, University of California, 635 E. Peltason Dr, Mail Code: 7550, Irvine, CA, 92697, USA
| | - Stephanie A Santorico
- Department of Mathematical and Statistical Sciences, University of Colorado, Denver, CO, USA
- Human Medical Genetics and Genomics Program, University of Colorado, Denver, CO, USA
- Department of Biostatistics & Informatics, University of Colorado, Denver, CO, USA
- Division of Biomedical Informatics & Personalized Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Karen L Edwards
- Department of Epidemiology and Biostatistics, Program in Public Health, University of California, 635 E. Peltason Dr, Mail Code: 7550, Irvine, CA, 92697, USA.
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18
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Mayoral LPC, Andrade GM, Mayoral EPC, Huerta TH, Canseco SP, Rodal Canales FJ, Cabrera-Fuentes HA, Cruz MM, Pérez Santiago AD, Alpuche JJ, Zenteno E, Ruíz HM, Cruz RM, Jeronimo JH, Perez-Campos E. Obesity subtypes, related biomarkers & heterogeneity. Indian J Med Res 2021; 151:11-21. [PMID: 32134010 PMCID: PMC7055173 DOI: 10.4103/ijmr.ijmr_1768_17] [Citation(s) in RCA: 104] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Obesity is a serious medical condition worldwide, which needs new approaches and recognized international consensus in treating diseases leading to morbidity. The aim of this review was to examine heterogeneous links among the various phenotypes of obesity in adults. Proteins and associated genes in each group were analysed to differentiate between biomarkers. A variety of terms for classification and characterization within this pathology are currently in use; however, there is no clear consensus in terminology. The most significant groups reviewed include metabolically healthy obese, metabolically abnormal obese, metabolically abnormal, normal weight and sarcopenic obese. These phenotypes do not define particular genotypes or epigenetic gene regulation, or proteins related to inflammation. There are many other genes linked to obesity, though the value of screening all of those for diagnosis has low predictive results, as there are no significant biomarkers. It is important to establish a consensus in the terminology used and the characteristics attributed to obesity subtypes. The identification of specific molecular biomarkers is also required for better diagnosis in subtypes of obesity.
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Affiliation(s)
- Laura Perez-Campos Mayoral
- Research Centre-Faculty of Medicine, National Autonomous University of Mexico-Benito Juárez Autonomous University of Oaxaca, Oaxaca, Mexico
| | - Gabriel Mayoral Andrade
- Research Centre-Faculty of Medicine, National Autonomous University of Mexico-Benito Juárez Autonomous University of Oaxaca, Oaxaca, Mexico
| | - Eduardo Perez-Campos Mayoral
- Research Centre-Faculty of Medicine, National Autonomous University of Mexico-Benito Juárez Autonomous University of Oaxaca, Oaxaca, Mexico
| | | | - Socorro Pina Canseco
- Research Centre-Faculty of Medicine, National Autonomous University of Mexico-Benito Juárez Autonomous University of Oaxaca, Oaxaca, Mexico
| | - Francisco J Rodal Canales
- Research Centre-Faculty of Medicine, National Autonomous University of Mexico-Benito Juárez Autonomous University of Oaxaca, Oaxaca, Mexico
| | - Héctor Alejandro Cabrera-Fuentes
- Cardiovascular and Metabolic Disorders Program, Duke-National University of Singapore, Singapore; Institute of Biochemistry, Medical School, Justus-Liebig University, Giessen, Germany
| | | | | | - Juan José Alpuche
- Research Centre-Faculty of Medicine, National Autonomous University of Mexico-Benito Juárez Autonomous University of Oaxaca, Oaxaca, Mexico
| | - Edgar Zenteno
- Research Centre-Faculty of Medicine, National Autonomous University of Mexico-Benito Juárez Autonomous University of Oaxaca, Oaxaca, Mexico
| | - Hector Martínez Ruíz
- Research Centre-Faculty of Medicine, National Autonomous University of Mexico-Benito Juárez Autonomous University of Oaxaca, Oaxaca, Mexico
| | - Ruth Martínez Cruz
- Research Centre-Faculty of Medicine, National Autonomous University of Mexico-Benito Juárez Autonomous University of Oaxaca, Oaxaca, Mexico
| | - Julia Hernandez Jeronimo
- Research Centre-Faculty of Medicine, National Autonomous University of Mexico-Benito Juárez Autonomous University of Oaxaca, Oaxaca, Mexico
| | - Eduardo Perez-Campos
- National Technological Institute of Mexico, ITOaxaca; Clinical Pathology Laboratory 'Dr. Eduardo Pérez Ortega' Oaxaca, Mexico
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19
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Justice AE, Chittoor G, Gondalia R, Melton PE, Lim E, Grove ML, Whitsel EA, Liu CT, Cupples LA, Fernandez-Rhodes L, Guan W, Bressler J, Fornage M, Boerwinkle E, Li Y, Demerath E, Heard-Costa N, Levy D, Stewart JD, Baccarelli A, Hou L, Conneely K, Mori TA, Beilin LJ, Huang RC, Gordon-Larsen P, Howard AG, North KE. Methylome-wide association study of central adiposity implicates genes involved in immune and endocrine systems. Epigenomics 2020; 12:1483-1499. [PMID: 32901515 PMCID: PMC7923253 DOI: 10.2217/epi-2019-0276] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2019] [Accepted: 05/22/2020] [Indexed: 12/14/2022] Open
Abstract
Aim: We conducted a methylome-wide association study to examine associations between DNA methylation in whole blood and central adiposity and body fat distribution, measured as waist circumference, waist-to-hip ratio and waist-to-height ratio adjusted for body mass index, in 2684 African-American adults in the Atherosclerosis Risk in Communities study. Materials & methods: We validated significantly associated cytosine-phosphate-guanine methylation sites (CpGs) among adults using the Women's Health Initiative and Framingham Heart Study participants (combined n = 5743) and generalized associations in adolescents from The Raine Study (n = 820). Results & conclusion: We identified 11 CpGs that were robustly associated with one or more central adiposity trait in adults and two in adolescents, including CpG site associations near TXNIP, ADCY7, SREBF1 and RAP1GAP2 that had not previously been associated with obesity-related traits.
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Affiliation(s)
- Anne E Justice
- Department of Population Health Sciences, Geisinger, Danville, PA 17822, USA
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Geetha Chittoor
- Department of Population Health Sciences, Geisinger, Danville, PA 17822, USA
| | - Rahul Gondalia
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Phillip E Melton
- School of Biomedical Science, Faculty of Health & Medical Sciences, The University of Western Australia, Perth, WA 6000, Australia
- School of Pharmacy & Biomedical Sciences, Faculty of Health Sciences, Curtin University, MRF Building, Perth, WA 6000, Australia
- Menzies Institute for Medical Research, College of Health & Medicine, University of Tasmania, Hobart, TA, 7000 Australia
| | - Elise Lim
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
| | - Megan L Grove
- Human Genetics Center, Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Eric A Whitsel
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Medicine, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
| | - L Adrienne Cupples
- Department of Biostatistics, Boston University, Boston, MA 02118, USA
- Framingham Heart Study, Framingham, MA, 01701, USA
| | - Lindsay Fernandez-Rhodes
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Biobehavioral Health, Pennsylvania State University, University Park, PA 16802, USA
| | - Weihua Guan
- Division of Biostatistics, University of Minnesota, Minneapolis, MN 55455, USA
| | - Jan Bressler
- Human Genetics Center, Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Myriam Fornage
- Center for Human Genetics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Brown Foundation Institute of Molecular Medicine, University of Texas Health Science Center at Houston McGovern Medical School, Houston, TX 77030, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics & Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Yun Li
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, NC 27599, USA
| | - Ellen Demerath
- Division of Epidemiology & Community Health, University of Minnesota, Minneapolis, MN 55455, USA
| | - Nancy Heard-Costa
- Framingham Heart Study, Framingham, MA, 01701, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Dan Levy
- Population sciences branch, NHLBI Framingham Heart Study, Framingham, MA 01702, USA
- Department of Medicine, Boston University, Boston, MA 02118, USA
| | - James D Stewart
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Andrea Baccarelli
- Laboratory of Environmental Epigenetics, Departments of Environmental Health Sciences & Epidemiology, Columbia University Mailman School of Public Health, New York, NY 10032, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University Chicago, Evanston, IL, USA
| | - Karen Conneely
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Trevor A Mori
- Medical School, University of Western Australia, Perth, Australia
| | | | - Rae-Chi Huang
- Telethon Kids Institute, University of Western Australia, Perth, Australia
| | - Penny Gordon-Larsen
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, NC 27516, USA
| | - Annie Green Howard
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, NC 27516, USA
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Carolina Population Center, University of North Carolina at Chapel Hill, NC 27516, USA
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20
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Mancilla VJ, Peeri NC, Silzer T, Basha R, Felini M, Jones HP, Phillips N, Tao MH, Thyagarajan S, Vishwanatha JK. Understanding the Interplay Between Health Disparities and Epigenomics. Front Genet 2020; 11:903. [PMID: 32973872 PMCID: PMC7468461 DOI: 10.3389/fgene.2020.00903] [Citation(s) in RCA: 27] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Accepted: 07/21/2020] [Indexed: 12/13/2022] Open
Abstract
Social epigenomics has emerged as an integrative field of research focused on identification of socio-environmental factors, their influence on human biology through epigenomic modifications, and how they contribute to current health disparities. Several health disparities studies have been published using genetic-based approaches; however, increasing accessibility and affordability of molecular technologies have allowed for an in-depth investigation of the influence of external factors on epigenetic modifications (e.g., DNA methylation, micro-RNA expression). Currently, research is focused on epigenetic changes in response to environment, as well as targeted epigenetic therapies and environmental/social strategies for potentially minimizing certain health disparities. Here, we will review recent findings in this field pertaining to conditions and diseases over life span encompassing prenatal to adult stages.
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Affiliation(s)
- Viviana J. Mancilla
- Department of Microbiology, Immunology and Genetics, Graduate School of Biomedical Sciences, University of North Texas Health Science Center, Fort Worth, TX, United States
| | - Noah C. Peeri
- Department of Biostatistics and Epidemiology, School of Public Health, University of North Texas Health Science Center, Fort Worth, TX, United States
| | - Talisa Silzer
- Department of Microbiology, Immunology and Genetics, Graduate School of Biomedical Sciences, University of North Texas Health Science Center, Fort Worth, TX, United States
| | - Riyaz Basha
- Department of Pediatrics, Texas College of Osteopathic Medicine, University of North Texas Health Science Center, Fort Worth, TX, United States
- Texas Center for Health Disparities, University of North Texas Health Science Center, Fort Worth, TX, United States
| | - Martha Felini
- Department of Pediatrics, Texas College of Osteopathic Medicine, University of North Texas Health Science Center, Fort Worth, TX, United States
- Texas Center for Health Disparities, University of North Texas Health Science Center, Fort Worth, TX, United States
| | - Harlan P. Jones
- Department of Microbiology, Immunology and Genetics, Graduate School of Biomedical Sciences, University of North Texas Health Science Center, Fort Worth, TX, United States
- Texas Center for Health Disparities, University of North Texas Health Science Center, Fort Worth, TX, United States
| | - Nicole Phillips
- Department of Microbiology, Immunology and Genetics, Graduate School of Biomedical Sciences, University of North Texas Health Science Center, Fort Worth, TX, United States
- Texas Center for Health Disparities, University of North Texas Health Science Center, Fort Worth, TX, United States
| | - Meng-Hua Tao
- Department of Biostatistics and Epidemiology, School of Public Health, University of North Texas Health Science Center, Fort Worth, TX, United States
- Texas Center for Health Disparities, University of North Texas Health Science Center, Fort Worth, TX, United States
| | - Srikantha Thyagarajan
- Department of Microbiology, Immunology and Genetics, Graduate School of Biomedical Sciences, University of North Texas Health Science Center, Fort Worth, TX, United States
- Texas Center for Health Disparities, University of North Texas Health Science Center, Fort Worth, TX, United States
| | - Jamboor K. Vishwanatha
- Department of Microbiology, Immunology and Genetics, Graduate School of Biomedical Sciences, University of North Texas Health Science Center, Fort Worth, TX, United States
- Texas Center for Health Disparities, University of North Texas Health Science Center, Fort Worth, TX, United States
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21
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Ouidir M, Zeng X, Workalemahu T, Shrestha D, Grantz KL, Mendola P, Zhang C, Tekola-Ayele F. Early pregnancy dyslipidemia is associated with placental DNA methylation at loci relevant for cardiometabolic diseases. Epigenomics 2020; 12:921-934. [PMID: 32677467 PMCID: PMC7466909 DOI: 10.2217/epi-2019-0293] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2019] [Accepted: 04/07/2020] [Indexed: 02/07/2023] Open
Abstract
Aim: To identify placental DNA methylation changes that are associated with early pregnancy maternal dyslipidemia. Materials & methods: We analyzed placental genome-wide DNA methylation (n = 262). Genes annotating differentially methylated CpGs were evaluated for gene expression in placenta (n = 64). Results: We found 11 novel significant differentially methylated CpGs associated with high total cholesterol, low-density lipoprotein cholesterol and triglycerides, and low high-density lipoprotein cholesterol. High triglycerides were associated with decreased methylation of cg02785814 (ALX4) and decreased expression of ALX4 in placenta. Genes annotating the differentially methylated CpGs play key roles in lipid metabolism and were enriched in dyslipidemia pathways. Functional annotation found cis-methylation quantitative trait loci for genetic loci in ALX4 and EXT2. Conclusion: Our findings lend novel insights into potential placental epigenetic mechanisms linked with maternal dyslipidemia. Trial Registration: ClinicalTrials.gov, NCT00912132.
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Affiliation(s)
- Marion Ouidir
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Xuehuo Zeng
- Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Tsegaselassie Workalemahu
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Deepika Shrestha
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Katherine L. Grantz
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Pauline Mendola
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Cuilin Zhang
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
| | - Fasil Tekola-Ayele
- Epidemiology Branch, Division of Intramural Population Health Research, Eunice Kennedy Shriver National Institute of Child Health & Human Development, National Institutes of Health, Bethesda, MD 20892-7004, USA
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22
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Rushing A, Sommer EC, Zhao S, Po'e EK, Barkin SL. Salivary epigenetic biomarkers as predictors of emerging childhood obesity. BMC MEDICAL GENETICS 2020; 21:34. [PMID: 32059710 PMCID: PMC7023819 DOI: 10.1186/s12881-020-0968-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/05/2019] [Accepted: 02/06/2020] [Indexed: 12/13/2022]
Abstract
BACKGROUND Epigenetics could facilitate greater understanding of disparities in the emergence of childhood obesity. While blood is a common tissue used in human epigenetic studies, saliva is a promising tissue. Our prior findings in non-obese preschool-aged Hispanic children identified 17 CpG dinucleotides for which differential methylation in saliva at baseline was associated with maternal obesity status. The current study investigated to what extent baseline DNA methylation in salivary samples in these 3-5-year-old Hispanic children predicted the incidence of childhood obesity in a 3-year prospective cohort. METHODS We examined a subsample (n = 92) of Growing Right Onto Wellness (GROW) trial participants who were randomly selected at baseline, prior to randomization, based on maternal phenotype (obese or non-obese). Baseline saliva samples were collected using the Oragene DNA saliva kit. Objective data were collected on child height and weight at baseline and 36 months later. Methylation arrays were processed using standard protocol. Associations between child obesity at 36 months and baseline salivary methylation at the previously identified 17 CpG dinucleotides were evaluated using multivariable logistic regression models. RESULTS Among the n = 75 children eligible for analysis, baseline methylation of Cg1307483 (NRF1) was significantly associated with emerging childhood obesity at 36-month follow-up (OR = 2.98, p = 0.04), after adjusting for child age, gender, child baseline BMI-Z, and adult baseline BMI. This translates to a model-estimated 48% chance of child obesity at 36-month follow-up for a child at the 75th percentile of NRF1 baseline methylation versus only a 30% chance of obesity for a similar child at the 25th percentile. Consistent with other studies, a higher baseline child BMI-Z during the preschool period was associated with the emergence of obesity 3 years later, but baseline methylation of NRF1 was associated with later obesity even after adjusting for child baseline BMI-Z. CONCLUSIONS Saliva offers a non-invasive means of DNA collection and epigenetic analysis. Our proof of principle study provides sound empirical evidence supporting DNA methylation in salivary tissue as a potential predictor of subsequent childhood obesity for Hispanic children. NFR1 could be a target for further exploration of obesity in this population.
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Affiliation(s)
- Amanda Rushing
- Louisiana State University Health Sciences Center, School of Medicine, 1901 Perdido Street, New Orleans, LA, 70112, USA
| | - Evan C Sommer
- Department of Pediatrics, Vanderbilt University Medical Center, 2146 Belcourt Ave, Nashville, TN, 37232-9225, USA
| | - Shilin Zhao
- Department of Biostatistics, Vanderbilt University Medical Center, 571 Preston Research Building, 2220 Pierce Ave, Nashville, TN, 37232-6838, USA
| | - Eli K Po'e
- Department of Pediatrics, Vanderbilt University Medical Center, 2146 Belcourt Ave, Nashville, TN, 37232-9225, USA
| | - Shari L Barkin
- Department of Pediatrics, Vanderbilt University School of Medicine, 2200 Children's Way, Doctor's Office Tower 8232, Nashville, TN, 37232-9225, USA.
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23
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Neighborhoods to Nucleotides - Advances and gaps for an obesity disparities systems epidemiology model. CURR EPIDEMIOL REP 2019; 6:476-485. [PMID: 36643055 PMCID: PMC9839192 DOI: 10.1007/s40471-019-00221-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Purpose of Review Disparities in obesity rates in the US continue to increase. Here we review progress and highlight gaps in understanding disparities in obesity with a focus on the Hispanic/Latino population from a systems epidemiology framework. We review seven domains: environment, behavior, biomarkers, nutrition, microbiome, genomics, and epigenomics/transcriptomics. We focus on recent advances that include at least two or more of these domains, and then provide a real world example of data collection efforts that reflect these domains. Recent Findings Research into DNA methylation related to discrimination and microbiome relating to eating behaviors and food content is furthering understanding of why disparities in obesity persist. Environmental and neighborhood level research is uncovering the importance of exposures such as air and noise pollution and systematic or structural racism for obesity and related outcomes through behaviors such as sleep.
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24
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Arpón A, Milagro FI, Ramos-Lopez O, Mansego ML, Riezu-Boj JI, Martínez JA. Methylome-Wide Association Study in Peripheral White Blood Cells Focusing on Central Obesity and Inflammation. Genes (Basel) 2019; 10:E444. [PMID: 31212707 PMCID: PMC6627499 DOI: 10.3390/genes10060444] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2019] [Revised: 06/03/2019] [Accepted: 06/07/2019] [Indexed: 12/13/2022] Open
Abstract
Epigenetic signatures such as DNA methylation may be associated with specific obesity traits in different tissues. The onset and development of some obesity-related complications are often linked to visceral fat accumulation. The aim of this study was to explore DNA methylation levels in peripheral white blood cells to identify epigenetic methylation marks associated with waist circumference (WC). DNA methylation levels were assessed using Infinium Human Methylation 450K and MethylationEPIC beadchip (Illumina) to search for putative associations with WC values of 473 participants from the Methyl Epigenome Network Association (MENA) project. Statistical analysis and Ingenuity Pathway Analysis (IPA) were employed for assessing the relationship between methylation and WC. A total of 669 CpGs were statistically associated with WC (FDR < 0.05, slope ≥ |0.1|). From these CpGs, 375 CpGs evidenced a differential methylation pattern between females with WC ≤ 88 and > 88 cm, and 95 CpGs between males with WC ≤ 102 and > 102 cm. These differentially methylated CpGs are located in genes related to inflammation and obesity according to IPA. Receiver operating characteristic (ROC) curves of the top four significant differentially methylated CpGs separated by sex discriminated individuals with presence or absence of abdominal fat. ROC curves of all the CpGs from females and one CpG from males were validated in an independent sample (n = 161). These methylation results add further insights about the relationships between obesity, adiposity-associated comorbidities, and DNA methylation where inflammation processes may be involved.
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Affiliation(s)
- Ana Arpón
- Department of Nutrition, Food Sciences and Physiology, University of Navarra, Irunlarrea 1,31008 Pamplona, Spain.
- Centre for Nutrition Research, University of Navarra, Irunlarrea 1, 31008, Pamplona, Spain.
| | - Fermín I Milagro
- Department of Nutrition, Food Sciences and Physiology, University of Navarra, Irunlarrea 1,31008 Pamplona, Spain.
- Centre for Nutrition Research, University of Navarra, Irunlarrea 1, 31008, Pamplona, Spain.
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, 28029, Madrid, Spain.
- Navarra Institute for Health Research (IdiSNa), 31008, Pamplona, Spain.
| | - Omar Ramos-Lopez
- Department of Nutrition, Food Sciences and Physiology, University of Navarra, Irunlarrea 1,31008 Pamplona, Spain.
- Centre for Nutrition Research, University of Navarra, Irunlarrea 1, 31008, Pamplona, Spain.
| | - Maria L Mansego
- Department of Bioinformatics, Making Genetics S.L., 31002, Pamplona, Spain.
| | - José-Ignacio Riezu-Boj
- Department of Nutrition, Food Sciences and Physiology, University of Navarra, Irunlarrea 1,31008 Pamplona, Spain.
- Centre for Nutrition Research, University of Navarra, Irunlarrea 1, 31008, Pamplona, Spain.
- Navarra Institute for Health Research (IdiSNa), 31008, Pamplona, Spain.
| | - J Alfredo Martínez
- Department of Nutrition, Food Sciences and Physiology, University of Navarra, Irunlarrea 1,31008 Pamplona, Spain.
- Centre for Nutrition Research, University of Navarra, Irunlarrea 1, 31008, Pamplona, Spain.
- Centro de Investigación Biomédica en Red Fisiopatología de la Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, 28029, Madrid, Spain.
- Navarra Institute for Health Research (IdiSNa), 31008, Pamplona, Spain.
- Precision Nutrition and Cardiometabolic Health Program, Madrid Institute for Advanced Studies (IMDEA), IMDEA Food, 28049, Madrid, Spain.
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25
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Samblas M, Milagro FI, Martínez A. DNA methylation markers in obesity, metabolic syndrome, and weight loss. Epigenetics 2019; 14:421-444. [PMID: 30915894 DOI: 10.1080/15592294.2019.1595297] [Citation(s) in RCA: 133] [Impact Index Per Article: 22.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The fact that not all individuals exposed to the same environmental risk factors develop obesity supports the hypothesis of the existence of underlying genetic and epigenetic elements. There is suggestive evidence that environmental stimuli, such as dietary pattern, particularly during pregnancy and early life, but also in adult life, can induce changes in DNA methylation predisposing to obesity and related comorbidities. In this context, the DNA methylation marks of each individual have emerged not only as a promising tool for the prediction, screening, diagnosis, and prognosis of obesity and metabolic syndrome features, but also for the improvement of weight loss therapies in the context of precision nutrition. The main objectives in this field are to understand the mechanisms involved in transgenerational epigenetic inheritance, and featuring the nutritional and lifestyle factors implicated in the epigenetic modifications. Likewise, DNA methylation modulation caused by diet and environment may be a target for newer therapeutic strategies concerning the prevention and treatment of metabolic diseases.
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Affiliation(s)
- Mirian Samblas
- a Department of Nutrition, Food Science and Physiology; Centre for Nutrition Research , University of Navarra , Pamplona , Spain
| | - Fermín I Milagro
- a Department of Nutrition, Food Science and Physiology; Centre for Nutrition Research , University of Navarra , Pamplona , Spain.,b CIBERobn, CIBER Fisiopatología de la Obesidad y Nutrición , Instituto de Salud Carlos III. Madrid , Spain.,c IdiSNA, Instituto de Investigación Sanitaria de Navarra (IdiSNA) , Pamplona , Spain
| | - Alfredo Martínez
- a Department of Nutrition, Food Science and Physiology; Centre for Nutrition Research , University of Navarra , Pamplona , Spain.,b CIBERobn, CIBER Fisiopatología de la Obesidad y Nutrición , Instituto de Salud Carlos III. Madrid , Spain.,c IdiSNA, Instituto de Investigación Sanitaria de Navarra (IdiSNA) , Pamplona , Spain.,d IMDEA, Research Institute on Food & Health Sciences , Madrid , Spain
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26
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Moody L, Xu GB, Chen H, Pan YX. Epigenetic regulation of carnitine palmitoyltransferase 1 (Cpt1a) by high fat diet. BIOCHIMICA ET BIOPHYSICA ACTA-GENE REGULATORY MECHANISMS 2018; 1862:141-152. [PMID: 30605728 DOI: 10.1016/j.bbagrm.2018.12.009] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2018] [Revised: 12/22/2018] [Accepted: 12/27/2018] [Indexed: 12/15/2022]
Abstract
Carnitine palmitoyltransferase 1 (Cpt1a) is a rate-limiting enzyme that mediates the transport of fatty acids into the mitochondria for subsequent beta-oxidation. The objective of this study was to uncover how diet mediates the transcriptional regulation of Cpt1a. Pregnant Sprague Dawley rats were exposed to either a high-fat (HF) or low-fat control diet during gestation and lactation. At weaning, male offspring received either a HF or control diet, creating 4 groups: lifelong control diet (C/C; n = 12), perinatal HF diet (HF/C; n = 9), post-weaning HF diet (C/HF; n = 10), and lifelong HF diet (HF/HF; n = 10). Only HF/HF animals had higher hepatic Cpt1a mRNA expression than C/C. Epigenetic analysis revealed reduced DNA methylation (DNAMe) and increased histone 3 lysine 4 dimethylation (H3K4Me2) upstream and within the promoter of Cpt1a in the HF/HF group. This was accompanied by increased peroxisome proliferator activated receptor alpha (PPARα) and CCAAT/enhancer binding protein beta (C/EBPβ) binding directly downstream of the Cpt1a transcription start site within the first intron. Findings were confirmed in rat hepatoma H4IIEC3 cells treated with non-esterified fatty acid (NEFA). After 12 h of NEFA treatment, there was an enrichment of SWI/SNF related matrix associated actin dependent regulator of chromatin subfamily D member 1 (BAF60a or SMARCD1) in the first intron of Cpt1a. We conclude that dietary fat elevates hepatic Cpt1a expression via a highly coordinated transcriptional mechanism involving increased H3K4Me2, reduced DNAMe, and recruitment of C/EBPβ, PPARα, PGC1α, and BAF60a to the gene.
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Affiliation(s)
- Laura Moody
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States of America.
| | - Guanying Bianca Xu
- Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States of America.
| | - Hong Chen
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States of America; Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States of America.
| | - Yuan-Xiang Pan
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States of America; Department of Food Science and Human Nutrition, University of Illinois at Urbana-Champaign, Urbana, IL 61801, United States of America; Illinois Informatics Institute, University of Illinois at Urbana-Champaign, Urbana, IL, 61801, United States of America.
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27
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Huang JV, Cardenas A, Colicino E, Schooling CM, Rifas-Shiman SL, Agha G, Zheng Y, Hou L, Just AC, Litonjua AA, DeMeo DL, Lin X, Oken E, Hivert MF, Baccarelli AA. DNA methylation in blood as a mediator of the association of mid-childhood body mass index with cardio-metabolic risk score in early adolescence. Epigenetics 2018; 13:1072-1087. [PMID: 30412002 PMCID: PMC6342073 DOI: 10.1080/15592294.2018.1543503] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2018] [Revised: 09/20/2018] [Accepted: 10/22/2018] [Indexed: 12/16/2022] Open
Abstract
Obesity is associated with higher cardio-metabolic risk even in childhood and adolescence; whether this association is mediated by epigenetic mechanisms remains unclear. We examined the extent to which mid-childhood body mass index (BMI) z-score (median age 7.7 years) was associated with cardio-metabolic risk score in early adolescence (median age 12.9 years) via mid-childhood DNA methylation among 265 children in the Project Viva. We measured DNA methylation in leukocytes using the Infinium Human Methylation450K BeadChip. We assessed mediation CpG-by-CpG using epigenome-wide association analyses, high-dimensional mediation analysis, and natural effect models. We observed mediation by mid-childhood DNA methylation at 6 CpGs for the association between mid-childhood BMI z-score and cardio-metabolic risk score in early adolescence in the high-dimensional mediation analysis (accounting for 10% of the total effect) and in the natural effect model (β = 0.04, P = 3.2e-2, accounting for 13% of the total effect). The natural direct effect of BMI z-score on cardio-metabolic risk score was still evident (β = 0.27, P = 1.1e-25). We also observed mediation by mid-childhood DNA methylation at 5 CpGs that was in the opposite direction from the total effect (natural effect model: β = -0.04, P = 2.0e-2). Mediation in different directions implies a complex role of DNA methylation in the association between BMI and cardio-metabolic risk and needs further investigation. Future studies with larger sample size and greater variability in cardio-metabolic risk will further help elucidate the role of DNA methylation for cardio-metabolic risk.
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Affiliation(s)
- Jian V. Huang
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, NY, NY, USA
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
| | - Andres Cardenas
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Elena Colicino
- Department of Environmental Medicine & Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - C. Mary Schooling
- School of Public Health, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Graduate School of Public Health and Health Policy, City University of New York, New York, USA
| | - Sheryl L. Rifas-Shiman
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
| | - Golareh Agha
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, NY, NY, USA
| | - Yinan Zheng
- Center for Population Epigenetics, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Lifang Hou
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Allan C. Just
- Department of Environmental Medicine & Public Health, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Augusto A. Litonjua
- Division of Pediatric Pulmonary Medicine, Department of Pediatrics, University of Rochester Medical Center, Rochester, NY, USA
| | - Dawn L. DeMeo
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Xihong Lin
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Emily Oken
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Marie-France Hivert
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Andrea A. Baccarelli
- Department of Environmental Health Sciences, Columbia Mailman School of Public Health, NY, NY, USA
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28
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Abstract
Epigenetics is the study of heritable mechanisms that can modify gene activity and phenotype without modifying the genetic code. The basis for the concept of epigenetics originated more than 2,000 yr ago as a theory to explain organismal development. However, the definition of epigenetics continues to evolve as we identify more of the components that make up the epigenome and dissect the complex manner by which they regulate and are regulated by cellular functions. A substantial and growing body of research shows that nutrition plays a significant role in regulating the epigenome. Here, we critically assess this diverse body of evidence elucidating the role of nutrition in modulating the epigenome and summarize the impact such changes have on molecular and physiological outcomes with regards to human health.
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Affiliation(s)
- Folami Y Ideraabdullah
- Departments of Genetics and Nutrition, Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, North Carolina; and Departments of Nutrition and Pediatrics, Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, North Carolina
| | - Steven H Zeisel
- Departments of Genetics and Nutrition, Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, North Carolina; and Departments of Nutrition and Pediatrics, Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, North Carolina
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29
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Abstract
BACKGROUND Longitudinal data and repeated measurements in epigenome-wide association studies (EWAS) provide a rich resource for understanding epigenetics. We summarize 7 analytical approaches to the GAW20 data sets that addressed challenges and potential applications of phenotypic and epigenetic data. All contributions used the GAW20 real data set and employed either linear mixed effect (LME) models or marginal models through generalized estimating equations (GEE). These contributions were subdivided into 3 categories: (a) quality control (QC) methods for DNA methylation data; (b) heritability estimates pretreatment and posttreatment with fenofibrate; and (c) impact of drug response pretreatment and posttreatment with fenofibrate on DNA methylation and blood lipids. RESULTS Two contributions addressed QC and identified large statistical differences with pretreatment and posttreatment DNA methylation, possibly a result of batch effects. Two contributions compared epigenome-wide heritability estimates pretreatment and posttreatment, with one employing a Bayesian LME and the other using a variance-component LME. Density curves comparing these studies indicated these heritability estimates were similar. Another contribution used a variance-component LME to depict the proportion of heritability resulting from a genetic and shared environment. By including environmental exposures as random effects, the authors found heritability estimates became more stable but not significantly different. Two contributions investigated treatment response. One estimated drug-associated methylation effects on triglyceride levels as the response, and identified 11 significant cytosine-phosphate-guanine (CpG) sites with or without adjusting for high-density lipoprotein. The second contribution performed weighted gene coexpression network analysis and identified 6 significant modules of at least 30 CpG sites, including 3 modules with topological differences pretreatment and posttreatment. CONCLUSIONS Four conclusions from this GAW20 working group are: (a) QC measures are an important consideration for EWAS studies that are investigating multiple time points or repeated measurements; (b) application of heritability estimates between time points for individual CpG sites is a useful QC measure for DNA methylation studies; (c) drug intervention demonstrated strong epigenome-wide DNA methylation patterns across the 2 time points; and (d) new statistical methods are required to account for the environmental contributions of DNA methylation across time. These contributions demonstrate numerous opportunities exist for the analysis of longitudinal data in future epigenetic studies.
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Affiliation(s)
- Haakon E. Nustad
- Department of Medical Genetics, Oslo University Hospital, Kirkeveien 166, 0450 Oslo, Norway
- Faculty of Medicine, University of Oslo, Klaus Torgårds vei 3, 0372 Oslo, Norway
- PharmaTox Strategic Research Initiative, University of Oslo, Sem Sælands vei 3, 0371 Oslo, Norway
| | - Marcio Almeida
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley School of Medicine, One West University Blvd., STDOI Modular Building #100, Brownsville, TX 78520 USA
| | - Angelo J. Canty
- Department of Mathematics and Statistics, McMaster University, 1280 Main St. W, Hamilton, ON L8S 4K1 Canada
| | - Marissa LeBlanc
- Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Klaus Torgårds vei 3, 0372 Oslo, Norway
| | - Christian M. Page
- Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Klaus Torgårds vei 3, 0372 Oslo, Norway
- Department of Non-communicable disease, Norwegian Institute of Public Health, Marcus Thranes Gate 6, 0473 Oslo, Norway
| | - Phillip E. Melton
- Curtin/UWA Centre for Genetic Origins of Health and Disease, School of Pharmacy and Biomedical Sciences, Curtin University and the University of Western Australia, 35 Stirling Hwy. (M409), Crawley, WA 6009 Australia
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30
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Fernández-Rhodes L, Howard AG, Tao R, Young KL, Graff M, Aiello AE, North KE, Justice AE. Characterization of the contribution of shared environmental and genetic factors to metabolic syndrome methylation heritability and familial correlations. BMC Genet 2018; 19:69. [PMID: 30255772 PMCID: PMC6157030 DOI: 10.1186/s12863-018-0634-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023] Open
Abstract
Background Transgenerational epigenetic inheritance has been posited as a possible contributor to the observed heritability of metabolic syndrome (MetS). Yet the extent to which estimates of epigenetic inheritance for DNA methylation sites are inflated by environmental and genetic covariance within families is still unclear. We applied current methods to quantify the environmental and genetic contributors to the observed heritability and familial correlations of four previously associated MetS methylation sites at three genes (CPT1A, SOCS3 and ABCG1) using real data made available through the GAW20. Results Our findings support the role of both shared environment and genetic variation in explaining the heritability of MetS and the four MetS cytosine-phosphate-guanine (CpG) sites, although the resulting heritability estimates were indistinguishable from one another. Familial correlations by type of relative pair generally followed our expectation based on relatedness, but in the case of sister and parent pairs we observed nonsignificant trends toward greater correlation than expected, as would be consistent with the role of shared environmental factors in the inflation of our estimated correlations. Conclusions Our work provides an interesting and flexible statistical framework for testing models of epigenetic inheritance in the context of human family studies. Future work should endeavor to replicate our findings and advance these methods to more robustly describe epigenetic inheritance patterns in human populations.
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Affiliation(s)
- Lindsay Fernández-Rhodes
- Department of Epidemiology, University of North Carolina at Chapel Hill, 137 East Franklin Street, Chapel Hill, NC, 27514, USA. .,Carolina Population Center, University of North Carolina at Chapel Hill, 136 East Franklin Street, Chapel Hill, NC, 27514, USA.
| | - Annie Green Howard
- Carolina Population Center, University of North Carolina at Chapel Hill, 136 East Franklin Street, Chapel Hill, NC, 27514, USA.,Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, 137 East Franklin Street, Chapel Hill, Chapel Hill, NC, 27514, USA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt University Medical Center, 2525 West End Avenue, Nashville, TN, 37203, USA
| | - Kristin L Young
- Department of Epidemiology, University of North Carolina at Chapel Hill, 137 East Franklin Street, Chapel Hill, NC, 27514, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, 137 East Franklin Street, Chapel Hill, NC, 27514, USA
| | - Allison E Aiello
- Department of Epidemiology, University of North Carolina at Chapel Hill, 137 East Franklin Street, Chapel Hill, NC, 27514, USA.,Carolina Population Center, University of North Carolina at Chapel Hill, 136 East Franklin Street, Chapel Hill, NC, 27514, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, 137 East Franklin Street, Chapel Hill, NC, 27514, USA
| | - Anne E Justice
- Department of Epidemiology, University of North Carolina at Chapel Hill, 137 East Franklin Street, Chapel Hill, NC, 27514, USA
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31
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Abstract
PURPOSE OF REVIEW It is becoming increasingly evident that epigenetic mechanisms, particularly DNA methylation, play a role in the regulation of blood lipid levels and lipid metabolism-linked phenotypes and diseases. RECENT FINDINGS Recent genome-wide methylation and candidate gene studies of blood lipids have highlighted several robustly replicated methylation markers across different ethnicities. Furthermore, many of these lipid-related CpG sites associated with blood lipids are also linked to lipid-related phenotypes and diseases. Integrating epigenome-wide association studies (EWAS) data with other layers of molecular data such as genetics or the transcriptome, accompanied by relevant statistical methods (e.g. Mendelian randomization), provides evidence for causal relationships. Recent data suggest that epigenetic changes can be consequences rather than causes of dyslipidemia. There is sparse information on many lipid classes and disorders of lipid metabolism, and also on the interplay of DNA methylation with other epigenetic layers such as histone modifications and regulatory RNAs. SUMMARY The current review provides a literature overview of epigenetic modifications in lipid metabolism and other lipid-related phenotypes and diseases focusing on EWAS of DNA methylation from January 2016 to September 2017. Recent studies strongly support the importance of epigenetic modifications, such as DNA methylation, in lipid metabolism and related diseases for relevant biological insights, reliable biomarkers, and even future therapeutics.
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Affiliation(s)
- Kirstin Mittelstraß
- Research Unit of Molecular Epidemiology
- Institute of Epidemiology, Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany
| | - Melanie Waldenberger
- Research Unit of Molecular Epidemiology
- Institute of Epidemiology, Helmholtz Zentrum München, Deutsches Forschungszentrum für Gesundheit und Umwelt (GmbH), Neuherberg, Germany
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32
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Titus AJ, Gallimore RM, Salas LA, Christensen BC. Cell-type deconvolution from DNA methylation: a review of recent applications. Hum Mol Genet 2018; 26:R216-R224. [PMID: 28977446 PMCID: PMC5886462 DOI: 10.1093/hmg/ddx275] [Citation(s) in RCA: 130] [Impact Index Per Article: 18.6] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2017] [Accepted: 07/11/2017] [Indexed: 02/07/2023] Open
Abstract
Recent advances in cell-type deconvolution approaches are adding to our understanding of the biology underlying disease development and progression. DNA methylation (DNAm) can be used as a biomarker of cell types, and through deconvolution approaches, to infer underlying cell type proportions. Cell-type deconvolution algorithms have two main categories: reference-based and reference-free. Reference-based algorithms are supervised methods that determine the underlying composition of cell types within a sample by leveraging differentially methylated regions (DMRs) specific to cell type, identified from DNAm measures of purified cell populations. Reference-free algorithms are unsupervised methods for use when cell-type specific DMRs are not available, allowing scientists to estimate putative cellular proportions or control for potential confounding from cell type. Reference-based deconvolution is typically applied to blood samples and has potentiated our understanding of the relation between immune profiles and disease by allowing estimation of immune cell proportions from archival DNA. Bioinformatic analyses using DNAm to infer immune cell proportions, part of a new field known as Immunomethylomics, provides a new direction for consideration in epigenome wide association studies (EWAS).
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Affiliation(s)
- Alexander J Titus
- Program in Quantitative Biomedical Sciences.,Department of Epidemiology
| | | | | | - Brock C Christensen
- Department of Epidemiology.,Department of Molecular and Systems Biology.,Department of Community and Family Medicine, Geisel School of Medicine at Dartmouth College, Hanover, NH 03755, USA
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33
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Rozman J, Rathkolb B, Oestereicher MA, Schütt C, Ravindranath AC, Leuchtenberger S, Sharma S, Kistler M, Willershäuser M, Brommage R, Meehan TF, Mason J, Haselimashhadi H, Hough T, Mallon AM, Wells S, Santos L, Lelliott CJ, White JK, Sorg T, Champy MF, Bower LR, Reynolds CL, Flenniken AM, Murray SA, Nutter LMJ, Svenson KL, West D, Tocchini-Valentini GP, Beaudet AL, Bosch F, Braun RB, Dobbie MS, Gao X, Herault Y, Moshiri A, Moore BA, Kent Lloyd KC, McKerlie C, Masuya H, Tanaka N, Flicek P, Parkinson HE, Sedlacek R, Seong JK, Wang CKL, Moore M, Brown SD, Tschöp MH, Wurst W, Klingenspor M, Wolf E, Beckers J, Machicao F, Peter A, Staiger H, Häring HU, Grallert H, Campillos M, Maier H, Fuchs H, Gailus-Durner V, Werner T, Hrabe de Angelis M. Identification of genetic elements in metabolism by high-throughput mouse phenotyping. Nat Commun 2018; 9:288. [PMID: 29348434 PMCID: PMC5773596 DOI: 10.1038/s41467-017-01995-2] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2016] [Accepted: 10/30/2017] [Indexed: 12/20/2022] Open
Abstract
Metabolic diseases are a worldwide problem but the underlying genetic factors and their relevance to metabolic disease remain incompletely understood. Genome-wide research is needed to characterize so-far unannotated mammalian metabolic genes. Here, we generate and analyze metabolic phenotypic data of 2016 knockout mouse strains under the aegis of the International Mouse Phenotyping Consortium (IMPC) and find 974 gene knockouts with strong metabolic phenotypes. 429 of those had no previous link to metabolism and 51 genes remain functionally completely unannotated. We compared human orthologues of these uncharacterized genes in five GWAS consortia and indeed 23 candidate genes are associated with metabolic disease. We further identify common regulatory elements in promoters of candidate genes. As each regulatory element is composed of several transcription factor binding sites, our data reveal an extensive metabolic phenotype-associated network of co-regulated genes. Our systematic mouse phenotype analysis thus paves the way for full functional annotation of the genome.
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Affiliation(s)
- Jan Rozman
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Birgit Rathkolb
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- Ludwig-Maximilians-Universität München, Gene Center, Institute of Molecular Animal Breeding and Biotechnology, Feodor-Lynen Strasse 25, 81377, Munich, Germany
| | - Manuela A Oestereicher
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Christine Schütt
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Aakash Chavan Ravindranath
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Stefanie Leuchtenberger
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Sapna Sharma
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Institute of Epidemiology II, Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Martin Kistler
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Monja Willershäuser
- Chair of Molecular Nutritional Medicine, Technical University of Munich, TUM School of Life Sciences Weihenstephan, 85354, Freising, Germany
- EKFZ - Else Kröner-Fresenius Center for Nutritional Medicine, Technical University of Munich, 85354, Freising, Germany
- ZIEL - Institute for Food & Health, Technical University of Munich, 85354, Freising, Germany
| | - Robert Brommage
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Terrence F Meehan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Jeremy Mason
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Hamed Haselimashhadi
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Tertius Hough
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Oxfordshire, OX11 0RD, UK
| | - Ann-Marie Mallon
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Oxfordshire, OX11 0RD, UK
| | - Sara Wells
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Oxfordshire, OX11 0RD, UK
| | - Luis Santos
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Oxfordshire, OX11 0RD, UK
| | - Christopher J Lelliott
- The Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
| | - Jacqueline K White
- The Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SA, UK
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, 04609, USA
| | - Tania Sorg
- CELPHEDIA, PHENOMIN, Institut Clinique de la Souris (ICS), 1 Rue Laurent Fries, 67404, Illkirch-Graffenstaden, France
- Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Parc d'innovation, 1 Rue Laurent Fries - BP 10142, 67404, Illkirch, France
- Centre National de la Recherche Scientifique, UMR7104, 67404, Illkirch, France
- Institut National de la Santé et de la Recherche Médicale, U964, 67404, Illkirch, France
- Université de Strasbourg, 67404, Illkirch, France
| | - Marie-France Champy
- CELPHEDIA, PHENOMIN, Institut Clinique de la Souris (ICS), 1 Rue Laurent Fries, 67404, Illkirch-Graffenstaden, France
- Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Parc d'innovation, 1 Rue Laurent Fries - BP 10142, 67404, Illkirch, France
- Centre National de la Recherche Scientifique, UMR7104, 67404, Illkirch, France
- Institut National de la Santé et de la Recherche Médicale, U964, 67404, Illkirch, France
- Université de Strasbourg, 67404, Illkirch, France
| | - Lynette R Bower
- Mouse Biology Program, University of California, One Shields Avenue, Davis, CA, 95616, USA
| | - Corey L Reynolds
- Department of Molecular and Human Genetics, Baylor College of Medicine, 7702 Main St, Houston Medical Center, Houston, TX, 77030-4406, USA
| | - Ann M Flenniken
- The Centre for Phenogenomics, 25 Orde St, Toronto, M5T 3H7, ON, Canada
- The Hospital for Sick Children, 600 University Avenue, Toronto, ON, M5G 1X5, Canada
- Lunenfeld-Tanenbaum Research Institute, Mount Sinai Hospital, Joseph and Wolf Lebovic Health Complex, 600 University Avenue, Toronto, ON, M5G 1X5, Canada
| | - Stephen A Murray
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, 04609, USA
| | - Lauryl M J Nutter
- The Centre for Phenogenomics, 25 Orde St, Toronto, M5T 3H7, ON, Canada
- The Hospital for Sick Children, 600 University Avenue, Toronto, ON, M5G 1X5, Canada
| | - Karen L Svenson
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, 04609, USA
| | - David West
- Children's Hospital Oakland Research Institute, 5700 Martin Luther King Jr. Way, Oakland, CA, 94609, USA
| | - Glauco P Tocchini-Valentini
- Monterotondo Mouse Clinic, Italian National Research Council (CNR), Institute of Cell Biology and Neurobiology, Adriano Buzzati-Traverso Campus, Via E. Ramarini 32, Monterotondo Scalo, RM, 00015, Italy
| | - Arthur L Beaudet
- The Centre for Phenogenomics, 25 Orde St, Toronto, M5T 3H7, ON, Canada
- The Hospital for Sick Children, 600 University Avenue, Toronto, ON, M5G 1X5, Canada
| | - Fatima Bosch
- Center of Animal Biotechnology and Gene Therapy and Department of Biochemistry and Molecular Biology, Universitat Autònoma de Barcelona, Bellaterra, Spain
| | - Robert B Braun
- The Jackson Laboratory, 600 Main Street, Bar Harbor, ME, 04609, USA
| | - Michael S Dobbie
- Australian Phenomics Network, John Curtin School of Medical Research, Australian National University, 131 Garran Road, Canberra, ACT, 2601, Australia
| | - Xiang Gao
- SKL of Pharmaceutical Biotechnology and Model Animal Research Center, Collaborative Innovation Center for Genetics and Development, Nanjing Biomedical Research Institute, Nanjing University, Nanjing, 210061, China
| | - Yann Herault
- CELPHEDIA, PHENOMIN, Institut Clinique de la Souris (ICS), 1 Rue Laurent Fries, 67404, Illkirch-Graffenstaden, France
- Institut de Génétique et de Biologie Moléculaire et Cellulaire (IGBMC), Parc d'innovation, 1 Rue Laurent Fries - BP 10142, 67404, Illkirch, France
- Centre National de la Recherche Scientifique, UMR7104, 67404, Illkirch, France
- Institut National de la Santé et de la Recherche Médicale, U964, 67404, Illkirch, France
- Université de Strasbourg, 67404, Illkirch, France
| | - Ala Moshiri
- Department of Ophthalmology & Vision Science, School of Medicine, U.C. Davis, 77 Cadillac Drive, Sacramento, 95825, CA, USA
| | - Bret A Moore
- William R. Pritchard Veterinary Medical Teaching Hospital, School of Veterinary Medicine, U.C. Davis, One Shields Avenue, Davis, 95616, CA, USA
| | - K C Kent Lloyd
- Mouse Biology Program, University of California, One Shields Avenue, Davis, CA, 95616, USA
| | - Colin McKerlie
- The Centre for Phenogenomics, 25 Orde St, Toronto, M5T 3H7, ON, Canada
- The Hospital for Sick Children, 600 University Avenue, Toronto, ON, M5G 1X5, Canada
| | - Hiroshi Masuya
- RIKEN BioResource Center, 3-1-1 Koyadai, Tsukuba, Ibaraki, 305-0074, Japan
| | - Nobuhiko Tanaka
- RIKEN BioResource Center, 3-1-1 Koyadai, Tsukuba, Ibaraki, 305-0074, Japan
| | - Paul Flicek
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Helen E Parkinson
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Radislav Sedlacek
- Czech Centre for Phenogenomics, Institute of Molecular Genetics, Prumyslova 595, 252 50, Vestec, Czech Republic
| | - Je Kyung Seong
- Korea Mouse Phenotyping Consortium (KMPC) and BK21 Program for Veterinary Science, Research Institute for Veterinary Science, College of Veterinary Medicine, Seoul National University, 599 Gwanangno, Gwanak-gu, Seoul, 151-742, South Korea
| | - Chi-Kuang Leo Wang
- National Laboratory Animal Center, National Applied Research Laboratories (NARLabs), 128 Yen-Chiou-Yuan Rd., Sec. 2, Nankang, Taipei, 11529, Taiwan
| | | | - Steve D Brown
- Medical Research Council Harwell (Mammalian Genetics Unit and Mary Lyon Centre), Oxfordshire, OX11 0RD, UK
| | - Matthias H Tschöp
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- Institute for Diabetes and Obesity, Helmholtz Diabetes Center at Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), 85764, Neuherberg, Germany
- Division of Metabolic Diseases, Department of Medicine, Technische Universität München, 80333, Munich, Germany
| | - Wolfgang Wurst
- Institute of Developmental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health GmbH, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
- Chair of Developmental Genetics, Center of Life and Food Sciences Weihenstephan, Technische Universität München, Ingolstädter Landstrasse 1, 85764, Neuherberg, Germany
- Deutsches Institut für Neurodegenerative Erkrankungen (DZNE) Site Munich, Feodor-Lynen-Str. 17, 81377, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Adolf-Butenandt-Institut, Ludwig-Maximilians-Universität München, Feodor-Lynen-Str. 17, 81377, Munich, Germany
| | - Martin Klingenspor
- Chair of Molecular Nutritional Medicine, Technical University of Munich, TUM School of Life Sciences Weihenstephan, 85354, Freising, Germany
- EKFZ - Else Kröner-Fresenius Center for Nutritional Medicine, Technical University of Munich, 85354, Freising, Germany
- ZIEL - Institute for Food & Health, Technical University of Munich, 85354, Freising, Germany
| | - Eckhard Wolf
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- Ludwig-Maximilians-Universität München, Gene Center, Institute of Molecular Animal Breeding and Biotechnology, Feodor-Lynen Strasse 25, 81377, Munich, Germany
| | - Johannes Beckers
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- Chair of Experimental Genetics, School of Life Science Weihenstephan, Technische Universität München, Alte Akademie 8, 85354, Freising, Germany
| | - Fausto Machicao
- Department of Internal Medicine, Division of Endocrinology, Diabetology, Vascular Medicine, Nephrology and Clinical Chemistry, University of Tübingen, 72076, Tübingen, Germany
| | - Andreas Peter
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- Department of Internal Medicine, Division of Endocrinology, Diabetology, Vascular Medicine, Nephrology and Clinical Chemistry, University of Tübingen, 72076, Tübingen, Germany
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the Eberhard-Karls-University of Tuebingen, Otfried-Müller-Str. 10, 72076, Tübingen, Germany
| | - Harald Staiger
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the Eberhard-Karls-University of Tuebingen, Otfried-Müller-Str. 10, 72076, Tübingen, Germany
- Institute of Pharmaceutical Sciences, Department of Pharmacy and Biochemistry, Eberhard Karls University Tübingen, 72076, Tübingen, Germany
| | - Hans-Ulrich Häring
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- Department of Internal Medicine, Division of Endocrinology, Diabetology, Vascular Medicine, Nephrology and Clinical Chemistry, University of Tübingen, 72076, Tübingen, Germany
- Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Center Munich at the Eberhard-Karls-University of Tuebingen, Otfried-Müller-Str. 10, 72076, Tübingen, Germany
| | - Harald Grallert
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Institute of Epidemiology II, Helmholtz Zentrum München, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- Clinical Cooperation Group Type 2 Diabetes, Helmholtz Zentrum München and Ludwig-Maximilians Universität München, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Monica Campillos
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
- Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Holger Maier
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Helmut Fuchs
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Valerie Gailus-Durner
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany
| | - Thomas Werner
- Internal Medicine Nephrology and Center for Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Martin Hrabe de Angelis
- German Mouse Clinic, Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.
- German Center for Diabetes Research (DZD), Ingolstädter Landstr. 1, 85764, Neuherberg, Germany.
- Chair of Experimental Genetics, School of Life Science Weihenstephan, Technische Universität München, Alte Akademie 8, 85354, Freising, Germany.
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Tobi EW, Slieker RC, Luijk R, Dekkers KF, Stein AD, Xu KM, Slagboom PE, van Zwet EW, Lumey LH, Heijmans BT. DNA methylation as a mediator of the association between prenatal adversity and risk factors for metabolic disease in adulthood. SCIENCE ADVANCES 2018; 4:eaao4364. [PMID: 29399631 PMCID: PMC5792223 DOI: 10.1126/sciadv.aao4364] [Citation(s) in RCA: 158] [Impact Index Per Article: 22.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2017] [Accepted: 01/03/2018] [Indexed: 05/05/2023]
Abstract
Although it is assumed that epigenetic mechanisms, such as changes in DNA methylation (DNAm), underlie the relationship between adverse intrauterine conditions and adult metabolic health, evidence from human studies remains scarce. Therefore, we evaluated whether DNAm in whole blood mediated the association between prenatal famine exposure and metabolic health in 422 individuals exposed to famine in utero and 463 (sibling) controls. We implemented a two-step analysis, namely, a genome-wide exploration across 342,596 cytosine-phosphate-guanine dinucleotides (CpGs) for potential mediators of the association between prenatal famine exposure and adult body mass index (BMI), serum triglycerides (TG), or glucose concentrations, which was followed by formal mediation analysis. DNAm mediated the association of prenatal famine exposure with adult BMI and TG but not with glucose. DNAm at PIM3 (cg09349128), a gene involved in energy metabolism, mediated 13.4% [95% confidence interval (CI), 5 to 28%] of the association between famine exposure and BMI. DNAm at six CpGs, including TXNIP (cg19693031), influencing β cell function, and ABCG1 (cg07397296), affecting lipid metabolism, together mediated 80% (95% CI, 38.5 to 100%) of the association between famine exposure and TG. Analyses restricted to those exposed to famine during early gestation identified additional CpGs mediating the relationship with TG near PFKFB3 (glycolysis) and METTL8 (adipogenesis). DNAm at the CpGs involved was associated with gene expression in an external data set and correlated with DNAm levels in fat depots in additional postmortem data. Our data are consistent with the hypothesis that epigenetic mechanisms mediate the influence of transient adverse environmental factors in early life on long-term metabolic health. The specific mechanism awaits elucidation.
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Affiliation(s)
- Elmar W. Tobi
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC Leiden, Netherlands
- Division of Human Nutrition, Wageningen University and Research, 6708 WE Wageningen, Netherlands
| | - Roderick C. Slieker
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC Leiden, Netherlands
| | - René Luijk
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC Leiden, Netherlands
- Medical Statistics, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC Leiden, Netherlands
| | - Koen F. Dekkers
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC Leiden, Netherlands
| | - Aryeh D. Stein
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Kate M. Xu
- Medical Statistics, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC Leiden, Netherlands
- Faculty of Psychology and Educational Sciences, Welten Institute, Open University of the Netherlands, 6419 AT Heerlen, Netherlands
| | | | - P. Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC Leiden, Netherlands
| | - Erik W. van Zwet
- Medical Statistics, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC Leiden, Netherlands
| | - L. H. Lumey
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC Leiden, Netherlands
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Bastiaan T. Heijmans
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC Leiden, Netherlands
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Avilés-Santa ML, Colón-Ramos U, Lindberg NM, Mattei J, Pasquel FJ, Pérez CM. From Sea to Shining Sea and the Great Plains to Patagonia: A Review on Current Knowledge of Diabetes Mellitus in Hispanics/Latinos in the US and Latin America. Front Endocrinol (Lausanne) 2017; 8:298. [PMID: 29176960 PMCID: PMC5687125 DOI: 10.3389/fendo.2017.00298] [Citation(s) in RCA: 24] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2017] [Accepted: 10/16/2017] [Indexed: 12/13/2022] Open
Abstract
The past two decades have witnessed many advances in the prevention, treatment, and control of diabetes mellitus (DM) and its complications. Increased screening has led to a greater recognition of type 2 diabetes mellitus (type 2 DM) and prediabetes; however, Hispanics/Latinos, the largest minority group in the US, have not fully benefited from these advances. The Hispanic/Latino population is highly diverse in ancestries, birth places, cultures, languages, and socioeconomic backgrounds, and it populates most of the Western Hemisphere. In the US, the prevalence of DM varies among Hispanic/Latino heritage groups, being higher among Mexicans, Puerto Ricans, and Dominicans, and lower among South Americans. The risk and prevalence of diabetes among Hispanics/Latinos are significantly higher than in non-Hispanic Whites, and nearly 40% of Hispanics/Latinos with diabetes have not been formally diagnosed. Despite these striking facts, the representation of Hispanics/Latinos in pharmacological and non-pharmacological clinical trials has been suboptimal, while the prevalence of diabetes in these populations continues to rise. This review will focus on the epidemiology, etiology and prevention of type 2 DM in populations of Latin American origin. We will set the stage by defining the terms Hispanic, Latino, and Latin American, explaining the challenges identifying Hispanics/Latinos in the scientific literature and databases, describing the epidemiology of diabetes-including type 2 DM and gestational diabetes mellitus (GDM)-and cardiovascular risk factors in Hispanics/Latinos in the US and Latin America, and discussing trends, and commonalities and differences across studies and populations, including methodology to ascertain diabetes. We will discuss studies on mechanisms of disease, and research on prevention of type 2 DM in Hispanics/Latinos, including women with GDM, youth and adults; and finalize with a discussion on lessons learned and opportunities to enhance research, and, consequently, clinical care oriented toward preventing type 2 DM in Hispanics/Latinos in the US and Latin America.
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Affiliation(s)
- M. Larissa Avilés-Santa
- National Heart, Lung, and Blood Institute at the National Institutes of Health, Bethesda, MD, United States
| | - Uriyoán Colón-Ramos
- Department of Global Health, Milken Institute School of Public Health, George Washington University, Washington, DC, United States
| | - Nangel M. Lindberg
- Kaiser Permanente Center for Health Research, Portland, OR, United States
| | - Josiemer Mattei
- Department of Nutrition, Harvard TH Chan School of Public Health, Boston, MA, United States
| | - Francisco J. Pasquel
- Department of Medicine, Emory University School of Medicine, Atlanta, GA, United States
| | - Cynthia M. Pérez
- University of Puerto Rico Graduate School of Public Health, San Juan, Puerto Rico
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Cheng Z, Zheng L, Almeida FA. Epigenetic reprogramming in metabolic disorders: nutritional factors and beyond. J Nutr Biochem 2017; 54:1-10. [PMID: 29154162 DOI: 10.1016/j.jnutbio.2017.10.004] [Citation(s) in RCA: 61] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2017] [Revised: 09/26/2017] [Accepted: 10/10/2017] [Indexed: 12/13/2022]
Abstract
Environmental factors (e.g., malnutrition and physical inactivity) contribute largely to metabolic disorders including obesity, type 2 diabetes, cardiometabolic disease and nonalcoholic fatty liver diseases. The abnormalities in metabolic activity and pathways have been increasingly associated with altered DNA methylation, histone modification and noncoding RNAs, whereas lifestyle interventions targeting diet and physical activity can reverse the epigenetic and metabolic changes. Here we review recent evidence primarily from human studies that links DNA methylation reprogramming to metabolic derangements or improvements, with a focus on cross-tissue (e.g., the liver, skeletal muscle, pancreas, adipose tissue and blood samples) epigenetic markers, mechanistic mediators of the epigenetic reprogramming, and the potential of using epigenetic traits to predict disease risk and intervention response. The challenges in epigenetic studies addressing the mechanisms of metabolic diseases and future directions are also discussed and prospected.
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Affiliation(s)
- Zhiyong Cheng
- Department of Human Nutrition, Foods, and Exercise, Fralin Translational Obesity Research Center, College of Agriculture and Life Science, Virginia Tech, Blacksburg, VA 24061, USA.
| | - Louise Zheng
- Department of Human Nutrition, Foods, and Exercise, Fralin Translational Obesity Research Center, College of Agriculture and Life Science, Virginia Tech, Blacksburg, VA 24061, USA
| | - Fabio A Almeida
- Department of Health Promotion, Social & Behavioral Health, College of Public Health, University of Nebraska Medical Center, Omaha, NE 68198, USA.
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Truong V, Huang S, Dennis J, Lemire M, Zwingerman N, Aïssi D, Kassam I, Perret C, Wells P, Morange PE, Wilson M, Trégouët DA, Gagnon F. Blood triglyceride levels are associated with DNA methylation at the serine metabolism gene PHGDH. Sci Rep 2017; 7:11207. [PMID: 28894120 PMCID: PMC5593822 DOI: 10.1038/s41598-017-09552-z] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2017] [Accepted: 07/18/2017] [Indexed: 12/14/2022] Open
Abstract
Efficient interventions to reduce blood triglycerides are few; newer and more tolerable intervention targets are needed. Understanding the molecular mechanisms underlying blood triglyceride levels variation is key to identifying new therapies. To explore the role of epigenetic mechanisms on triglyceride levels, a blood methylome scan was conducted in 199 individuals from 5 French-Canadian families ascertained on venous thromboembolism, and findings were replicated in 324 French unrelated patients with venous thromboembolism. Genetic context and functional relevance were investigated. Two DNA methylation sites associated with triglyceride levels were identified. The first one, located in the ABCG1 gene, was recently reported, whereas the second one, located in the promoter of the PHGDH gene, is novel. The PHGDH methylation site, cg14476101, was found to be associated with variation in triglyceride levels in a threshold manner: cg14476101 was inversely associated with triglyceride levels only when triglyceride levels were above 1.12 mmol/L (discovery P-value = 8.4 × 10-6; replication P-value = 0.0091). Public databases findings supported a functional role of cg14476101 on PHGDH expression. PHGDH catalyses the first step in the serine biosynthesis pathway. These findings highlight the role of epigenetic regulation of the PHGDH gene in triglyceride metabolism, providing novel insights on putative intervention targets.
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Affiliation(s)
- Vinh Truong
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Siying Huang
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Jessica Dennis
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | | | - Nora Zwingerman
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Dylan Aïssi
- Sorbonne Universités, UPMC Univ. Paris 06, INSERM, UMR_S 1166, Team Genomics & Pathophysiology of Cardiovascular Diseases, Paris, France
- ICAN Institute for Cardiometabolism and Nutrition, Paris, France
| | - Irfahan Kassam
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Claire Perret
- Sorbonne Universités, UPMC Univ. Paris 06, INSERM, UMR_S 1166, Team Genomics & Pathophysiology of Cardiovascular Diseases, Paris, France
- ICAN Institute for Cardiometabolism and Nutrition, Paris, France
| | - Philip Wells
- Department of Medicine, Faculty of Medicine, University of Ottawa, Ottawa, Canada
| | | | - Michael Wilson
- Genetics and Genome Biology Program, SickKids Research Institute, Toronto, Canada
| | - David-Alexandre Trégouët
- Sorbonne Universités, UPMC Univ. Paris 06, INSERM, UMR_S 1166, Team Genomics & Pathophysiology of Cardiovascular Diseases, Paris, France
- ICAN Institute for Cardiometabolism and Nutrition, Paris, France
| | - France Gagnon
- Division of Epidemiology, Dalla Lana School of Public Health, University of Toronto, Toronto, Canada.
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Critical Role of the Human ATP-Binding Cassette G1 Transporter in Cardiometabolic Diseases. Int J Mol Sci 2017; 18:ijms18091892. [PMID: 28869506 PMCID: PMC5618541 DOI: 10.3390/ijms18091892] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2017] [Revised: 08/30/2017] [Accepted: 08/30/2017] [Indexed: 12/15/2022] Open
Abstract
ATP-binding cassette G1 (ABCG1) is a member of the large family of ABC transporters which are involved in the active transport of many amphiphilic and lipophilic molecules including lipids, drugs or endogenous metabolites. It is now well established that ABCG1 promotes the export of lipids, including cholesterol, phospholipids, sphingomyelin and oxysterols, and plays a key role in the maintenance of tissue lipid homeostasis. Although ABCG1 was initially proposed to mediate cholesterol efflux from macrophages and then to protect against atherosclerosis and cardiovascular diseases (CVD), it becomes now clear that ABCG1 exerts a larger spectrum of actions which are of major importance in cardiometabolic diseases (CMD). Beyond a role in cellular lipid homeostasis, ABCG1 equally participates to glucose and lipid metabolism by controlling the secretion and activity of insulin and lipoprotein lipase. Moreover, there is now a growing body of evidence suggesting that modulation of ABCG1 expression might contribute to the development of diabetes and obesity, which are major risk factors of CVD. In order to provide the current understanding of the action of ABCG1 in CMD, we here reviewed major findings obtained from studies in mice together with data from the genetic and epigenetic analysis of ABCG1 in the context of CMD.
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Bell CG. The Epigenomic Analysis of Human Obesity. Obesity (Silver Spring) 2017; 25:1471-1481. [PMID: 28845613 DOI: 10.1002/oby.21909] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2017] [Revised: 05/09/2017] [Accepted: 05/11/2017] [Indexed: 12/31/2022]
Abstract
OBJECTIVE Analysis of the epigenome-the chemical modifications and packaging of the genome that can influence or indicate its activity-enables molecular insight into cell type-specific machinery. It can, therefore, reveal the pathophysiological mechanisms at work in disease. Detected changes can also represent physiological responses to adverse environmental exposures, thus enabling the epigenetic mark of DNA methylation to act as an epidemiological biomarker, even in surrogate tissue. This makes epigenomic analysis an attractive prospect to further understand the pathobiology and epidemiological aspects of obesity. Furthermore, integrating epigenomic data with known obesity-associated common genetic variation can aid in deciphering their molecular mechanisms. METHODS AND CONCLUSIONS This review primarily examines epidemiological or population-based studies of epigenetic modifications in relation to adiposity traits, as opposed to animal or cell models. It discusses recent work exploring the epigenome with respect to human obesity, which to date has predominately consisted of array-based studies of DNA methylation in peripheral blood. It is of note that highly replicated BMI DNA methylation associations are not causal, but strongly driven by coassociations for more precisely measured intertwined outcomes and factors, such as hyperlipidemia, hyperglycemia, and inflammation. Finally, the potential for the future exploration of the epigenome in obesity and related disorders is considered.
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Affiliation(s)
- Christopher G Bell
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
- Epigenomic Medicine, Biological Sciences, Faculty of Environmental and Natural Sciences, University of Southampton, Southampton, UK
- Human Development and Health Academic Unit, Institute of Developmental Sciences, University of Southampton, Southampton, UK
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
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40
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Fall T, Mendelson M, Speliotes EK. Recent Advances in Human Genetics and Epigenetics of Adiposity: Pathway to Precision Medicine? Gastroenterology 2017; 152:1695-1706. [PMID: 28214526 PMCID: PMC5576453 DOI: 10.1053/j.gastro.2017.01.054] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2016] [Revised: 01/26/2017] [Accepted: 01/30/2017] [Indexed: 12/26/2022]
Abstract
Obesity is a heritable trait that contributes to substantial global morbidity and mortality. Here, we summarize findings from the past decade of genetic and epigenetic research focused on unravelling the underpinnings of adiposity. More than 140 genetic regions now are known to influence adiposity traits. The genetics of general adiposity, as measured by body mass index, and that of abdominal obesity, as measured by waist-to-hip ratio, have distinct biological backgrounds. Gene expression associated with general adiposity is enriched in the nervous system. In contrast, genes associated with abdominal adiposity function in adipose tissue. Recent population-based epigenetic analyses have highlighted additional distinct loci. We discuss how associated genetic variants can lead to understanding causal mechanisms, and to disentangling reverse causation in epigenetic analyses. Discoveries emerging from population genomics are identifying new disease markers and potential novel drug targets to better define and combat obesity and related diseases.
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Affiliation(s)
- Tove Fall
- Department of Medical Sciences and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Michael Mendelson
- The Framingham Heart Study, Framingham, Massachusetts,Population Sciences Branch, National Heart, Lung and Blood Institute, National Institutes of Health, Bethesda, Maryland,Department of Cardiology, Boston Children’s Hospital, Boston, Massachusetts
| | - Elizabeth K. Speliotes
- Department of Internal Medicine, Division of Gastroenterology,Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
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Dunstan J, Bressler JP, Moran TH, Pollak JS, Hirsch AG, Bailey-Davis L, Glass TA, Schwartz BS. Associations of LEP, CRH, ICAM-1, and LINE-1 methylation, measured in saliva, with waist circumference, body mass index, and percent body fat in mid-childhood. Clin Epigenetics 2017; 9:29. [PMID: 28360946 PMCID: PMC5372250 DOI: 10.1186/s13148-017-0327-5] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2017] [Accepted: 03/18/2017] [Indexed: 12/28/2022] Open
Abstract
BACKGROUND Genetics explains a small proportion of variance in body mass index at the population level. Epigenetics, commonly measured by gene methylation, holds promise for understanding obesity risk factors and mechanisms. METHODS Participants were 431 adolescents aged 10-15 years. BMI z-score, waist circumference z-score, and percent body fat were measured. Saliva samples were collected and methylation of promoter regions of four candidate genes or sequences (LEP, ICAM-1, CRH, and LINE-1) were measured in 3-4 CpG sites each. Linear regression was used to identify associations of methylation with obesity-related outcomes. RESULTS After adjusting for age, in sex-stratified analysis, the three obesity-related outcomes were negatively associated with LEP methylation in obese boys only. There were no associations of methylation of the other genes or sequences and the obesity-related outcomes. CONCLUSIONS Our results are consistent with prior studies that reported sex differences in associations of obesity-related outcomes with LEP methylation, and also as would be expected in adipose tissue, the source of circulating leptin. The findings suggest that saliva might be an acceptable tissue for epigenetics studies in adolescents.
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Affiliation(s)
- Jocelyn Dunstan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA
| | - Joseph P. Bressler
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA
| | - Timothy H. Moran
- Department of Psychiatry and Behavioral Sciences, Johns Hopkins School of Medicine, Baltimore, MD USA
| | - Jonathan S. Pollak
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA
| | - Annemarie G. Hirsch
- Department of Epidemiology and Health Services Research, Geisinger Health System, Danville, PA USA
| | - Lisa Bailey-Davis
- Department of Epidemiology and Health Services Research, Geisinger Health System, Danville, PA USA
| | - Thomas A. Glass
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA
| | - Brian S. Schwartz
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD USA
- Department of Epidemiology and Health Services Research, Geisinger Health System, Danville, PA USA
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Sayols-Baixeras S, Irvin MR, Arnett DK, Elosua R, Aslibekyan SW. Epigenetics of Lipid Phenotypes. CURRENT CARDIOVASCULAR RISK REPORTS 2016; 10:31. [PMID: 28496562 PMCID: PMC5421987 DOI: 10.1007/s12170-016-0513-6] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
Dyslipidemia is a well-established risk factor for cardiovascular disease, the main cause of death worldwide. Blood lipid profiles are patterned by both genetic and environmental factors. In recent years, epigenetics has emerged as a paradigm that unifies these influences. In this review, we have summarized the latest evidence implicating epigenetic mechanisms-DNA methylation, histone modification, and regulation by RNAs-in lipid homeostasis. Key findings have emerged in a number of novel epigenetic loci located in biologically plausible genes (e.g. CPT1A, ABCG1, SREBF1, and others), as well as microRNA-33a/b. Evidence from animal and cell culture models suggests a complex interplay between different classes of epigenetic processes in the lipid-related genomic regions. While epigenetic findings hold the potential to explain the interindividual variability in lipid profiles as well as the underlying mechanisms, they have yet to be translated into effective therapies for dyslipidemia.
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Affiliation(s)
- Sergi Sayols-Baixeras
- Cardiovascular Epidemiology and Genetics Group, Institut Hospital del Mar d'Investigacions Mediques (IMIM), Dr. Aiguader, 88, Barcelona 08003, Spain, Universitat Pompeu Fabra (UPF), Barcelona 08003, Spain, (tel) 34-93-316-07-27, (fax) 34-93-316-04-10
| | - Marguerite R Irvin
- Department of Epidemiology, University of Alabama at Birmingham, 1665 University Blvd, RPHB 220F, Birmingham, AL 35205, USA, (tel) 1-205-975-7672, (fax)1-205-975-3329
| | - Donna K Arnett
- College of Public Health, University of Kentucky, 111 Washington Avenue, Lexington, KY 40536, USA, (tel) 1-859-257-5678, (fax) 1-859-257-8811
| | - Roberto Elosua
- Cardiovascular Epidemiology and Genetics Group, Institut Hospital del Mar d'Investigacions Mediques (IMIM), Dr. Aiguader, 88, Barcelona 08003, Spain, (tel) 34-93-316-08-00, (fax) 34-93-316-04-10
| | - Stella W Aslibekyan
- Department of Epidemiology, University of Alabama at Birmingham, 1665 University Blvd, RPHB 230J, Birmingham, AL 35205, USA, (tel) 1-205-975-7675, (fax) 1-205-975-3329
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