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Wang Z, Peng H, Gao W, Cao W, Lv J, Yu C, Huang T, Sun D, Wang B, Liao C, Pang Y, Pang Z, Cong L, Wang H, Wu X, Liu Y, Li L. Blood DNA methylation markers associated with type 2 diabetes, fasting glucose, and HbA1c levels: An epigenome-wide association study in 316 adult twin pairs. Genomics 2021; 113:4206-4213. [PMID: 34774679 DOI: 10.1016/j.ygeno.2021.11.005] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/09/2021] [Revised: 09/26/2021] [Accepted: 11/06/2021] [Indexed: 11/26/2022]
Abstract
DNA methylation plays an important role in the development and etiology of type 2 diabetes; however, few epigenomic studies have been conducted on twins. Herein, a two-stage study was performed to explore the associations between DNA methylation and type 2 diabetes, fasting plasma glucose, and HbA1c. DNA methylation in 316 twin pairs from the Chinese National Twin Registry (CNTR) was measured using Illumina Infinium BeadChips. In the discovery sample, the results revealed that 63 CpG sites and 6 CpG sites were significantly associated with fasting plasma glucose and HbA1c, respectively. In the replication sample, cg19690313 in TXNIP was associated with both fasting plasma glucose (P = 1.23 × 10-17, FDR < 0.001) and HbA1c (P = 2.29 × 10-18, FDR < 0.001). Furthermore, cg04816311, cg08309687, and cg09249494 may provide new insight in the metabolic mechanism of HbA1c. Our study provides solid evidence that cg19690313 on TXNIP correlates with HbA1c and fasting plasma glucose levels.
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Affiliation(s)
- Zhaonian Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Hexiang Peng
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Wenjing Gao
- 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
| | - Biqi Wang
- 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 Diseases 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
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
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Song YM, Lee K. Comparison of the associations between appendicular lean mass adjustment methods and cardiometabolic factors. Nutr Metab Cardiovasc Dis 2020; 30:2271-2278. [PMID: 32980247 DOI: 10.1016/j.numecd.2020.07.036] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 06/28/2020] [Accepted: 07/22/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND AND AIMS To compare the cross-sectional and longitudinal associations between appendicular lean mass (ALM) and cardiometabolic risk factors according to body-size adjustment methods and the contributions of genetic and/or environmental factors to the correlations between those traits. METHODS AND RESULTS Regression coefficients per sex-specific 1 standard deviation in bodyweight (wt), body mass index (BMI), or height-squared (ht2) adjusted ALM (assessed using a dual-energy X-ray absorptiometer (DXA) and a bioelectrical impedance analyzer (BIA) at baseline)/changes in these indices (assessed using BIA) were compared in terms of their associations with blood pressure (BP), lipid profiles, and insulin resistance profiles in 2655 participants for cross-sectional analysis and 332 participants for longitudinal analysis (follow-up time, 32.2 ± 7.9 months). A bivariate genetic analysis of the genetic/environmental cross-trait correlations was conducted to determine their cross-sectional relationships. After adjusting for sociodemographic factors, health behaviors, and BMI in the analysis for ALM/ht2, ALM/wt and ALM/BMI had favorable associations with all cardiometabolic risk factors, while ALM/ht2 had favorable associations with some risk factors. In longitudinal associations, changes in ALM/wt and ALM/BMI had inverse associations with increments of lipid profiles, insulin, and homeostasis model assessment of insulin resistance (HOMA), while change in ALM/ht2 did not have associations with increments of cardiometabolic risk factors. ALM/ht2 had genetic correlations with seven of nine risk factors; ALM/wt and ALM/BMI had correlations with three and one risk factors, respectively. CONCLUSION ALM/wt and ALM/BMI are better indicators for cardiometabolic risk factors; genetic factors may contribute more to the correlations between ALM/ht2 and those traits.
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Affiliation(s)
- Yun-Mi Song
- Department of Family Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Kayoung Lee
- Department of Family Medicine, Busan Paik Hospital, Inje University College of Medicine, Busan, Republic of Korea.
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Generali E, Ceribelli A, Stazi MA, Selmi C. Lessons learned from twins in autoimmune and chronic inflammatory diseases. J Autoimmun 2017; 83:51-61. [PMID: 28431796 DOI: 10.1016/j.jaut.2017.04.005] [Citation(s) in RCA: 78] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2017] [Accepted: 04/10/2017] [Indexed: 12/16/2022]
Abstract
Autoimmunity and chronic inflammation recognize numerous shared factors and, as a result, the resulting diseases frequently coexist in the same patients or respond to the same treatments. Among the convenient truths of autoimmune and chronic inflammatory diseases, there is now agreement that these are complex conditions in which the individual genetic predisposition provides a rate of heritability. The concordance rates in monozygotic and dizygotic twins allows to estimate the weight of the environment in determining disease susceptibility, despite recent data supporting that only a minority of immune markers depend on hereditary factors. Concordance rates in monozygotic and dizygotic twins should be evaluated over an observation period to minimize the risk of false negatives and this is well represented by type I diabetes mellitus. Further, concordance rates in monozygotic twins should be compared to those in dizygotic twins, which share 50% of their genes, as in regular siblings, but also young-age environmental factors. Twin studies have been extensively performed in several autoimmune conditions and cumulatively suggest that some diseases, i.e. celiac disease and psoriasis, are highly genetically determined, while rheumatoid arthritis or systemic sclerosis have a limited role for genetics. These observations are necessary to interpret data gathered by genome-wide association studies of polymorphisms and DNA methylation in MZ twins. New high-throughput technological platforms are awaited to provide new insights into the mechanisms of disease discordance in twins beyond strong associations such as those with HLA alleles.
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Affiliation(s)
- Elena Generali
- Division of Rheumatology and Clinical Immunology, Humanitas Research Hospital, Rozzano, Milan, Italy
| | - Angela Ceribelli
- Division of Rheumatology and Clinical Immunology, Humanitas Research Hospital, Rozzano, Milan, Italy
| | - Maria Antonietta Stazi
- Italian Twin Registry, Centre for Behavioural Sciences and Mental Health, Istituto Superiore di Sanità, Rome, Italy
| | - Carlo Selmi
- Division of Rheumatology and Clinical Immunology, Humanitas Research Hospital, Rozzano, Milan, Italy; BIOMETRA Department, University of Milan, Milan, Italy.
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