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Rakowski A, Monti R, Lippert C. TransferGWAS of T1-weighted brain MRI data from UK Biobank. PLoS Genet 2024; 20:e1011332. [PMID: 39671448 DOI: 10.1371/journal.pgen.1011332] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2024] [Revised: 12/31/2024] [Accepted: 11/07/2024] [Indexed: 12/15/2024] Open
Abstract
Genome-wide association studies (GWAS) traditionally analyze single traits, e.g., disease diagnoses or biomarkers. Nowadays, large-scale cohorts such as UK Biobank (UKB) collect imaging data with sample sizes large enough to perform genetic association testing. Typical approaches to GWAS on high-dimensional modalities extract predefined features from the data, e.g., volumes of regions of interest. This limits the scope of such studies to predefined traits and can ignore novel patterns present in the data. TransferGWAS employs deep neural networks (DNNs) to extract low-dimensional representations of imaging data for GWAS, eliminating the need for predefined biomarkers. Here, we apply transferGWAS on brain MRI data from UKB. We encoded 36, 311 T1-weighted brain magnetic resonance imaging (MRI) scans using DNN models trained on MRI scans from the Alzheimer's Disease Neuroimaging Initiative, and on natural images from the ImageNet dataset, and performed a multivariate GWAS on the resulting features. We identified 289 independent loci, associated among others with bone density, brain, or cardiovascular traits, and 11 regions having no previously reported associations. We fitted polygenic scores (PGS) of the deep features, which improved predictions of bone mineral density and several other traits in a multi-PGS setting, and computed genetic correlations with selected phenotypes, which pointed to novel links between diffusion MRI traits and type 2 diabetes. Overall, our findings provided evidence that features learned with DNN models can uncover additional heritable variability in the human brain beyond the predefined measures, and link them to a range of non-brain phenotypes.
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Affiliation(s)
- Alexander Rakowski
- Digital Health Machine Learning, Hasso Plattner Institute for Digital Engineering, University of Potsdam, Germany
| | - Remo Monti
- Digital Health Machine Learning, Hasso Plattner Institute for Digital Engineering, University of Potsdam, Germany
- Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association, Berlin Institute for Medical Systems Biology, Berlin, Germany
| | - Christoph Lippert
- Digital Health Machine Learning, Hasso Plattner Institute for Digital Engineering, University of Potsdam, Germany
- Hasso Plattner Institute for Digital Health at Mount Sinai, New York, New York, United States of America
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2
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Burtscher J, Kopp M, Klimont J, Ulmer H, Strasser B, Burtscher M. Age- and sex-dependent associations between self-reported physical activity levels and self-reported cardiovascular risk factors: a population-based cross-sectional survey. BMC Public Health 2024; 24:2843. [PMID: 39415183 PMCID: PMC11481313 DOI: 10.1186/s12889-024-20351-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2024] [Accepted: 10/09/2024] [Indexed: 10/18/2024] Open
Abstract
BACKGROUND The amount of regular physical activity (PA) can modulate the prevalence of traditional risk factors for cardiovascular disease (CVD) such as obesity, systemic hypertension, hypercholesterolemia, and type 2 diabetes (T2D). However, how different PA levels either below (< 600 MET min/week), within (600-1200 MET min/week), or above (> 1200 MET min/week) the range of the minimal WHO recommendations impact the age- and sex-dependent prevalence of these risk factors remains to be elucidated. METHODS This cross-sectional study was performed to evaluate these relationships using population-based self-reported data collected in a central European country (Austria, 2019). The sample included a total of 15,461 persons (7166 males: 16-95 + years, BMI 26.6 ± 4.4; 8295 females: 16-95 + years, BMI 25.1 ± 5.0). Besides various lifestyle factors (e.g., dietary habits, smoking, and alcohol consumption), variables of particular interest were the age- and sex-dependent amount of weekly PA and prevalence of risk factors for CVD. Sex-specific logistic regression analyses were applied to estimate adjusted odds ratios (ORs) for the associations between self-reported PA and risk factor prevalence. RESULTS Relatively small beneficial effects were found regarding the prevalence of risk factors for CVD when achieving PA levels corresponding to 600-1200 MET min/week as compared to those who did not meet these recommendations. However, exceeding the WHO recommendations provided much more pronounced benefits, especially in younger and older age groups. Adjusted ORs revealed that high volumes of PA (> 1200 MET min/week) were associated with a 32-43% reduction in the prevalence of obesity and T2D compared to those who did not achieve the WHO recommendations (< 600 MET min/week), as well as with a lower prevalence of systemic hypertension only in women and a lower prevalence of hypercholesterolemia only in men. CONCLUSIONS Exceeding minimal WHO recommendations for PA promises large beneficial effects, particularly on the prevalence of obesity and T2D. Demonstrated sex differences in PA levels and their association with cardiovascular risk factors may provide an important basis for preventive health counseling.
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Affiliation(s)
- Johannes Burtscher
- Institute of Sport Sciences, University of Lausanne, Lausanne, CH-1015, Switzerland
| | - Martin Kopp
- Institute of Sport Science, University of Innsbruck, Innsbruck, A-6020, Austria
| | - Jeannette Klimont
- Unit Demography and Health, Directorate Social Statistics, Vienna, 1110, Statistics Austria, Austria
| | - Hanno Ulmer
- Institute of Medical Statistics and Informatics, Medical University of Innsbruck, Innsbruck, 6020, Austria
| | - Barbara Strasser
- Ludwig Boltzmann Institute for Rehabilitation Research, Vienna, 1100, Austria
- Faculty of Medicine, Sigmund Freud Private University, Vienna, 1020, Austria
| | - Martin Burtscher
- Institute of Sport Science, University of Innsbruck, Innsbruck, A-6020, Austria.
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Tang H, Wang J, Deng P, Li Y, Cao Y, Yi B, Zhu L, Zhu S, Lu Y. Transcriptome-wide association study-derived genes as potential visceral adipose tissue-specific targets for type 2 diabetes. Diabetologia 2023; 66:2087-2100. [PMID: 37540242 PMCID: PMC10542736 DOI: 10.1007/s00125-023-05978-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 05/22/2023] [Indexed: 08/05/2023]
Abstract
AIMS/HYPOTHESIS This study aimed to assess the causal relationship between visceral obesity and type 2 diabetes and subsequently to screen visceral adipose tissue (VAT)-specific targets for type 2 diabetes. METHODS We examined the causal relationship between VAT and type 2 diabetes using bidirectional Mendelian randomisation (MR) followed by multivariable MR. We conducted a transcriptome-wide association study (TWAS) leveraging prediction models and a large-scale type 2 diabetes genome-wide association study (74,124 cases and 824,006 controls) to identify candidate genes in VAT and used summary-data-based MR (SMR) and co-localisation analysis to map causal genes. We performed enrichment and single-cell RNA-seq analyses to determine the cell-specific localisation of the TWAS-identified genes. We also conducted knockdown experiments in 3T3-L1 pre-adipocytes. RESULTS MR analyses showed a causal relationship between genetically increased VAT mass and type 2 diabetes (inverse-variance weighted OR 2.48 [95% CI 2.21, 2.79]). Ten VAT-specific candidate genes were associated with type 2 diabetes after Bonferroni correction, including five causal genes supported by SMR and co-localisation: PABPC4 (1p34.3); CCNE2 (8q22.1); HAUS6 (9p22.1); CWF19L1 (10q24.31); and CCDC92 (12q24.31). Combined with enrichment analyses, clarifying cell-type specificity with single-cell RNA-seq data indicated that most TWAS-identified candidate genes appear more likely to be associated with adipocytes in VAT. Knockdown experiments suggested that Pabpc4 likely contributes to regulating differentiation and energy metabolism in 3T3-L1 adipocytes. CONCLUSIONS/INTERPRETATION Our findings provide new insights into the genetic basis and biological processes of the association between VAT accumulation and type 2 diabetes and warrant investigation through further functional studies to validate these VAT-specific candidate genes.
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Affiliation(s)
- Haibo Tang
- Department of Metabolic and Bariatric Surgery, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Jie Wang
- Clinical Research Center, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Peizhi Deng
- Clinical Research Center, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Yalan Li
- Clinical Research Center, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Yaoquan Cao
- Department of Metabolic and Bariatric Surgery, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Bo Yi
- Department of Metabolic and Bariatric Surgery, The Third Xiangya Hospital, Central South University, Changsha, China
| | - Liyong Zhu
- Department of Metabolic and Bariatric Surgery, The Third Xiangya Hospital, Central South University, Changsha, China.
| | - Shaihong Zhu
- Department of Metabolic and Bariatric Surgery, The Third Xiangya Hospital, Central South University, Changsha, China.
| | - Yao Lu
- Clinical Research Center, The Third Xiangya Hospital, Central South University, Changsha, China.
- School of Life Course Sciences, King's College London, London, UK.
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4
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Cleven L, Dziuba A, Krell-Roesch J, Schmidt SCE, Bös K, Jekauc D, Woll A. Longitudinal associations between physical activity and five risk factors of metabolic syndrome in middle-aged adults in Germany. Diabetol Metab Syndr 2023; 15:82. [PMID: 37098550 PMCID: PMC10131386 DOI: 10.1186/s13098-023-01062-5] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 04/14/2023] [Indexed: 04/27/2023] Open
Abstract
BACKGROUND We examined the longitudinal association between (change in) physical activity (PA) with new onset of five risk factors of metabolic syndrome among 657 middle-aged adults (mean age 44.1 (standard deviation (SD) 8.6) years) who were free of the respective outcome at baseline, in a longitudinal cohort study spanning over 29 years. METHODS Levels of habitual PA and sports-related PA were assessed by a self-reported questionnaire. Incident elevated waist circumference (WC), elevated triglycerides (TG), reduced high-density lipoprotein cholesterols (HDL), elevated blood pressure (BP), and elevated blood-glucose (BG) were assessed by physicians and by self-reported questionnaires. We calculated Cox proportional hazard ratio regressions and 95% confidence intervals. RESULTS Over time, participants developed (cases of incident risk factor; mean (SD) follow-up time) elevated WC (234 cases; 12.3 (8.2) years), elevated TG (292 cases; 11.1 (7.8) years), reduced HDL (139 cases; 12.4 (8.1) years), elevated BP (185 cases; 11.4 (7.5) years), or elevated BG (47 cases; 14.2 (8.5) years). For PA variables at baseline, risk reductions ranging between 37 and 42% for reduced HDL levels were detected. Furthermore, higher levels of PA (≥ 16.6 METh per week) were associated with a 49% elevated risk for incident elevated BP. Participants who increased PA levels over time, had risk reductions ranging between 38 and 57% for elevated WC, elevated TG and reduced HDL. Participants with stable high amounts of PA from baseline to follow-up had risk reductions ranging between 45 and 87% for incident reduced HDL and elevated BG. CONCLUSIONS PA at baseline, starting PA engagement, maintaining and increasing PA level over time are associated with favorable metabolic health outcomes.
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Affiliation(s)
- Laura Cleven
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, 76131, Karlsruhe, Germany.
| | - Anna Dziuba
- Institute of Sport Sciences, Department of Sport Psychology, Goethe University Frankfurt, Ginnheimer Landstraße 39, 60487, Frankfurt, Germany
| | - Janina Krell-Roesch
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, 76131, Karlsruhe, Germany
| | - Steffen C E Schmidt
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, 76131, Karlsruhe, Germany
| | - Klaus Bös
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, 76131, Karlsruhe, Germany
| | - Darko Jekauc
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, 76131, Karlsruhe, Germany
| | - Alexander Woll
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Engler-Bunte-Ring 15, 76131, Karlsruhe, Germany
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Wei Y, Richardson TG, Zhan Y, Carlsson S. Childhood adiposity and novel subtypes of adult-onset diabetes: a Mendelian randomisation and genome-wide genetic correlation study. Diabetologia 2023; 66:1052-1056. [PMID: 36843089 PMCID: PMC10163070 DOI: 10.1007/s00125-023-05883-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 01/24/2023] [Indexed: 02/28/2023]
Abstract
AIMS/HYPOTHESIS We investigated whether the impacts of childhood adiposity on adult-onset diabetes differ across proposed diabetes subtypes using a Mendelian randomisation (MR) design. METHODS We performed MR analysis using data from European genome-wide association studies of childhood adiposity, latent autoimmune diabetes in adults (LADA, proxy for severe autoimmune diabetes), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD) and mild age-related diabetes (MARD). RESULTS Higher levels of childhood adiposity had positive genetically predicted effects on LADA (OR 1.62, 95% CI 1.05, 2.52), SIDD (OR 2.11, 95% CI 1.18, 3.80), SIRD (OR 2.76, 95% CI 1.60, 4.75) and MOD (OR 7.30, 95% CI 4.17, 12.78), but not MARD (OR 1.06, 95% CI 0.70, 1.60). CONCLUSIONS/INTERPRETATION Childhood adiposity is a risk factor not only for adult-onset diabetes primarily characterised by obesity or insulin resistance, but also for subtypes primarily characterised by insulin deficiency or autoimmunity. These findings emphasise the importance of preventing childhood obesity.
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Affiliation(s)
- Yuxia Wei
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
| | - Tom G Richardson
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Yiqiang Zhan
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, China
| | - Sofia Carlsson
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
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Handley D, Rafey MF, Almansoori S, Brazil JF, McCarthy A, Amin HA, O’Donnell M, Blakemore AI, Finucane FM. Higher Waist Hip Ratio Genetic Risk Score Is Associated with Reduced Weight Loss in Patients with Severe Obesity Completing a Meal Replacement Programme. J Pers Med 2022; 12:jpm12111881. [PMID: 36579607 PMCID: PMC9695448 DOI: 10.3390/jpm12111881] [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: 09/27/2022] [Revised: 10/24/2022] [Accepted: 11/03/2022] [Indexed: 11/12/2022] Open
Abstract
Background: A better understanding of the influence of genetic factors on the response to lifestyle interventions in people with obesity may allow the development of more personalised, effective and efficient therapeutic strategies. We sought to determine the influence of six obesity-related genetic risk scores on the magnitude of weight lost by patients with severe obesity who completed a dietary intervention. Methods: In this single-centre prospective cohort study, participants with severe and complicated obesity who completed a 24-week, milk-based meal replacement programme were genotyped to detect the frequency of common risk alleles for obesity and type 2 diabetes-related traits. Genetic risk scores (GRS) for six of these traits were derived. Participants with a potentially deleterious monogenic gene variant were excluded from the analysis. Results: In 93 patients completing the programme who were not carrying a known obesity-related gene mutation, 35.5% had diabetes, 53.8% were female, mean age was 51.4 ± 11 years, mean body mass index was 51.5 ± 8.7 and mean total weight loss percent at 24 weeks was 16 ± 6.3%. The waist-hip ratio (WHR) GRS was inversely associated with percentage total weight loss at 24 weeks (adjusted β for one standard deviation increase in WHR GRS -11.6 [-23.0, -0.3], p = 0.045), and patients in the lowest tertile of WHR GRS lost more weight. Conclusions: Patients with severe and complicated obesity with a genetic predisposition to central fat accumulation had less weight loss in a 24-week milk-based meal replacement programme, but there was no evidence for influence from the five other obesity-related genetic risk scores on the response to dietary restriction.
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Affiliation(s)
- Dale Handley
- College of Health, Medical and Life Sciences, Brunel University London, London UB8 3PH, UK
| | - Mohammed Faraz Rafey
- Bariatric Medicine Service, Centre for Diabetes, Endocrinology and Metabolism, Galway University Hospitals, H91 YR71 Galway, Ireland
- HRB Clinical Research Facility, University of Galway, H91 CF50 Galway, Ireland
- Department of Medicine, University of Galway, H91 CF50 Galway, Ireland
| | - Sumaya Almansoori
- College of Health, Medical and Life Sciences, Brunel University London, London UB8 3PH, UK
- Faculty of Medicine, Imperial College London, London SW7 2BX, UK
- International Centre for Forensic Science, General Department of Forensic Science and Criminology, Dubai Police, Dubai 00000, United Arab Emirates
| | - John F. Brazil
- Bariatric Medicine Service, Centre for Diabetes, Endocrinology and Metabolism, Galway University Hospitals, H91 YR71 Galway, Ireland
- HRB Clinical Research Facility, University of Galway, H91 CF50 Galway, Ireland
- Department of Medicine, University of Galway, H91 CF50 Galway, Ireland
| | - Aisling McCarthy
- Bariatric Medicine Service, Centre for Diabetes, Endocrinology and Metabolism, Galway University Hospitals, H91 YR71 Galway, Ireland
| | - Hasnat A. Amin
- College of Health, Medical and Life Sciences, Brunel University London, London UB8 3PH, UK
| | - Martin O’Donnell
- HRB Clinical Research Facility, University of Galway, H91 CF50 Galway, Ireland
- Department of Medicine, University of Galway, H91 CF50 Galway, Ireland
| | - Alexandra I. Blakemore
- College of Health, Medical and Life Sciences, Brunel University London, London UB8 3PH, UK
- Department of Medicine, University of Galway, H91 CF50 Galway, Ireland
- Faculty of Medicine, Imperial College London, London SW7 2BX, UK
| | - Francis M. Finucane
- College of Health, Medical and Life Sciences, Brunel University London, London UB8 3PH, UK
- Bariatric Medicine Service, Centre for Diabetes, Endocrinology and Metabolism, Galway University Hospitals, H91 YR71 Galway, Ireland
- HRB Clinical Research Facility, University of Galway, H91 CF50 Galway, Ireland
- Department of Medicine, University of Galway, H91 CF50 Galway, Ireland
- Correspondence: ; Tel.: +353-(39)-1893803
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7
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Li X, Wang S, Dunk M, Yang W, Qi X, Sun Z, Xu W. Association of life-course reproductive duration with mortality: a population-based twin cohort study. Am J Obstet Gynecol 2022; 227:748.e1-748.e13. [PMID: 35779587 DOI: 10.1016/j.ajog.2022.06.053] [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: 12/01/2021] [Revised: 06/09/2022] [Accepted: 06/21/2022] [Indexed: 11/01/2022]
Abstract
BACKGROUND Although age at menopause has been linked to mortality, the association between the entire reproductive lifespan and mortality remains unclear. OBJECTIVE This study aimed to examine to what extent life-course reproductive duration is associated with all-cause mortality and explore the role of a healthy lifestyle and familial background in such an association. STUDY DESIGN A total of 11,669 women (mean age, 63.54 years) from the Swedish Twin Registry were followed for up to 19 years. Information on reproductive duration (the interval between ages at menarche and menopause) and lifestyle factors (including smoking, alcohol consumption, and physical activity; divided into unfavorable/intermediate/favorable) was collected on the basis of a structured questionnaire. Survival status was obtained from the Sweden Cause of Death Register. The data were analyzed using generalized estimating equation models, Laplace regression, and conditional logistic regression. RESULTS In the generalized estimating equation model, compared with those with ≤34 reproductive years, the odds ratio (95% confidence interval) of all-cause mortality was 0.79 (0.68-0.90) for those with ≥40 reproductive years, which prolonged survival time by 0.84 (0.24-1.43) years. Women with ≥40 reproductive years plus a favorable lifestyle (odds ratio, 0.28; 95% confidence interval, 0.23-0.35) were at a lower risk of all-cause mortality than those with <40 reproductive years plus an unfavorable lifestyle. An additive interaction between ≥40 reproductive years and a favorable lifestyle on all-cause mortality was observed (attributable proportion, 0.584; 95% confidence interval, 0.016-1.151). The odds ratios in conditional logistic regression and generalized estimating equation models did not differ significantly (P=.67). CONCLUSION A longer reproductive lifespan is associated with reduced all-cause mortality and prolongs survival by 0.84 years. A favorable lifestyle may amplify the beneficial effect of longer reproductive lifespan on mortality. Familial background does not account for the observed association.
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Affiliation(s)
- Xuerui Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China; Tianjin Center for International Collaborative Research in Environment, Nutrition and Public Health, Tianjin, China
| | - Shuqi Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China; Tianjin Center for International Collaborative Research in Environment, Nutrition and Public Health, Tianjin, China
| | - Michelle Dunk
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institute and Stockholm University, Stockholm, Sweden; Department of Psychology, University of Wisconsin-Milwaukee, Milwaukee, WI
| | - Wenzhe Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China; Tianjin Center for International Collaborative Research in Environment, Nutrition and Public Health, Tianjin, China
| | - Xiuying Qi
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China; Tianjin Center for International Collaborative Research in Environment, Nutrition and Public Health, Tianjin, China
| | - Zhuoyu Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China; Tianjin Center for International Collaborative Research in Environment, Nutrition and Public Health, Tianjin, China.
| | - Weili Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China; Tianjin Center for International Collaborative Research in Environment, Nutrition and Public Health, Tianjin, China; Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institute and Stockholm University, Stockholm, Sweden.
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8
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Dashti HS, Miranda N, Cade BE, Huang T, Redline S, Karlson EW, Saxena R. Interaction of obesity polygenic score with lifestyle risk factors in an electronic health record biobank. BMC Med 2022; 20:5. [PMID: 35016652 PMCID: PMC8753909 DOI: 10.1186/s12916-021-02198-9] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/30/2021] [Accepted: 11/23/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Genetic and lifestyle factors have considerable effects on obesity and related diseases, yet their effects in a clinical cohort are unknown. This study in a patient biobank examined associations of a BMI polygenic risk score (PRS), and its interactions with lifestyle risk factors, with clinically measured BMI and clinical phenotypes. METHODS The Mass General Brigham (MGB) Biobank is a hospital-based cohort with electronic health record, genetic, and lifestyle data. A PRS for obesity was generated using 97 genetic variants for BMI. An obesity lifestyle risk index using survey responses to obesogenic lifestyle risk factors (alcohol, education, exercise, sleep, smoking, and shift work) was used to dichotomize the cohort into high and low obesogenic index based on the population median. Height and weight were measured at a clinical visit. Multivariable linear cross-sectional associations of the PRS with BMI and interactions with the obesity lifestyle risk index were conducted. In phenome-wide association analyses (PheWAS), similar logistic models were conducted for 675 disease outcomes derived from billing codes. RESULTS Thirty-three thousand five hundred eleven patients were analyzed (53.1% female; age 60.0 years; BMI 28.3 kg/m2), of which 17,040 completed the lifestyle survey (57.5% female; age: 60.2; BMI: 28.1 (6.2) kg/m2). Each standard deviation increment in the PRS was associated with 0.83 kg/m2 unit increase in BMI (95% confidence interval (CI) =0.76, 0.90). There was an interaction between the obesity PRS and obesity lifestyle risk index on BMI. The difference in BMI between those with a high and low obesogenic index was 3.18 kg/m2 in patients in the highest decile of PRS, whereas that difference was only 1.55 kg/m2 in patients in the lowest decile of PRS. In PheWAS, the obesity PRS was associated with 40 diseases spanning endocrine/metabolic, circulatory, and 8 other disease groups. No interactions were evident between the PRS and the index on disease outcomes. CONCLUSIONS In this hospital-based clinical biobank, obesity risk conferred by common genetic variants was associated with elevated BMI and this risk was attenuated by a healthier patient lifestyle. Continued consideration of the role of lifestyle in the context of genetic predisposition in healthcare settings is necessary to quantify the extent to which modifiable lifestyle risk factors may moderate genetic predisposition and inform clinical action to achieve personalized medicine.
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Affiliation(s)
- Hassan S Dashti
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA. .,Broad Institute, Cambridge, MA, USA. .,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.
| | - Nicole Miranda
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Brian E Cade
- Broad Institute, Cambridge, MA, USA.,Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Tianyi Huang
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.,Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Elizabeth W Karlson
- Mass General Brigham Personalized Medicine, Mass General Brigham HealthCare, Boston, MA, USA.,Department of Medicines, Brigham and Women's Hospital and Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA.,Division of Rheumatology, Inflammation and Immunity, Brigham and Women's Hospital, Boston, MA, USA
| | - Richa Saxena
- Center for Genomic Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.,Broad Institute, Cambridge, MA, USA.,Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA.,Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
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9
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Guo J, Li X, Yang R, Marseglia A, Dove A, Johnell K, Xu W. Association of body mass index and its long-term changes with cardiometabolic diseases: A nationwide twin study. Clin Nutr 2021; 40:5467-5474. [PMID: 34656027 DOI: 10.1016/j.clnu.2021.09.030] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 09/15/2021] [Accepted: 09/17/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND & AIMS The association between higher body mass index (BMI) and cardiometabolic diseases (CMDs, including type 2 diabetes and cardiovascular diseases) is not well understood. We aimed to examine the association of BMI and its long-term changes with cardiometabolic diseases (CMDs) and explore the role of familial background and healthy lifestyle in this association. METHODS Within the Swedish Twin Registry, 36 622 CMD-free individuals aged ≥40 were followed for up to 16 years. BMI data was collected at baseline and 25-35 years prior to baseline. Healthy lifestyle (non-smoking, no/mild alcohol consumption, and regular physical activity) was assessed as unfavourable (none or only one of these factors) vs. favourable (two or three). Incident CMDs were identified by linkage with the Swedish National Patient Registry. Two strategies were followed: 1) Cox models in all twin individuals; 2) stratified Cox models in CMD-discordant twin pairs. RESULTS At baseline, 16 195 (44.2%) study participants had overweight/obesity (BMI ≥ 25 kg/m2) and 11 202 (30.6%) developed CMDs over follow-up. Among all participants, the hazard ratio (HR) and 95% confidence interval (CI) of developing any CMD was 1.52 (1.45-1.58) for people with overweight/obesity compared to normal BMI (20-25 kg/m2). Compared to stable normal BMI, HRs (95% CIs) of CMDs were 1.28 (1.02-1.59) and 1.33 (1.24-1.43) for only earlier life or only later life overweight/obesity, respectively, and 1.69 (1.55-1.85) for overweight/obesity both in earlier and later life. In stratified Cox analyses conducted among all CMD-discordant twin pairs, overweight/obesity was associated with greater risk of CMDs (1.37, 95% CI 1.18-1.61). In joint effect analysis, the risk of CMDs related to overweight/obesity was diminished 32% among people with a favourable lifestyle (1.51, 95% CI 1.44-1.58) compared to those with overweight/obesity and an unfavourable lifestyle (2.20, 95% CI 2.03-2.38). CONCLUSIONS Overweight/obesity is associated with an increased risk of CMDs, and shared genetic and early-life environmental factors might not account for this association. However, a favourable lifestyle could attenuate the risk of high BMI-related CMDs.
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Affiliation(s)
- Jie Guo
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Sweden.
| | - Xuerui Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Rongrong Yang
- Public Health Science and Engineering College, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Anna Marseglia
- Division of Clinical Geriatrics, Center for Alzheimer Research, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Abigail Dove
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Sweden
| | - Kristina Johnell
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Weili Xu
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Sweden; Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
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10
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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. Overweight and risk of type 2 diabetes: A prospective Chinese twin study. DIABETES & METABOLISM 2021; 48:101278. [PMID: 34520837 DOI: 10.1016/j.diabet.2021.101278] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 08/04/2021] [Accepted: 08/07/2021] [Indexed: 12/21/2022]
Abstract
OBJECTIVES This study aimed to estimate the association between overweight and type 2 diabetes mellitus (T2DM) in twins, and further to explore whether genetic and early-life environmental factors account for this association. METHODS This study included 31,197 twin individuals from the Chinese National Twin Registry (CNTR). Generalized estimating equation (GEE) models were applied for unmatched case-control analysis. Conditional logistic regressions were used in co-twin matched case-control analysis. Logistic regressions were fitted to examine the differences in odds ratios (ORs) from the GEE models and conditional logistic regressions. Bivariate genetic model was used to explore the genetic and environmental correlation between body mass index (BMI) and T2DM. RESULTS In the GEE model, overweight was associated with a higher T2DM risk (OR=2.71, 95% confidence interval (CI): 1.96∼3.73), compared with participants with normal BMI. In the multi-adjusted conditional logistic regression, the association was still significant (OR=2.60, 95% CI: 1.15∼5.87). The ORs from the unmatched and matched analyses were different (P = 0.042). Particularly, overweight could increase T2DM risk in monozygotic (MZ) twins, and the difference in ORs between the unmatched and matched designs was significant (P = 0.014). After controlling for age and sex, the positive BMI-T2DM association was partly due to a significant genetic correlation (rA= 0.31, 95% CI: 0.20∼0.41). CONCLUSIONS Our findings suggest that genetics and early-life environments might account for the observed overweight-T2DM association. Genetic correlation between BMI and T2DM further provides evidence for the influence of overlap genes on their association.
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Affiliation(s)
- Yu'e Xi
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Wenjing Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
| | - Ke Zheng
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Shengfeng Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Tao Huang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Chunxiao Liao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
| | - Zengchang Pang
- Qingdao Municipal Center for Disease Control and Prevention, Qingdao 266033, China
| | - Min Yu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou 310051, China
| | - Hua Wang
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing 210009, China
| | - Xianping Wu
- Sichuan Center for Disease Control and Prevention, Chengdu 610041, China
| | - Zhong Dong
- Beijing Center for Disease Prevention and Control, Beijing 100013, China
| | - Fan Wu
- Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
| | - Guohong Jiang
- Tianjin Centers for Disease Control and Prevention, Tianjin 300011, China
| | - Xiaojie Wang
- Qinghai Center for Diseases Prevention and Control, Xining 810007, China
| | - Yu Liu
- Heilongjiang Provincial Center for Disease Control and Prevention, Harbin 150030, China
| | - Jian Deng
- Handan Center for Disease Control and Prevention, Handan 056001, China
| | - Lin Lu
- Yunnan Center for Disease Control and Prevention, Kunming 650034, China
| | - Weihua Cao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China.
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing 100191, China
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11
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Untangling the genetic link between type 1 and type 2 diabetes using functional genomics. Sci Rep 2021; 11:13871. [PMID: 34230558 PMCID: PMC8260770 DOI: 10.1038/s41598-021-93346-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2020] [Accepted: 06/16/2021] [Indexed: 02/06/2023] Open
Abstract
There is evidence pointing towards shared etiological features between type 1 diabetes (T1D) and type 2 diabetes (T2D) despite both phenotypes being considered genetically distinct. However, the existence of shared genetic features for T1D and T2D remains complex and poorly defined. To better understand the link between T1D and T2D, we employed an integrated functional genomics approach involving extensive chromatin interaction data (Hi-C) and expression quantitative trait loci (eQTL) data to characterize the tissue-specific impacts of single nucleotide polymorphisms associated with T1D and T2D. We identified 195 pleiotropic genes that are modulated by tissue-specific spatial eQTLs associated with both T1D and T2D. The pleiotropic genes are enriched in inflammatory and metabolic pathways that include mitogen-activated protein kinase activity, pertussis toxin signaling, and the Parkinson's disease pathway. We identified 8 regulatory elements within the TCF7L2 locus that modulate transcript levels of genes involved in immune regulation as well as genes important in the etiology of T2D. Despite the observed gene and pathway overlaps, there was no significant genetic correlation between variant effects on T1D and T2D risk using European ancestral summary data. Collectively, our findings support the hypothesis that T1D and T2D specific genetic variants act through genetic regulatory mechanisms to alter the regulation of common genes, and genes that co-locate in biological pathways, to mediate pleiotropic effects on disease development. Crucially, a high risk genetic profile for T1D alters biological pathways that increase the risk of developing both T1D and T2D. The same is not true for genetic profiles that increase the risk of developing T2D. The conversion of information on genetic susceptibility to the protein pathways that are altered provides an important resource for repurposing or designing novel therapies for the management of diabetes.
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12
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Li X, Yang R, Yang W, Xu H, Song R, Qi X, Xu W. Association of low birth weight with cardiometabolic diseases in Swedish twins: a population-based cohort study. BMJ Open 2021; 11:e048030. [PMID: 34183347 PMCID: PMC8240562 DOI: 10.1136/bmjopen-2020-048030] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVES To examine the association between low birth weight (LBW) and cardiometabolic diseases (CMDs, including heart disease, stroke and type 2 diabetes mellitus) in adulthood, and to explore whether genetic, early-life environmental and healthy lifestyle factors play a role in this association. DESIGN A population-based twin study. SETTING Twins from the Swedish Twin Registry who were born in 1958 or earlier participated in the Screening Across the Lifespan Twin (SALT) study for a full-scale screening during 1998-2002 and were followed up until 2014. PARTICIPANTS 19 779 twin individuals in Sweden with birthweight data available (mean age: 55.45 years). PRIMARY AND SECONDARY OUTCOME MEASURES CMDs were assessed based on self-reported medical records, medication use and records from the National Patient Registry. A lifestyle index encompassing smoking status, alcohol consumption, exercise levels and Body Mass Index was derived from the SALT survey and categorised as unfavourable, intermediate or favourable. Data were analysed using generalised estimating equation (GEE) models and conditional logistic regression models. RESULTS Of all participants, 3998 (20.2%) had LBW and 5335 (27.0%) had incident CMDs (mean age at onset: 63.64±13.26 years). In GEE models, the OR of any CMD was 1.39 (95% CI 1.27 to 1.52) for LBW. In conditional logistic regression models, the LBW-CMD association became non-significant (OR=1.21, 95% CI 0.94 to 1.56). The difference in ORs from the two models was statistically significant (p<0.001). In the joint effect analysis, the multiadjusted OR of CMDs was 3.47 (95% CI 2.72 to 4.43) for participants with LBW plus an unfavourable lifestyle and 1.25 (95% CI 0.96 to 1.62) for those with LBW plus a favourable lifestyle. CONCLUSION LBW is associated with an increased risk of adult CMDs, and genetic and early-life environmental factors may account for this association. However, a favourable lifestyle profile may modify this risk.
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Affiliation(s)
- Xuerui Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin, China
| | - Rongrong Yang
- Public Health Science and Engineering College, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Wenzhe Yang
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin, China
| | - Hui Xu
- Big Data and Engineering Research Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Ruixue Song
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin, China
| | - Xiuying Qi
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin, China
| | - Weili Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
- Tianjin Key Laboratory of Environment, Nutrition and Public Health, Tianjin, China
- Center for International Collaborative Research on Environment, Nutrition and Public Health, Tianjin, China
- Aging Research Center, Department of Neurobiology, Health Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
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13
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Yang R, Xu H, Pedersen NL, Li X, Yu J, Bao C, Qi X, Xu W. A healthy lifestyle mitigates the risk of heart disease related to type 2 diabetes: a prospective nested case-control study in a nationwide Swedish twin cohort. Diabetologia 2021; 64:530-539. [PMID: 33169206 PMCID: PMC7864843 DOI: 10.1007/s00125-020-05324-z] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 09/28/2020] [Indexed: 12/15/2022]
Abstract
AIMS/HYPOTHESIS We aimed to examine the association between type 2 diabetes and major subtypes of heart disease, to assess the role of genetic and early-life familial environmental factors in this association and to explore whether and to what extent a healthy lifestyle mitigates the risk of heart disease related to type 2 diabetes. METHODS In this prospective nested case-control study based on the Swedish Twin Registry, 41,463 twin individuals who were aged ≥40 and heart disease-free were followed up for 16 years (from 1998 to 2014) to detect incident heart disease. Type 2 diabetes was ascertained from self-report, the National Patient Registry and glucose-lowering medication use. Heart disease diagnosis (including coronary heart disease, cardiac arrhythmias and heart failure) and onset age were identified from the National Patient Registry. Healthy lifestyle-related factors consisted of being a non-smoker, no/mild alcohol consumption, regular physical activity and being non-overweight. Participants were divided into three groups according to the number of lifestyle-related factors: (1) unfavourable (participants who had no or only one healthy lifestyle factor); (2) intermediate (any two or three); and (3) favourable (four). Generalised estimating equation models for unmatched case-control design and conditional logistic regression for co-twin control design were used in data analyses. RESULTS Of all participants, 2304 (5.5%) had type 2 diabetes at baseline. During the observation period, 9262 (22.3%) had any incident heart disease. In unmatched case-control analyses and co-twin control analyses, the multi-adjusted OR and 95% CI of heart disease related to type 2 diabetes was 4.36 (3.95, 4.81) and 4.89 (3.88, 6.16), respectively. The difference in ORs from unmatched case-control analyses vs co-twin control analyses was statistically significant (OR 1.57; 95% CI 1.42, 1.73; p < 0.001). In stratified analyses by type 2 diabetes, compared with an unfavourable lifestyle, an intermediate lifestyle or a favourable lifestyle was associated with a significant 32% (OR 0.68; 95% CI 0.49, 0.93) or 56% (OR 0.44; 95% CI 0.30, 0.63) decrease in heart disease risk among patients with type 2 diabetes, respectively. There were significant additive and multiplicative interactions between lifestyle and type 2 diabetes on heart disease. CONCLUSIONS/INTERPRETATION Type 2 diabetes is associated with more than fourfold increased risk of heart disease. The association still remains statistically significant, even after fully controlling for genetic and early-life familial environmental factors. However, greater adherence to a healthy lifestyle may significantly mitigate the risk of heart disease related to type 2 diabetes. Graphical abstract.
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Affiliation(s)
- Rongrong Yang
- Public Health Science and Engineering College, Tianjin University of Traditional Chinese Medicine, Tianjin, China
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Hui Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
- Big Data and Engineering Research Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, China
| | - Nancy L Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Psychology, University of Southern California, Los Angeles, CA, USA
| | - Xuerui Li
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China
| | - Jing Yu
- Department of Physiology and Pathophysiology, School of Basic Medicine, Tianjin Medical University, Tianjin, China
| | - Cuiping Bao
- Department of Radiology, Tianjin Union Medical Centre, Tianjin, China
| | - Xiuying Qi
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China.
| | - Weili Xu
- Department of Epidemiology and Biostatistics, School of Public Health, Tianjin Medical University, Tianjin, China.
- Aging Research Center, Department of Neurobiology, Health Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
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14
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Nas Z, Zavos HMS, Sumathipala A, Jayaweera K, Siribaddana S, Hotopf M, Rijsdijk FV. Associations Between Anxiety Symptoms and Health-Related Quality of Life: A Population-Based Twin Study in Sri Lanka. Behav Genet 2021; 51:394-404. [PMID: 33604755 PMCID: PMC8225527 DOI: 10.1007/s10519-021-10051-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2020] [Accepted: 02/03/2021] [Indexed: 11/01/2022]
Abstract
Anxiety not only concerns mental wellbeing but also negatively impacts other areas of health. Yet, there is limited research on (a) the genetic and environmental aetiology of such relationships; (b) sex differences in aetiology and (c) non-European samples. In this study, we investigated the genetic and environmental variation and covariation of anxiety symptoms and eight components of health-related quality of life (QoL), as measured by the short form health survey (SF-36), using genetic twin model fitting analysis. Data was drawn from the Colombo Twin and Singleton Study (COTASS), a population-based sample in Sri Lanka with data on twins (N = 2921) and singletons (N = 1027). Individual differences in anxiety and QoL traits showed more shared environmental (family) effects in women. Men did not show familial effects. Anxiety negatively correlated with all eight components of QoL, mostly driven by overlapping unique (individual-specific) environmental effects in both sexes and overlapping shared environmental effects in women. This is the first study in a South Asian population supporting the association between poor mental health and reduced QoL, highlighting the value of integrated healthcare services. Associations were largely environmental, on both individual and family levels, which could be informative for therapy and intervention.
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Affiliation(s)
- Zeynep Nas
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
| | - Helena M S Zavos
- Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Athula Sumathipala
- Institute for Research and Development, Colombo, Sri Lanka.,Research Institute for Primary Care and Health Sciences, Faculty of Health, Keele University, Keele, UK
| | | | - Sisira Siribaddana
- Faculty of Medicine & Allied Sciences, Rajarata University of Sri Lanka, Anuradhapura, Sri Lanka
| | - Matthew Hotopf
- Psychological Medicine Department, Institute of Psychiatry, Psychology, and Neuroscience, King's College London, London, UK.,NIHR Biomedical Research Centre for Mental Health at the South London and Maudsley NHS Foundation Trust, King's College London, London, UK
| | - Frühling V Rijsdijk
- Social, Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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15
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Cleven L, Krell-Roesch J, Nigg CR, Woll A. The association between physical activity with incident obesity, coronary heart disease, diabetes and hypertension in adults: a systematic review of longitudinal studies published after 2012. BMC Public Health 2020; 20:726. [PMID: 32429951 PMCID: PMC7238737 DOI: 10.1186/s12889-020-08715-4] [Citation(s) in RCA: 123] [Impact Index Per Article: 24.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2019] [Accepted: 04/15/2020] [Indexed: 12/21/2022] Open
Abstract
BACKGROUND A growing body of studies that investigated the longitudinal association between physical activity (PA) and the outcome of incident obesity, coronary heart disease (CHD), diabetes and hypertension has become available in recent years. Thus, the purpose of this systematic review was to provide an update on the association between PA and onset of obesity, CHD, diabetes and hypertension in individuals aged ≥18 years who were free of the respective conditions at baseline. METHODS We systematically searched OVID, Pubmed, and Web of Science databases for pertinent literature published between January of 2012 and February of 2019. To ensure that conclusions are based on high quality evidence, we only included longitudinal studies conducted in samples of ≥500 participants and with ≥5 years of follow-up. RESULT The search yielded 8929 records of which 26 were included in this review. Three studies were conducted on the outcome of incident obesity, eight on incident CHD, nine on incident diabetes, four on incident hypertension, one on the outcome of both diabetes and hypertension, and one on the outcome of CHD, diabetes and hypertension. Overall, there was an association between PA and lower risk of incident obesity, CHD and diabetes, but not hypertension. Higher levels or amount of PA were associated with a reduced risk of new onset of the respective diseases in 20 studies (77%). Whereas four studies reported an elevated risk of incidence of diseases with lower PA levels (15%). PA was not associated with incidence of diseases in two studies (8%). CONCLUSION Higher levels of PA are likely associated with a lower risk of becoming obese, develop CHD or diabetes. These findings replicate and strengthen conclusions from earlier reviews underlining the importance of promoting PA in adults. The associations between PA and incident hypertension were less consistent. More research, particularly using prospective cohort designs in large population-based samples, is needed to further untangle the association between PA and incident hypertension. TRAIL REGISTRATION CRD42019124474 (PROSPERO Protocol registration). Date of registration in PROSPERO 27 February 2019.
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Affiliation(s)
- Laura Cleven
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
| | - Janina Krell-Roesch
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
- Translational Neuroscience and Aging Laboratory, Mayo Clinic, Scottsdale, AZ USA
| | - Claudio R. Nigg
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
- Present address: Institute of Sports Science, University of Bern, Bern, Switzerland
| | - Alexander Woll
- Institute of Sports and Sports Science, Karlsruhe Institute of Technology, Karlsruhe, Germany
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Abstract
Approximately 12% of U.S. adults have type 2 diabetes (T2D). Diagnosed T2D is caused by a combination of genetic and environmental factors including age and lifestyle. In adults 45 years and older, the Discordant Twin (DISCOTWIN) consortium of twin registries from Europe and Australia showed a moderate-to-high contribution of genetic factors of T2D with a pooled heritability of 72%. The purpose of this study was to investigate the contributions of genetic and environmental factors of T2D in twins 45 years and older in a U.S. twin cohort (Washington State Twin Registry, WSTR) and compare the estimates to the DISCOTWIN consortium. We also compared these estimates with twins under the age of 45. Data were obtained from 2692 monozygotic (MZ) and same-sex dizygotic (DZ) twin pairs over 45 and 4217 twin pairs under 45 who responded to the question 'Has a doctor ever diagnosed you with (type 2) diabetes?' Twin similarity was analyzed using both tetrachoric correlations and structural equation modeling. Overall, 9.4% of MZ and 14.7% of DZ twins over the age of 45 were discordant for T2D in the WSTR, compared to 5.1% of MZ and 8% of DZ twins in the DISCOTWIN consortium. Unlike the DISCOTWIN consortium in which heritability was 72%, heritability was only 52% in the WSTR. In twins under the age of 45, heritability did not contribute to the variance in T2D. In a U.S. sample of adult twins, environmental factors appear to be increasingly important in the development of T2D.
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Wehby GL, Shane D. Genetic variation in health insurance coverage. INTERNATIONAL JOURNAL OF HEALTH ECONOMICS AND MANAGEMENT 2019; 19:301-316. [PMID: 30421388 DOI: 10.1007/s10754-018-9255-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2017] [Accepted: 11/03/2018] [Indexed: 06/09/2023]
Abstract
We provide the first investigation into whether and how much genes explain having health insurance coverage or not and possible mechanisms for genetic variation. Using a twin-design that compares identical and non-identical twins from a national sample of US twins from the National Survey of Midlife Development in the United States, we find that genetic effects explain over 40% of the variation in whether a person has any health coverage versus not, and nearly 50% of the variation in whether individuals younger than 65 have private coverage versus whether they have no coverage at all. Nearly one third of the genetic variation in being uninsured versus having private coverage is explained by employment industry, self-employment status, and income, and together with education, they explain over 40% of the genetic influence. Marital status, number of children, and available measures of health status, risk preferences, and prevention effort do not appear to be important channels for genetic effects. That genes have meaningful effects on the insurance status suggests an important source of heterogeneity in insurance take up.
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Affiliation(s)
- George L Wehby
- Department of Health Management and Policy, University of Iowa, 145 N. Riverside Dr., 100 College of Public Health Bldg., Room N250, Iowa City, IA, 52242-2007, USA.
- Department of Economics, University of Iowa, Iowa City, IA, USA.
- Department of Preventive and Community Dentistry, University of Iowa, Iowa City, IA, USA.
- Public Policy Center, University of Iowa, Iowa City, IA, USA.
- National Bureau of Economic Research, Cambridge, MA, USA.
| | - Dan Shane
- Department of Health Management and Policy, University of Iowa, 145 N. Riverside Dr., 100 College of Public Health Bldg., Room N250, Iowa City, IA, 52242-2007, USA
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18
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Carlsson S, Kuja-Halkola R, Magnusson C, Lagerros YT, Andersson T. Tobacco and type 2 diabetes: is the association explained by genetic factors? Int J Epidemiol 2019; 48:926-933. [PMID: 30726916 DOI: 10.1093/ije/dyz002] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/14/2019] [Indexed: 11/13/2022] Open
Abstract
BACKGROUND Smoking and use of Swedish smokeless tobacco (snus) are associated with increased risk of type 2 diabetes (T2D). Our aim was to estimate the unique and shared genetic components of these traits and to what extent the association is explained by shared genetic factors. METHODS We used twins of the Swedish Twin Registry who responded to a questionnaire between 1998 and 2006 (n = 40 247) and were followed until 2015 in the National Prescription and Patient Registries. We estimated hazard ratios (HRs) and odds ratios (ORs) for the association between smoking/snus use and T2D (n = 2130) and used structural equation models to estimate genetic and environmental variance components and genetic correlations. RESULTS Current smokers [HR 1.69, 95% confidence interval (CI), 1.49-1.92] and snus users (HR 1.19, 95% CI 1.01-1.41) had an increased risk of T2D. In within-pair analyses of monozygotic twins, corresponding ORs were 1.36, 95% CI 0.75-2.46 (smoking) and 1.54, 95% CI 0.80-2.99 (snus). Heritability was 43% (95% CI 36-51) for ever smoking, 58% (95% CI 44- 70) for ever snus use and 66% (95% CI 59-72) for T2D. The genetic correlation with T2D was 18% (95% CI 1-35) for smoking and -6% (95% CI -24 to 4) for snus use, indicating that only a small fraction of the genetic influence is shared. CONCLUSIONS We could confirm that consumers of snus and cigarettes are at increased risk of T2D. Both snus use and smoking have strong genetic components, which appears to be attributable primarily to genes that are distinct from those promoting T2D.
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Affiliation(s)
- Sofia Carlsson
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Ralf Kuja-Halkola
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet and Centre for Epidemiology and Community Medicine, Stockholm County Council, Stockholm, Sweden
| | - Cecilia Magnusson
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden.,Department of Medicine, Karolinska Institutet, Stockholm, Sweden
| | | | - Tomas Andersson
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.,Centre for Occupational and Environmental Medicine, Stockholm County Council, Stockholm, Sweden
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19
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Wehby GL, Domingue BW, Wolinsky FD. Genetic Risks for Chronic Conditions: Implications for Long-term Wellbeing. J Gerontol A Biol Sci Med Sci 2019; 73:477-483. [PMID: 28958056 DOI: 10.1093/gerona/glx154] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2017] [Accepted: 08/04/2017] [Indexed: 11/12/2022] Open
Abstract
Background Relationships between genetic risks for chronic diseases and long-run wellbeing are largely unexplored. We examined the associations between genetic predispositions to several chronic conditions and long-term functional health and socioeconomic status (SES). Methods We used data on a nationally representative sample of 9,317 adults aged 65 years or older from the 1992 to 2012 Health and Retirement Survey (HRS) in the US. Survey data were linked to genetic data on nearly 2 million single-nucleotide polymorphisms (SNPs). We measured individual-level genetic predispositions for coronary-artery disease, type 2 diabetes (T2D), obesity, rheumatoid arthritis (RA), Alzheimer's disease, and major depressive disorder (MDD) by polygenic risk scores (PRS) derived from genome-wide association studies (GWAS). The outcomes were self-rated health, depressive symptoms, cognitive ability, activities of everyday life, educational attainment, and wealth. We employed regression analyses for the outcomes including all polygenic scores and adjusting for gender, birth period, and genetic ancestry. Results The polygenic scores had important associations with functional health and SES. An increase in genetic risk for all conditions except T2D was significantly (p < .01) associated with reduced functional health and socioeconomic outcomes. The magnitudes of functional health declines were meaningful and in many cases equivalent in magnitude to several years of aging. These associations were robust to several sensitivity checks for ancestry and adjustment for parental educational attainment and age at death or the last interview if alive. Conclusion Stronger genetic predispositions for leading chronic conditions are related to worse long-run health and SES outcomes, likely reflecting the adverse effects of the onset of these conditions on one's wellbeing.
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Affiliation(s)
- George L Wehby
- Department of Health Management and Policy, University of Iowa, IA.,Department of Economics, University of Iowa, IA.,Department of Preventive & Community Dentistry, and Public Policy Center, University of Iowa, IA.,National Bureau of Economic Research, Cambridge, MA
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20
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Kaur Y, Wang DX, Liu HY, Meyre D. Comprehensive identification of pleiotropic loci for body fat distribution using the NHGRI-EBI Catalog of published genome-wide association studies. Obes Rev 2019; 20:385-406. [PMID: 30565845 DOI: 10.1111/obr.12806] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Revised: 10/05/2018] [Accepted: 10/15/2018] [Indexed: 12/22/2022]
Abstract
We conducted a hypothesis-free cross-trait analysis for waist-to-hip ratio adjusted for body mass index (WHRadjBMI ) loci derived through genome-wide association studies (GWAS). Summary statistics from published GWAS were used to capture all WHRadjBMI single-nucleotide polymorphisms (SNPs), and their proxy SNPs were identified. These SNPs were used to extract cross-trait associations between WHRadjBMI SNPs and other traits through the NHGRI-EBI GWAS Catalog. Pathway analysis was conducted for pleiotropic WHRadjBMI SNPs. We found 160 WHRadjBMI SNPs and 3675 proxy SNPs. Cross-trait analysis identified 239 associations, of which 100 were for obesity traits. The remaining 139 associations were filtered down to 101 unique linkage disequilibrium block associations, which were grouped into 13 categories: lipids, red blood cell traits, white blood cell counts, inflammatory markers and autoimmune diseases, type 2 diabetes-related traits, adiponectin, cancers, blood pressure, height, neuropsychiatric disorders, electrocardiography changes, urea measurement, and others. The highest number of cross-trait associations were found for triglycerides (n = 10), high-density lipoprotein cholesterol (n = 9), and reticulocyte counts (n = 8). Pathway analysis for WHRadjBMI pleiotropic SNPs found immune function pathways as the top canonical pathways. Results from our original methodology indicate a novel genetic association between WHRadjBMI and reticulocyte counts and highlight the pleiotropy between abdominal obesity, immune pathways, and other traits.
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Affiliation(s)
- Yuvreet Kaur
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.,Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Dominic X Wang
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.,Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Hsin-Yen Liu
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.,Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - David Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada.,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada
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21
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Abdullah N, Murad NAA, Attia J, Oldmeadow C, Kamaruddin MA, Jalal NA, Ismail N, Jamal R, Scott RJ, Holliday EG. Differing Contributions of Classical Risk Factors to Type 2 Diabetes in Multi-Ethnic Malaysian Populations. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:E2813. [PMID: 30544761 PMCID: PMC6313591 DOI: 10.3390/ijerph15122813] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Revised: 12/03/2018] [Accepted: 12/04/2018] [Indexed: 12/12/2022]
Abstract
The prevalence of type 2 diabetes is escalating rapidly in Asian countries, with the rapid increase likely attributable to a combination of genetic and lifestyle factors. Recent research suggests that common genetic risk variants contribute minimally to the rapidly rising prevalence. Rather, recent changes in dietary patterns and physical activity may be more important. This nested case-control study assessed the association and predictive utility of type 2 diabetes lifestyle risk factors in participants from Malaysia, an understudied Asian population with comparatively high disease prevalence. The study sample comprised 4077 participants from The Malaysian Cohort project and included sub-samples from the three major ancestral groups: Malay (n = 1323), Chinese (n = 1344) and Indian (n = 1410). Association of lifestyle factors with type 2 diabetes was assessed within and across ancestral groups using logistic regression. Predictive utility was quantified and compared between groups using the Area Under the Receiver-Operating Characteristic Curve (AUC). In predictive models including age, gender, waist-to-hip ratio, physical activity, location, family history of diabetes and average sleep duration, the AUC ranged from 0.76 to 0.85 across groups and was significantly higher in Chinese than Malays or Indians, likely reflecting anthropometric differences. This study suggests that obesity, advancing age, a family history of diabetes and living in a rural area are important drivers of the escalating prevalence of type 2 diabetes in Malaysia.
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Affiliation(s)
- Noraidatulakma Abdullah
- School of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle, New South Wales, 2308, Australia.
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000, Kuala Lumpur, Malaysia.
| | - Nor Azian Abdul Murad
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000, Kuala Lumpur, Malaysia.
| | - John Attia
- Clinical Research Design, IT and Statistical Support (CReDITSS) Unit, Hunter Medical Research Institute, Newcastle, New South Wales, 2305, Australia.
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health and Medicine, University of Newcastle, Newcastle, New South Wales, 2308, Australia.
| | - Christopher Oldmeadow
- Clinical Research Design, IT and Statistical Support (CReDITSS) Unit, Hunter Medical Research Institute, Newcastle, New South Wales, 2305, Australia.
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health and Medicine, University of Newcastle, Newcastle, New South Wales, 2308, Australia.
| | - Mohd Arman Kamaruddin
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000, Kuala Lumpur, Malaysia.
| | - Nazihah Abd Jalal
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000, Kuala Lumpur, Malaysia.
| | - Norliza Ismail
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000, Kuala Lumpur, Malaysia.
| | - Rahman Jamal
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, 56000, Kuala Lumpur, Malaysia.
| | - Rodney J Scott
- School of Biomedical Sciences and Pharmacy, Faculty of Health and Medicine, University of Newcastle, Newcastle, New South Wales, 2308, Australia.
- Hunter Area Pathology Service, John Hunter Hospital, Newcastle, New South Wales, 2305, Australia.
| | - Elizabeth G Holliday
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health and Medicine, University of Newcastle, Newcastle, New South Wales, 2308, Australia.
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22
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Young AI, Frigge ML, Gudbjartsson DF, Thorleifsson G, Bjornsdottir G, Sulem P, Masson G, Thorsteinsdottir U, Stefansson K, Kong A. Relatedness disequilibrium regression estimates heritability without environmental bias. Nat Genet 2018; 50:1304-1310. [PMID: 30104764 PMCID: PMC6130754 DOI: 10.1038/s41588-018-0178-9] [Citation(s) in RCA: 109] [Impact Index Per Article: 15.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2018] [Accepted: 06/29/2018] [Indexed: 01/21/2023]
Abstract
Heritability measures the proportion of trait variation that is due to genetic inheritance. Measurement of heritability is important in the nature-versus-nurture debate. However, existing estimates of heritability may be biased by environmental effects. Here, we introduce relatedness disequilibrium regression (RDR), a novel method for estimating heritability. RDR avoids most sources of environmental bias by exploiting variation in relatedness due to random Mendelian segregation. We used a sample of 54,888 Icelanders who had both parents genotyped to estimate the heritability of 14 traits, including height (55.4%, s.e. 4.4%) and educational attainment (17.0%, s.e. 9.4%). Our results suggest that some other estimates of heritability may be inflated by environmental effects.
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Affiliation(s)
- Alexander I Young
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
| | | | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Augustine Kong
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, University of Oxford, Oxford, UK.
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland.
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23
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Oh HJ, Choi CW. Relationship of the hs-CRP Levels with FBG, Fructosamine, and HbA 1c in Non-diabetic Obesity Adults. KOREAN JOURNAL OF CLINICAL LABORATORY SCIENCE 2018. [DOI: 10.15324/kjcls.2018.50.2.190] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Affiliation(s)
- Hye Jong Oh
- Department of Biomedical Laboratory Science, Hanlyo University, Gwangyang, Korea
| | - Cheol Won Choi
- Department of Biomedical Laboratory Science, Hanlyo University, Gwangyang, Korea
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24
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Opposite Genetic Effects of CMIP Polymorphisms on the Risk of Type 2 Diabetes and Obesity: A Family-Based Study in China. Int J Mol Sci 2018; 19:ijms19041011. [PMID: 29597287 PMCID: PMC5979311 DOI: 10.3390/ijms19041011] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Revised: 03/23/2018] [Accepted: 03/26/2018] [Indexed: 02/08/2023] Open
Abstract
C-Maf Inducing Protein (CMIP) gene polymorphisms were reported to be associated with type 2 diabetes mellitus (T2DM). Whether the association between CMIP and T2DM is mediated via obesity-related phenotypes is still unclear. We analyzed the association of CMIP rs2925979 with T2DM and a comprehensive set of obesity-related phenotypes in 1576 families ascertained from a Chinese population. These families included a total of 3444 siblings (1582 with T2DM, 963 with prediabetes, and 899 with a normal glucose level). Using multi-level mixed effects regression models, we found that each copy of CMIP rs2925979_T allele was associated with a 29% higher risk of T2DM in females (p = 9.30 × 10-4), while it was not significantly associated with T2DM in males (p = 0.705). Meanwhile, rs2925979_T allele was associated with lower levels of body mass index (BMI), waist circumference (WC), hip circumference (HC), percentage of body fat (PBF), PBF of arms, PBF of legs, and PBF of trunk in nondiabetes females (all p < 0.05). The opposite associations of rs2925979_T allele with T2DM and obesity-related phenotypes suggest that CMIP may exert independent pleiotropic effects on T2DM and obesity-related phenotypes in females.
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25
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Kim J, Kim J, Kwak M, Bajaj M. Genetic prediction of type 2 diabetes using deep neural network. Clin Genet 2018; 93:822-829. [DOI: 10.1111/cge.13175] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Revised: 11/02/2017] [Accepted: 11/08/2017] [Indexed: 12/25/2022]
Affiliation(s)
- J. Kim
- Division of Diabetes, Metabolism, and Endocrinology, Department of Medicine; Baylor College of Medicine, Baylor Clinic Endocrinology; Houston Texas
- Department of Medicine; Baylor St Luke’s Medical Center; Houston Texas
| | - J. Kim
- School of Electrical Engineering; Korea Advanced Institute of Science and Technology; Daejeon South Korea
| | - M.J. Kwak
- Department of Medicine; The University of Texas McGovern Medical School; Houston Texas
| | - M. Bajaj
- Division of Diabetes, Metabolism, and Endocrinology, Department of Medicine; Baylor College of Medicine, Baylor Clinic Endocrinology; Houston Texas
- Department of Medicine; Baylor St Luke’s Medical Center; Houston Texas
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26
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Badri NW, Flatt SW, Barkai HS, Pakiz B, Heath DD, Rock CL. Insulin Resistance Improves More in Women than In Men in Association with a Weight Loss Intervention. ACTA ACUST UNITED AC 2018; 8. [PMID: 29552423 PMCID: PMC5856149 DOI: 10.4172/2165-7904.1000365] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
Background Fasting glucose and homeostatic model assessment-insulin resistance (HOMA-IR) are important measures of the risk for metabolic syndrome and diabetes. Weight loss interventions are considered part of the first line of therapy for those who develop disease states associated with insulin resistance, such as pre-diabetes, diabetes, or metabolic syndrome. Sex differences in insulin resistance have been extensively reported, but sex differences in the ability to improve insulin sensitivity are not well-established. This study sought to identify factors that predict change in HOMA-IR in response to weight loss. Methods Non-diabetic subjects who were overweight/obese (n=100) were randomly assigned to a walnut-enriched reduced-energy diet or a standard reduced-energy-density diet in a 6-month weight loss intervention. There were no significant differences in weight change, glucose, insulin, or HOMA-IR between the two diet groups. These subjects were combined into a single cohort and analyzed with multivariate analysis. Results The combined groups lost an average of 8.7 kg (p<0.0001), decreased serum glucose by an average 0.2 mmol/L (p<0.001), and decreased HOMA-IR by an average of 1.4 (p<0.0001). Change in HOMA-IR (R2=0.69) was positively associated with weight change (p<0.0001) and male sex (p<0.01), and negatively associated with baseline HOMA-IR (p<0.0001). Conclusion Findings from this study suggest that men may have a more difficult time improving insulin sensitivity as compared with women with an equivalent weight loss and baseline HOMA-IR. One hypothesis to explain the differences across sexes may be due to sex differences in visceral adipose fat (VAT). This may mean that insulin resistant men require more aggressive intervention than women to prevent progression to metabolic syndrome or diabetes.
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Affiliation(s)
- N W Badri
- Department of Family Medicine and Public Health, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - S W Flatt
- Department of Family Medicine and Public Health, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - H S Barkai
- Department of Family Medicine and Public Health, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - B Pakiz
- Department of Family Medicine and Public Health, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - D D Heath
- Department of Family Medicine and Public Health, School of Medicine, University of California, San Diego, La Jolla, CA, USA
| | - C L Rock
- Department of Family Medicine and Public Health, School of Medicine, University of California, San Diego, La Jolla, CA, USA
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27
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Goetzman ES, Gong Z, Schiff M, Wang Y, Muzumdar RH. Metabolic pathways at the crossroads of diabetes and inborn errors. J Inherit Metab Dis 2018; 41:5-17. [PMID: 28952033 PMCID: PMC6757345 DOI: 10.1007/s10545-017-0091-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2017] [Revised: 08/30/2017] [Accepted: 09/08/2017] [Indexed: 12/18/2022]
Abstract
Research over the past two decades has led to advances in our understanding of the genetic and metabolic factors that underlie the pathogenesis of type 2 diabetes mellitus (T2DM). While T2DM is defined by its hallmark metabolic symptoms, the genetic risk factors for T2DM are more immune-related than metabolism-related, and the observed metabolic disease may be secondary to chronic inflammation. Regardless, these metabolic changes are not benign, as the accumulation of some metabolic intermediates serves to further drive the inflammation and cell stress, eventually leading to insulin resistance and ultimately to T2DM. Because many of the biochemical changes observed in the pre-diabetic state (i.e., ectopic lipid storage, increased acylcarnitines, increased branched-chain amino acids) are also observed in patients with rare inborn errors of fatty acid and amino acid metabolism, an interesting question is raised regarding whether isolated metabolic gene defects can confer an increased risk for T2DM. In this review, we attempt to address this question by summarizing the literature regarding the metabolic pathways at the crossroads of diabetes and inborn errors of metabolism. Studies using cell culture and animal models have revealed that, within a given pathway, disrupting some genes can lead to insulin resistance while for others there may be no effect or even improved insulin sensitivity. This differential response to ablating a single metabolic gene appears to be dependent upon the specific metabolic intermediates that accumulate and whether these intermediates subsequently activate inflammatory pathways. This highlights the need for future studies to determine whether certain inborn errors may confer increased risk for diabetes as the patients age.
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Affiliation(s)
- Eric S Goetzman
- Department of Pediatrics, School of Medicine, University of Pittsburgh, 4401 Penn Ave, Pittsburgh, PA, 15224, USA.
- Children's Hospital of Pittsburgh, Rangos 5117, 4401 Penn Avenue, Pittsburgh, PA, 15224, USA.
| | - Zhenwei Gong
- Department of Pediatrics, School of Medicine, University of Pittsburgh, 4401 Penn Ave, Pittsburgh, PA, 15224, USA
| | - Manuel Schiff
- UMR1141, PROTECT, INSERM, Université Paris Diderot, Sorbonne Paris Cité, Paris, France
- Reference Center for Inborn Errors of Metabolism, Robert Debré University Hospital, APHP, Paris, France
| | - Yan Wang
- Department of Pediatrics, School of Medicine, University of Pittsburgh, 4401 Penn Ave, Pittsburgh, PA, 15224, USA
| | - Radhika H Muzumdar
- Department of Pediatrics, School of Medicine, University of Pittsburgh, 4401 Penn Ave, Pittsburgh, PA, 15224, USA
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28
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Abdullah N, Abdul Murad NA, Mohd Haniff EA, Syafruddin SE, Attia J, Oldmeadow C, Kamaruddin MA, Abd Jalal N, Ismail N, Ishak M, Jamal R, Scott RJ, Holliday EG. Predicting type 2 diabetes using genetic and environmental risk factors in a multi-ethnic Malaysian cohort. Public Health 2017; 149:31-38. [PMID: 28528225 DOI: 10.1016/j.puhe.2017.04.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Revised: 03/17/2017] [Accepted: 04/05/2017] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Malaysia has a high and rising prevalence of type 2 diabetes (T2D). While environmental (non-genetic) risk factors for the disease are well established, the role of genetic variations and gene-environment interactions remain understudied in this population. This study aimed to estimate the relative contributions of environmental and genetic risk factors to T2D in Malaysia and also to assess evidence for gene-environment interactions that may explain additional risk variation. STUDY DESIGN This was a case-control study including 1604 Malays, 1654 Chinese and 1728 Indians from the Malaysian Cohort Project. METHODS The proportion of T2D risk variance explained by known genetic and environmental factors was assessed by fitting multivariable logistic regression models and evaluating McFadden's pseudo R2 and the area under the receiver-operating characteristic curve (AUC). Models with and without the genetic risk score (GRS) were compared using the log likelihood ratio Chi-squared test and AUCs. Multiplicative interaction between genetic and environmental risk factors was assessed via logistic regression within and across ancestral groups. Interactions were assessed for the GRS and its 62 constituent variants. RESULTS The models including environmental risk factors only had pseudo R2 values of 16.5-28.3% and AUC of 0.75-0.83. Incorporating a genetic score aggregating 62 T2D-associated risk variants significantly increased the model fit (likelihood ratio P-value of 2.50 × 10-4-4.83 × 10-12) and increased the pseudo R2 by about 1-2% and AUC by 1-3%. None of the gene-environment interactions reached significance after multiple testing adjustment, either for the GRS or individual variants. For individual variants, 33 out of 310 tested associations showed nominal statistical significance with 0.001 < P < 0.05. CONCLUSION This study suggests that known genetic risk variants contribute a significant but small amount to overall T2D risk variation in Malaysian population groups. If gene-environment interactions involving common genetic variants exist, they are likely of small effect, requiring substantially larger samples for detection.
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Affiliation(s)
- N Abdullah
- School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, Newcastle, NSW, Australia; UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - N A Abdul Murad
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - E A Mohd Haniff
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - S E Syafruddin
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - J Attia
- Clinical Research Design, IT and Statistical Support (CReDITSS) Unit, Hunter Medical Research Institute, Newcastle, NSW, Australia; Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health, University of Newcastle, Newcastle, NSW, Australia
| | - C Oldmeadow
- Clinical Research Design, IT and Statistical Support (CReDITSS) Unit, Hunter Medical Research Institute, Newcastle, NSW, Australia; Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health, University of Newcastle, Newcastle, NSW, Australia
| | - M A Kamaruddin
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - N Abd Jalal
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - N Ismail
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - M Ishak
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - R Jamal
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia.
| | - R J Scott
- School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, Newcastle, NSW, Australia; Hunter Area Pathology Service, John Hunter Hospital, Newcastle, NSW, Australia
| | - E G Holliday
- Clinical Research Design, IT and Statistical Support (CReDITSS) Unit, Hunter Medical Research Institute, Newcastle, NSW, Australia; Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health, University of Newcastle, Newcastle, NSW, Australia.
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29
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Sánchez-Pozos K, Menjívar M. Genetic Component of Type 2 Diabetes in a Mexican Population. Arch Med Res 2016; 47:496-505. [DOI: 10.1016/j.arcmed.2016.12.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2016] [Accepted: 12/05/2016] [Indexed: 01/15/2023]
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30
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Lack of association between type 2 diabetes and major depression: epidemiologic and genetic evidence in a multiethnic population. Transl Psychiatry 2015; 5:e618. [PMID: 26261886 PMCID: PMC4564566 DOI: 10.1038/tp.2015.113] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/26/2015] [Revised: 06/16/2015] [Accepted: 06/25/2015] [Indexed: 01/07/2023] Open
Abstract
The positive association between depression and type 2 diabetes (T2D) has been controversial, and little is known about the molecular determinants linking these disorders. Here we investigated the association between T2D and depression at the clinical and genetic level in a multiethnic cohort. We studied 17,404 individuals from EpiDREAM (3209 depression cases and 14,195 controls) who were at risk for T2D and had both phenotypic and genotypic information available at baseline. The glycemic status was determined using the 2003 American Diabetes Association criteria and an oral glucose tolerance test. Major depressive episode during the previous 12 months was diagnosed using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition diagnostic criteria. Twenty single-nucleotide polymorphisms (SNPs) previously associated with T2D were genotyped using the cardiovascular gene-centric 50-K SNP array and were analyzed separately and in combination using an unweighted genotype score (GS). Multivariate logistic regression models adjusted for age, sex, ethnicity and body mass index were performed. Newly diagnosed impaired fasting glucose (IFG)/impaired glucose tolerance (IGT), T2D and dysglycemia status were not associated with major depression (0.30 ⩽ P ⩽ 0.65). Twelve out of twenty SNPs and the GS were associated with IFG/IGT, T2D and/or dysglycemia status (6.0 × 10(-35) ⩽ P ⩽ 0.048). In contrast, the 20 SNPs and GS were not associated with depression (P ⩾ 0.09). Our cross-sectional data do not support an association between T2D and depression at the clinical and genetic level in a multiethnic population at risk for T2D.
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Anderson D, Cordell HJ, Fakiola M, Francis RW, Syn G, Scaman ESH, Davis E, Miles SJ, McLeay T, Jamieson SE, Blackwell JM. First genome-wide association study in an Australian aboriginal population provides insights into genetic risk factors for body mass index and type 2 diabetes. PLoS One 2015; 10:e0119333. [PMID: 25760438 PMCID: PMC4356593 DOI: 10.1371/journal.pone.0119333] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2014] [Accepted: 01/28/2015] [Indexed: 12/15/2022] Open
Abstract
A body mass index (BMI) >22kg/m2 is a risk factor for type 2 diabetes (T2D) in Aboriginal Australians. To identify loci associated with BMI and T2D we undertook a genome-wide association study using 1,075,436 quality-controlled single nucleotide polymorphisms (SNPs) genotyped (Illumina 2.5M Duo Beadchip) in 402 individuals in extended pedigrees from a Western Australian Aboriginal community. Imputation using the thousand genomes (1000G) reference panel extended the analysis to 6,724,284 post quality-control autosomal SNPs. No associations achieved genome-wide significance, commonly accepted as P<5x10-8. Nevertheless, genes/pathways in common with other ethnicities were identified despite the arrival of Aboriginal people in Australia >45,000 years ago. The top hit (rs10868204 Pgenotyped = 1.50x10-6; rs11140653 Pimputed_1000G = 2.90x10-7) for BMI lies 5' of NTRK2, the type 2 neurotrophic tyrosine kinase receptor for brain-derived neurotrophic factor (BDNF) that regulates energy balance downstream of melanocortin-4 receptor (MC4R). PIK3C2G (rs12816270 Pgenotyped = 8.06x10-6; rs10841048 Pimputed_1000G = 6.28x10-7) was associated with BMI, but not with T2D as reported elsewhere. BMI also associated with CNTNAP2 (rs6960319 Pgenotyped = 4.65x10-5; rs13225016 Pimputed_1000G = 6.57x10-5), previously identified as the strongest gene-by-environment interaction for BMI in African-Americans. The top hit (rs11240074 Pgenotyped = 5.59x10-6, Pimputed_1000G = 5.73x10-6) for T2D lies 5' of BCL9 that, along with TCF7L2, promotes beta-catenin's transcriptional activity in the WNT signaling pathway. Additional hits occurred in genes affecting pancreatic (KCNJ6, KCNA1) and/or GABA (GABRR1, KCNA1) functions. Notable associations observed for genes previously identified at genome-wide significance in other populations included MC4R (Pgenotyped = 4.49x10-4) for BMI and IGF2BP2 Pimputed_1000G = 2.55x10-6) for T2D. Our results may provide novel functional leads in understanding disease pathogenesis in this Australian Aboriginal population.
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Affiliation(s)
- Denise Anderson
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
| | - Heather J. Cordell
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, NE1 3BZ, United Kingdom
| | - Michaela Fakiola
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
- Cambridge Institute for Medical Research, Department of Medicine, and Department of Pathology, University of Cambridge, Cambridge, United Kingdom
| | - Richard W. Francis
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
| | - Genevieve Syn
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
| | - Elizabeth S. H. Scaman
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
| | - Elizabeth Davis
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
- Department of Endocrinology and Diabetes, Princess Margaret Hospital for Children, Subiaco, Western Australia, 6008, Australia
| | - Simon J. Miles
- Ngangganawili Aboriginal Health Service, Wiluna, Western Australia, 6646, Australia
| | - Toby McLeay
- Ngangganawili Aboriginal Health Service, Wiluna, Western Australia, 6646, Australia
| | - Sarra E. Jamieson
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
| | - Jenefer M. Blackwell
- Telethon Kids Institute, The University of Western Australia, Subiaco, Western Australia, 6008, Australia
- Cambridge Institute for Medical Research, Department of Medicine, and Department of Pathology, University of Cambridge, Cambridge, United Kingdom
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Wehby GL, Domingue BW, Boardman JD. Prevention, Use of Health Services, and Genes: Implications of Genetics for Policy Formation. JOURNAL OF POLICY ANALYSIS AND MANAGEMENT : [THE JOURNAL OF THE ASSOCIATION FOR PUBLIC POLICY ANALYSIS AND MANAGEMENT] 2015; 34:519-536. [PMID: 26106669 PMCID: PMC5844353 DOI: 10.1002/pam.21835] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/31/2023]
Abstract
We evaluate the hypothesis that genetic factors influence the use of health services and prevention behaviors in a national sample of adult twins in the United States. The analysis compares the correlation of these outcomes between identical twins, who share all their genes, to the correlation between nonidentical twins, who share, on average, only one-half of their genes. Because the environmental similarities of twins are assumed to be the same for identical and nonidentical twin pairs, researchers can partition the variance in behavioral outcomes that are due to genetic and environmental factors. Using established methods in this field, we find evidence of significant genetic influences on preferences toward prevention, overall prevention effort, routine checkups, and prescription drug use. Use of curative services does not appear to be influenced by genes. Our findings offer several implications for policymakers and researchers and suggest that genetics could be informative for health services and policy research.
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Affiliation(s)
- George L Wehby
- National Bureau of Economic Research, and Departments of Health Management and Policy, Economics, Preventive & Community Dentistry, and the Public Policy center at the University of Iowa, Iowa City, IA 52242.
| | - Benjamin W Domingue
- Institute of Behavioral Science at the University of Colorad, Boulder, CO 80302.
| | - Jason D Boardman
- Department of Sociology & the Institute of Behavioral Science at the University of Colorado, Boulder, CO 80302.
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Domonkos Tarnoki A, Laszlo Tarnoki D, Molnar AA. Past, present and future of cardiovascular twin studies. COR ET VASA 2014. [DOI: 10.1016/j.crvasa.2014.07.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Sutton G, Minguet J, Ferrero C, Bramlage P. U300, a novel long-acting insulin formulation. Expert Opin Biol Ther 2014; 14:1849-60. [PMID: 25311556 DOI: 10.1517/14712598.2014.970633] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
INTRODUCTION Insulin glargine (100 U/ml; U100) was the first long-acting basal insulin analog to be introduced into clinical practice and it remains the most widely used. Although U100 is an effective and safe treatment, research is ongoing to optimize the time-action profile. The focus of this review is insulin glargine [rDNA origin] injection 300 U/ml (U300), a novel formulation that contains a higher concentration of insulin than U100. AREAS COVERED The clinical efficacy and safety of U300 in patients with type 1 and type 2 diabetes mellitus are discussed, with an emphasis on recently released data from the Phase III EDITION clinical trials. EXPERT OPINION The higher concentration of insulin in U300 results in a distinct pharmacokinetic and pharmacodynamic profile. U300 has a longer duration of action than U100 and plasma insulin exposure is less variable. Both insulin formulations exhibit a similar efficacy and safety profile, but importantly, U300 is associated with less body weight gain and a lower incidence of hypoglycaemic events.
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Affiliation(s)
- Gemma Sutton
- Institute for Research and Medicine Advancement (IRMEDICA) , Barcelona , Spain
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Grarup N, Sandholt CH, Hansen T, Pedersen O. Genetic susceptibility to type 2 diabetes and obesity: from genome-wide association studies to rare variants and beyond. Diabetologia 2014; 57:1528-41. [PMID: 24859358 DOI: 10.1007/s00125-014-3270-4] [Citation(s) in RCA: 134] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2013] [Accepted: 04/22/2014] [Indexed: 12/29/2022]
Abstract
During the past 7 years, genome-wide association studies have shed light on the contribution of common genomic variants to the genetic architecture of type 2 diabetes, obesity and related intermediate phenotypes. The discoveries have firmly established more than 175 genomic loci associated with these phenotypes. Despite the tight correlation between type 2 diabetes and obesity, these conditions do not appear to share a common genetic background, since they have few genetic risk loci in common. The recent genetic discoveries do however highlight specific details of the interplay between the pathogenesis of type 2 diabetes, insulin resistance and obesity. The focus is currently shifting towards investigations of data from targeted array-based genotyping and exome and genome sequencing to study the individual and combined effect of low-frequency and rare variants in metabolic disease. Here we review recent progress as regards the concepts, methodologies and derived outcomes of studies of the genetics of type 2 diabetes and obesity, and discuss avenues to be investigated in the future within this research field.
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Affiliation(s)
- Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, DIKU Building, Universitetsparken 1, 2100, Copenhagen Ø, Denmark,
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Li A, Meyre D. Jumping on the Train of Personalized Medicine: A Primer for Non-Geneticist Clinicians: Part 2. Fundamental Concepts in Genetic Epidemiology. ACTA ACUST UNITED AC 2014; 10:101-117. [PMID: 25598767 PMCID: PMC4287874 DOI: 10.2174/1573400510666140319235334] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2013] [Revised: 02/07/2014] [Accepted: 04/18/2014] [Indexed: 12/12/2022]
Abstract
With the decrease in sequencing costs, personalized genome sequencing will eventually become common in medical practice. We therefore write this series of three reviews to help non-geneticist clinicians to jump into the fast-moving field of personalized medicine. In the first article of this series, we reviewed the fundamental concepts in molecular genetics. In this second article, we cover the key concepts and methods in genetic epidemiology including the classification of genetic disorders, study designs and their implementation, genetic marker selection, genotyping and sequencing technologies, gene identification strategies, data analyses and data interpretation. This review will help the reader critically appraise a genetic association study. In the next article, we will discuss the clinical applications of genetic epidemiology in the personalized medicine area.
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Affiliation(s)
- Aihua Li
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON L8N 3Z5, Canada
| | - David Meyre
- Department of Clinical Epidemiology and Biostatistics, McMaster University, Hamilton, ON L8N 3Z5, Canada
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Aaltonen S, Kujala UM, Kaprio J. Factors behind leisure-time physical activity behavior based on Finnish twin studies: the role of genetic and environmental influences and the role of motives. BIOMED RESEARCH INTERNATIONAL 2014; 2014:931820. [PMID: 24809061 PMCID: PMC3997869 DOI: 10.1155/2014/931820] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/29/2013] [Revised: 02/18/2014] [Accepted: 03/06/2014] [Indexed: 01/01/2023]
Abstract
Different approaches are being taken to clarify the role of various factors in the development of physical activity behaviors. Genetic studies are a new area of physical activity research and also the motives for physical activity have been widely studied. The purpose of this paper is to review the findings emerging from the longitudinal genetic studies on leisure-time physical activity and to evaluate the associations between motivational factors and leisure-time physical activity. The focus is to review recent findings of longitudinal Finnish twin studies. The results of the latest longitudinal Finnish twin studies point to the existence of age-specific genetic and environmental influences on leisure-time physical activity. Variations in environmental factors seem to explain the observed deterioration in leisure-time physical activity levels. A decline in genetic influences is seen first from adolescence to young adulthood and again from the age of thirty to the mid-thirties. In the Finnish twin participants, mastery, physical fitness, and psychological state were the major motivation factors associated with consistent leisure-time physical activity behavior. The results also indicate that intrinsic motivation factors may be important for engagement in leisure-time physical activity.
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Affiliation(s)
- Sari Aaltonen
- Department of Public Health, The Hjelt Institute, University of Helsinki, P.O. Box 41, Mannerheimintie 172, 00014 Helsinki, Finland
- Department of Health Sciences, University of Jyväskylä P.O. Box 35, 40014 Jyväskylä, Finland
| | - Urho M. Kujala
- Department of Health Sciences, University of Jyväskylä P.O. Box 35, 40014 Jyväskylä, Finland
| | - Jaakko Kaprio
- Department of Public Health, The Hjelt Institute, University of Helsinki, P.O. Box 41, Mannerheimintie 172, 00014 Helsinki, Finland
- Institute for Molecular Medicine, University of Helsinki, P.O. Box 21, Tukholmankatu 8, 00014 Helsinki, Finland
- Department of Mental Health and Substance Abuse Services, National Institute for Health and Welfare, P.O. Box 30, 00271 Helsinki, Finland
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Abdullah N, Attia J, Oldmeadow C, Scott RJ, Holliday EG. The architecture of risk for type 2 diabetes: understanding Asia in the context of global findings. Int J Endocrinol 2014; 2014:593982. [PMID: 24744783 PMCID: PMC3976842 DOI: 10.1155/2014/593982] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2013] [Accepted: 01/30/2014] [Indexed: 02/07/2023] Open
Abstract
The prevalence of Type 2 diabetes is rising rapidly in both developed and developing countries. Asia is developing as the epicentre of the escalating pandemic, reflecting rapid transitions in demography, migration, diet, and lifestyle patterns. The effective management of Type 2 diabetes in Asia may be complicated by differences in prevalence, risk factor profiles, genetic risk allele frequencies, and gene-environment interactions between different Asian countries, and between Asian and other continental populations. To reduce the worldwide burden of T2D, it will be important to understand the architecture of T2D susceptibility both within and between populations. This review will provide an overview of known genetic and nongenetic risk factors for T2D, placing the results from Asian studies in the context of broader global research. Given recent evidence from large-scale genetic studies of T2D, we place special emphasis on emerging knowledge about the genetic architecture of T2D and the potential contribution of genetic effects to population differences in risk.
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Affiliation(s)
- Noraidatulakma Abdullah
- School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, Newcastle, NSW 2308, Australia
- UKM Medical Molecular Biology Institute (UMBI), Universiti Kebangsaan Malaysia, Kuala Lumpur, Malaysia
| | - John Attia
- Clinical Research Design, IT and Statistical Support (CReDITSS) Unit, Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health, University of Newcastle, Newcastle, NSW 2305, Australia
| | - Christopher Oldmeadow
- Clinical Research Design, IT and Statistical Support (CReDITSS) Unit, Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health, University of Newcastle, Newcastle, NSW 2305, Australia
| | - Rodney J. Scott
- School of Biomedical Sciences and Pharmacy, Faculty of Health, University of Newcastle, Newcastle, NSW 2308, Australia
- Hunter Area Pathology Service, John Hunter Hospital, Newcastle, NSW 2305, Australia
| | - Elizabeth G. Holliday
- Clinical Research Design, IT and Statistical Support (CReDITSS) Unit, Hunter Medical Research Institute, Newcastle, NSW 2305, Australia
- Centre for Clinical Epidemiology and Biostatistics, School of Medicine and Public Health, Faculty of Health, University of Newcastle, Newcastle, NSW 2305, Australia
- *Elizabeth G. Holliday:
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