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O CK, Fan B, Tsoi STF, Tam CHT, Wan R, Lau ESH, Shi M, Lim CKP, Yu G, Ho JPY, Chow EYK, Kong APS, Ozaki R, So WY, Ma RCW, Luk AOY, Chan JCN. A polygenic risk score derived from common variants of monogenic diabetes genes is associated with young-onset type 2 diabetes and cardiovascular-kidney complications. Diabetologia 2025; 68:367-381. [PMID: 39579208 PMCID: PMC11732898 DOI: 10.1007/s00125-024-06320-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/05/2024] [Accepted: 09/16/2024] [Indexed: 11/25/2024]
Abstract
AIMS/HYPOTHESIS Monogenic diabetes is caused by rare mutations in genes usually implicated in beta cell biology. Common variants of monogenic diabetes genes (MDG) may jointly influence the risk of young-onset type 2 diabetes (YOD, diagnosed before the age of 40 years) and cardiovascular and kidney events. METHODS Using whole-exome sequencing data, we constructed a weighted polygenic risk score (wPRS) consisting of 135 common variants (minor allele frequency >0.01) of 34 MDG based on r2>0.2 for linkage disequilibrium in a discovery case-control cohort of 453 adults with YOD (median [IQR] age 39.7 [34.9-46.9] years) and 405 without YOD (median [IQR] age 56.7 [50.3-61.0] years), followed by validation in an independent cross-sectional cohort with array-based genotyping for YOD and a prospective cohort of individuals with type 2 diabetes for cardiovascular and kidney events. RESULTS In the discovery cohort, the OR of the 135 common variants for YOD ranged from 1.00 to 2.61. In the validation cohort (920 YOD and 4910 non-YOD), top-10%-wPRS was associated with an OR of 1.42 (95% CI 1.03, 1.95, p=0.033) for YOD compared with bottom-10%-wPRS. In 2313 individuals with type 2 diabetes (median [IQR]: age 53.4 [45.4-61.7] years; disease duration 4.0 [1.0-9.0] years) observed for a median (IQR) of 17.5 (14.4-21.8) years, standardised wPRS was associated with increased HR for incident cardiovascular events (1.16 [95% CI 1.06, 1.27], p=0.001), kidney events (1.09 [95% CI 1.02, 1.16], p=0.013) and cardiovascular-kidney events (1.10 [95% CI 1.03, 1.16], p=0.003). Using the 'bottom-20%-wPRS plus baseline disease duration <5 years' group as referent, the 'top-20%-wPRS plus baseline disease duration 5 to <10 years' group had unadjusted and adjusted HR of 1.60 (95% CI 1.17, 2.19, p=0.003) and 1.62 (95% CI 1.16, 2.26, p=0.005), respectively, for cardiovascular-kidney events compared with 1.38 (95% CI 0.97, 1.98, p=0.075) and 1.06 (95% CI 0.72, 1.57, p=0.752) in the 'bottom-20%-wPRS plus baseline disease duration ≥10 years' group. CONCLUSIONS/INTERPRETATION Common variants of MDG increased risk for YOD and cardiovascular-kidney events.
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Affiliation(s)
- Chun-Kwan O
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Baoqi Fan
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Sandra T F Tsoi
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Claudia H T Tam
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Raymond Wan
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Eric S H Lau
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Mai Shi
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Cadmon K P Lim
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Gechang Yu
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Jane P Y Ho
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Elaine Y K Chow
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Alice P S Kong
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Risa Ozaki
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Wing Yee So
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong, China.
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Lin B, Pan L, He H, Hu Y, Tu J, Zhang L, Cui Z, Ren X, Wang X, Nai J, Shan G. Heritability and genetic correlations of obesity indices and cardiometabolic traits in the Northern Chinese families. Ann Hum Genet 2025; 89:1-11. [PMID: 39239922 DOI: 10.1111/ahg.12578] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Revised: 08/11/2024] [Accepted: 08/21/2024] [Indexed: 09/07/2024]
Abstract
OBJECTIVE This study aimed to investigate the heritability of various obesity indices and their shared genetic factors with cardiometabolic traits in the Chinese nuclear family. METHODS A total of 1270 individuals from 538 nuclear families were included in this cross-sectional study. Different indices were used to quantify fat mass and distribution, including body index mass (BMI), visceral fat index (VFI), and body fat percent (BFP). Heritability and genetic correlations for all quantitative traits were estimated using variance component models. The susceptibility-threshold model was utilized to estimate the heritability for binary traits. RESULTS Heritability estimates for obesity indices were highest for BMI (59%), followed by BFP (49%), and VFI (40%). Heritability estimates for continuous cardiometabolic traits varied from 24% to 50%. All obesity measures exhibited consistently significant positive genetic correlations with blood pressure, fasting blood glucose, and uric acid (rG range: 0.26-0.57). However, diverse genetic correlations between various obesity indices and lipid profiles were observed. Significant genetic correlations were limited to specific pairs: BFP and total cholesterol (rG = 0.24), BFP and low-density lipoprotein cholesterol (rG = 0.25), and VFI and triglyceride (rG = 0.33). CONCLUSION The genetic overlap between various obesity indices and cardiometabolic traits underscores the importance of pleiotropic genes. Further studies are warranted to investigate specific shared genetic and environmental factors between obesity and cardiometabolic diseases.
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Affiliation(s)
- Binbin Lin
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Li Pan
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Huijing He
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Yaoda Hu
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Ji Tu
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
| | - Ling Zhang
- Department of Epidemiology and Health Statistics, School of Public Health, Capital Medical University, Beijing, China
| | - Ze Cui
- Department of Chronic and Noncommunicable Disease Prevention and Control, Hebei Provincial Center for Disease Control and Prevention, Shijiazhuang, Hebei, China
| | - Xiaolan Ren
- Department of Chronic and Noncommunicable Disease Prevention and Control, Gansu Provincial Center for Disease Control and Prevention, Lanzhou, Gansu, China
| | - Xianghua Wang
- Institute of Biomedical Engineering, Chinese Academy of Medical Sciences, Tianjin, China
| | - Jing Nai
- Clinical Laboratory, Beijing Hepingli Hospital, Beijing, China
| | - Guangliang Shan
- Department of Epidemiology and Statistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences and School of Basic Medicine, Peking Union Medical College, Beijing, China
- State Key Laboratory of Common Mechanism Research for Major Diseases, Beijing, China
- School of Population Medicine and Public Health, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Chan JC, O CK, Luk AO. Young-Onset Diabetes in East Asians: From Epidemiology to Precision Medicine. Endocrinol Metab (Seoul) 2024; 39:239-254. [PMID: 38626908 PMCID: PMC11066447 DOI: 10.3803/enm.2024.1968] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/24/2024] [Revised: 03/13/2024] [Accepted: 03/20/2024] [Indexed: 05/03/2024] Open
Abstract
Precision diagnosis is the keystone of clinical medicine. In East Asians, classical type 1 diabetes is uncommon in patients with youngonset diabetes diagnosed before age of 40, in whom a family history, obesity, and beta-cell and kidney dysfunction are key features. Young-onset diabetes affects one in five Asian adults with diabetes in clinic settings; however, it is often misclassified, resulting in delayed or non-targeted treatment. Complex aetiologies, long disease duration, aggressive clinical course, and a lack of evidence-based guidelines have contributed to variable care standards and premature death in these young patients. The high burden of comorbidities, notably mental illness, highlights the numerous knowledge gaps related to this silent killer. The majority of adult patients with youngonset diabetes are managed as part of a heterogeneous population of patients with various ages of diagnosis. A multidisciplinary care team led by physicians with special interest in young-onset diabetes will help improve the precision of diagnosis and address their physical, mental, and behavioral health. To this end, payors, planners, and providers need to align and re-design the practice environment to gather data systematically during routine practice to elucidate the multicausality of young-onset diabetes, treat to multiple targets, and improve outcomes in these vulnerable individuals.
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Affiliation(s)
- Juliana C.N. Chan
- Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - Chun-Kwan O
- Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - Andrea O.Y. Luk
- Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
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Yu G, Tam HCH, Huang C, Shi M, Lim CKP, Chan JCN, Ma RCW. Lessons and Applications of Omics Research in Diabetes Epidemiology. Curr Diab Rep 2024; 24:27-44. [PMID: 38294727 PMCID: PMC10874344 DOI: 10.1007/s11892-024-01533-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/04/2024] [Indexed: 02/01/2024]
Abstract
PURPOSE OF REVIEW Recent advances in genomic technology and molecular techniques have greatly facilitated the identification of disease biomarkers, advanced understanding of pathogenesis of different common diseases, and heralded the dawn of precision medicine. Much of these advances in the area of diabetes have been made possible through deep phenotyping of epidemiological cohorts, and analysis of the different omics data in relation to detailed clinical information. In this review, we aim to provide an overview on how omics research could be incorporated into the design of current and future epidemiological studies. RECENT FINDINGS We provide an up-to-date review of the current understanding in the area of genetic, epigenetic, proteomic and metabolomic markers for diabetes and related outcomes, including polygenic risk scores. We have drawn on key examples from the literature, as well as our own experience of conducting omics research using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank, as well as other cohorts, to illustrate the potential of omics research in diabetes. Recent studies highlight the opportunity, as well as potential benefit, to incorporate molecular profiling in the design and set-up of diabetes epidemiology studies, which can also advance understanding on the heterogeneity of diabetes. Learnings from these examples should facilitate other researchers to consider incorporating research on omics technologies into their work to advance the field and our understanding of diabetes and its related co-morbidities. Insights from these studies would be important for future development of precision medicine in diabetes.
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Affiliation(s)
- Gechang Yu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Henry C H Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Chuiguo Huang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Mai Shi
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Cadmon K P Lim
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, HKSAR, China.
- Chinese University of Hong Kong- Shanghai Jiao Tong University Joint Research Centre in Diabetes Genomics and Precision Medicine, Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, HKSAR, China.
- Laboratory for Molecular Epidemiology in Diabetes, Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, HKSAR, China.
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Wang Y, Hong X, 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. Age effect on the shared etiology of glycemic traits and serum lipids: evidence from a Chinese twin study. J Endocrinol Invest 2024; 47:535-546. [PMID: 37524979 DOI: 10.1007/s40618-023-02164-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 07/24/2023] [Indexed: 08/02/2023]
Abstract
PURPOSE Diabetes and dyslipidemia are among the most common chronic diseases with increasing global disease burdens, and they frequently occur together. The study aimed to investigate differences in the heritability of glycemic traits and serum lipid indicators and differences in overlapping genetic and environmental influences between them across age groups. METHODS This study included 1189 twin pairs from the Chinese National Twin Registry and divided them into three groups: aged ≤ 40, 41-50, and > 50 years old. Univariate and bivariate structural equation models (SEMs) were conducted on glycemic indicators and serum lipid indicators, including blood glucose (GLU), glycated hemoglobin A1c (HbA1c), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C) and high-density lipoprotein cholesterol (HDL-C), in the total sample and three age groups. RESULTS All phenotypes showed moderate to high heritability (0.37-0.64). The heritability of HbA1c demonstrated a downward trend with age (HbA1c: 0.50-0.79), while others remained relatively stable (GLU: 0.55-0.62, TC: 0.58-0.66, TG: 0.50-0.63, LDL-C: 0.24-0.58, HDL-C: 0.31-0.57). The bivariate SEMs demonstrated that GLU and HbA1c were correlated with each serum lipid indicator (0.10-0.17), except HDL-C. Except for HbA1c and LDL-C, as well as HbA1c and HDL-C, differences in genetic correlations underlying glycemic traits and serum lipids between age groups were observed, with the youngest group showing a significantly higher genetic correlation than the oldest group. CONCLUSION Across the whole adulthood, genetic influences were consistently important for GLU, TC, TG, LDL-C and HDL-C, and age may affect the shared genetic influences between glycemic traits and serum lipids. Further studies are needed to elucidate the role of age in the interactions of genes related to glycemic traits and serum lipids.
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Affiliation(s)
- Y Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - X Hong
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - W Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - J Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - C Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - T Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - D Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - C Liao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Y Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Z Pang
- Qingdao Center for Disease Control and Prevention, Qingdao, China
| | - M Yu
- Zhejiang Center for Disease Control and Prevention, Hangzhou, China
| | - H Wang
- Jiangsu Center for Disease Control and Prevention, Nanjing, China
| | - X Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Y Liu
- Heilongjiang Center for Disease Control and Prevention, Harbin, China
| | - W Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
| | - L Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
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He J, Fan B, Lau ESH, Chu N, Ng NYH, Leung KHT, Poon EWM, Kong APS, Ma RCW, Luk AOY, Chan JCN, Chow E. Enhanced prediction of abnormal glucose tolerance using an extended non-invasive risk score incorporating routine renal biochemistry. BMJ Open Diabetes Res Care 2024; 12:e003768. [PMID: 38373805 PMCID: PMC10882282 DOI: 10.1136/bmjdrc-2023-003768] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/13/2023] [Accepted: 01/20/2024] [Indexed: 02/21/2024] Open
Abstract
INTRODUCTION Type 2 diabetes is preventable in subjects with impaired glucose tolerance based on 2-hour plasma glucose (2hPG) during 75 g oral glucose tolerance test (OGTT). We incorporated routine biochemistry to improve the performance of a non-invasive diabetes risk score to identify individuals with abnormal glucose tolerance (AGT) defined by 2hPG≥7.8 mmol/L during OGTT. RESEARCH DESIGN AND METHODS We used baseline data of 1938 individuals from the community-based "Better Health for Better Hong Kong - Hong Kong Family Diabetes Study (BHBHK-HKFDS) Cohort" recruited in 1998-2003. We incorporated routine biochemistry in a validated non-invasive diabetes risk score, and evaluated its performance using area under receiver operating characteristics (AUROC) with internal and external validation. RESULTS The AUROC of the original non-invasive risk score to predict AGT was 0.698 (95% CI, 0.662 to 0.733). Following additional inclusion of fasting plasma glucose, serum potassium, creatinine, and urea, the AUROC increased to 0.778 (95% CI, 0.744 to 0.809, p<0.001). Net reclassification improved by 31.9% (p<0.001) overall, by 30.8% among people with AGT and 1.1% among people without AGT. The extended model showed good calibration (χ2=11.315, p=0.1845) and performance on external validation using an independent data set (AUROC=0.722, 95% CI, 0.680 to 0.764). CONCLUSIONS The extended risk score incorporating clinical and routine biochemistry can be integrated into an electronic health records system to select high-risk subjects for evaluation of AGT using OGTT for prevention of diabetes.
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Affiliation(s)
- Jie He
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Baoqi Fan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong Faculty of Medicine, Hong Kong Special Administrative Region, China
| | - Eric S H Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Natural Chu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Noel Yat Hey Ng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Kathy Ho Ting Leung
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Emily W M Poon
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Alice Pik Shan Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong Faculty of Medicine, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong Faculty of Medicine, Hong Kong Special Administrative Region, China
| | - Ronald Ching Wan Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong Faculty of Medicine, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong Faculty of Medicine, Hong Kong Special Administrative Region, China
| | - Andrea O Y Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong Faculty of Medicine, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong Faculty of Medicine, Hong Kong Special Administrative Region, China
- Phase 1 Clinical Trial Centre, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
| | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong Faculty of Medicine, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong Faculty of Medicine, Hong Kong Special Administrative Region, China
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong Faculty of Medicine, Hong Kong Special Administrative Region, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong Faculty of Medicine, Hong Kong Special Administrative Region, China
- Phase 1 Clinical Trial Centre, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
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Ding K, Zhou Z, Ma Y, Li X, Xiao H, Wu Y, Wu T, Chen D. Identification of Novel Metabolic Subtypes Using Multi-Trait Limited Mixed Regression in the Chinese Population. Biomedicines 2022; 10:biomedicines10123093. [PMID: 36551856 PMCID: PMC9775185 DOI: 10.3390/biomedicines10123093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 11/25/2022] [Accepted: 11/29/2022] [Indexed: 12/03/2022] Open
Abstract
The aggregation and interaction of metabolic risk factors leads to highly heterogeneous pathogeneses, manifestations, and outcomes, hindering risk stratification and targeted management. To deconstruct the heterogeneity, we used baseline data from phase II of the Fangshan Family-Based Ischemic Stroke Study (FISSIC), and a total of 4632 participants were included. A total of 732 individuals who did not have any component of metabolic syndrome (MetS) were set as a reference group, while 3900 individuals with metabolic abnormalities were clustered into subtypes using multi-trait limited mixed regression (MFMR). Four metabolic subtypes were identified with the dominant characteristics of abdominal obesity, hypertension, hyperglycemia, and dyslipidemia. Multivariate logistic regression showed that the hyperglycemia-dominant subtype had the highest coronary heart disease (CHD) risk (OR: 6.440, 95% CI: 3.177-13.977) and that the dyslipidemia-dominant subtype had the highest stroke risk (OR: 2.450, 95% CI: 1.250-5.265). Exome-wide association studies (EWASs) identified eight SNPs related to the dyslipidemia-dominant subtype with genome-wide significance, which were located in the genes APOA5, BUD13, ZNF259, and WNT4. Functional analysis revealed an enrichment of top genes in metabolism-related biological pathways and expression in the heart, brain, arteries, and kidneys. Our findings provide directions for future attempts at risk stratification and evidence-based management in populations with metabolic abnormalities from a systematic perspective.
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Peng J, Lu F, Zhong M, Zhao Y, Wang Z, Zhang W. TBXAS1 Gene Polymorphism Is Associated with the Risk of Ischemic Stroke of Metabolic Syndrome in a Chinese Han Population. DISEASE MARKERS 2022; 2022:9717510. [PMID: 35923246 PMCID: PMC9343182 DOI: 10.1155/2022/9717510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 07/01/2022] [Accepted: 07/14/2022] [Indexed: 11/17/2022]
Abstract
Objective To investigate the association between thromboxane A synthase 1 (TBXAS1) gene polymorphism and metabolic syndrome (MS) and explore whether gene polymorphism could act as biomarkers in MS and its components or whether it could play a role in MS-related damage. Methods A total of 3072 eligible subjects were obtained, of which 1079 cases were controls and 1993 cases were MS patients. Subjects were followed up for 5 years, and the endpoint were recorded. The gene polymorphism of TBXAS1 was detected by using the Sequenom MassArray method. Results Significant differences were observed in ischemic stroke and NC_000007.14: g.139985896C>T (P < 0.05). The incidence of ischemic stroke was significantly higher in T allele carriers than in C (P < 0.05). C allele was the protective factor of the onset of ischemic stroke. There were negative interactions between C allele and waist circumference (WC), systolic blood pressure (SBP), diastolic blood pressure (DBP), triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), and fasting plasma glucose (FPG). Conclusion These findings suggest that NC_000007.14: g.139985896C>T was related to the incidence of ischemic stroke in the whole and MS population, and individuals who carry the C allele have a reduced risk of ischemic stroke, which may be used as a promising biomarker of disease risk in patients with MS.
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Affiliation(s)
- Jie Peng
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, the State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China
- Department of Geriatric Medicine, Qilu Hospital of Shandong University, Key Laboratory of Cardiovascular Proteomics of Shandong Province, Jinan, China
| | - Fanghong Lu
- Cardio-Cerebrovascular Control and Research Center, Institute of Basic Medicine, Shandong Academy of Medical Sciences, Jinan, China
| | - Ming Zhong
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, the State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China
| | - Yingxin Zhao
- Cardio-Cerebrovascular Control and Research Center, Institute of Basic Medicine, Shandong Academy of Medical Sciences, Jinan, China
| | - Zhihao Wang
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, the State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China
- Department of Geriatric Medicine, Qilu Hospital of Shandong University, Key Laboratory of Cardiovascular Proteomics of Shandong Province, Jinan, China
| | - Wei Zhang
- The Key Laboratory of Cardiovascular Remodeling and Function Research, Chinese Ministry of Education, Chinese National Health Commission and Chinese Academy of Medical Sciences, the State and Shandong Province Joint Key Laboratory of Translational Cardiovascular Medicine, Qilu Hospital of Shandong University, Jinan, Shandong, China
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Cheung JTK, Lau E, Tsui CCT, Siu ELN, Tse NKW, Hui NYL, Ma RCW, Kong APS, Fu A, Lau V, Jia W, Sheu WHH, Sobrepena L, Yoon KH, Tan ATB, Chia YC, Sosale A, Saboo BD, Kesavadev J, Goh SY, Nguyen TK, Thewjitcharoen Y, Suwita R, Luk AOY, Yang A, Chow E, Lim LL, Chan JCN. Combined associations of family history and self-management with age at diagnosis and cardiometabolic risk in 86,931 patients with type 2 diabetes: Joint Asia Diabetes Evaluation (JADE) Register from 11 countries. BMC Med 2022; 20:249. [PMID: 35831899 PMCID: PMC9281062 DOI: 10.1186/s12916-022-02424-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/11/2022] [Accepted: 05/31/2022] [Indexed: 12/02/2022] Open
Abstract
BACKGROUND Family history (FamH) of type 2 diabetes might indicate shared genotypes, environments, and/or behaviors. We hypothesize that FamH interacts with unhealthy behaviors to increase the risk of early onset of diabetes and poor cardiometabolic control. METHODS In a cross-sectional analysis of the prospective Joint Asia Diabetes Evaluation Register including patients from 427 clinics in 11 Asian countries/regions in 2007-2021, we defined positive FamH as affected parents/siblings and self-management as (1) healthy lifestyles (balanced diet, non-use of alcohol and tobacco, regular physical activity) and (2) regular self-monitoring of blood glucose (SMBG). RESULTS Among 86,931 patients with type 2 diabetes (mean±SD age: 56.6±11.6 years; age at diagnosis of diabetes: 49.8±10.5 years), the prevalence of FamH ranged from 39.1% to 85.3% in different areas with FamH affecting mother being most common (32.5%). The FamH group (n=51,705; 59.5%) was diagnosed 4.6 years earlier than the non-FamH group [mean (95% CI): 47.9 (47.8-48.0) vs. 52.5 (52.4-52.6), logrank p<0.001]. In the FamH group, patients with both parents affected had the earliest age at diagnosis [44.6 (44.5-44.8)], followed by affected single parent [47.7 (47.6-47.8)] and affected siblings only [51.5 (51.3-51.7), logrank p<0.001]. The FamH plus ≥2 healthy lifestyle group had similar age at diagnosis [48.2 (48.1-48.3)] as the non-FamH plus <2 healthy lifestyle group [50.1 (49.8-50.5)]. The FamH group with affected parents had higher odds of hyperglycemia, hypertension, and dyslipidemia than the FamH group with affected siblings, with the lowest odds in the non-FamH group. Self-management (healthy lifestyles plus SMBG) was associated with higher odds of attaining HbA1c<7%, blood pressure<130/80mmHg, and LDL-C<2.6 mmol/L especially in the FamH group (FamH×self-management, pinteraction=0.050-0.001). CONCLUSIONS In Asia, FamH was common and associated with young age of diagnosis which might be delayed by healthy lifestyle while self management was associated with better control of cardiometabolic risk factors especially in those with FamH.
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Affiliation(s)
- Johnny T K Cheung
- Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Eric Lau
- Asia Diabetes Foundation, Shatin, Hong Kong Special Administrative Region, Shatin, China.,Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Cyrus C T Tsui
- Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Edmond L N Siu
- Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Naomi K W Tse
- Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Nicole Y L Hui
- Faculty of Medicine, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China
| | - Ronald C W Ma
- Asia Diabetes Foundation, Shatin, Hong Kong Special Administrative Region, Shatin, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Alice P S Kong
- Asia Diabetes Foundation, Shatin, Hong Kong Special Administrative Region, Shatin, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China.,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Amy Fu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Vanessa Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Weiping Jia
- Shanghai Sixth People's Hospital, Shanghai, China
| | - Wayne H H Sheu
- Department of Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | | | - K H Yoon
- Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, South Korea
| | - Alexander T B Tan
- Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Yook-Chin Chia
- Department of Medical Sciences, School of Medical and Life Sciences, Sunway University, Subang Jaya, Selangor, Malaysia.,Department of Primary Care Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | | | - Banshi D Saboo
- Dia Care - Diabetes Care & Hormone Clinic, Ahmedabad, Gujarat, India
| | - Jothydev Kesavadev
- Jothydev's Diabetes & Research Center, Thiruvananthapuram, Kerala, India
| | - Su-Yen Goh
- Department of Endocrinology, Singapore General Hospital, Singapore, Singapore
| | | | | | - Raymond Suwita
- Cerebrocardiovascular Diabetes Group Clinic (CDG), Jakarta, Indonesia
| | - Andrea O Y Luk
- Asia Diabetes Foundation, Shatin, Hong Kong Special Administrative Region, Shatin, China.,Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Aimin Yang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Elaine Chow
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China.,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China
| | - Lee Ling Lim
- Asia Diabetes Foundation, Shatin, Hong Kong Special Administrative Region, Shatin, China.,Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China.,Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Juliana C N Chan
- Asia Diabetes Foundation, Shatin, Hong Kong Special Administrative Region, Shatin, China. .,Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China. .,Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China. .,Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong Special Administrative Region, China.
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Akbarzadeh M, Riahi P, Ramezankhani A, Dehkordi SR, Roudbar MA, Zarkesh M, Guity K, Khalili D, Zahedi AS, Azizi F, Daneshpour MS. Parental Transmission Plays the Major Role in High Aggregation of Type 2 Diabetes in Iranian Families: Tehran Lipid and Glucose Study. Can J Diabetes 2021; 46:60-68. [PMID: 34419346 DOI: 10.1016/j.jcjd.2021.05.009] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Revised: 04/25/2021] [Accepted: 05/27/2021] [Indexed: 11/25/2022]
Abstract
BACKGROUND This study is the first to evaluate familial aggregation, heritability and inheritance mode of type 2 diabetes (T2D) in Tehran Lipid Glucose Study (TLGS) participants as a representative sample of the Iranian population. METHODS From the ongoing family-based TLGS cohort, 13,741 individuals at least 20 years of age (mean ± standard deviation, 39.71±16.56) were assessed. After correcting family structures using genomic information from the Tehran Cardiometabolic Genetic Study, 2,594 constituent pedigrees were constructed. Familial aggregation was assessed based on genealogic index testing, familial intraclass correlation and positive family history. Family-based heritability was checked with 2 linear mixed models, including 2 different random components: the kinship matrix and the genomic relationship matrix. The mode of inheritance of T2D was investigated by complex segregation analysis (CSA). RESULTS Familial aggregation of T2D was significant (p<0.05), and family-based heritability showed a high degree of genetic variation in T2D between individuals at 65% (standard error, 0.034). Within first-degree relatives (parent/offspring and siblings), the likelihood of a parental affect was higher than in siblings (odds ratio, 4.11 vs 1.65). Family history of T2D among first-degree relatives was more noteworthy than for second-degree relatives (odds ratio, 3.84 vs 0.59). CSA revealed that the polygenic model is best to illustrate the mode of inheritance of T2D for TLGS participants. CONCLUSIONS Our findings demonstrate that the heritability of T2D with polygenic mode in the Iranian population is higher than the global average. We also found that T2D is transmitted equally into siblings, with parental affect the leading risk factor. These data suggest that policymakers should change individual-level to family-level prevention.
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Affiliation(s)
- Mahdi Akbarzadeh
- Cellular and Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Parisa Riahi
- Cellular and Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Azra Ramezankhani
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Saeid Rasekhi Dehkordi
- Cellular and Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mahmoud Amiri Roudbar
- Department of Animal Science, Safiabad-Dezful Agricultural and Natural Resources Research and Education Center, Agricultural Research, Education & Extension Organization, Dezful, Iran
| | - Maryam Zarkesh
- Cellular and Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Kamran Guity
- Cellular and Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Davood Khalili
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Asiyeh Sadat Zahedi
- Cellular and Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Maryam S Daneshpour
- Cellular and Molecular Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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Xi Y, Gao W, Zheng K, Lv J, Yu C, Wang S, Huang T, Sun D, Liao C, Pang Y, Pang Z, Yu M, Wang H, Wu X, Dong Z, Wu F, Jiang G, Wang X, Liu Y, Deng J, Lu L, Cao W, Li L. The Roles of Genetic and Early-Life Environmental Factors in the Association Between Overweight or Obesity and Hypertension: A Population-Based Twin Study. Front Endocrinol (Lausanne) 2021; 12:743962. [PMID: 34675880 PMCID: PMC8525506 DOI: 10.3389/fendo.2021.743962] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 09/15/2021] [Indexed: 01/14/2023] Open
Abstract
AIMS/HYPOTHESIS We aimed to explore whether and to what extent overweight or obesity could increase the risk of hypertension, and further to estimate the roles of genetic and early-life familial environmental factors in their association. METHODS This prospective twin study was based on the Chinese National Twin Registry (CNTR), which collected information from self-report questionnaires. We conducted unmatched case-control analysis to examine the association between overweight or obesity and hypertension. And further to explore whether genetics and familiar environments shared within a twin pair, accounted for their association via co-twin matched case-control design. Generalized estimating equation (GEE) models and conditional logistic regressions were used in the unmatched and matched analyses, respectively. Then, we used logistic regressions to test the difference in odds ratios (ORs) between the unmatched and matched analyses. Finally, through bivariate twin model, the roles of genetic and environmental factors in the body mass index (BMI)- hypertension association were estimated. RESULTS Overall, we included a total of 30,617 twin individuals, of which 7533 (24.6%) twin participants were overweight or obesity and 757 (2.5%) developed hypertension during a median follow-up time of 4.4 years. In the GEE model, overweight or obesity was associated with a 94% increased risk of hypertension (OR=1.94, 95% confidence interval (CI): 1.64~2.30). In the conditional logistic regression, the multi-adjusted OR was 1.80 (95% CI: 1.18~2.74). The difference in OR between unmatched and matched analyses was significant (P=0.016). Specifically, overweight or obesity was not associated with hypertension risk in the co-twin design when we full controlled genetic and familiar environmental factors (OR=0.89, 95 CI: 0.46~1.72). After controlling for age and sex, we found the positive BMI-hypertension association was mainly explained by a genetic correlation between them (rA= 0.59, 95% CI: 0.44~1.00). CONCLUSIONS/INTERPRETATION Genetics and early-life environments shared by participants within a twin pair appear to account for the association between overweight or obesity and hypertension risk.
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Affiliation(s)
- Yu’e Xi
- 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
- *Correspondence: Wenjing Gao, ; Weihua Cao,
| | - Ke Zheng
- 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
| | - Shengfeng Wang
- 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 Municipal Center for Disease Control and Prevention , Qingdao, China
| | - Min Yu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Hua Wang
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu, China
| | - Zhong Dong
- Beijing Center for Disease Prevention and Control, Beijing, China
| | - Fan Wu
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai, China
| | - Guohong Jiang
- Tianjin Centers for Disease Control and Prevention, Tianjin, China
| | - Xiaojie Wang
- Qinghai Center for Diseases Prevention and Control, Xining, China
| | - Yu Liu
- Heilongjiang Provincial Center for Disease Control and Prevention, Harbin, China
| | - Jian Deng
- Handan Center for Disease Control and Prevention, Handan, China
| | - Lin Lu
- Yunnan Center for Disease Control and Prevention, Kunming, China
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- *Correspondence: Wenjing Gao, ; Weihua Cao,
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
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12
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Wu X, Li Y, Man B, Li D. Assessing MicroRNA-375 Levels in Type 2 Diabetes Mellitus (T2DM) Patients and Their First-Degree Relatives with T2DM. Diabetes Metab Syndr Obes 2021; 14:1445-1451. [PMID: 33824598 PMCID: PMC8018570 DOI: 10.2147/dmso.s298735] [Citation(s) in RCA: 12] [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: 12/23/2020] [Accepted: 03/04/2021] [Indexed: 12/20/2022] Open
Abstract
PURPOSE The pancreatic islet specific microRNA-375 (miR-375) is overexpressed in type 2 diabetes mellitus (T2DM) patients suppressing the glucose-induced insulin secretion. Thus, miR-375 may serve as a biomarker for the early prediction of T2DM among high-risk individuals. We conducted this clinical study to assess the significance of miR-375 among type 2 diabetes mellitus (T2DM) patients and their first-degree relatives. PATIENTS AND METHODS We included 56 Han Chinese individuals (N: NGT = 21, T2DM = 10, FD-NGT =13 and FD-T2DM = 12) who received medical health check-ups from January 2018 to September 2018 at The Third Hospital of Yunnan Province, China. They were categorized as normal glucose tolerance (NGT), T2DM, first-degree relatives with normal glucose tolerance (FD-NGT) and first-degree relatives with T2DM (FD-T2DM). OGTT, C-peptide and Insulin tests were performed to confirm the diagnosis. The miR-375 levels were determined by Quantitative real-time RT-PCR (qRT-PCR). RESULTS The OGTT test showed a significant difference in T2DM and FD-T2DM groups compared with NGT and FD-NGT (p< 0.05). Similar results were observed during C-peptide and insulin tests. Interestingly, the 2-hour insulin test showed FD-NGT group having a significantly higher mean ± standard error of (64.240 ± 12.775) compared to NGT (28.836 ± 10.875). Assessment of miR-375 expression levels in 4 groups showed a significant up-regulation in T2DM and FD-T2DM compared with NGT and FD-NGT groups. A slight increase in miRNA expression was observed in FD-NGT compared with NGT group but was not statistically significant. CONCLUSION The OGTT, C-peptide and insulin tests revealed a statistically significant difference in T2DM and FD-T2DM compared with NGT and FD-NGT groups. A significantly higher miR-375 expression was also observed in T2DM and FD-T2DM groups compared with NGT and FD-NGT and thus, miR-375 may serve as a stable biomarker for the early prediction of T2DM among high-risk individuals.
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Affiliation(s)
- Xu Wu
- The Third People’s Hospital of Yunnan Province, Department of Clinical Laboratory, Kunming, 650200, People’s Republic of China
| | - Yashan Li
- The Third People’s Hospital of Yunnan Province, Department of Clinical Laboratory, Kunming, 650200, People’s Republic of China
| | - Baohua Man
- The Third People’s Hospital of Yunnan Province, Department of Clinical Laboratory, Kunming, 650200, People’s Republic of China
| | - Dexuan Li
- The Third People’s Hospital of Yunnan Province, Department of Clinical Laboratory, Kunming, 650200, People’s Republic of China
- Correspondence: Dexuan Li Department of Clinical Laboratory, The Third People’s Hospital of Yunnan Province, No. 292 Beijing Road, Kunming, 650200, People’s Republic of China Email
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Chiu H, Lee MY, Wu PY, Huang JC, Chen SC, Chang JM. Comparison of the effects of sibling and parental history of type 2 diabetes on metabolic syndrome. Sci Rep 2020; 10:22131. [PMID: 33335312 PMCID: PMC7747734 DOI: 10.1038/s41598-020-79382-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 12/07/2020] [Indexed: 02/07/2023] Open
Abstract
The aim of this study was to investigate the associations between sibling history, parental history and simultaneous sibling and parental history of diabetes, and the presence of the metabolic syndrome (MetS) and its components. Our study comprised 5000 participants from Taiwan Biobank until April, 2014. The participants were stratified into four groups according to sibling and/or parental family history (FH) of DM. MetS was defined as having 3 of the following 5 abnormalities based on the standard of the NCEP ATP III and modified criteria for Asians. The prevalence of MetS and its traits was estimated and compared among the four familial risk strata. Multivariate logistic regression analysis showed participants with sibling FH of DM [vs. no FH of DM; odds ratio (OR) 1.815; 95% confidence interval (CI) 1.293 to 2.548; p = 0.001], participants with parental FH of DM (vs. no FH of DM; OR 1.771; 95% CI 1.468 to 2.135; p < 0.001), and participants with simultaneous sibling and parental FH of DM (vs. no FH of DM; OR 2.961; 95% CI 2.108 to 4.161; p < 0.001) were significantly associated with MetS. A synergistic effect of sibling FH of DM and parental FH of DM on the association of MetS was also observed. In a nationally representative sample of Taiwan adults, a simultaneous sibling and parental history of diabetes shows a significant, independent association with MetS and its components, except for abdominal obesity. The association highlights the importance of obtaining stratified FH information in clinical practice and may help to identify individuals who should be targeted for screening and early prevention of MetS.
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Affiliation(s)
- Hsuan Chiu
- Department of General Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Mei-Yueh Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Pei-Yu Wu
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Department of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, 482, Shan-Ming Rd., Hsiao-Kang Dist., Kaohsiung, 812, Taiwan, ROC
| | - Jiun-Chi Huang
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Department of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, 482, Shan-Ming Rd., Hsiao-Kang Dist., Kaohsiung, 812, Taiwan, ROC.,Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Szu-Chia Chen
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan. .,Department of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, 482, Shan-Ming Rd., Hsiao-Kang Dist., Kaohsiung, 812, Taiwan, ROC. .,Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan. .,Research Center for Environmental Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
| | - Jer-Ming Chang
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
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14
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Zhao J, Zhu XY, Ren Y, Li JY. Analysis of the correlation between periodontal disease and metabolic syndrome among coal mine workers: A clinical study. Medicine (Baltimore) 2020; 99:e21566. [PMID: 32872008 PMCID: PMC7437729 DOI: 10.1097/md.0000000000021566] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/02/2020] [Accepted: 07/06/2020] [Indexed: 11/26/2022] Open
Abstract
Metabolic syndrome (MetS) refers to the pathological state of metabolic disorders in the body's proteins, fats, carbohydrates and other substances. MetS is a systemic metabolic disease. Periodontal disease is also a part of systemic inflammatory diseases. Among Chinese patients with middle-aged and elderly MetS, the periodontal morbidity is very high, which is due to the involvement of inflammatory mediators in the pathogenesis of MetS and periodontal disease. The latter may also be a risk factor for the former's morbidity and promotion of disease progression. At present, there are not many investigations and studies on periodontal examination data and periodontal disease prevalence of patients with MetS. Coal mine workers, especially coal mine underground workers, have different work natures and different working environments. See related report.We will collect the clinical diagnosis and treatment information of the enrolled patients. We will focus on checking the incidence of periodontal disease and recording. Establish a database, check every 10 medical records, and make corrections in time to ensure data accuracy. We will popularize oral hygiene knowledge for the included patients and guide them to brush their teeth correctly and how to use dental floss. We will perform periodontal examination on the patients' teeth by site and record the plaque index, gingival sulcus bleeding index, periodontal pocket exploration depth and other indicators. We will repeat the above inspection items and record in the second and fourth weeks of the experiment.This study will explore the correlation between periodontal disease and MetS of coal mine workers. We aim to clarify the role and mechanism of MetS in the occurrence and development of periodontal diseases, guide the prevention of periodontal diseases, and thus reduce the prevalence of periodontal diseases. TRIAL REGISTRATION:: ClinicalTrials.gov, ChiCTR2000034177, Registered on 27 June 2020.
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Affiliation(s)
| | | | - Yan Ren
- Kailuan General Hospital, Tangshan
| | - Jin-yuan Li
- School of stomatology, North China University of Science and Technology, Hebei China
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15
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Wang W, Zhang C, Liu H, Xu C, Duan H, Tian X, Zhang D. Heritability and genome-wide association analyses of fasting plasma glucose in Chinese adult twins. BMC Genomics 2020; 21:491. [PMID: 32682390 PMCID: PMC7368793 DOI: 10.1186/s12864-020-06898-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2019] [Accepted: 07/09/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Currently, diabetes has become one of the leading causes of death worldwide. Fasting plasma glucose (FPG) levels that are higher than optimal, even if below the diagnostic threshold of diabetes, can also lead to increased morbidity and mortality. Here we intend to study the magnitude of the genetic influence on FPG variation by conducting structural equation modelling analysis and to further identify specific genetic variants potentially related to FPG levels by performing a genome-wide association study (GWAS) in Chinese twins. RESULTS The final sample included 382 twin pairs: 139 dizygotic (DZ) pairs and 243 monozygotic (MZ) pairs. The DZ twin correlation for the FPG level (rDZ = 0.20, 95% CI: 0.04-0.36) was much lower than half that of the MZ twin correlation (rMZ = 0.68, 95% CI: 0.62-0.74). For the variation in FPG level, the AE model was the better fitting model, with additive genetic parameters (A) accounting for 67.66% (95% CI: 60.50-73.62%) and unique environmental or residual parameters (E) accounting for 32.34% (95% CI: 26.38-39.55%), respectively. In the GWAS, although no genetic variants reached the genome-wide significance level (P < 5 × 10- 8), 28 SNPs exceeded the level of a suggestive association (P < 1 × 10- 5). One promising genetic region (2q33.1) around rs10931893 (P = 1.53 × 10- 7) was found. After imputing untyped SNPs, we found that rs60106404 (P = 2.38 × 10- 8) located at SPATS2L reached the genome-wide significance level, and 216 SNPs exceeded the level of a suggestive association. We found 1007 genes nominally associated with the FPG level (P < 0.05), including SPATS2L, KCNK5, ADCY5, PCSK1, PTPRA, and SLC26A11. Moreover, C1orf74 (P = 0.014) and SLC26A11 (P = 0.021) were differentially expressed between patients with impaired fasting glucose and healthy controls. Some important enriched biological pathways, such as β-alanine metabolism, regulation of insulin secretion, glucagon signaling in metabolic regulation, IL-1 receptor pathway, signaling by platelet derived growth factor, cysteine and methionine metabolism pathway, were identified. CONCLUSIONS The FPG level is highly heritable in the Chinese population, and genetic variants are significantly involved in regulatory domains, functional genes and biological pathways that mediate FPG levels. This study provides important clues for further elucidating the molecular mechanism of glucose homeostasis and discovering new diagnostic biomarkers and therapeutic targets for diabetes.
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Affiliation(s)
- Weijing Wang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 38 Dengzhou Road, Shibei District, Qingdao, 266021 Shandong Province China
| | - Caixia Zhang
- The First Hospital of Yulin, Yulin, Shanxi China
| | - Hui Liu
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 38 Dengzhou Road, Shibei District, Qingdao, 266021 Shandong Province China
| | - Chunsheng Xu
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong China
- Qingdao Institute of Preventive Medicine, Qingdao, Shandong China
| | - Haiping Duan
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong China
- Qingdao Institute of Preventive Medicine, Qingdao, Shandong China
| | - Xiaocao Tian
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao, Shandong China
| | - Dongfeng Zhang
- Department of Epidemiology and Health Statistics, Public Health College, Qingdao University, No. 38 Dengzhou Road, Shibei District, Qingdao, 266021 Shandong Province China
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16
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Meamar R, Amini M, Aminorroaya A, Nasri M, Abyar M, Feizi A. Severity of the metabolic syndrome as a predictor of prediabetes and type 2 diabetes in first degree relatives of type 2 diabetic patients: A 15-year prospective cohort study. World J Diabetes 2020; 11:202-212. [PMID: 32477456 PMCID: PMC7243485 DOI: 10.4239/wjd.v11.i5.202] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/16/2019] [Revised: 03/16/2020] [Accepted: 03/23/2020] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Type 2 diabetes mellitus (T2DM) has high morbidity and mortality worldwide, therefore there is of paramount importance to identify the risk factors in the populations at risk early in the course of illness. A strong correlation between severity of metabolic syndrome (MetS) and HbA1c, fasting insulin and insulin resistance has been reported. Accordingly, the MetS severity score (or MestS Z-score) can potentially be used to predict the risk of T2DM progression over time. AIM To evaluate the association the of MestS Z-score in first degree relatives (FDRs) of T2DM with the risk of prediabetes and type 2 diabetes in future. METHODS A prospective open cohort study was conducted between 2003-2018. At baseline, the sample comprised of 1766 FDRs of patients with T2DM who had a normal glucose tolerance test. Relative risk (RR) and 95% confidence interval were calculated based on logistic regression. The receiver-operator characteristic analysis and area under the curve based on MetS Z-score were used to evaluate the risk of prediabetes and diabetes among the FDR population. RESULTS Baseline MetS Z-scores were associated with the its latest values (P < 0.0001). Compared with individuals who were T2DM free at the end of follow up, those who developed T2DM had higher MetS Z-score at baseline (P < 0.001). In multivariable logistic regression analyses for every unit elevation in MetS Z-score at the baseline, the RR for developing future T2DM and prediabetes was (RR = 1.94, RR = 3.84), (RR = 1.5, RR = 2.17) in total population and female group, respectively (P < 0.05). The associations remained significant after adjusting the potential confounding variables. A cut off value of 0.97 and 0.94 was defined in the receiver-operator characteristic curve based on the MetS Z-score for differentiating female patients with diabetes and prediabetes from the normal population, respectively. CONCLUSION The MetS Z-score was associated with an increased risk of future T2DM. Appropriate interventions at earlier stages for preventing and attenuating MetS effects may be considered as an effective strategy for FDR as at-risk population.
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Affiliation(s)
- Rokhsareh Meamar
- Isfahan Endocrine and Metabolism Research Center, Isfahan Clinical Toxicology Research Center, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran
| | - Masoud Amini
- Isfahan Endocrine and Metabolism Research Center, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran
| | - Ashraf Aminorroaya
- Isfahan Endocrine and Metabolism Research Center, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran
| | - Maryam Nasri
- Grovemead Health Center, London NW4-3EB, United Kingdom
| | - Majid Abyar
- Isfahan Endocrine and Metabolism Research Center, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran
| | - Awat Feizi
- Isfahan Endocrine and Metabolism Research Center, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran
- Department of Biostatistics and Epidemiology, School of Health, Isfahan University of Medical Sciences, Isfahan 81746-73461, Iran
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17
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Bjerregaard LG, Damborg ML, Osler M, Sørensen TIA, Baker JL. Body mass index and height in relation to type 2 diabetes by levels of intelligence and education in a large cohort of Danish men. Eur J Epidemiol 2020; 35:1167-1175. [PMID: 32372338 DOI: 10.1007/s10654-020-00641-4] [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: 10/29/2019] [Accepted: 04/28/2020] [Indexed: 10/24/2022]
Abstract
Socioeconomic status (SES) is inversely associated with risks of type 2 diabetes (T2D). We investigated if young men's cognitive function, measured by intelligence test scores and educational level, as determinants of SES modified associations between body mass index (BMI) and height with the risk of T2D. 369 989 young men from the Danish Conscription Database born between 1939 and 1959 with information on measured height, weight, intelligence test scores, and education were linked to the Danish National Patient Register. During follow-up from 1977 through 2015, T2D was recorded in 32 188 men. Hazard ratios (HR) and 95% confidence intervals (95% CI) were estimated by Cox regressions. BMIs below-average (z-scores ≤ 0) were not related to risks of T2D. For BMIs above-average (z-scores > 0), positive associations between BMI and T2D were slightly stronger among men with higher intelligence test scores or longer educations than among men with lower levels of these factors (pinteraction-values < 0.004). Irrespective of BMI, incidence rates of T2D were higher among men with low levels of intelligence test score and education. Height was inversely associated with T2D (per z-score, HR = 0.96 (95% CI 0.95-0.97) and the association did not vary by intelligence test scores or education (all pinteraction-values > 0.59). While below-average BMI was not associated with T2D risk, above-average BMIs were and these association were stronger among men with high cognitive function. Nevertheless, T2D risk was higher at lower levels of cognitive function throughout the range of BMI. Height was inversely associated with T2D and it was not modified by cognitive function.
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Affiliation(s)
- Lise G Bjerregaard
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, The Capital Region, Hovedvejen 5, Nordre Fasanvej 57, 2000, Frederiksberg, Copenhagen, Denmark
| | - Mille L Damborg
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, The Capital Region, Hovedvejen 5, Nordre Fasanvej 57, 2000, Frederiksberg, Copenhagen, Denmark
| | - Merete Osler
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, The Capital Region, Hovedvejen 5, Nordre Fasanvej 57, 2000, Frederiksberg, Copenhagen, Denmark
| | - Thorkild I A Sørensen
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, Human Genomics and Metagenomics in Metabolism, University of Copenhagen, Copenhagen, Denmark.,Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jennifer L Baker
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, The Capital Region, Hovedvejen 5, Nordre Fasanvej 57, 2000, Frederiksberg, Copenhagen, Denmark. .,Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, Human Genomics and Metagenomics in Metabolism, University of Copenhagen, Copenhagen, Denmark.
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18
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Muazu S, Ibrahim H, Puepet F, Mubi B, Gezawa I, Mustapha S, Bakki B, Talle A, Michael G, Aliyu I. Prevalence and risk factors for impaired glucose regulation among first-degree relatives of patients with type 2 diabetes mellitus in Maiduguri, Northeastern Nigeria. JOURNAL OF DIABETOLOGY 2020. [DOI: 10.4103/jod.jod_5_19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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19
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Rhee EJ, Cho JH, Kwon H, Park SE, Jung JH, Han KD, Park YG, Kim YH, Lee WY. Relation between Baseline Height and New Diabetes Development: A Nationwide Population-Based Study. Diabetes Metab J 2019; 43:794-803. [PMID: 30968616 PMCID: PMC6943257 DOI: 10.4093/dmj.2018.0184] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2018] [Accepted: 12/01/2018] [Indexed: 12/20/2022] Open
Abstract
BACKGROUND Short stature and leg length are associated with risk of diabetes and obesity. However, it remains unclear whether this association is observed in Asians. We evaluated the association between short stature and increased risk for diabetes using the Korean National Health Screening (KNHS) dataset. METHODS We assessed diabetes development in 2015 in 21,122,422 non-diabetic Koreans (mean age 43 years) enrolled in KNHS from 2009 to 2012 using International Classification of Diseases 10th (ICD-10) code and anti-diabetic medication prescription. Risk was measured in age- and sex-dependent quintile groups of baseline height (20 to 39, 40 to 59, ≥60 years). RESULTS During median 5.6-year follow-up, 532,918 cases (2.5%) of diabetes occurred. The hazard ratio (HR) for diabetes development gradually increased from the 5th (reference) to 1st quintile group of baseline height after adjustment for confounding factors (1.000, 1.076 [1.067 to 1.085], 1.097 [1.088 to 1.107], 1.141 [1.132 to 1.151], 1.234 [1.224 to 1.244]), with similar results in analysis by sex. The HR per 5 cm height increase was lower than 1.00 only in those with fasting blood glucose (FBG) below 100 mg/dL (0.979 [0.975 to 0.983]), and in lean individuals (body mass index [BMI] 18.5 to 23 kg/m²: 0.993 [0.988 to 0.998]; BMI <18.5 kg/m²: 0.918 [0.9 to 0.935]). CONCLUSION Height was inversely associated with diabetes risk in this nationwide study of Korean adults. This association did not differ by sex, and was significant in lean individuals and those with normal FBG levels.
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Affiliation(s)
- Eun Jung Rhee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jung Hwan Cho
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Hyemi Kwon
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Se Eun Park
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea
| | - Jin Hyung Jung
- Department of Biostatistics, Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Kyung Do Han
- Department of Biostatistics, Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Yong Gyu Park
- Department of Biostatistics, Biomedicine & Health Sciences, College of Medicine, The Catholic University of Korea, Seoul, Korea
| | - Yang Hyun Kim
- Department of Family Medicine, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Korea
| | - Won Young Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Korea.
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20
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Song J, Jiang X, Juan J, Cao Y, Chibnik LB, Hofman A, Wu T, Hu Y. Role of metabolic syndrome and its components as mediators of the genetic effect on type 2 diabetes: A family-based study in China. J Diabetes 2019; 11:552-562. [PMID: 30520249 DOI: 10.1111/1753-0407.12882] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Revised: 11/12/2018] [Accepted: 11/29/2018] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Metabolic syndrome (MetS) share a genetic basis with type 2 diabetes (T2D). However, whether MetS and its components mediate genetic susceptibility to T2D is not completely understood. METHODS We assessed the effects of MetS and its components on associations T2D and 18 genome-wide association studies-identified variants using a two-stage strategy based on parametric models involving 7110 Chinese participants (2436 were T2D patients) across 2885 families. Multilevel logistic regression was used to account for the intrafamilial correlation. RESULTS Metabolic syndrome significantly mediated the effect of a melatonin receptor 1B (MTNR1B) polymorphism on T2D risk (OR of average causal mediation effect [ORACME ] 1.004; 95% confidence interval [CI] 1.001-1.008; P = 0.018). In addition, low high-density lipoprotein cholesterol (HDL-C) levels mediated the genetic effects of MTNR1B (ORACME 1.012; 95% CI 1.007-1.015; P < 0.001), solute carrier family 30 member 8 (SLC30A8; ORACME 1.001; 95% CI 1.000-1.007; P < 0.040), B-cell lymphoma/leukemia 11A (BCL11A; ORACME 1.009; 95% CI 1.007-1.016; P < 0.001), prospero homeobox 1 (PROX1; ORACME 1.005; 95% CI 1.003-1.011; P < 0.001) and a disintegrin and metallopeptidase with thrombospondin type 1 motif 9 (ADAMTS9; ORACME 1.006; 95% CI 1.001-1.009; P = 0.022), whereas increased fasting blood glucose (FBG) significantly mediated the genetic effect of BCL11A (ORACME 1.017; 95% CI 1.003-1.021; P = 0.012). CONCLUSIONS This study provides evidence that MetS and two of its components (HDL-C, FBG) may be involved in mediating the genetic predisposition to T2D, which emphasize the importance of maintaining normal HDL-C and FBG levels.
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Affiliation(s)
- Jing Song
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Xia Jiang
- Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts
| | - Juan Juan
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Yaying Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Lori B Chibnik
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts
- Channing Division of Network Medicine, Brigham and Women's Hospital, Boston, Massachusetts
| | - Albert Hofman
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, Massachusetts
| | - Tao Wu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Yonghua Hu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
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21
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Feizi A, Meamar R, Eslamian M, Amini M, Nasri M, Iraj B. Area under the curve during OGTT in first-degree relatives of diabetic patients as an efficient indicator of future risk of type 2 diabetes and prediabetes. Clin Endocrinol (Oxf) 2017; 87:696-705. [PMID: 28793372 DOI: 10.1111/cen.13443] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2017] [Revised: 07/11/2017] [Accepted: 07/26/2017] [Indexed: 12/30/2022]
Abstract
OBJECTIVE To establish whether the area under the curve of an OGTT has a predictive role in identifying prediabetic and diabetic subjects among first-degree relatives (FDR) of patients with diabetes mellitus type 2 (DM). DESIGN, PATIENTS AND MEASUREMENTS In a population-based cohort study, 766 FDR of diabetic patients with a normal glucose tolerance test (NGT) completed a 2-hour OGTT. They were followed up for 7 years and classified according to the American Diabetes Association criteria into: NGT, impaired fasting glucose (IFG), impaired glucose tolerance (IGT) and DM. Relative risk (RR) and 95% confidence intervals (95%CI) were calculated based on logistic regression. Receiver operator characteristic (ROC) analysis along with AUC at different intervals and at time points during the OGTT was used to evaluate the risk of prediabetes and diabetes. RESULTS Twenty-three subjects (3%) developed type 2 DM, 118 (29.3%) IFG, 81 (11.5%) IGT and 544 (71%) subjects remained NGT. AUC and mean difference of glucose in all high-risk groups demonstrated significant differences in both intervals and time points when compared to the NGT group. The cut-off values during OGTT to predict prediabetes and diabetes was determined as blood glucose more than 7.2 and 7.8 mmol/L at 30 and 60 minutes, respectively. The time point 60 has the highest predictive role for the development of diabetes, alone, and improved the performance of a prediction model containing multiple important clinical risk factors. CONCLUSION The data suggest that the glycaemic response to an OGTT may predict the risk of development of diabetes in first-degree relatives of DM patients.
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Affiliation(s)
- Awat Feizi
- Isfahan Endocrine & metabolism Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
- Department of Biostatistics and Epidemiology, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Rokhsareh Meamar
- Isfahan Endocrine & metabolism Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Mohammad Eslamian
- Isfahan Endocrine & metabolism Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Masoud Amini
- Isfahan Endocrine & metabolism Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Maryam Nasri
- Central London Community Health Trust, London, UK
| | - Bijan Iraj
- Isfahan Endocrine & metabolism Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
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22
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Zhang Y, Luk AOY, Chow E, Ko GTC, Chan MHM, Ng M, Kong APS, Ma RCW, Ozaki R, So WY, Chow CC, Chan JCN. High risk of conversion to diabetes in first-degree relatives of individuals with young-onset type 2 diabetes: a 12-year follow-up analysis. Diabet Med 2017; 34:1701-1709. [PMID: 28945282 DOI: 10.1111/dme.13516] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 09/19/2017] [Indexed: 11/27/2022]
Abstract
AIM Family history of diabetes is an established risk factor for Type 2 diabetes, but the impact of a family history of young-onset diabetes (onset < 40 years) on future risk of diabetes among first-degree relatives is unclear. In this prospective study, we examined the influence of family history of late- versus young-onset diabetes on the development of diabetes in a young to middle-aged Chinese population. METHODS Some 365 siblings identified through probands with Type 2 diabetes and 452 participants from a community-based health awareness project (aged 18-55 years) who underwent metabolic assessment during the period 1998-2002 were followed to 2012-2013 to determine their glycaemic status. Multivariate logistic regression was performed to investigate the association of family history of diabetes presented at different age categories with development of diabetes. RESULTS In this cohort, 53.4% (n = 167) of participants with a family history of young-onset diabetes, 30.1% (n = 68) of those with a family history of late-onset diabetes and 14.4% (n = 40) of those without a family history developed diabetes. Using logistic regression, family history of diabetes presented at ages ≥ 50, 40-49, 30-39 and < 30 years, increased conversion to diabetes with respective odds ratios of 2.4, 5.8, 9.4 and 7.0 (P < 0.001 for all), after adjustment for socio-economic status, smoking, obesity, hypertension and dyslipidaemia. Among participants without diabetes at baseline, risk association of family history of late-onset diabetes with incident diabetes was not sustained, whereas that of family history of young-onset diabetes remained robust on further adjustment for baseline glycaemic measurements. CONCLUSIONS First-degree relatives of people with Type 2 diabetes, especially relatives of those with young-onset diabetes, are at high risk for diabetes.
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Affiliation(s)
- Y Zhang
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - A O Y Luk
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Li Ka Shing Institute of Health and Sciences, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - E Chow
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - G T C Ko
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - M H M Chan
- Department of Chemical Pathology, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - M Ng
- Department of Haematology, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - A P S Kong
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Li Ka Shing Institute of Health and Sciences, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - R C W Ma
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Li Ka Shing Institute of Health and Sciences, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - R Ozaki
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - W Y So
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - C C Chow
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
| | - J C N Chan
- Department of Medicine and Therapeutics, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Hong Kong Institute of Diabetes and Obesity, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
- Li Ka Shing Institute of Health and Sciences, Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong
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Wessel J, Marrero D. Genetic Testing for Type 2 Diabetes in High-Risk Children: the Case for Primordial Prevention. RESEARCH IDEAS AND OUTCOMES 2017. [DOI: 10.3897/rio.3.e20695] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022] Open
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Wang JY, Liu CS, Lung CH, Yang YT, Lin MH. Investigating spousal concordance of diabetes through statistical analysis and data mining. PLoS One 2017; 12:e0183413. [PMID: 28817654 PMCID: PMC5560637 DOI: 10.1371/journal.pone.0183413] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2017] [Accepted: 08/03/2017] [Indexed: 12/30/2022] Open
Abstract
OBJECTIVE Spousal clustering of diabetes merits attention. Whether old-age vulnerability or a shared family environment determines the concordance of diabetes is also uncertain. This study investigated the spousal concordance of diabetes and compared the risk of diabetes concordance between couples and noncouples by using nationally representative data. METHODS A total of 22,572 individuals identified from the 2002-2013 National Health Insurance Research Database of Taiwan constituted 5,643 couples and 5,643 noncouples through 1:1 dual propensity score matching (PSM). Factors associated with concordance in both spouses with diabetes were analyzed at the individual level. The risk of diabetes concordance between couples and noncouples was compared at the couple level. Logistic regression was the main statistical method. Statistical data were analyzed using SAS 9.4. C&RT and Apriori of data mining conducted in IBM SPSS Modeler 13 served as a supplement to statistics. RESULTS High odds of the spousal concordance of diabetes were associated with old age, middle levels of urbanization, and high comorbidities (all P < 0.05). The dual PSM analysis revealed that the risk of diabetes concordance was significantly higher in couples (5.19%) than in noncouples (0.09%; OR = 61.743, P < 0.0001). CONCLUSIONS A high concordance rate of diabetes in couples may indicate the influences of assortative mating and shared environment. Diabetes in a spouse implicates its risk in the partner. Family-based diabetes care that emphasizes the screening of couples at risk of diabetes by using the identified risk factors is suggested in prospective clinical practice interventions.
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Affiliation(s)
- Jong-Yi Wang
- Department of Health Services Administration, China Medical University, Taichung, Taiwan
| | - Chiu-Shong Liu
- Department of Family Medicine, China Medical University Hospital, Taichung, Taiwan
- Department of Medicine, China Medical University, Taichung, Taiwan
| | - Chi-Hsuan Lung
- Department of Social Work, National Quemoy University, Kinmen, Taiwan
| | - Ya-Tun Yang
- Management Center, Kuang Tien General Hospital, Taichung, Taiwan
| | - Ming-Hung Lin
- Department of Public Health, China Medical University, Taichung, Taiwan
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Miranda-Lora AL, Vilchis-Gil J, Molina-Díaz M, Flores-Huerta S, Klünder-Klünder M. Heritability, parental transmission and environment correlation of pediatric-onset type 2 diabetes mellitus and metabolic syndrome-related traits. Diabetes Res Clin Pract 2017; 126:151-159. [PMID: 28242438 DOI: 10.1016/j.diabres.2017.02.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2016] [Revised: 12/27/2016] [Accepted: 02/02/2017] [Indexed: 01/16/2023]
Abstract
AIM To estimate the heritability, parental transmission and environmental contributions to the phenotypic variation in type 2 diabetes mellitus and metabolic syndrome-related traits in families of Mexican children and adolescents. METHODS We performed a cross-sectional study of 184 tri-generational pedigrees with a total of 1160 individuals (99 families with a type 2 diabetes mellitus proband before age 19). The family history of type 2 diabetes mellitus in three generations was obtained by interview. Demographic, anthropometric, biochemical and lifestyle information was corroborated in parents and offspring. We obtained correlations for metabolic traits between relative pairs, and variance component methods were used to determine the heritability and environmental components. RESULTS The heritability of early-onset of type 2 diabetes mellitus was 0.50 (p<1.0e-7). The heritability was greater than 0.5 for hypertension, hypoalphalipoproteinemia, hypercholesterolemia, body mass index, waist circumference, blood pressure, 2-h insulin, and cholesterol (p<0.001). In contrast, we observed a high environmental correlation (>0.50) for blood pressure, HbA1c and HDL-cholesterol after multivariate adjustment (p<0.05). Several traits, such as type 2 diabetes mellitus and insulin resistance, were significantly correlated only through the mother and others, such as hypertriglyceridemia, were significantly correlated only through the father. CONCLUSION This study demonstrates that type 2 diabetes mellitus and metabolic syndrome-related traits are highly heritable among Mexican children and adolescents. Furthermore, several cardiometabolic factors have strong heritability and/or high environmental contributions that highlight the complex architecture of these alterations.
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Affiliation(s)
- América L Miranda-Lora
- Research Unit of Medicine Based on Evidence, Hospital Infantil de México Federico Gómez, Mexico City, Mexico
| | - Jenny Vilchis-Gil
- Community Health Research Department, Hospital Infantil de México Federico Gómez, Mexico City, Mexico
| | - Mario Molina-Díaz
- Department of Endocrinology, Hospital Infantil de México Federico Gómez, Mexico City, Mexico
| | - Samuel Flores-Huerta
- Community Health Research Department, Hospital Infantil de México Federico Gómez, Mexico City, Mexico
| | - Miguel Klünder-Klünder
- Community Health Research Department, Hospital Infantil de México Federico Gómez, Mexico City, Mexico; Research Committee, Latin American Society for Pediatric Gastroenterology, Hepatology and Nutrition (LASPGHAN), Mexico City, Mexico.
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26
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Bellatorre A, Jackson SH, Choi K. Development of the diabetes typology model for discerning Type 2 diabetes mellitus with national survey data. PLoS One 2017; 12:e0173103. [PMID: 28253317 PMCID: PMC5333874 DOI: 10.1371/journal.pone.0173103] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2016] [Accepted: 02/15/2017] [Indexed: 01/09/2023] Open
Abstract
Objective To classify individuals with diabetes mellitus (DM) into DM subtypes using population-based studies. Design Population-based survey Setting Individuals participated in 2003–2004, 2005–2006, or 2009–2010 the National Health and Nutrition Examination Survey (NHANES), and 2010 Coronary Artery Risk Development in Young Adults (CARDIA) survey (research materials obtained from the National Heart, Lung, and Blood Institute Biologic Specimen and Data Repository Information Coordinating Center) Participants 3084, 3040 and 3318 US adults from the 2003–2004, 2005–2006 and 2009–2010 NHANES samples respectively, and 5,115 US adults in the CARDIA cohort Primary outcome measures We proposed the Diabetes Typology Model (DTM) through the use of six composite measures based on the Homeostatic Model Assessment (HOMA-IR, HOMA-%β, high HOMA-%S), insulin and glucose levels, and body mass index and conducted latent class analyses to empirically classify individuals into different classes. Results Three empirical latent classes consistently emerged across studies (entropy = 0.81–0.998). These three classes were likely Type 1 DM, likely Type 2 DM, and atypical DM. The classification has high sensitivity (75.5%), specificity (83.3%), and positive predictive value (97.4%) when validated against C-peptide level. Correlates of Type 2 DM were significantly associated with model-identified Type 2 DM. Compared to regression analysis on known correlates of Type 2 DM using all diabetes cases as outcomes, using DTM to remove likely Type 1 DM and atypical DM cases results in a 2.5–5.3% r-square improvement in the regression analysis, as well as model fits as indicated by significant improvement in -2 log likelihood (p<0.01). Lastly, model-defined likely Type 2 DM was significantly associated with known correlates of Type 2 DM (e.g., age, waist circumference), which provide additional validation of the DTM-defined classes. Conclusions Our Diabetes Typology Model reflects a promising first step toward discerning likely DM types from population-based data. This novel tool will improve how large population-based studies can be used to examine behavioral and environmental factors associated with different types of DM.
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Affiliation(s)
- Anna Bellatorre
- Division of Intramural Research, National Institute on Minority Health and Health Disparities, Bethesda, Maryland, United States of America
| | - Sharon H. Jackson
- Division of Intramural Research, National Institute on Minority Health and Health Disparities, Bethesda, Maryland, United States of America
| | - Kelvin Choi
- Division of Intramural Research, National Institute on Minority Health and Health Disparities, Bethesda, Maryland, United States of America
- * E-mail:
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Deng L, Liu S, Gong Y, Tian H, Liu Y, Song J, Ran X, Yu H, Zhang X, Long Y, Ren Y. Increased Metabolic Disorders and Impaired Insulin Secretory Function in the First-Degree Relatives of Type 2 Diabetic Patients with Normal Glucose Tolerance. Metab Syndr Relat Disord 2016; 14:431-436. [PMID: 27689409 DOI: 10.1089/met.2016.0002] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Affiliation(s)
- Liling Deng
- Development of Endocrinology and Metabolism, West China Hospital of Sichuan University, Chengdu, China
| | - Songfang Liu
- Division of Endocrinology and Metabolism, Ninth Hospital of Xi'an, Xi'an, China
| | - Yuan Gong
- Development of Endocrinology and Metabolism, West China Hospital of Sichuan University, Chengdu, China
| | - Haoming Tian
- Development of Endocrinology and Metabolism, West China Hospital of Sichuan University, Chengdu, China
| | - Yuanyuan Liu
- Development of Endocrinology and Metabolism, West China Hospital of Sichuan University, Chengdu, China
| | - Jie Song
- Development of Endocrinology and Metabolism, West China Hospital of Sichuan University, Chengdu, China
| | - Xingwu Ran
- Development of Endocrinology and Metabolism, West China Hospital of Sichuan University, Chengdu, China
| | - Honglin Yu
- Laboratory of Endocrinology and Metabolism, West China Hospital of Sichuan University, Chengdu, China
| | - Xiangxun Zhang
- Laboratory of Endocrinology and Metabolism, West China Hospital of Sichuan University, Chengdu, China
| | - Yang Long
- Laboratory of Endocrinology and Metabolism, West China Hospital of Sichuan University, Chengdu, China
| | - Yan Ren
- Development of Endocrinology and Metabolism, West China Hospital of Sichuan University, Chengdu, China
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Sung YJ, Pérusse L, Sarzynski MA, Fornage M, Sidney S, Sternfeld B, Rice T, Terry G, Jacobs DR, Katzmarzyk P, Curran JE, Carr JJ, Blangero J, Ghosh S, Després JP, Rankinen T, Rao D, Bouchard C. Genome-wide association studies suggest sex-specific loci associated with abdominal and visceral fat. Int J Obes (Lond) 2016; 40:662-74. [PMID: 26480920 PMCID: PMC4821694 DOI: 10.1038/ijo.2015.217] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2015] [Revised: 10/05/2015] [Accepted: 10/06/2015] [Indexed: 12/21/2022]
Abstract
BACKGROUND To identify loci associated with abdominal fat and replicate prior findings, we performed genome-wide association (GWA) studies of abdominal fat traits: subcutaneous adipose tissue (SAT); visceral adipose tissue (VAT); total adipose tissue (TAT) and visceral to subcutaneous adipose tissue ratio (VSR). SUBJECTS AND METHODS Sex-combined and sex-stratified analyses were performed on each trait with (TRAIT-BMI) or without (TRAIT) adjustment for body mass index (BMI), and cohort-specific results were combined via a fixed effects meta-analysis. A total of 2513 subjects of European descent were available for the discovery phase. For replication, 2171 European Americans and 772 African Americans were available. RESULTS A total of 52 single-nucleotide polymorphisms (SNPs) encompassing 7 loci showed suggestive evidence of association (P<1.0 × 10(-6)) with abdominal fat in the sex-combined analyses. The strongest evidence was found on chromosome 7p14.3 between a SNP near BBS9 gene and VAT (rs12374818; P=1.10 × 10(-7)), an association that was replicated (P=0.02). For the BMI-adjusted trait, the strongest evidence of association was found between a SNP near CYCSP30 and VAT-BMI (rs10506943; P=2.42 × 10(-7)). Our sex-specific analyses identified one genome-wide significant (P<5.0 × 10(-8)) locus for SAT in women with 11 SNPs encompassing the MLLT10, DNAJC1 and EBLN1 genes on chromosome 10p12.31 (P=3.97 × 10(-8) to 1.13 × 10(-8)). The THNSL2 gene previously associated with VAT in women was also replicated (P=0.006). The six gene/loci showing the strongest evidence of association with VAT or VAT-BMI were interrogated for their functional links with obesity and inflammation using the Biograph knowledge-mining software. Genes showing the closest functional links with obesity and inflammation were ADCY8 and KCNK9, respectively. CONCLUSIONS Our results provide evidence for new loci influencing abdominal visceral (BBS9, ADCY8, KCNK9) and subcutaneous (MLLT10/DNAJC1/EBLN1) fat, and confirmed a locus (THNSL2) previously reported to be associated with abdominal fat in women.
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Affiliation(s)
- Yun Ju Sung
- Division of Biostatistics, Washington University School of Medicine, St-Louis, MO
| | - Louis Pérusse
- Department of Kinesiology, School of Medicine and Institute of Nutrition and Functional Foods, Laval University, Québec, QC
| | - Mark A. Sarzynski
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA
| | - Myriam Fornage
- Center for Human Genetics, University of Texas Health Science Center, Houston, TX
| | - Steve Sidney
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Barbara Sternfeld
- Division of Research, Kaiser Permanente Northern California, Oakland, CA
| | - Treva Rice
- Division of Biostatistics, Washington University School of Medicine, St-Louis, MO
| | - Gregg Terry
- Department of Radiology, School of Medicine, Vanderbilt University, Nahsville, TN
| | - David R. Jacobs
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN
| | - Peter Katzmarzyk
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA
| | - Joanne E Curran
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, TX
| | - John Jeffrey Carr
- Department of Radiology, School of Medicine, Vanderbilt University, Nahsville, TN
| | - John Blangero
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, TX
| | - Sujoy Ghosh
- Cardiovascular and Metabolic Disorders Program and Center for Computational Biology, Duke-NUS Graduate Medical School, Singapore
| | - Jean-Pierre Després
- Department of Kinesiology, School of Medicine and Institute of Nutrition and Functional Foods, Laval University, Québec, QC
- Centre de recherché de l’Institut universitaire de cardiologie et de pneumologie de Québec, Québec, QC
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA
| | - D.C. Rao
- Division of Biostatistics, Washington University School of Medicine, St-Louis, MO
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA
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Janghorbani M, Amini M. Progression from optimal blood glucose and pre-diabetes to type 2 diabetes in a high risk population with or without hypertension in Isfahan, Iran. Diabetes Res Clin Pract 2015; 108:414-22. [PMID: 25814432 DOI: 10.1016/j.diabres.2015.03.002] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/12/2014] [Revised: 09/03/2014] [Accepted: 03/06/2015] [Indexed: 12/25/2022]
Abstract
AIM To estimate the progression rates from normal glucose tolerance (NGT), isolated impaired glucose tolerance (IGT), isolated impaired fasting glucose (IFG) and combined IFG/IGT to type 2 diabetes (T2D) in a high risk population with and without hypertension (HTN) in Isfahan, Iran. METHODS During a mean (SD) follow-up period of 6.8 (1.7) years, 1489 non-diabetic first-degree relatives of patients with T2D with or without HTN were followed for the occurrence of T2D. At baseline and through follow-ups, participants underwent a standard 75g 2-h oral glucose tolerance test. Blood pressure was measured by standardised protocols and HTN was defined according to the criteria of the JNC7. RESULTS The progression rate (95% confidence interval) from NGT, isolated IFG, isolated IGT, and combined IFG/IGT to T2D was 10.0 (4.3, 19.6), 21.7 (9.5, 42.3), 28.2 (12.3, 54.7) and 64.7 (41.0, 96.4) per 1000 person-years in participants with HTN and 3.1 (1.5, 4.7), 16.3 (10.3, 24.2), 25.9 (17.0, 37.7) and 57.9 (46.1, 71.7) per 1000 person-years in participants without HTN based on 10,134 person-years of follow-up. Compared with individuals with NGT and without HTN, individuals with NGT and HTN, isolated IFG, isolated IGT, and combined IFG/IGT with or without HTN at baseline were more likely to progress to T2D. Compared with participants without HTN, individuals with concomitant HTN were not significantly more likely to progress to T2D. CONCLUSIONS Compared with individuals without HTN, the presence of NGT, isolated IFG, isolated IGT, and combined IFG/IGT with concomitant HTN was not associated with higher likelihood of progression to T2D in high-risk individuals in Iran.
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Affiliation(s)
- Mohsen Janghorbani
- Department of Epidemiology and Biostatistics, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran; Isfahan Endocrine and Metabolism Research Center, Isfahan University of Medical Sciences, Isfahan, Iran.
| | - Masoud Amini
- Isfahan Endocrine and Metabolism Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
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Sung J, Lee K, Song YM, Lee M, Kim J. Genetic and baseline metabolic factors for incident diabetes and HbA(1c) at follow-up: the healthy twin study. Diabetes Metab Res Rev 2015; 31:376-84. [PMID: 25400114 DOI: 10.1002/dmrr.2619] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2014] [Revised: 10/03/2014] [Accepted: 10/27/2014] [Indexed: 12/30/2022]
Abstract
BACKGROUND We investigated baseline anthropometric/metabolic traits predicting incident diabetes, genetic/environmental relationships between these traits and HbA1c at follow-up and the contribution of genetics, covariates and environments to variance in HbA(1c) at follow-up and incident diabetes. METHODS Nondiabetic twins (n = 869) and their family members (n = 949) were followed over 3.7 ± 1.4 years (44.3 ± 12.8 years of age); baseline anthropometric/metabolic traits were measured. Fasting plasma glucose and HbA(1c) were measured at follow-up. Incident diabetes was defined as HbA(1c) ≥6.5% or fasting plasma glucose ≥7 mmol/L. RESULTS Age-adjusted incident diabetes was 4.9% in men and 4.1% in women. Odd ratio for incident diabetes was 2.34-2.40, 1.25-1.28, 1.22-1.27 and 1.89 per standard deviation of baseline fasting plasma glucose, white blood cell (WBC), triglycerides and waist circumference, respectively, in multivariate generalized estimating equation models (p < 0.05). Age-adjusted and sex-adjusted heritability was 0.85 for diabetes and 0.72 for HbA(1c). In bivariate analyses adjusted for age, sex and body mass index at baseline, HbA1c at follow-up showed significant genetic and environmental correlations with baseline glucose (0.44, 0.17), significant genetic correlation with baseline waist circumference (0.16) and triglycerides (0.30) and significant environmental correlation with baseline WBC (0.09). Variance in HbA1c at follow-up and incident diabetes was explained by genetics (33% and 28%, respectively), covariates (36% and 48%, respectively), shared environments (7% and 0%, respectively) and errors (24% and 24%, respectively). CONCLUSIONS High values for baseline fasting plasma glucose, WBC, triglycerides and waist circumference are independent risk factors for incident diabetes. While genetic influences strongly contribute to variance in HbA1c at follow-up and incident diabetes, these risk factors significantly contribute to the remaining variance.
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Affiliation(s)
- Joohon Sung
- Department of Epidemiology, School of Public Health, Seoul National University, Seoul, South Korea; Institute of Health Environment, Seoul National University, Seoul, South Korea
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Rankinen T, Sarzynski MA, Ghosh S, Bouchard C. Are there genetic paths common to obesity, cardiovascular disease outcomes, and cardiovascular risk factors? Circ Res 2015; 116:909-22. [PMID: 25722444 PMCID: PMC4416656 DOI: 10.1161/circresaha.116.302888] [Citation(s) in RCA: 84] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2014] [Accepted: 12/08/2014] [Indexed: 12/24/2022]
Abstract
Clustering of obesity, coronary artery disease, and cardiovascular disease risk factors is observed in epidemiological studies and clinical settings. Twin and family studies have provided some supporting evidence for the clustering hypothesis. Loci nearest a lead single nucleotide polymorphism (SNP) showing genome-wide significant associations with coronary artery disease, body mass index, C-reactive protein, blood pressure, lipids, and type 2 diabetes mellitus were selected for pathway and network analyses. Eighty-seven autosomal regions (181 SNPs), mapping to 56 genes, were found to be pleiotropic. Most pleiotropic regions contained genes associated with coronary artery disease and plasma lipids, whereas some exhibited coaggregation between obesity and cardiovascular disease risk factors. We observed enrichment for liver X receptor (LXR)/retinoid X receptor (RXR) and farnesoid X receptor/RXR nuclear receptor signaling among pleiotropic genes and for signatures of coronary artery disease and hepatic steatosis. In the search for functionally interacting networks, we found that 43 pleiotropic genes were interacting in a network with an additional 24 linker genes. ENCODE (Encyclopedia of DNA Elements) data were queried for distribution of pleiotropic SNPs among regulatory elements and coding sequence variations. Of the 181 SNPs, 136 were annotated to ≥ 1 regulatory feature. An enrichment analysis found over-representation of enhancers and DNAse hypersensitive regions when compared against all SNPs of the 1000 Genomes pilot project. In summary, there are genomic regions exerting pleiotropic effects on cardiovascular disease risk factors, although only a few included obesity. Further studies are needed to resolve the clustering in terms of DNA variants, genes, pathways, and actionable targets.
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Affiliation(s)
- Tuomo Rankinen
- From the Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA (T.R., M.A.S., S.G., C.B.); and Cardiovascular and Metabolic Disorders Program (S.G.) and Center for Computational Biology (S.G.), Duke-NUS Graduate Medical School, Singapore, Singapore
| | - Mark A Sarzynski
- From the Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA (T.R., M.A.S., S.G., C.B.); and Cardiovascular and Metabolic Disorders Program (S.G.) and Center for Computational Biology (S.G.), Duke-NUS Graduate Medical School, Singapore, Singapore
| | - Sujoy Ghosh
- From the Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA (T.R., M.A.S., S.G., C.B.); and Cardiovascular and Metabolic Disorders Program (S.G.) and Center for Computational Biology (S.G.), Duke-NUS Graduate Medical School, Singapore, Singapore
| | - Claude Bouchard
- From the Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, LA (T.R., M.A.S., S.G., C.B.); and Cardiovascular and Metabolic Disorders Program (S.G.) and Center for Computational Biology (S.G.), Duke-NUS Graduate Medical School, Singapore, Singapore.
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32
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Hoque ME, Khokan MR, Bari W. "Impact of stature on non-communicable diseases: evidence based on Bangladesh Demographic and Health Survey, 2011 data". BMC Public Health 2014; 14:1007. [PMID: 25261299 PMCID: PMC4195861 DOI: 10.1186/1471-2458-14-1007] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2014] [Accepted: 09/16/2014] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND In this paper, an attempt has been made to explore the relationship between height and occurrence of the non-communicable diseases such as diabetes and hypertension. METHODS For the purpose of analysis, Bangladesh Demographic and Health Survey (BDHS), 2011 data was used. Bivariate analysis along with a Chi-square test was performed to examine association between height and diseases. To measure the impact of stature on diabetes and hypertension, three different logistic regression models (Model I: considering only quartiles of height, Model II: covariates of model I along with demographic variables and Model III: covariates of model II along with clinical variable) were considered. RESULTS Occurrence of diabetes and hypertension was found to be inversely related with the height of participants. This inverse association was statistically significant for all three models. After controlling the demographic and clinical variables simultaneously, the odds ratio for highest quartile compared to the lowest quartile was 0.82 with 95% confidence interval (0.69, 0.98) for diabetes; whereas it was 0.72 with 95% confidence interval (0.55, 0.95) for hypertension. CONCLUSIONS Findings of this paper indicate that persons with shorter stature are substantially more likely to develop diabetes as well as hypertension. The occurrence of non-communicable diseases like diabetes and hypertension can be reduced by controlling genetic and non-genetic (early-life and childhood) factors that may influence the height.
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Affiliation(s)
- Md Erfanul Hoque
- Department of Statistics, Biostatistics & Informatics, University of Dhaka, Dhaka, 1000, Bangladesh.
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Naranjo DM, Jacobs EA, Fisher L, Hessler D, Fernandez A. Age and glycemic control among low-income Latinos. J Immigr Minor Health 2014; 15:898-902. [PMID: 22843322 DOI: 10.1007/s10903-012-9689-0] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Younger adult patients with diabetes often have poorer glycemic control (HbA1c) than older patients. It is not known if this relationship holds true in the Latino population. Objective was to explore the relationship between age and HbA1c in a Mexican American population and what plausible factors might mediate this relationship. We analyzed data from 387 patients with diabetes self-identified as Mexican American recruited as a part of a cross-sectional study of safety net patients in two cities. Patients completed questionnaires and their last HbA1c was extracted from the medical record. We conducted multivariate regression analyses and Baron and Kenny tests of mediation. Participants were young with mean age of 53 ± 12 years. Younger age was associated with a higher HbA1c and having a higher fat diet. High fat diet partially mediated the relationship between age and HbA1c (p < 0.001 to p < 0.01). Age's indirect effect on HbA1c through diet was significant (Sobel = -2.44, p = 0.01). Younger Mexican American patients had higher HbA1c compared to older patients. Having a diet high in fat partially explained this relationship. Future epidemiological studies are needed to understand the multifaceted relationship between age and glycemic control.
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Affiliation(s)
- Diana M Naranjo
- Department of Pediatrics, UCSF School of Medicine, San Francisco, CA 94143-0318, USA.
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Mamtani M, Meikle PJ, Kulkarni H, Weir JM, Barlow CK, Jowett JB, Bellis C, Dyer TD, Almasy L, Mahaney MC, Duggirala R, Comuzzie AG, Blangero J, Curran JE. Plasma dihydroceramide species associate with waist circumference in Mexican American families. Obesity (Silver Spring) 2014; 22:950-6. [PMID: 23929697 PMCID: PMC3918249 DOI: 10.1002/oby.20598] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/17/2013] [Accepted: 08/03/2013] [Indexed: 12/11/2022]
Abstract
OBJECTIVE Waist circumference (WC), the clinical marker of central obesity, is gaining popularity as a screening tool for type 2 diabetes (T2D). While there is epidemiologic evidence favoring the WC-T2D association, its biological substantiation is generally weak. Our objective was to determine the independent association of plasma lipid repertoire with WC. METHODS Samples and data from the San Antonio Family Heart Study of 1208 Mexican Americans from 42 extended families were used. Association of plasma lipidomic profiles with the cross-sectionally assessed WC was determined. Plasma lipidomic profiling entailed liquid chromatography with mass spectrometry. Statistical analyses included multivariable polygenic regression models and bivariate trait analyses using the SOLAR software. RESULTS After adjusting for age and sex interactions, body mass index, homeostasis model of assessment-insulin resistance, total cholesterol, triglycerides, high density lipoproteins and use of lipid lowering drugs, dihydroceramides as a class were associated with WC. Dihydroceramide species 18:0, 20:0, 22:0, and 24:1 were significantly associated and genetically correlated with WC. Two sphingomyelin species (31:1 and 41:1) were also associated with WC. CONCLUSIONS Plasma dihydroceramide levels independently associate with WC. Thus, high resolution plasma lipidomic studies can provide further credence to the biological underpinnings of the association of WC with T2D.
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Affiliation(s)
- Manju Mamtani
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| | - Peter J. Meikle
- Baker IDI Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
| | - Hemant Kulkarni
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| | - Jacquelyn M. Weir
- Baker IDI Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
| | | | - Jeremy B. Jowett
- Baker IDI Heart and Diabetes Institute, Melbourne, VIC 3004, Australia
| | - Claire Bellis
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| | - Thomas D. Dyer
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| | - Laura Almasy
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| | - Michael C. Mahaney
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| | | | - Anthony G. Comuzzie
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| | - John Blangero
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
| | - Joanne E. Curran
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX 78227, USA
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Celik C, Tasdemir N, Abali R, Bastu E, Yilmaz M. Progression to impaired glucose tolerance or type 2 diabetes mellitus in polycystic ovary syndrome: a controlled follow-up study. Fertil Steril 2014; 101:1123-8.e1. [PMID: 24502891 DOI: 10.1016/j.fertnstert.2013.12.050] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2013] [Revised: 12/23/2013] [Accepted: 12/26/2013] [Indexed: 01/01/2023]
Abstract
OBJECTIVE To investigate whether retesting with the oral glucose tolerance test (OGTT) is useful and necessary for all women with polycystic ovary syndrome (PCOS). DESIGN Follow-up study. SETTING Tertiary medical center. PATIENT(S) Eighty-four women with PCOS and 45 healthy controls. INTERVENTION(S) Peripheral venous blood sampling. MAIN OUTCOME MEASURE(S) We performed a 75-g 2-hour OGTT in women with normal glucose tolerance (NGT) and impaired glucose tolerance (IGT) at the time of the first test with and without PCOS. RESULT(S) The average follow-up period for women with PCOS was 2.6 years (range, 2-4.17 years). Seventy-eight of these women had NGT at baseline, 11.5% converted to IGT, with an annualized incidence rate of 4.5%. Of those women with IGT at baseline (n = 6), 33.3% converted to type 2 diabetes mellitus, with an annualized incidence rate of 10.4%. In the healthy subjects, the average follow-up period was 2.6 years (range, 2-4.08 years). Forty-two of these women had NGT at baseline, 2.3% converted to IGT, giving a progression of 0.9% per year. Among the three women with IGT at baseline, 33.3% reverted to NGT, and 66.6% had persistent IGT. CONCLUSION(S) Conversion rates from NGT to IGT or type 2 diabetes mellitus were accelerated in women with PCOS compared with healthy subjects. Women with PCOS should be tested regularly for early detection of abnormal glucose tolerance. In addition, the interval for periodic rescreening should be determined by further studies involving more women with PCOS.
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Affiliation(s)
- Cem Celik
- Department of Gynecology and Obstetrics, Faculty of Medicine, Namik Kemal University, Tekirdag, Turkey.
| | - Nicel Tasdemir
- Department of Gynecology and Obstetrics, Faculty of Medicine, Namik Kemal University, Tekirdag, Turkey
| | - Remzi Abali
- Department of Gynecology and Obstetrics, Faculty of Medicine, Namik Kemal University, Tekirdag, Turkey
| | - Ercan Bastu
- Department of Gynecology and Obstetrics, Faculty of Medicine, Istanbul University, Istanbul, Turkey
| | - Murat Yilmaz
- Department of Endocrinology and Metabolism, Faculty of Medicine, Namik Kemal University, Tekirdag, Turkey
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Abstract
In the 2013 issue of the International Diabetes Federation (IDF) Diabetes Atlas, the prevalence of diabetes in the Western Pacific (WP) Region was reported to be 8.6% in 2013, or 138 million adults, and estimated to rise to 11.1%, or 201 million adults, in 2035. The prevalence estimates of impaired glucose tolerance in 2013 and 2035 were 6.8% and 9.0%, respectively. Over 50% of people with diabetes were undiagnosed. In 2013, 187 million deaths were attributable to diabetes, 44% of which occurred in the under the age of 60. The WP Region is home to one quarter of the world's population, and includes China with the largest number of people with diabetes as well as Pacific Islands countries with the highest prevalence rates. There is a rapid increase in diabetes prevalence in the young-to-middle aged adults, possibly driven by high rates of childhood obesity and gestational diabetes as well as rapid demographic and sociocultural transitions. Differences in genetics, ethnicity, cultures and socioeconomic development have led to complex host-environment-lifestyle interactions with marked disease heterogeneity, further influenced by access to care and treatment. Despite these challenges, the WP Region has provided notable examples to prevent and control diabetes.
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Affiliation(s)
- Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China; Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China; Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong, China.
| | - Nam H Cho
- Department of Preventive Medicine, Ajou University School of Medicine, Suwon, Republic of Korea
| | - Naoko Tajima
- Jikei University School of Medicine, Tokyo, Japan
| | - Jonathan Shaw
- Baker IDI Heart and Diabetes Institute, Melbourne, Australia
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Ma RCW, Lee HM, Lam VKL, Tam CHT, Ho JSK, Zhao HL, Guan J, Kong APS, Lau E, Zhang G, Luk A, Wang Y, Tsui SKW, Chan TF, Hu C, Jia WP, Park KS, Lee HK, Furuta H, Nanjo K, Tai ES, Ng DPK, Tang NLS, Woo J, Leung PC, Xue H, Wong J, Leung PS, Lau TCK, Tong PCY, Xu G, Ng MCY, So WY, Chan JCN. Familial young-onset diabetes, pre-diabetes and cardiovascular disease are associated with genetic variants of DACH1 in Chinese. PLoS One 2014; 9:e84770. [PMID: 24465431 PMCID: PMC3896349 DOI: 10.1371/journal.pone.0084770] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2013] [Accepted: 11/19/2013] [Indexed: 01/02/2023] Open
Abstract
In Asia, young-onset type 2 diabetes (YOD) is characterized by obesity and increased risk for cardiovascular disease (CVD). In a genome-wide association study (GWAS) of 99 Chinese obese subjects with familial YOD diagnosed before 40-year-old and 101 controls, the T allele of rs1408888 in intron 1 of DACH1(Dachshund homolog 1) was associated with an odds ratio (OR) of 2.49(95% confidence intervals:1.57-3.96, P = 8.4 × 10(-5)). Amongst these subjects, we found reduced expression of DACH1 in peripheral blood mononuclear cells (PBMC) from 63 cases compared to 65 controls (P = 0.02). In a random cohort of 1468 cases and 1485 controls, amongst top 19 SNPs from GWAS, rs1408888 was associated with type 2 diabetes with a global P value of 0.0176 and confirmation in a multiethnic Asian case-control cohort (7370/7802) with an OR of 1.07(1.02-1.12, P(meta) = 0.012). In 599 Chinese non-diabetic subjects, rs1408888 was linearly associated with systolic blood pressure and insulin resistance. In a case-control cohort (n = 953/953), rs1408888 was associated with an OR of 1.54(1.07-2.22, P = 0.019) for CVD in type 2 diabetes. In an autopsy series of 173 non-diabetic cases, TT genotype of rs1408888 was associated with an OR of 3.31(1.19-9.19, P = 0.0214) and 3.27(1.25-11.07, P = 0.0184) for coronary heart disease (CHD) and coronary arteriosclerosis. Bioinformatics analysis revealed that rs1408888 lies within regulatory elements of DACH1 implicated in islet development and insulin secretion. The T allele of rs1408888 of DACH1 was associated with YOD, prediabetes and CVD in Chinese.
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Affiliation(s)
- Ronald Ching Wan Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Heung Man Lee
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Vincent Kwok Lim Lam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Claudia Ha Ting Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Janice Siu Ka Ho
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Hai-Lu Zhao
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Jing Guan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Alice Pik Shan Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Eric Lau
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Guozhi Zhang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Andrea Luk
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Ying Wang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Stephen Kwok Wing Tsui
- School of Biomedical Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Ting Fung Chan
- School of Life Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Cheng Hu
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, People’s Republic of China
| | - Wei Ping Jia
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, People’s Republic of China
| | - Kyong Soo Park
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology and Department of Internal Medicine, College of Medicine, Seoul National University, Chongno-gu, Seoul, Korea
| | - Hong Kyu Lee
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology and Department of Internal Medicine, College of Medicine, Seoul National University, Chongno-gu, Seoul, Korea
| | - Hiroto Furuta
- First Department of Medicine, Wakayama Medical University, Wakayama, Japan
| | - Kishio Nanjo
- First Department of Medicine, Wakayama Medical University, Wakayama, Japan
| | - E. Shyong Tai
- Department of Epidemiology and Public Health, National University of Singapore, Singapore, Singapore
| | - Daniel Peng-Keat Ng
- Department of Epidemiology and Public Health, National University of Singapore, Singapore, Singapore
| | - Nelson Leung Sang Tang
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Department of Chemical Pathology, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Jean Woo
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Ping Chung Leung
- Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Hong Xue
- Department of Biochemistry, Hong Kong University of Science and Technology, Hong Kong SAR, People’s Republic of China
| | - Jeffrey Wong
- Department of Biochemistry, Hong Kong University of Science and Technology, Hong Kong SAR, People’s Republic of China
| | - Po Sing Leung
- School of Biomedical Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Terrence C. K. Lau
- School of Biomedical Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Peter Chun Yip Tong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People’s Republic of China
| | - Gang Xu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Maggie Chor Yin Ng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Wing Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
| | - Juliana Chung Ngor Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People’s Republic of China
- Li Ka Shing Institute of Health Science, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People’s Republic of China
- * E-mail:
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Mamtani M, Kulkarni H, Dyer TD, Almasy L, Mahaney MC, Duggirala R, Comuzzie AG, Blangero J, Curran JE. Waist circumference is genetically correlated with incident Type 2 diabetes in Mexican-American families. Diabet Med 2014; 31:31-5. [PMID: 23796311 PMCID: PMC3849209 DOI: 10.1111/dme.12266] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/18/2013] [Indexed: 12/20/2022]
Abstract
AIMS We aimed to determine the genetic and environmental correlation between various anthropometric indexes and incident Type 2 diabetes with a focus on waist circumference. METHODS We used the data on extended Mexican-American families (808 subjects, 7617.92 person-years follow-up) from the San Antonio Family Heart Study and estimated the genetic and environmental correlations of 16 anthropometric indexes with the genetic liability of incident Type 2 diabetes. We performed bivariate trait analyses using the solar software package. RESULTS All 16 anthropometric indexes were significantly heritable (range of heritabilities 0.24-0.99). Thirteen indexes were found to have significant environmental correlation with the liability of incident Type 2 diabetes. In contrast, only anthropometric indexes consisting of waist circumference (waist circumference, waist-hip ratio and waist-height ratio) were significantly genetically correlated (genetic correlation coefficients: 0.45, 0.55 and 0.44, respectively) with the liability of incident Type 2 diabetes. We did not observe such a correlation for BMI. CONCLUSIONS Waist circumference as a predictor of future Type 2 diabetes is supported by the finding that they share common genetic influences.
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Affiliation(s)
- M Mamtani
- Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA
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Genetic and Environmental Correlations Between Body Mass Index and Waist Circumference in China: The Qingdao Adolescent Twin Study. Behav Genet 2013; 43:340-7. [DOI: 10.1007/s10519-013-9597-7] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2012] [Accepted: 05/22/2013] [Indexed: 01/06/2023]
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Lam VKL, Ma RCW, Lee HM, Hu C, Park KS, Furuta H, Wang Y, Tam CHT, Sim X, Ng DPK, Liu J, Wong TY, Tai ES, Morris AP, DIAGRAM Consortium, Tang NLS, Woo J, Leung PC, Kong APS, Ozaki R, Jia WP, Lee HK, Nanjo K, Xu G, Ng MCY, So WY, Chan JCN. Genetic associations of type 2 diabetes with islet amyloid polypeptide processing and degrading pathways in asian populations. PLoS One 2013; 8:e62378. [PMID: 23776430 PMCID: PMC3679113 DOI: 10.1371/journal.pone.0062378] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2012] [Accepted: 03/21/2013] [Indexed: 01/09/2023] Open
Abstract
Type 2 diabetes (T2D) is a complex disease characterized by beta cell dysfunctions. Islet amyloid polypeptide (IAPP) is highly conserved and co-secreted with insulin with over 40% of autopsy cases of T2D showing islet amyloid formation due to IAPP aggregation. Dysregulation in IAPP processing, stabilization and degradation can cause excessive oligomerization with beta cell toxicity. Previous studies examining genetic associations of pathways implicated in IAPP metabolism have yielded conflicting results due to small sample size, insufficient interrogation of gene structure and gene-gene interactions. In this multi-staged study, we screened 89 tag single nucleotide polymorphisms (SNPs) in 6 candidate genes implicated in IAPP metabolism and tested for independent and joint associations with T2D and beta cell dysfunctions. Positive signals in the stage-1 were confirmed by de novo and in silico analysis in a multi-centre unrelated case-control cohort. We examined the association of significant SNPs with quantitative traits in a subset of controls and performed bioinformatics and relevant functional analyses. Amongst the tag SNPs, rs1583645 in carboxypeptidase E (CPE) and rs6583813 in insulin degrading enzyme (IDE) were associated with 1.09 to 1.28 fold increased risk of T2D (PMeta = 9.4×10−3 and 0.02 respectively) in a meta-analysis of East Asians. Using genetic risk scores (GRS) with each risk variant scoring 1, subjects with GRS≥3 (8.2% of the cohort) had 56% higher risk of T2D than those with GRS = 0 (P = 0.01). In a subcohort of control subjects, plasma IAPP increased and beta cell function index declined with GRS (P = 0.008 and 0.03 respectively). Bioinformatics and functional analyses of CPE rs1583645 predicted regulatory elements for chromatin modification and transcription factors, suggesting differential DNA-protein interactions and gene expression. Taken together, these results support the importance of dysregulation of IAPP metabolism in T2D in East Asians.
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Affiliation(s)
- Vincent Kwok Lim Lam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Ronald Ching Wan Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People's Republic of China
- Li Ka Shing Institute of Health, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Heung Man Lee
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Cheng Hu
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, People's Republic of China
| | - Kyong Soo Park
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology and Department of Internal Medicine, College of Medicine, Seoul National University, Chongno-gu, Seoul, Korea
| | - Hiroto Furuta
- First Department of Medicine, Wakayama Medical University, Wakayama, Japan
| | - Ying Wang
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Claudia Ha Ting Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Xueling Sim
- Centre for Molecular Epidemiology, Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Daniel Peng-Keat Ng
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Jianjun Liu
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Genome Institute of Singapore, Agency for Science, Technology and Research, Singapore, Singapore
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
| | - E. Shyong Tai
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Duke-National University of Singapore Graduate Medical School, Singapore, Singapore
| | - Andrew P. Morris
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | | | - Nelson Leung Sang Tang
- Department of Chemical Pathology, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Jean Woo
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Ping Chung Leung
- Department of Orthopaedics and Traumatology, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Alice Pik Shan Kong
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Risa Ozaki
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Wei Ping Jia
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai Key Clinical Center for Metabolic Disease, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, People's Republic of China
| | - Hong Kyu Lee
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology and Department of Internal Medicine, College of Medicine, Seoul National University, Chongno-gu, Seoul, Korea
| | - Kishio Nanjo
- First Department of Medicine, Wakayama Medical University, Wakayama, Japan
| | - Gang Xu
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People's Republic of China
- Li Ka Shing Institute of Health, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Maggie Chor Yin Ng
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Wing-Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
| | - Juliana Chung Ngor Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong SAR, People's Republic of China
- Li Ka Shing Institute of Health, The Chinese University of Hong Kong, The Prince of Wales Hospital, Shatin, Hong Kong SAR, People's Republic of China
- * E-mail:
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Ma RCW, Chan JCN. Type 2 diabetes in East Asians: similarities and differences with populations in Europe and the United States. Ann N Y Acad Sci 2013; 1281:64-91. [PMID: 23551121 PMCID: PMC3708105 DOI: 10.1111/nyas.12098] [Citation(s) in RCA: 612] [Impact Index Per Article: 51.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
There is an epidemic of diabetes in Asia. Type 2 diabetes develops in East Asian patients at a lower mean body mass index (BMI) compared with those of European descent. At any given BMI, East Asians have a greater amount of body fat and a tendency to visceral adiposity. In Asian patients, diabetes develops at a younger age and is characterized by early β cell dysfunction in the setting of insulin resistance, with many requiring early insulin treatment. The increasing proportion of young-onset and childhood type 2 diabetes is posing a particular threat, with these patients being at increased risk of developing diabetic complications. East Asian patients with type 2 diabetes have a higher risk of developing renal complications than Europeans and, with regard to cardiovascular complications, a predisposition for developing strokes. In addition to cardiovascular-renal disease, cancer is emerging as the other main cause of mortality. While more research is needed to explain these interethnic differences, urgent and concerted actions are needed to raise awareness, facilitate early diagnosis, and encourage preventive strategies to combat these growing disease burdens.
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Affiliation(s)
- Ronald C W Ma
- Department of Medicine and Therapeutics, Hong Kong Institute of Diabetes and Obesity, and Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, The Prince of Wales Hospital, Hong Kong, China.
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Rs4074134 near BDNF gene is associated with type 2 diabetes mellitus in Chinese Han population independently of body mass index. PLoS One 2013; 8:e56898. [PMID: 23431394 PMCID: PMC3576386 DOI: 10.1371/journal.pone.0056898] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2012] [Accepted: 01/15/2013] [Indexed: 01/06/2023] Open
Abstract
Obesity and family history are the most important predictors for type 2 diabetes mellitus(T2DM) in the Chinese Han population. However, it is not known whether the genetic loci related to obesity are associated with the risk of developing T2DM in this population. The present case-control study evaluated the associations between five genetic loci for obesity and the pathogenesis of T2DM. The study included 1117 Chinese Han patients with T2DM, 1629 patients with pre-diabetes (impaired fasting glucose and impaired glucose tolerance, IFG/IGT) and 1113 control subjects residing in Beijing. Five genetic loci including rs2815752 near NEGR1, rs10938397 near GNPDA2, rs4074134 near BDNF, rs17782313 near MC4R and rs1084753 near KCTD15 were genotyped. The results showed an association between rs4074134-BDNF minor allele and T2DM irrespective of age, gender and body mass index (BMI) (OR = 0.87; 95%CI: 0.77–0.99, P = 0.04). This SNP was also associated with pre-diabetes (OR = 0.87; 95%CI: 0.77–0.97, P = 0.01) independently of age, gender and BMI. No associations were found between diabetes or pre-diabetes and any of the other SNP loci studied. Genotype–phenotype association analysis (adjusting for age and gender) showed rs4074134-BDNF to be associated with BMI, waist circumference, fasting and postprandial plasma glucose, fasting serum insulin, and HOMA-IR in subjects without T2DM. However, fasting and postprandial plasma glucose were the only significant factors after adjusting for BMI. These results suggest that the common variation of BDNF (rs4074134) is associated with T2DM independently of obesity in Chinese Han population. This variant also has an effect on plasma glucose concentration, BMI and insulin sensitivity.
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Janghorbani M, Amini M. Incidence of type 2 diabetes by HbA1c and OGTT: the Isfahan Diabetes Prevention Study. Acta Diabetol 2012; 49 Suppl 1:S73-S79. [PMID: 21340503 DOI: 10.1007/s00592-011-0260-6] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2010] [Accepted: 12/13/2010] [Indexed: 01/12/2023]
Abstract
The aim of this study was to estimate the incidence of type 2 diabetes using newly proposed hemoglobin A(1C) (HbA(1c)) and current oral glucose tolerance test (OGTT) definition in an Iranian non-diabetic population. A total of 923 non-diabetic first-degree relatives (FDRs) of patients with type 2 diabetes 30-70 years old in 2003-2005 were followed through 2009 for the occurrence of type 2 diabetes. At baseline and through follow-ups, participants underwent a standard 75 g 2-h OGTT and HbA(1c) measurements. Prediction of progression to type 2 diabetes by OGTT-defined or HbA(1c)-defined diabetes was assessed with area under the receiver operating characteristic (ROC) curves based upon measurement of fasting plasma glucose, 2-h post-load glucose values, and HbA(1c). The prevalence of type 2 diabetes was 9.2% (95% CI: 8.2, 10.2) by OGTT-defined diabetes and 7.9% (95% CI: 6.9, 9.0) by HbA(1c) ≥ 6.5. The incidence of type 2 diabetes was 2.0% (95% CI: 1.6, 2.4) (1.8% men and 2.1% women) per year by the current OGTT definition, whereas the incidence rates were 1.7% (95% CI: 1.3, 2.0) (1.6% men and 1.7% women) per year by HbA(1c) ≥ 6.5%. Of those diagnosed with type 2 diabetes by OGTT, 69.6% had HbA(1c) <6.5% and therefore would not have been classified as having type 2 diabetes. The incidence and prevalence of diabetes using newly proposed HbA(1c) threshold in this FDRs of patients with type 2 diabetes were slightly lower than using current OGTT definition.
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Affiliation(s)
- Mohsen Janghorbani
- Department of Epidemiology and Biostatistics, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran.
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Janghorbani M, Momeni F, Dehghani M. Hip circumference, height and risk of type 2 diabetes: systematic review and meta-analysis. Obes Rev 2012; 13:1172-81. [PMID: 22943765 DOI: 10.1111/j.1467-789x.2012.01030.x] [Citation(s) in RCA: 45] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Although several epidemiological studies have investigated the relationship between type 2 diabetes mellitus (T2DM) and hip circumference or height, the results are inconsistent. The present systematic review and meta-analysis of published observational studies was conducted to assess the effects of hip circumference and height on diabetes risk. Online databases were searched through January 2012, and the reference lists of pertinent articles reporting observational studies in humans were examined. Pooled relative risks (RR) and 95% confidence intervals (CI) were calculated with a random-effects model. Eighteen studies (nine cross-sectional and nine cohort) were included, with 250,497 participants and 7,765 cases of T2DM. Hip circumference was inversely associated with an increased risk of T2DM in men (summary RR [95% CI] 0.60 [0.45, 0.80]) and women (0.54 [0.42, 0.70]). These results were consistent between cross-sectional and cohort studies. An inverse association between height and T2DM was observed in women only (summary RR [95% CI] 0.83 [0.73, 0.95]). Our meta-analysis strongly supports an inverse relationship between hip circumference and risk of T2DM in men and women. The inverse association between height and risk was significant only in women.
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Affiliation(s)
- M Janghorbani
- Department of Epidemiology and Biostatistics, Isfahan University of Medical Sciences, Isfahan, Iran.
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Janghorbani M, Amini M. Associations of hip circumference and height with incidence of type 2 diabetes: the Isfahan diabetes prevention study. Acta Diabetol 2012; 49 Suppl 1:S107-14. [PMID: 22080142 DOI: 10.1007/s00592-011-0351-4] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2011] [Accepted: 10/21/2011] [Indexed: 01/20/2023]
Abstract
The aim of this study was to determine the effects of hip circumference (HC) and height on diabetes incidence in non-diabetic first-degree relatives (FDRs) of patients with type 2 diabetes. A total of 1,092 (254 men and 838 women) non-diabetics FDRs ≥ 30 years old in 2003-2005 were followed through 2010 for the occurrence of type 2 diabetes. At baseline and through follow-ups, participants were underwent a standard 75 g 2-h oral glucose tolerance test. The incidence of type 2 diabetes was 17.0 (95% CI: 13.7, 20.2) (13.0 men and 18.1 women) per 1,000 person-year based on 6,015 person-years of follow-up. Height was inversely associated with diabetes incidence. The age-, gender-, and waist-adjusted relative risk (95% CI) of diabetes was 0.54 (0.31, 0.93) for highest quartile of height and 0.59 (0.25, 1.37) for highest quartile of HC compared with lowest quartile. These data indicate that height was inversely associated with diabetes incidence, independently of gender among FDRs of patients with type 2 diabetes.
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Affiliation(s)
- Mohsen Janghorbani
- Department of Epidemiology and Biostatistics, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran.
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Janghorbani M, Amini M. Glycated hemoglobin as a predictor for metabolic syndrome in an Iranian population with normal glucose tolerance. Metab Syndr Relat Disord 2012; 10:430-6. [PMID: 23046172 DOI: 10.1089/met.2012.0070] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND The aim of this study was to determine the ability of glycated hemoglobin (GHb) to predict metabolic syndrome in an Iranian population with normal glucose tolerance (NGT). METHODS A cross-sectional study of first-degree relatives (FDRs) of patients with type 2 diabetes was conducted from 2003 to 2005. A total of 1386 FDRs of consecutive patients with type 2 diabetes 30-60 years old (355 men and 1031 women) with NGT were examined. All subjects underwent a standard 75-gram 2-h oral glucose tolerance test and GHb measurement. Consensus criteria in 2009 were used to identify metabolic syndrome. Unadjusted and adjusted multivariate logistic regression analysis was performed to assess the risk of metabolic syndrome. The mean [standard deviation (SD)] age of participants was 42.4 (6.3) years. RESULTS The prevalence of metabolic syndrome was 17.5% in men and 21.5% in women. The multivariate-adjusted odds ratio (95% CI) of metabolic syndrome was 2.01 (1.03, 3.93) for the highest quintile of GHb compared with lowest quintile. These data indicate that GHb was associated with metabolic syndrome, independently of gender among FDRs of patients with type 2 diabetes with NGT. CONCLUSIONS These data indicate that GHb below the level for prediabetes might be a predictive measure of metabolic syndrome in FDRs of patients with type 2 diabetes with NGT.
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Affiliation(s)
- Mohsen Janghorbani
- School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran.
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Ali NS, Khuwaja AK, Adnan-ur-Rahman, Nanji K. Retrospective analysis of metabolic syndrome: prevalence and distribution in executive population in urban pakistan. INTERNATIONAL JOURNAL OF FAMILY MEDICINE 2012; 2012:649383. [PMID: 22988504 PMCID: PMC3440857 DOI: 10.1155/2012/649383] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/30/2012] [Revised: 07/26/2012] [Accepted: 07/29/2012] [Indexed: 08/20/2024]
Abstract
Background. Metabolic Syndrome (MetS) is a major public health concern. Objective. The aim of this study was to estimate the frequency of MetS, its components, and factors associated with MetS amongst apparently healthy individuals in Pakistan. Methods. A retrospective cross-sectional study was conducted at the executive Clinics of Aga Khan Hospital, Pakistan. Medical records of patients aged ≥18 years visiting the clinics from July 2011 to December 2011 were consecutively reviewed. Records in which either MetS components data or 10% of overall data was missing were excluded. A total of 1329 participants' records was included in final analysis. Data was analyzed using SPSS version 19 and multivariable logistic regression was used to identify the factors associated with MetS. Results. A total of 847 (63.7%) participants had MetS; mean age of the participants were 47.6 ± 11.6 years. About 70.4% were males and 29.6% were females. Approximately 70% of participants had BMI ≥25 kg/m(2). MetS was associated with male gender (AOR = 2.1; 95% C.I: 1.6-3.2) and history of diabetes among parents (AOR = 3.0; 95% C.I: 1.6-6.0). Conclusion. This study shows that a large proportion of population has MetS and is overweight or obese. This requires urgent interventions on part of health care providers' especially family physicians. Educating masses about life style factors can make a difference. Further researches on this issue are warranted.
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Affiliation(s)
- Niloufer Sultan Ali
- Department of Family Medicine, Aga Khan University Hospital, Aga Khan University, Stadium Road, P.O. Box 3500, Karachi 74800, Pakistan
| | - Ali Khan Khuwaja
- Department of Family Medicine, Aga Khan University Hospital, Aga Khan University, Stadium Road, P.O. Box 3500, Karachi 74800, Pakistan
| | - Adnan-ur-Rahman
- Jinnah Postgraduate Medical College, Jinnah Postgraduate Medical Centre (JPMC), Rafiquee Shaheed Road, P.O. Box 3937, Karachi 74800, Pakistan
| | - Kashmira Nanji
- Department of Family Medicine, Aga Khan University Hospital, Aga Khan University, Stadium Road, P.O. Box 3500, Karachi 74800, Pakistan
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Janghorbani M, Amini M. Comparison of glycated hemoglobin with fasting plasma glucose in definition of glycemic component of the metabolic syndrome in an Iranian population. Diabetes Metab Syndr 2012; 6:136-139. [PMID: 23158976 DOI: 10.1016/j.dsx.2012.09.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
AIMS The aim of this study was to compare the utility of glycated hemoglobin (GHb) versus the fasting plasma glucose (FPG) in definition of glycemic component of the metabolic syndrome (MetS) in a non-diabetic Iranian population. METHODS A cross-sectional study of first-degree relatives (FDRs) of patients with type 2 diabetes was conducted from 2003 to 2005. A total of 2410 non-diabetic FDRs of consecutive patients with type 2 diabetes 30-60 years old were examined. All subjects underwent a standard 75 g 2-h oral glucose tolerance test and GHb measurement. Consensus criteria in 2009 were used to identify MetS. Glycemic component of MetS was defined as either FPG≥100 mg/dl or GHb≥5.7%. The mean (SD) age of participants was 43.6 (6.5) years. RESULTS The prevalence of MetS was 33.5% (95% confidence interval (CI): 31.6, 35.4) based on FPG criterion alone and 28.6% (95% CI: 26.8, 30.4) based on GHb criterion alone. Use of combination of both criteria increased the prevalence of MetS (36.7%; 95% CI: 34.8, 38.6). There was 88.7% (95% CI: 87.5, 90.0) agreement between the GHb and FPG when either was used to define MetS (κ coefficient=0.737). CONCLUSIONS These data indicate that using GHb may be an acceptable surrogate of FPG to define glycemic component of MetS.
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Affiliation(s)
- Mohsen Janghorbani
- School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran.
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Janghorbani M, Amini M. Normal fasting plasma glucose and risk of prediabetes and type 2 diabetes: the Isfahan Diabetes Prevention Study. Rev Diabet Stud 2012; 8:490-8. [PMID: 22580730 PMCID: PMC3359693 DOI: 10.1900/rds.2011.8.490] [Citation(s) in RCA: 15] [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: 12/11/2011] [Revised: 01/09/2012] [Accepted: 02/02/2012] [Indexed: 01/28/2023] Open
Abstract
AIM To determine the association of fasting plasma glucose (FPG) level within normal range and the risk of prediabetes and type 2 diabetes in an Iranian population. METHODS A total of 806 first-degree relatives (FDRs) of patients with type 2 diabetes who had FPG levels less than 5.6 mmol/l (100 mg/dl) in 2003 to 2005, and who did not have diabetes or impaired fasting glucose (IFG), were followed through 2010 for the occurrence of prediabetes or type 2 diabetes. At baseline and through follow-ups, participants underwent a standard 75 g 2-hour oral glucose tolerance test (OGTT). RESULTS The incidence of type 2 diabetes, impaired glucose tolerance (IGT), and IFG was 9.6 (95% confidence interval (CI): 6.8-12.4), 28.7 (23.8-33.6), and 33.0 (27.7-38.2) per 1,000 person-years based on 4,489 person-years of follow-up, respectively. FPG was associated with the incidence of diabetes, IGT, and IFG. The multivariate-adjusted hazard ratios (95% CI) for diabetes, IGT, and IFG were 1.36 (1.01-1.84), 1.45 (1.10-1.91) and 1.31 (1.00-1.71), for the highest quintile of FPG compared with the lowest quintile, respectively. CONCLUSIONS An increase in FPG in the normal range is associated with an increase in the incidence of IGT, IFG, and type 2 diabetes. These results prove FPG in the normal range to be useful in identifying apparently healthy FDRs of patients with type 2 diabetes at risk of developing prediabetes and diabetes.
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Affiliation(s)
- Mohsen Janghorbani
- Department of Epidemiology, School of Public Health, Isfahan University of Medical Sciences, Isfahan, Iran.
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Povel CM, Boer JMA, Feskens EJM. Shared genetic variance between the features of the metabolic syndrome: heritability studies. Mol Genet Metab 2011; 104:666-9. [PMID: 21963081 DOI: 10.1016/j.ymgme.2011.08.035] [Citation(s) in RCA: 22] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2011] [Revised: 08/31/2011] [Accepted: 08/31/2011] [Indexed: 12/27/2022]
Abstract
Heritability estimates of MetS range from approximately 10%-30%. The genetic variation that is shared among MetS features can be calculated by genetic correlation coefficients. The objective of this paper is to identify MetS feature as well as MetS related features which have much genetic variation in common, by reviewing the literature regarding genetic correlation coefficients. Identification of features, that have much genetic variation in common, may eventually facilitate the search for pleitropic genetic variants that may explain the clustering of MetS features. A PubMed search with the search terms "(metabolic syndrome OR insulin resistance syndrome) and (heritability OR genetic correlation OR pleiotropy)" was performed. Studies published before 7th July 2011, which presented genetic correlation coefficients between the different MetS features and genetic correlation coefficients of MetS and its features with adipose tissue-, pro-inflammatory and pro-thrombotic biomarkers were included. Nine twin and 19 family studies were included in the review. Genetic correlations varied, but were strongest between waist circumference and HOMA-IR (r(2): 0.36 to 0.79, median: 0.50), HDL cholesterol and triglycerides (r(2): -0.05 to -0.59, median -0.45), adiponectin and MetS (r(2): -0.32 to -0.43; median -0.38), adiponectin and insulin (r(2): -0.10 to -0.60; median -0.30) and between adiponectin and HDL-cholesterol (r(2): -0.22 to -0.51, median -0.29). In conclusion, heritability studies suggest that genetic pleiotropy exist especially between certain MetS features, as well as between MetS and adiponectin. Further research on actual genetic variants responsible for the genetic pleiotropy of these combinations will provide more insight into the etiology of MetS.
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Affiliation(s)
- C M Povel
- Division of Human Nutrition, Wageningen University, Wageningen, The Netherlands.
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