1
|
Wagh R, Hatem G, Andersson J, Kunte P, Bandyopadhyay S, Yajnik CS, Prasad RB. Parent-of-origin effects in the life-course evolution of cardiometabolic traits. Diabetologia 2025; 68:1298-1314. [PMID: 40175764 PMCID: PMC12069499 DOI: 10.1007/s00125-025-06396-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2024] [Accepted: 01/22/2025] [Indexed: 04/04/2025]
Abstract
AIMS/HYPOTHESIS Cardiometabolic traits are heritable, and some display parent-of-origin effects, which indicates preferential inheritance from one parent or parental bias. Most studies of these phenomena have focused on adult populations. We aimed to investigate the heritability and parent-of-origin effects on cardiometabolic traits in a birth cohort with serial measurements to determine whether these patterns emerged early in life. METHODS The Pune Maternal Nutrition Study comprises a birth cohort in which offspring and parents were studied from birth and followed up for 24 years. We investigated parent-of-origin effects on cardiometabolic traits cross-sectionally at available timepoints using linear regression, and longitudinally across the life course using mixed-effect regression. Maternal and paternal effects on offspring phenotype were modelled after adjusting for age, sex and BMI. Parent-of-origin effects were calculated based on the difference between maternal and paternal effects. We also investigated these effects in another birth cohort, that of the Pune Children's Study. Genetic parent-of-origin effects were assessed using generalised estimating equations after taking the parental origin of the alleles into account. RESULTS Birthweight showed a maternal parent-of-origin effect. At 24 years, maternal bias was seen for some obesity-related traits for daughters, while paternal bias was seen for WHR in sons. A shift from paternal bias at 6 years to maternal bias at 24 years for the skinfold thickness was observed in daughters. Fasting glucose and lipids showed maternal bias at 6, 12 and 24 years. For fasting insulin and HOMA2-S, a negative maternal effect at 6 years transitioned to a positive one at 12 years. For HOMA2-B, a paternal effect at 6 years transitioned to a maternal one at 12 years, and this remained so at 24 years. Some of these findings were also observed in the cohort from the Pune Children's Study. Longitudinal modelling revealed stronger paternal effects over time for fasting insulin and HOMA indices but maternal effects for glucose and lipids, reflecting their cumulative effect over time. Genetic variants at the KCNQ1 locus showed a maternal parent-of-origin effect on birthweight, on HOMA2-B at 12 years, and on lipids at 6 and 12 years. CONCLUSIONS/INTERPRETATION Our study provides proof of concept of the existence of parent-of-origin effects on cardiometabolic traits from birth, through childhood and puberty, until adult age. Our results indicate a predominantly maternal influence on intrauterine, pubertal and reproductive-age metabolism in the offspring. While the longitudinal analysis indicated a maternal bias for the macronutrients (glucose and lipids), and a paternal bias for glucose-insulin metabolism, the cross-sectional analysis revealed a transition between parental influence across physiological stages. This dynamic relationship may have its origins in the life-history theory of evolution, and could inform strategies for primordial prevention aimed at curbing the rising burden of cardiometabolic disease. Further studies are needed to determine the mechanisms underlying such effects.
Collapse
Affiliation(s)
- Rucha Wagh
- Diabetes Unit, Kamalnayan Bajaj Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, India
- Symbiosis School of Biological Sciences, Symbiosis International (Deemed University), Pune, India
| | - Gad Hatem
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden
| | - Jonas Andersson
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden
| | - Pooja Kunte
- Diabetes Unit, Kamalnayan Bajaj Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, India
| | | | - Chittaranjan S Yajnik
- Diabetes Unit, Kamalnayan Bajaj Diabetology Research Centre, King Edward Memorial Hospital and Research Centre, Pune, India
| | - Rashmi B Prasad
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden.
- Institute of Molecular Medicine Finland, Helsinki University, Helsinki, Finland.
| |
Collapse
|
2
|
Noroozzadeh M, Mousavi M, Naz MSG, Farahmand M, Azizi F, Ramezani Tehrani F. Early menopause in mothers and the risks of pre-diabetes and type 2 diabetes mellitus in female and male offspring: a population-based cohort study. Reprod Biol Endocrinol 2025; 23:76. [PMID: 40405295 PMCID: PMC12096570 DOI: 10.1186/s12958-025-01405-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/01/2025] [Accepted: 04/26/2025] [Indexed: 05/24/2025] Open
Abstract
BACKGROUND Genetic factors and an unfavorable intrauterine environment may contribute to the development of metabolic disorders in offspring later in life. The present study aims to investigate and compare the risks of pre-diabetes mellitus (pre-DM), type 2 diabetes mellitus (T2DM) and abnormal glucose tolerance in female and male offspring with early maternal menopausal age versus those with normal maternal menopausal age, later in life. METHODS In this prospective population-based study, there were 1,516 females and 1,563 males with normal maternal menopausal age, as well as 213 females and 237 males with early maternal menopausal age. Unadjusted and adjusted cox regression models were used to assess the hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between early maternal menopausal age with pre-DM, T2DM and abnormal glucose tolerance in offspring. Statistical analysis was performed using the STATA software package; the significance level was set at P < 0.05. RESULTS The present study revealed a higher risk of pre-DM in female offspring with early maternal menopausal age compared to females with normal maternal menopausal age (unadjusted HR (95% CI): 1.42 (0.98, 2.05); P = 0.06 (marginal significant) and adjusted HR (95% CI): 1.47 (1.00, 2.16); P = 0.04). Additionally, a higher risk of abnormal glucose tolerance among female offspring with early maternal menopausal age in adjusted model was observed (HR (95% CI): 1.13 (0.99-1.29); P = 0.06, marginal significant). However, no significant differences were observed in the risks of developing pre-DM and abnormal glucose tolerance in male offspring with early maternal menopausal age compared to males with normal maternal menopausal age in both unadjusted and adjusted models. No significant difference was observed in the risk of T2DM in the offspring with early maternal menopausal age compared to offspring with normal maternal menopausal age. CONCLUSIONS This pioneering study, characterized by a long-term follow-up, demonstrated that early maternal menopausal age is associated with an increased risk of developing pre-DM in female offspring later in life. It may be advisable to implement screening for pre-DM and glucose metabolism disorders in these female offspring. CLINICAL TRIAL NUMBER Not applicable.
Collapse
Affiliation(s)
- Mahsa Noroozzadeh
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Molecular Biology, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, 23 Arabi Ave, Yaman Street, Velenjak, Tehran, 1985717413, Iran
| | - Maryam Mousavi
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Molecular Biology, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, 23 Arabi Ave, Yaman Street, Velenjak, Tehran, 1985717413, Iran
| | - Marzieh Saei Ghare Naz
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Molecular Biology, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, 23 Arabi Ave, Yaman Street, Velenjak, Tehran, 1985717413, Iran
| | - Maryam Farahmand
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Molecular Biology, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, 23 Arabi Ave, Yaman Street, Velenjak, Tehran, 1985717413, Iran
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Disorders, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fahimeh Ramezani Tehrani
- Reproductive Endocrinology Research Center, Research Institute for Endocrine Molecular Biology, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, 23 Arabi Ave, Yaman Street, Velenjak, Tehran, 1985717413, Iran.
- Foundation for Research & Education Excellence, Vestavia Hills, AL, USA.
| |
Collapse
|
3
|
Iwata M, Okazawa T, Higuchi K, Tobe K. Association between the type of family history of diabetes and the risk and age at onset of diabetes in the Japanese general population. Diabetol Int 2025; 16:316-325. [PMID: 40166441 PMCID: PMC11954760 DOI: 10.1007/s13340-025-00792-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2024] [Accepted: 01/08/2025] [Indexed: 04/02/2025]
Abstract
Aim The objective of this cross-sectional study was to clarify the relationship between the type of first-degree family history of diabetes (FHD) and the presence and age at onset of diabetes (AOD) in the Japanese general population. Material and methods Using anonymized processed data collected from community-based health checkups, we classified 10,691 subjects into 5 groups according to the type of FHD as follows: (1) no FHD; (2) diabetes only in a sibling (sFHD); (3) diabetes only in the mother (mFHD); (4) diabetes only in the father (pFHD); and (5) diabetes in ≥ 2 family members, e.g., one parent plus a sibling or both parents (FHD in ≥ 2 family members). Result Results of multivariate logistic regression analysis performed using the no FHD group as reference revealed a significant association between a positive FHD and the presence of diabetes (odds ratio: sFHD, 3.67; mFHD, 3.70; pFHD, 2.88; FHD in ≥ 2 family members, 6.35; P < 0.0001 for all). Moreover, the AOD was significantly younger in all the four groups with FHD than in the group without FHD (P < 0.01), being the youngest in the group of FHD in ≥ 2 family members. Conclusion Our results revealed that the degree of associations between a positive FHD and the presence of diabetes and AOD differ according to the type of FHD. In particular, FHD in ≥ 2 family members appears to be especially strongly associated with a high risk of diabetes and a younger AOD.
Collapse
Affiliation(s)
- Minoru Iwata
- Second Department of Human Science, Faculty of Medicine, University of Toyama, 2630 Sugitani, Toyama, Toyama 930-0194 Japan
- First Department of Internal Medicine, Faculty of Medicine, University of Toyama, Toyama, Toyama Japan
| | - Teruyo Okazawa
- Department of Internal Medicine, Sakurai Hospital, Kurobe, Toyama Japan
| | - Kiyohiro Higuchi
- Department of Internal Medicine, JA Niigata Kouseiren Itoigawa General Hospital, Itoigawa, Niigata Japan
| | - Kazuyuki Tobe
- First Department of Internal Medicine, Faculty of Medicine, University of Toyama, Toyama, Toyama Japan
- Research Center for Pre-Disease Science, University of Toyama, Toyama, Toyama Japan
| |
Collapse
|
4
|
Smith KR, Meeks H, Curtis D, Brown BB, Kole K, Kowaleski‐Jones L. Family history of type 2 diabetes and the risk of type 2 diabetes among young and middle-aged adults. Chronic Dis Transl Med 2025; 11:46-56. [PMID: 40051822 PMCID: PMC11880113 DOI: 10.1002/cdt3.147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 06/18/2024] [Accepted: 07/10/2024] [Indexed: 03/09/2025] Open
Abstract
Background The prevalence of type 2 diabetes has been growing among younger and middle-aged adults in the United States. A portion of this increase for this age group may be attributable to shared type 2 diabetes risks with family members. How family history of type 2 diabetes history is associated with type 2 diabetes risk among younger and middle-aged adults is not well understood. Methods This population-based retrospective cohort study uses administrative, genealogical, and electronic medical records from the Utah Population Database. The study population comprises offspring born between 1970 and 1990 and living in the four urban Utah counties in the United States between 1990 and 2015. The sample comprises 360,907 individuals without a type 2 diabetes diagnosis and 14,817 with a diagnosis. Using multivariate logistic regressions, we estimate the relative risk (RR) of type 2 diabetes associated with the number of affected first- (FDRs), second- (SDRs), and third-degree (first cousin) relatives for the full sample and for Hispanic-specific and sex-specific subsets. Results Individuals with 2+ FDRs with type 2 diabetes have a significant risk of type 2 diabetes in relation to those with no affected FDRs (RR = 3.31 [3.16, 3.48]). Individuals with 2+ versus no SDRs with type 2 diabetes have significant but lower risks (RR = 1.32 [1.25, 1.39]). Those with 2+ versus no affected first cousins have a similarly low risk (RR = 1.28 [1.21, 1.35]). Larger RRs are experienced by males (2+ vs. 0 FDRs, RR = 3.55) than females (2+ vs. 0 FDRs, RR = 3.18) (p < 0.05 for the interaction). These familial associations are partly mediated by the individual's own obesity. Conclusions The risks of type 2 diabetes are significantly associated with having affected first-, second-, and third-degree relatives, especially for men. One of the forces contributing to the rising patterns of type 2 diabetes among young and middle-aged adults is their connection to affected, often older, kin.
Collapse
Affiliation(s)
- Ken R. Smith
- Department of Family and Consumer StudiesUniversity of UtahSalt Lake CityUtahUSA
| | - Huong Meeks
- Department of PediatricsUniversity of UtahSalt Lake CityUtahUSA
| | - David Curtis
- Department of Family and Consumer StudiesUniversity of UtahSalt Lake CityUtahUSA
| | - Barbara B. Brown
- Department of Family and Consumer StudiesUniversity of UtahSalt Lake CityUtahUSA
| | - Kyle Kole
- Department of Family and Consumer StudiesUniversity of UtahSalt Lake CityUtahUSA
| | - Lori Kowaleski‐Jones
- Department of Family and Consumer StudiesUniversity of UtahSalt Lake CityUtahUSA
| |
Collapse
|
5
|
Herrerías-García A, Jacobo-Tovar E, Hernández-Robles CM, Guardado-Mendoza R. Pancreatic beta cell function and insulin resistance profiles in first-degree relatives of patients with prediabetes and type 2 diabetes. Acta Diabetol 2025; 62:253-261. [PMID: 39150512 DOI: 10.1007/s00592-024-02352-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Accepted: 07/30/2024] [Indexed: 08/17/2024]
Abstract
AIMS To evaluate insulin secretion and insulin resistance profiles in individuals with family history of prediabetes and type 2 diabetes. METHODS This was a cross-sectional study to evaluate clinical and metabolic profiles between individuals with type 2 diabetes, prediabetes and their relatives. There were 911 subjects divided into five groups: (i) normoglycemic (NG), (ii) type 2 diabetes, (iii) prediabetes, (iv) first-degree relatives of patients with type 2 diabetes (famT2D), and (v) first-degree relatives of patients with prediabetes (famPD); anthropometrical, biochemical and nutritional evaluation, as well as insulin resistance and pancreatic beta cell function measurement was performed by oral glucose tolerance to compare between groups. RESULTS The most prevalent type 2 diabetes risk factors were dyslipidemia (81%), family history of type 2 diabetes (76%), central obesity (73%), male sex (63%), and sedentary lifestyle (60%), and most of them were progressively associated to prediabetes and type 2 diabetes groups. Insulin sensitivity was lower in famT2D groups in comparison to NG group (p < 0.0001). FamPD and famT2D had a 10% lower pancreatic beta cell function (DI) than the NG group (NG group 2.78 ± 1.0, famPD 2.5 ± 0.85, famT2D 2.4 ± 0.75, p˂0.001). CONCLUSIONS FamPD and famT2D patients had lower pancreatic beta cell function than NG patients, highlighting that defects in insulin secretion and insulin sensitivity appear long time before the development of hyperglycemia in patients genetically predisposed.
Collapse
Affiliation(s)
- Anaid Herrerías-García
- Metabolic Research Laboratory, Department of Medicine and Nutrition, University of Guanajuato, Blvd. Milenio 1001, Predio San Carlos, 37670, León, Guanajuato, Mexico
| | - Emmanuel Jacobo-Tovar
- Metabolic Research Laboratory, Department of Medicine and Nutrition, University of Guanajuato, Blvd. Milenio 1001, Predio San Carlos, 37670, León, Guanajuato, Mexico
| | - Claudia Mariana Hernández-Robles
- Metabolic Research Laboratory, Department of Medicine and Nutrition, University of Guanajuato, Blvd. Milenio 1001, Predio San Carlos, 37670, León, Guanajuato, Mexico
| | - Rodolfo Guardado-Mendoza
- Metabolic Research Laboratory, Department of Medicine and Nutrition, University of Guanajuato, Blvd. Milenio 1001, Predio San Carlos, 37670, León, Guanajuato, Mexico.
| |
Collapse
|
6
|
Jin Z, Rothwell J, Lim KK. Screening for Type 2 Diabetes Mellitus: A Systematic Review of Recent Economic Evaluations. VALUE IN HEALTH : THE JOURNAL OF THE INTERNATIONAL SOCIETY FOR PHARMACOECONOMICS AND OUTCOMES RESEARCH 2025:S1098-3015(25)00019-1. [PMID: 39880196 DOI: 10.1016/j.jval.2025.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/19/2024] [Revised: 01/05/2025] [Accepted: 01/08/2025] [Indexed: 01/31/2025]
Abstract
OBJECTIVES To examine recent economic evaluations and understand whether any type 2 diabetes mellitus (T2DM) screening designs may represent better value for money and to rate their methodological qualities. METHODS We systematically searched 3 concepts (economic evaluations [EEs], T2DM, screening) in 5 databases (Medline, Embase, EconLit, Web of Science, and Cochrane) for EEs published between 2010 and 2023. Two independent reviewers screened for and rated their methodological quality (using the Consensus on Health Economics Criteria Checklist-Extended). RESULTS Of 32 EEs, a majority were from high-income countries (69%). Half used single biomarkers (50%) to screen adults ≥30 to <60 years old (60%) but did not report locations (69%), treatments for those diagnosed (66%), diagnostic methods (57%), or screening intervals (54%). Compared with no screening, T2DM screening using single biomarkers was found to be not cost-effective (23/54 comparisons), inconclusive (16/54), dominant (11/54), or cost-effective (4/54). Compared with no screening, screening with a risk score and single biomarkers was found to be cost-effective (21/40) or dominant (19/40). The risk score alone was mostly dominant (6/10). Compared with universal screening, targeted screening among obese, overweight, or older people may be cost-effective or dominant. Compared with fasting plasma glucose or fasting capillary glucose, screening using risk scores was found to be mostly dominant or cost-effective. Expanding screening locations or lowering HbA1c or fasting plasma glucose thresholds was found to be dominant or cost-effective. Each EE had 4 to 17 items (median 13/20) on Consensus on Health Economics Criteria Checklist-Extended rated "Yes/Rather Yes." CONCLUSIONS EE findings varied based on screening tools, intervals, locations, minimum screening age, diagnostic methods, and treatment. Future EEs should more comprehensively report screening designs and evaluate T2DM screening in low-income countries.
Collapse
Affiliation(s)
- Zixuan Jin
- School of Life Course & Population Sciences, Faculty of Life Sciences and Medicine/MPH Graduate, King's College London, London, England, UK
| | - Joshua Rothwell
- GKT School of Medical Education, Faculty of Life Sciences & Medicine/MBBS Student, King's College London, London, England, UK; Department of Radiology, School of Clinical Medicine/PhD Student, University of Cambridge, Cambridge, England, UK
| | - Ka Keat Lim
- Health Economics and Policy Research Unit, Wolfson Institute of Population Health/Lecturer in Health Economics, Queen Mary University of London, London, England, UK; School of Life Course & Population Sciences, Faculty of Life Sciences and Medicine/Visiting Lecturer, King's College London, London, England, UK.
| |
Collapse
|
7
|
Ukai T, Tabuchi T, Iso H. The association between an individual's development of non-communicable diseases and their spouse's development of the same disease: the Longitudinal Survey of Middle-aged and Elderly Persons. Environ Health Prev Med 2025; 30:23. [PMID: 40159246 PMCID: PMC11955831 DOI: 10.1265/ehpm.24-00294] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2024] [Accepted: 01/13/2025] [Indexed: 04/02/2025] Open
Abstract
BACKGROUND Studies have shown that married couples often share similar lifestyles, as well as lifestyle-associated conditions such as diabetes, hypertension, and hyperlipidemia. This study aims to prospectively investigate the association between an individual's development of a non-communicable disease and the subsequent development of the same condition in their spouse. METHODS This population-based cohort study utilized 12 waves of annual prospective surveys from 2005 onwards in Japan, with a discrete-time design. A total of 9,417 middle-aged couples (18,834 participants; discrete-time observations = 118,876) were included. Each participant whose spouse had developed one of six conditions was propensity score-matched with five controls whose spouses had not been diagnosed with the condition: diabetes [n = 1374 vs n = 6870], hypertension [n = 2657 vs n = 13285], hypercholesterolemia [n = 3321 vs n = 16605], stroke [n = 567 vs n = 2835], coronary heart disease (CHD) [n = 1093 vs n = 5465] or cancer [n = 923 vs n = 4615]. Using conditional logistic regression, we assessed participants' development of the same condition within three years following their spouse's diagnosis. RESULTS Participants whose spouses had developed diabetes, hypertension, hypercholesterolemia, or CHD were more likely to develop the same condition within three years. The odds ratios (ORs) and 95% confidence intervals (CIs) were: 1.96 (1.53-2.50), 1.20 (1.06-1.36), 1.63 (1.47-1.81) and 1.43 (1.05-1.95), respectively. No significant associations were observed in stroke [1.69 (0.80-3.58)] or cancer [1.08 (0.75-1.54)]. CONCLUSION Spouses of individuals recently diagnosed with certain metabolic conditions are at a higher risk of developing those conditions themselves. These findings may provide valuable guidance for targeting and personalizing chronic disease screening and prevention efforts.
Collapse
Affiliation(s)
- Tomohiko Ukai
- Department of Epidemiology and Clinical Research, The Research Institute of Tuberculosis, 3-1-24 Matsuyama, Kiyose, Tokyo 204-8533, Japan
| | - Takahiro Tabuchi
- Division of Epidemiology, School of Public Health, Tohoku University Graduate School of Medicine, 2-1 Seiryo-machi, Aoba-ku, Sendai, Miyagi 980-8575, Japan
- Cancer Control Center, Osaka International Cancer Institute, 3-1-69 Otemae, Chuo-ku, Osaka 541-8567, Japan
| | - Hiroyasu Iso
- Institute for Global Health Policy Research, National Center for Global Health and Medicine, 1-21-1 Toyama Shinjuku-ku, Tokyo 162-8655, Japan
| |
Collapse
|
8
|
Imamura M, Maeda S. Genetic studies of type 2 diabetes, and microvascular complications of diabetes. Diabetol Int 2024; 15:699-706. [PMID: 39469559 PMCID: PMC11512959 DOI: 10.1007/s13340-024-00727-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 04/24/2024] [Indexed: 10/30/2024]
Abstract
Genome-wide association studies (GWAS) have significantly advanced the identification of genetic susceptibility variants associated with complex diseases. As of 2023, approximately 800 variants predisposing individuals to the risk of type 2 diabetes (T2D) were identified through GWAS, and the majority of studies were predominantly conducted in European populations. Despite the shared nature of the majority of genetic susceptibility loci across diverse ethnic populations, GWAS in non-European populations, including Japanese and East Asian populations, have revealed population-specific T2D loci. Currently, polygenic risk scores (PRSs), encompassing millions of associated variants, can identify individuals with a higher T2D risk than the general population. However, GWAS focusing on microvascular complications of diabetes have identified a limited number of disease-susceptibility loci. Ongoing efforts are crucial to enhance the applicability of PRS for all ethnic groups and unravel the genetic architecture of microvascular complications of diabetes.
Collapse
Affiliation(s)
- Minako Imamura
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Okinawa 903-0215 Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Nishihara-Cho, Okinawa 930-0215 Japan
| | - Shiro Maeda
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of Medicine, University of the Ryukyus, Nishihara-Cho, Okinawa 903-0215 Japan
- Division of Clinical Laboratory and Blood Transfusion, University of the Ryukyus Hospital, Nishihara-Cho, Okinawa 930-0215 Japan
| |
Collapse
|
9
|
Wimberley T, Brikell I, Astrup A, Larsen JT, Petersen LV, Albiñana C, Vilhjálmsson BJ, Bulik CM, Chang Z, Fanelli G, Bralten J, Mota NR, Salas-Salvadó J, Fernandez-Aranda F, Bulló M, Franke B, Børglum A, Mortensen PB, Horsdal HT, Dalsgaard S. Shared familial risk for type 2 diabetes mellitus and psychiatric disorders: a nationwide multigenerational genetics study. Psychol Med 2024; 54:2976-2985. [PMID: 38801094 DOI: 10.1017/s0033291724001053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 05/29/2024]
Abstract
BACKGROUND Psychiatric disorders and type 2 diabetes mellitus (T2DM) are heritable, polygenic, and often comorbid conditions, yet knowledge about their potential shared familial risk is lacking. We used family designs and T2DM polygenic risk score (T2DM-PRS) to investigate the genetic associations between psychiatric disorders and T2DM. METHODS We linked 659 906 individuals born in Denmark 1990-2000 to their parents, grandparents, and aunts/uncles using population-based registers. We compared rates of T2DM in relatives of children with and without a diagnosis of any or one of 11 specific psychiatric disorders, including neuropsychiatric and neurodevelopmental disorders, using Cox regression. In a genotyped sample (iPSYCH2015) of individuals born 1981-2008 (n = 134 403), we used logistic regression to estimate associations between a T2DM-PRS and these psychiatric disorders. RESULTS Among 5 235 300 relative pairs, relatives of individuals with a psychiatric disorder had an increased risk for T2DM with stronger associations for closer relatives (parents:hazard ratio = 1.38, 95% confidence interval 1.35-1.42; grandparents: 1.14, 1.13-1.15; and aunts/uncles: 1.19, 1.16-1.22). In the genetic sample, one standard deviation increase in T2DM-PRS was associated with an increased risk for any psychiatric disorder (odds ratio = 1.11, 1.08-1.14). Both familial T2DM and T2DM-PRS were significantly associated with seven of 11 psychiatric disorders, most strongly with attention-deficit/hyperactivity disorder and conduct disorder, and inversely with anorexia nervosa. CONCLUSIONS Our findings of familial co-aggregation and higher T2DM polygenic liability associated with psychiatric disorders point toward shared familial risk. This suggests that part of the comorbidity is explained by shared familial risks. The underlying mechanisms still remain largely unknown and the contributions of genetics and environment need further investigation.
Collapse
Affiliation(s)
- Theresa Wimberley
- The National Centre for Register-based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Centre for Integrated Register-based Research (CIRRAU), Aarhus University, Aarhus, Denmark
| | - Isabell Brikell
- The National Centre for Register-based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
- Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Aske Astrup
- The National Centre for Register-based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
| | - Janne T Larsen
- The National Centre for Register-based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
| | - Liselotte V Petersen
- The National Centre for Register-based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
| | - Clara Albiñana
- The National Centre for Register-based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
| | - Bjarni J Vilhjálmsson
- The National Centre for Register-based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
- Bioinformatics Research Centre, Aarhus University, Aarhus, Denmark
| | - Cynthia M Bulik
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, USA
- Department of Nutrition, University of North Carolina at Chapel Hill, Chapel Hill, USA
| | - Zheng Chang
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Giuseppe Fanelli
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Biomedical and Neuromotor Sciences, University of Bologna, Bologna, Italy
| | - Janita Bralten
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Nina R Mota
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
| | - Jordi Salas-Salvadó
- Department of Biochemistry & Biotechnology, School of Medicine, IISPV, Rovira i Virgili University. Reus, Spain
- Institute of Health Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII). Madrid, Spain
| | - Fernando Fernandez-Aranda
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII). Madrid, Spain
- Clinical Psychology Unit, University Hospital Bellvitge, Hospitalet del Llobregat, Spain
- Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Hospitalet del Llobregat, Spain
- Psychoneurobiology of Eating and Addictive Behaviours Group, Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet del Llobregat, Spain
| | - Monica Bulló
- Department of Biochemistry & Biotechnology, School of Medicine, IISPV, Rovira i Virgili University. Reus, Spain
- Institute of Health Pere Virgili (IISPV), Reus, Spain
- Consorcio CIBER, M.P. Fisiopatología de la Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III (ISCIII). Madrid, Spain
- Center of Environmental, Food and Toxicological Technology - TecnATox, Rovira i Virgili University, 43201 Reus, Spain
| | - Barbara Franke
- Department of Human Genetics, Radboud University Medical Center, Nijmegen, The Netherlands
- Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, The Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Anders Børglum
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Department of Biomedicine, Aarhus University, Aarhus, Denmark
| | - Preben B Mortensen
- The National Centre for Register-based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Centre for Integrated Register-based Research (CIRRAU), Aarhus University, Aarhus, Denmark
| | - Henriette T Horsdal
- The National Centre for Register-based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
| | - Søren Dalsgaard
- The National Centre for Register-based Research, School of Business and Social Sciences, Aarhus University, Aarhus, Denmark
- The Lundbeck Foundation Initiative for Integrative Psychiatric Research (iPSYCH), Aarhus, Denmark
- Child and Adolescent Psychiatry Mental Health Center, Copenhagen University Hospital - Mental Health Services CPH, Copenhagen, Denmark
- Department of Clinical Medicine, Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| |
Collapse
|
10
|
Zhu M, Li Y, Wang W, Liu Y, Tong T, Liu Y. Development, validation and visualization of a web-based nomogram for predicting risk of new-onset diabetes after percutaneous coronary intervention. Sci Rep 2024; 14:13652. [PMID: 38871809 PMCID: PMC11176295 DOI: 10.1038/s41598-024-64430-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2024] [Accepted: 06/10/2024] [Indexed: 06/15/2024] Open
Abstract
Simple and practical tools for screening high-risk new-onset diabetes after percutaneous coronary intervention (PCI) (NODAP) are urgently needed to improve post-PCI prognosis. We aimed to evaluate the risk factors for NODAP and develop an online prediction tool using conventional variables based on a multicenter database. China evidence-based Chinese medicine database consisted of 249, 987 patients from 4 hospitals in mainland China. Patients ≥ 18 years with implanted coronary stents for acute coronary syndromes and did not have diabetes before PCI were enrolled in this study. According to the occurrence of new-onset diabetes mellitus after PCI, the patients were divided into NODAP and Non-NODAP. After least absolute shrinkage and selection operator regression and logistic regression, the model features were selected and then the nomogram was developed and plotted. Model performance was evaluated by the receiver operating characteristic curve, calibration curve, Hosmer-Lemeshow test and decision curve analysis. The nomogram was also externally validated at a different hospital. Subsequently, we developed an online visualization tool and a corresponding risk stratification system to predict the risk of developing NODAP after PCI based on the model. A total of 2698 patients after PCI (1255 NODAP and 1443 non-NODAP) were included in the final analysis based on the multicenter database. Five predictors were identified after screening: fasting plasma glucose, low-density lipoprotein cholesterol, hypertension, family history of diabetes and use of diuretics. And then we developed a web-based nomogram ( https://mr.cscps.com.cn/wscoringtool/index.html ) incorporating the above conventional factors for predicting patients at high risk for NODAP. The nomogram showed good discrimination, calibration and clinical utility and could accurately stratify patients into different NODAP risks. We developed a simple and practical web-based nomogram based on multicenter database to screen for NODAP risk, which can assist clinicians in accurately identifying patients at high risk of NODAP and developing post-PCI management strategies to improved patient prognosis.
Collapse
Affiliation(s)
- Mengmeng Zhu
- National Clinical Research Center for TCM Cardiology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, No.1 of Xiyuan Caochang, Haidian District, Beijing, 100091, China
- Cardiovascular Disease Group, China Center for Evidence-Based Medicine of TCM, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yiwen Li
- National Clinical Research Center for TCM Cardiology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, No.1 of Xiyuan Caochang, Haidian District, Beijing, 100091, China
- Cardiovascular Disease Group, China Center for Evidence-Based Medicine of TCM, China Academy of Chinese Medical Sciences, Beijing, China
- Beijing Key Laboratory of Traditional Chinese Medicine Basic Research on Prevention and Treatment for Major Diseases, Experimental Research Center, China Academy of Chinese Medical Sciences, Beijing, China
| | - Wenting Wang
- National Clinical Research Center for TCM Cardiology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, No.1 of Xiyuan Caochang, Haidian District, Beijing, 100091, China
- Cardiovascular Disease Group, China Center for Evidence-Based Medicine of TCM, China Academy of Chinese Medical Sciences, Beijing, China
| | - Yanfei Liu
- National Clinical Research Center for TCM Cardiology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, No.1 of Xiyuan Caochang, Haidian District, Beijing, 100091, China
- Cardiovascular Disease Group, China Center for Evidence-Based Medicine of TCM, China Academy of Chinese Medical Sciences, Beijing, China
- The Second Department of Geriatrics, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China
| | - Tiejun Tong
- Department of Mathematics, Hong Kong Baptist University, Kowloon Tong, Hong Kong, SAR, China
| | - Yue Liu
- National Clinical Research Center for TCM Cardiology, Xiyuan Hospital, China Academy of Chinese Medical Sciences, No.1 of Xiyuan Caochang, Haidian District, Beijing, 100091, China.
- Cardiovascular Disease Group, China Center for Evidence-Based Medicine of TCM, China Academy of Chinese Medical Sciences, Beijing, China.
- The Second Department of Geriatrics, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
| |
Collapse
|
11
|
Ndetei DM, Mutiso V, Musyimi C, Nyamai P, Lloyd C, Sartorius N. Association of type 2 diabetes with family history of diabetes, diabetes biomarkers, mental and physical disorders in a Kenyan setting. Sci Rep 2024; 14:11037. [PMID: 38745063 PMCID: PMC11094016 DOI: 10.1038/s41598-024-61984-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 05/13/2024] [Indexed: 05/16/2024] Open
Abstract
This study aimed to determine the degree of family relations and associated socio-demographics characteristics, clinical/physical and mental disorders in type 2 diabetes mellitus in a Kenyan diabetes clinic. This study was part of a large multicentre study whose protocol and results had been published. It took place at the outpatient diabetes clinic at a County Teaching and Referral Hospital in South East Kenya involving 182 participants. We used a socio-demographic questionnaire, the Hamilton Depression (HAM-D) and PHQ-9 rating scales for depression, the MINI International Neuropsychiatric Interview (MINI; V5 or V6) for DSM-5 diagnoses, the WHO-5 Well-being scale and Problem Areas in Diabetes Scale (PAID). We extracted from the notes all physical conditions. We enquired about similar conditions in 1st and 2nd degree relatives. Descriptive, Chi-square test, Fisher's exact test, one way ANOVA, and Multinomial logistic regression analysis were conducted to test achievements of our specific aims. Of the 182 patients who participated in the study, 45.1% (82/182) reported a family history of diabetes. Conditions significantly (p < 0.05) associated with a degree of family history of diabetes were retinopathy, duration of diabetes (years), hypertension, and depressive disorder. On average 11.5% (21/182) scored severe depression (≥ 10) on PHQ-9 and 85.2% (115/182) scored good well-being (≥ 13 points). All DSM-5 psychiatric conditions were found in the 182 patients in varying prevalence regardless of relations. In addition, amongst the 182 patients, the highest prevalence was poor well-being on the WHO quality of life tool. This was followed by post-traumatic disorders (current), suicidality, and psychotic lifetime on DSM-5. The least prevalent on DSM-5 was eating disorders. Some type 2 diabetes mellitus physical disorders and depression have increased incidence in closely related patients. Overall, for all the patients, the prevalence of all DSM-5 diagnoses varied from 0.5 to 9.9%.
Collapse
Affiliation(s)
- David M Ndetei
- Department of Psychiatry, University of Nairobi, Nairobi, Kenya.
- Africa Mental Health Research and Training Foundation, Mawensi Road, Off Elgon Road, Mawensi Garden, P.O. Box 48423-00100, Nairobi, Kenya.
- World Psychiatric Association Collaborating Centre for Research and Training, Nairobi, Kenya.
| | - Victoria Mutiso
- Africa Mental Health Research and Training Foundation, Mawensi Road, Off Elgon Road, Mawensi Garden, P.O. Box 48423-00100, Nairobi, Kenya
- World Psychiatric Association Collaborating Centre for Research and Training, Nairobi, Kenya
| | - Christine Musyimi
- Africa Mental Health Research and Training Foundation, Mawensi Road, Off Elgon Road, Mawensi Garden, P.O. Box 48423-00100, Nairobi, Kenya
- World Psychiatric Association Collaborating Centre for Research and Training, Nairobi, Kenya
| | - Pascalyne Nyamai
- Africa Mental Health Research and Training Foundation, Mawensi Road, Off Elgon Road, Mawensi Garden, P.O. Box 48423-00100, Nairobi, Kenya
- World Psychiatric Association Collaborating Centre for Research and Training, Nairobi, Kenya
| | | | - Norman Sartorius
- Association for the Improvement of Mental Health Programmes (AMH), Geneva, Switzerland
| |
Collapse
|
12
|
Imamura M, Maeda S. Perspectives on genetic studies of type 2 diabetes from the genome-wide association studies era to precision medicine. J Diabetes Investig 2024; 15:410-422. [PMID: 38259175 PMCID: PMC10981147 DOI: 10.1111/jdi.14149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2023] [Revised: 12/24/2023] [Accepted: 01/04/2024] [Indexed: 01/24/2024] Open
Abstract
Genome-wide association studies (GWAS) have facilitated a substantial and rapid increase in the number of confirmed genetic susceptibility variants for complex diseases. Approximately 700 variants predisposing individuals to the risk for type 2 diabetes have been identified through GWAS until 2023. From 2018 to 2022, hundreds of type 2 diabetes susceptibility loci with smaller effect sizes were identified through large-scale GWAS with sample sizes of 200,000 to >1 million. The clinical translation of genetic information for type 2 diabetes includes the development of novel therapeutics and risk predictions. Although drug discovery based on loci identified in GWAS remains challenging owing to the difficulty of functional annotation, global efforts have been made to identify novel biological mechanisms and therapeutic targets by applying multi-omics approaches or searching for disease-associated coding variants in isolated founder populations. Polygenic risk scores (PRSs), comprising up to millions of associated variants, can identify individuals with higher disease risk than those in the general population. In populations of European descent, PRSs constructed from base GWAS data with a sample size of approximately 450,000 have predicted the onset of diseases well. However, European GWAS-derived PRSs have limited predictive performance in non-European populations. The predictive accuracy of a PRS largely depends on the sample size of the base GWAS data. The results of GWAS meta-analyses for multi-ethnic groups as base GWAS data and cross-population polygenic prediction methodology have been applied to establish a universal PRS applicable to small isolated ethnic populations.
Collapse
Affiliation(s)
- Minako Imamura
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of MedicineUniversity of the RyukyusNishihara‐ChoJapan
- Division of Clinical Laboratory and Blood TransfusionUniversity of the Ryukyus HospitalNishihara‐ChoJapan
| | - Shiro Maeda
- Department of Advanced Genomic and Laboratory Medicine, Graduate School of MedicineUniversity of the RyukyusNishihara‐ChoJapan
- Division of Clinical Laboratory and Blood TransfusionUniversity of the Ryukyus HospitalNishihara‐ChoJapan
| |
Collapse
|
13
|
Sullivan SO', Al Hageh C, Henschel A, Chacar S, Abchee A, Zalloua P, Nader M. HDL levels modulate the impact of type 2 diabetes susceptibility alleles in older adults. Lipids Health Dis 2024; 23:56. [PMID: 38389069 PMCID: PMC10882764 DOI: 10.1186/s12944-024-02039-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2023] [Accepted: 02/02/2024] [Indexed: 02/24/2024] Open
Abstract
BACKGROUND Type 2 Diabetes (T2D) is influenced by genetic, environmental, and ageing factors. Ageing pathways exacerbate metabolic diseases. This study aimed to examine both clinical and genetic factors of T2D in older adults. METHODS A total of 2,909 genotyped patients were enrolled in this study. Genome Wide Association Study was conducted, comparing T2D patients to non-diabetic older adults aged ≥ 60, ≥ 65, or ≥ 70 years, respectively. Binomial logistic regressions were applied to examine the association between T2D and various risk factors. Stepwise logistic regression was conducted to explore the impact of low HDL (HDL < 40 mg/dl) on the relationship between the genetic variants and T2D. A further validation step using data from the UK Biobank with 53,779 subjects was performed. RESULTS The association of T2D with both low HDL and family history of T2D increased with the age of control groups. T2D susceptibility variants (rs7756992, rs4712523 and rs10946403) were associated with T2D, more significantly with increased age of the control group. These variants had stronger effects on T2D risk when combined with low HDL cholesterol levels, especially in older control groups. CONCLUSIONS The findings highlight a critical role of age, genetic predisposition, and HDL levels in T2D risk. The findings suggest that individuals over 70 years who have high HDL levels without the T2D susceptibility alleles may be at the lowest risk of developing T2D. These insights can inform tailored preventive strategies for older adults, enhancing personalized T2D risk assessments and interventions.
Collapse
Affiliation(s)
- Siobhán O ' Sullivan
- Department of Biological Sciences, College of Medicine and Health Sciences, Khalifa University, Abu Dhabi, United Arab Emirates
| | - Cynthia Al Hageh
- Department of Public Health and Epidemiology, College of Medicine and Health Sciences, Khalifa University, Abu Dhabi, United Arab Emirates
| | - Andreas Henschel
- Department of Computer Science, College of Engineering, Khalifa University, Abu Dhabi, United Arab Emirates
| | - Stephanie Chacar
- Department of Medical Sciences, College of Medicine and Health Sciences, Khalifa University, PO Box 127788, Abu Dhabi, United Arab Emirates
| | - Antoine Abchee
- Faculty of Medicine, University of Balamand, Balamand, Lebanon
| | - Pierre Zalloua
- Faculty of Medicine, University of Balamand, Balamand, Lebanon.
- Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Department of Public Health and Epidemiology, College of Medicine and Health Sciences, Khalifa University, Abu Dhabi, United Arab Emirates.
| | - Moni Nader
- Department of Medical Sciences, College of Medicine and Health Sciences, Khalifa University, PO Box 127788, Abu Dhabi, United Arab Emirates.
| |
Collapse
|
14
|
Triatin RD, Chen Z, Ani A, Wang R, Hartman CA, Nolte IM, Thio CHL, Snieder H. Familial co-aggregation and shared genetics of cardiometabolic disorders and traits: data from the multi-generational Lifelines Cohort Study. Cardiovasc Diabetol 2023; 22:282. [PMID: 37865744 PMCID: PMC10590015 DOI: 10.1186/s12933-023-02017-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Accepted: 10/07/2023] [Indexed: 10/23/2023] Open
Abstract
BACKGROUND It is unclear to what extent genetics explain the familial clustering and the co-occurrence of distinct cardiometabolic disorders in the general population. We therefore aimed to quantify the familial (co-)aggregation of various cardiometabolic disorders and to estimate the heritability of cardiometabolic traits and their genetic correlations using the large, multi-generational Lifelines Cohort Study. METHODS We used baseline data of 162,416 participants from Lifelines. Cardiometabolic disorders including type 2 diabetes (T2D), cardiovascular diseases, hypertension, obesity, hypercholesterolemia, and metabolic syndrome (MetS), were defined in adult participants. Fifteen additional cardiometabolic traits indexing obesity, blood pressure, inflammation, glucose regulation, and lipid levels were measured in all included participants. Recurrence risk ratios (λR) for first-degree relatives (FDR) indexed familial (co-)aggregation of cardiometabolic disorders using modified conditional Cox proportional hazards models and were compared to those of spouses. Heritability (h2), shared environment, and genetic correlation (rg) were estimated using restricted maximum likelihood variance decomposition methods, adjusted for age, age2, and sex. RESULTS Individuals with a first-degree relative with a cardiometabolic disorder had a higher risk of the same disorder, ranging from λFDR of 1.23 (95% CI 1.20-1.25) for hypertension to λFDR of 2.48 (95% CI 2.15-2.86) for T2D. Most of these were higher than in spouses (λSpouses < λFDR), except for obesity which was slightly higher in spouses. We found moderate heritability for cardiometabolic traits (from h2CRP: 0.26 to h2HDL: 0.50). Cardiometabolic disorders showed positive familial co-aggregation, particularly between T2D, MetS, and obesity (from λFDR obesity-MetS: 1.28 (95% CI 1.24-1.32) to λFDR MetS-T2D: 1.61 (95% CI 1.52-1.70)), consistent with the genetic correlations between continuous intermediate traits (ranging from rg HDL-Triglycerides: - 0.53 to rg LDL-Apolipoprotein B: 0.94). CONCLUSIONS There is positive familial (co-)aggregation of cardiometabolic disorder, moderate heritability of intermediate traits, and moderate genetic correlations between traits. These results indicate that shared genetics and common genetic architecture contribute to cardiometabolic disease.
Collapse
Affiliation(s)
- Rima D Triatin
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001 (FA40), 9700RB, Groningen, The Netherlands
- Department of Biomedical Sciences, Faculty of Medicine, Universitas Padjadjaran, Bandung, Indonesia
| | - Zekai Chen
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001 (FA40), 9700RB, Groningen, The Netherlands
| | - Alireza Ani
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001 (FA40), 9700RB, Groningen, The Netherlands
- Department of Bioinformatics, Isfahan University of Medical Sciences, Isfahan, 8174673461, Iran
| | - Rujia Wang
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001 (FA40), 9700RB, Groningen, The Netherlands
| | - Catharina A Hartman
- Department of Psychiatry, Interdisciplinary Center Psychopathology and Emotion Regulation (ICPE), University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Ilja M Nolte
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001 (FA40), 9700RB, Groningen, The Netherlands
| | - Chris H L Thio
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001 (FA40), 9700RB, Groningen, The Netherlands.
- Department of Population Health Sciences, Institute for Risk Assessment Sciences (IRAS), Utrecht University, Utrecht, The Netherlands.
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Hanzeplein 1, P.O. Box 30.001 (FA40), 9700RB, Groningen, The Netherlands.
| |
Collapse
|
15
|
Walia GK, Sharma P, Agarwal T, Lal M, Negandhi H, Prabhakaran D, Khadgawat R, Sachdeva MP, Gupta V. Genetic associations of TMEM154, PRC1 and ZFAND6 loci with type 2 diabetes in an endogamous business community of North India. PLoS One 2023; 18:e0291339. [PMID: 37738238 PMCID: PMC10516421 DOI: 10.1371/journal.pone.0291339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2023] [Accepted: 08/27/2023] [Indexed: 09/24/2023] Open
Abstract
BACKGROUND More than 250 loci have been identified by genome-wide scans for type 2 diabetes in different populations. South Asians have a very different manifestation of the diseases and hence role of these loci need to be investigated among Indians with huge burden of cardio-metabolic disorders. Thus the present study aims to validate the recently identified GWAS loci in an endogamous caste population in North India. METHODS 219 T2D cases and 184 controls were recruited from hospitals and genotyped for 15 GWAS loci of T2D. Regression models adjusted for covariates were run to examine the association for T2D and fasting glucose levels. RESULTS We validated three variants for T2D namely, rs11634397 at ZFAND6 (OR = 3.05, 95%CI = 1.02-9.19, p = 0.047) and rs8042680 at PRC1 (OR = 3.67, 95%CI = 1.13-11.93, p = 0.031) showing higher risk and rs6813195 at TMEM154 (OR = 0.28, 95%CI = 0.09-0.90, p = 0.033) showing protective effect. The combined risk of 9 directionally consistent variants was also found to be significantly associated with T2D (OR = 1.91, 95%CI = 1.18-3.08, p = 0.008). One variant rs10842994 at KLHDC5 was validated for 9.15mg/dl decreased fasting glucose levels (SE = -17.25-1.05, p = 0.027). CONCLUSION We confirm the role of ZFAND6, PRC1 and TMEM154 in the pathophysiology of type 2 diabetes among Indians. More efforts are needed with larger sample sizes to validate the diabetes GWAS loci in South Asian populations for wider applicability.
Collapse
Affiliation(s)
- Gagandeep Kaur Walia
- Public Health Foundation of India, Gurugram, India
- Centre for Chronic Disease Control, Safdarjung Development Area, New Delhi, India
| | - Pratiksha Sharma
- Indian Institute of Public Health-Delhi, Public Health Foundation of India, Gurugram, India
| | - Tripti Agarwal
- Indian Institute of Public Health-Delhi, Public Health Foundation of India, Gurugram, India
| | - Moti Lal
- Department of Anthropology, University of Delhi, Delhi, India
| | | | - Dorairaj Prabhakaran
- Public Health Foundation of India, Gurugram, India
- Centre for Chronic Disease Control, Safdarjung Development Area, New Delhi, India
| | - Rajesh Khadgawat
- Department of Endocrinology, All India Institute of Medical Sciences, Ansari Nagar, New Delhi, India
| | | | - Vipin Gupta
- Department of Anthropology, University of Delhi, Delhi, India
| |
Collapse
|
16
|
Abdulaziz Alrashed F, Ahmad T, Almurdi MM, Alqahtani AS, Alamam DM, Alsubiheen AM. Investigating the relationship between lifestyle factors, family history, and diabetes mellitus in non-diabetic visitors to primary care centers. Saudi J Biol Sci 2023; 30:103777. [PMID: 37663393 PMCID: PMC10472303 DOI: 10.1016/j.sjbs.2023.103777] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 07/31/2023] [Accepted: 08/05/2023] [Indexed: 09/05/2023] Open
Abstract
We investigated the risk levels associated with diabetes mellitus. They were assessed based on whether anyone in their family had a history of diabetes. The data collected are measurements of blood pressure, weight, height, and smoking habits, as well as physical activity and educational status. Based on the American Diabetes Association's (ADA) recommendations, the questionnaire included a diabetes risk assessment. The risk of diabetes was 76.3% among participants with a family history of diabetes. There is a 41.1% chance of diabetes among those participants whose fathers had diabetes, and a 39.3% chance of diabetes among those participants whose mothers had diabetes. Additionally, those participants who have siblings with diabetes were 24% at high risk for developing diabetes. The prevalence of the risk of having a family history of diabetes is higher in the women in the family (RR = 3.12; P = 0.0001) as compared to the men in the family (RR = 1.9; P = 0.0001). Risk of diabetes more in the male (1.13 times higher) in the current study based on the ADA scale. There is evidence that various factors, including lifestyle choices, physical attributes, and family history, influence the risk of developing diabetes in the current study. The results of the current study indicate that there is a strong association between patients with T2D and those who have a family history of diabetes. Considering Saudi Arabia's high diabetes risk, evidence-based lifestyle modifications are needed.
Collapse
Affiliation(s)
- Fahad Abdulaziz Alrashed
- Department of Cardiac Sciences, College of Medicine, King Saud University, P.O. Box 7805, Riyadh 11472, Saudi Arabia
| | - Tauseef Ahmad
- Department of Medical Education, College of Medicine, King Saud University, P.O. Box 7805, Riyadh 11472, Saudi Arabia
| | - Muneera M. Almurdi
- Department of Health Rehabilitation Sciences, College of Applied Medical Sciences, King Saud University, P.O. Box 10219, Riyadh 11433, Saudi Arabia
| | - Abdulfattah S. Alqahtani
- Department of Health Rehabilitation Sciences, College of Applied Medical Sciences, King Saud University, P.O. Box 10219, Riyadh 11433, Saudi Arabia
| | - Dalyah M. Alamam
- Department of Health Rehabilitation Sciences, College of Applied Medical Sciences, King Saud University, P.O. Box 10219, Riyadh 11433, Saudi Arabia
| | - Abdulrahman M. Alsubiheen
- Department of Health Rehabilitation Sciences, College of Applied Medical Sciences, King Saud University, P.O. Box 10219, Riyadh 11433, Saudi Arabia
| |
Collapse
|
17
|
Liao PJ, Ting MK, Kuo CF, Ding YH, Lin CM, Hsu KH. Kinship analysis of type 2 diabetes mellitus familial aggregation in Taiwan. Biomed J 2023; 46:100549. [PMID: 35863666 PMCID: PMC10345230 DOI: 10.1016/j.bj.2022.07.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/27/2021] [Revised: 05/11/2022] [Accepted: 07/11/2022] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND Family disease history plays a vital role in type 2 diabetes mellitus (T2DM) risk. However, the familial aggregation of T2DM among different kinship relatives warrants further investigation. METHODS This nationwide kinship relationship study collected 2000-2016 data of two to five generations of the Taiwanese population from the National Health Insurance Research Database. Approximately 4 million family trees were constructed from the records of 20, 890, 264 Taiwanese residents during the study period. T2DM was diagnosed on the basis of ICD-9-CM codes 250.x0 or 250.x2, with three consecutive related prescriptions. The Cox proportional hazard model was used for statistical analysis. RESULTS Compared with their counterparts, individuals who had first-degree relatives with T2DM were more likely to develop T2DM during the follow-up period (hazard ratio [HR], 2.37-27.75), followed by individuals who had second-degree relatives with T2DM (HR, 1.29-1.88). T2DM relative risk was higher in those with an affected mother than in those with affected father. The HR for T2DM was 20.32 (95%CI = 15.64-26.42) among male individuals with an affected twin brother, whereas among female individuals with an affected twin sister, it was 60.07 (95%CI = 40.83-88.36). The HRs presented a dose-response relationship with the number of affected family members. CONCLUSION The study suggests a significant familial aggregation of T2DM occurrence; these findings could aid in identifying the high-risk group for T2DM and designing early intervention strategies and treatment plans.
Collapse
Affiliation(s)
- Pei-Ju Liao
- International Program of Health Informatics and Management, and Master Degree Program in Health and Long-term Care Industry, Chang Gung University, Taoyuan, Taiwan; Department of Nephrology, Chang Gung Memorial Hospital at Keelung, Keelung, Taiwan
| | - Ming-Kuo Ting
- Division of Endocrinology and Metabolism, Chang Gung Memorial Hospital at Keelung, Keelung, Taiwan
| | - Chang-Fu Kuo
- Division of Rheumatology, Allergy and Immunology, Chang Gung Memorial Hospital at Taoyuan, Taoyuan, Taiwan
| | - Yu-Hao Ding
- Laboratory for Epidemiology, Department of Health Care Management, and Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan
| | - Ciao-Ming Lin
- Laboratory for Epidemiology, Department of Health Care Management, and Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan
| | - Kuang-Hung Hsu
- Laboratory for Epidemiology, Department of Health Care Management, and Healthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan; Department of Emergency Medicine, Department of Urology, Chang Gung Memorial Hospital at Taoyuan, Taoyuan, Taiwan; Research Center for Food and Cosmetic Safety, College of Human Ecology, Chang Gung University of Science and Technology, Taoyuan, Taiwan; Department of Safety, Health and Environmental Engineering, Ming Chi University of Technology, New Taipei, Taiwan.
| |
Collapse
|
18
|
Ortiz GG, Torres-Mendoza BMG, Ramírez-Jirano J, Marquez-Pedroza J, Hernández-Cruz JJ, Mireles-Ramirez MA, Torres-Sánchez ED. Genetic Basis of Inflammatory Demyelinating Diseases of the Central Nervous System: Multiple Sclerosis and Neuromyelitis Optica Spectrum. Genes (Basel) 2023; 14:1319. [PMID: 37510224 PMCID: PMC10379341 DOI: 10.3390/genes14071319] [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: 05/10/2023] [Revised: 06/15/2023] [Accepted: 06/20/2023] [Indexed: 07/30/2023] Open
Abstract
Demyelinating diseases alter myelin or the coating surrounding most nerve fibers in the central and peripheral nervous systems. The grouping of human central nervous system demyelinating disorders today includes multiple sclerosis (MS) and neuromyelitis optica spectrum disorders (NMOSD) as distinct disease categories. Each disease is caused by a complex combination of genetic and environmental variables, many involving an autoimmune response. Even though these conditions are fundamentally similar, research into genetic factors, their unique clinical manifestations, and lesion pathology has helped with differential diagnosis and disease pathogenesis knowledge. This review aims to synthesize the genetic approaches that explain the differential susceptibility between these diseases, explore the overlapping clinical features, and pathological findings, discuss existing and emerging hypotheses on the etiology of demyelination, and assess recent pathogenicity studies and their implications for human demyelination. This review presents critical information from previous studies on the disease, which asks several questions to understand the gaps in research in this field.
Collapse
Affiliation(s)
- Genaro Gabriel Ortiz
- Department of Philosophical and Methodological Disciplines and Service of Molecular Biology in Medicine Hospital, Civil University Health Sciences Center, University of Guadalajara, Guadalajara 44340, Jalisco, Mexico
- Department of Neurology, High Specialty Medical Unit, Western National Medical Center of the Mexican Institute of Social Security, Guadalajara 44329, Jalisco, Mexico
| | - Blanca M G Torres-Mendoza
- Department of Philosophical and Methodological Disciplines and Service of Molecular Biology in Medicine Hospital, Civil University Health Sciences Center, University of Guadalajara, Guadalajara 44340, Jalisco, Mexico
- Neurosciences Division, Western Biomedical Research Center, Mexican Social Security Institute (Instituto Mexicano del Seguro Social, IMSS), Guadalajara 44340, Jalisco, Mexico
| | - Javier Ramírez-Jirano
- Neurosciences Division, Western Biomedical Research Center, Mexican Social Security Institute (Instituto Mexicano del Seguro Social, IMSS), Guadalajara 44340, Jalisco, Mexico
| | - Jazmin Marquez-Pedroza
- Neurosciences Division, Western Biomedical Research Center, Mexican Social Security Institute (Instituto Mexicano del Seguro Social, IMSS), Guadalajara 44340, Jalisco, Mexico
- Coordination of Academic Activities, Western Biomedical Research Center, Mexican Social Security Institute (Instituto Mexicano del Seguro Social, IMSS), Guadalajara 44340, Jalisco, Mexico
| | - José J Hernández-Cruz
- Department of Neurology, High Specialty Medical Unit, Western National Medical Center of the Mexican Institute of Social Security, Guadalajara 44329, Jalisco, Mexico
| | - Mario A Mireles-Ramirez
- Department of Neurology, High Specialty Medical Unit, Western National Medical Center of the Mexican Institute of Social Security, Guadalajara 44329, Jalisco, Mexico
| | - Erandis D Torres-Sánchez
- Department of Medical and Life Sciences, University Center of la Cienega, University of Guadalajara, Ocotlan 47820, Jalisco, Mexico
| |
Collapse
|
19
|
Zhao Z, Cao Q, Lu J, Lin H, Gao Z, Xu M, Xu Y, Wang T, Li M, Chen Y, Wang S, Zeng T, Hu R, Yu X, Chen G, Su Q, Mu Y, Chen L, Tang X, Yan L, Qin G, Wan Q, Wang G, Shen F, Luo Z, Qin Y, Chen L, Huo Y, Li Q, Ye Z, Zhang Y, Liu C, Wang Y, Wu S, Yang T, Deng H, Zhao J, Shi L, Ning G, Wang W, Bi Y. Association of Spousal Diabetes Status and Ideal Cardiovascular Health Metrics With Risk of Incident Diabetes Among Chinese Adults. JAMA Netw Open 2023; 6:e2319038. [PMID: 37351887 PMCID: PMC10290251 DOI: 10.1001/jamanetworkopen.2023.19038] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 05/03/2023] [Indexed: 06/24/2023] Open
Abstract
Importance Spouses share common socioeconomic, environmental, and lifestyle factors, and multiple studies have found that spousal diabetes status was associated with diabetes prevalence. But the association of spousal diabetes status and ideal cardiovascular health metrics (ICVHMs) assessed by the American Heart Association's Life's Essential 8 measures with incident diabetes has not been comprehensively characterized, especially in large-scale cohort studies. Objective To explore the association of spousal diabetes status and cardiovascular health metrics with risk of incident diabetes in Chinese adults. Design, Setting, and Participants This cohort study included individuals in the China Cardiovascular Disease and Cancer Cohort without diabetes who underwent baseline and follow-up glucose measurements and had spouses with baseline glucose measurements. The data were collected in January 2011 to December 2012 and March 2014 to December 2016. The spousal study had a mean (SD) follow-up of 3.6 (0.9) years (median [IQR], 3.2 [2.9-4.5] years). Statistical analysis was performed from July to November 2022. Exposure Spousal diabetes status was diagnosed according to the 2010 American Diabetes Association (ADA) criteria. All participants provided detailed clinical, sociodemographic, and lifestyle information included in cardiovascular health metrics. Main Outcomes and Measures Incident diabetes, diagnosed according to 2010 ADA criteria. Results Overall, 34 821 individuals were included, with a mean (SD) age of 56.4 (8.3) years and 16 699 (48.0%) male participants. Spousal diabetes diagnosis was associated with an increased risk of incident diabetes (hazard ratio [HR], 1.15; 95% CI, 1.03-1.30). Furthermore, participants whose spouses had uncontrolled glycated hemoglobin (HbA1c) had a higher risk of diabetes (HR, 1.20; 95% CI, 1.04-1.39) but the risk of diabetes in participants whose spouses had controlled HbA1c did not increase significantly (HR, 1.10; 95% CI, 0.92-1.30). Moreover, this association varied with composite cardiovascular health status. Diabetes risk in individuals who had poor cardiovascular health status (<4 ICVHMs) was associated with spousal diabetes status (3 ICVHMs: HR, 1.50; 95% CI, 1.15-1.97), while diabetes risk in individuals who had intermediate to ideal cardiovascular health status (≥4 ICVHMs) was not associated with it (4 ICVHMs: HR, 1.01; 95% CI, 0.69-1.50). Conclusions and Relevance In this study, spousal diabetes diagnosis with uncontrolled HbA1c level was associated with increased risk of incident diabetes, but strict management of spousal HbA1c level and improving ICVHM profiles may attenuate the association of spousal diabetes status with diabetes risk. These findings suggest the potential benefit of couple-based lifestyle or pharmaceutical interventions for diabetes.
Collapse
Affiliation(s)
- Zhiyun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qiuyu Cao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hong Lin
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhengnan Gao
- Dalian Municipal Central Hospital, Dalian, China
| | - Min Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yu Xu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tiange Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Mian Li
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuhong Chen
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shuangyuan Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Tianshu Zeng
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ruying Hu
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Xuefeng Yu
- Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Gang Chen
- Fujian Provincial Hospital, Fujian Medical University, Fuzhou, China
| | - Qing Su
- Xinhua Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yiming Mu
- Chinese People’s Liberation Army General Hospital, Beijing, China
| | - Lulu Chen
- Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xulei Tang
- The First Hospital of Lanzhou University, Lanzhou, China
| | - Li Yan
- Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, China
| | - Guijun Qin
- The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qin Wan
- The Affiliated Hospital of Southwest Medical University, Luzhou, China
| | - Guixia Wang
- The First Hospital of Jilin University, Changchun, China
| | - Feixia Shen
- The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
| | - Zuojie Luo
- The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yingfen Qin
- The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Li Chen
- Qilu Hospital of Shandong University, Jinan, China
| | - Yanan Huo
- Jiangxi Provincial People’s Hospital Affiliated to Nanchang University, Nanchang, China
| | - Qiang Li
- The Second Affiliated Hospital of Harbin Medical University, Harbin, China
| | - Zhen Ye
- Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China
| | - Yinfei Zhang
- Central Hospital of Shanghai Jiading District, Shanghai, China
| | - Chao Liu
- Jiangsu Province Hospital on Integration of Chinese and Western Medicine, Nanjing, China
| | - Youmin Wang
- The First Affiliated Hospital of Anhui Medical University, Hefei, China
| | - Shengli Wu
- Karamay Municipal People’s Hospital, Xinjiang, China
| | - Tao Yang
- The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Huacong Deng
- The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jiajun Zhao
- Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China
| | - Lixin Shi
- Guiqian International General Hospital, Guiyang, China
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Weiqing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yufang Bi
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| |
Collapse
|
20
|
Nielsen J, Shivashankar R, Cunningham SA, Prabhakaran D, Tandon N, Mohan V, Iqbal R, Narayan KV, Ali MK, Patel SA. Couple concordance in diabetes, hypertension and dyslipidaemia in urban India and Pakistan and associated socioeconomic and household characteristics and modifiable risk factors. J Epidemiol Community Health 2023; 77:336-342. [PMID: 36918271 PMCID: PMC11771309 DOI: 10.1136/jech-2022-219979] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Accepted: 02/18/2023] [Indexed: 03/16/2023]
Abstract
BACKGROUND Concordance in chronic disease status has been observed within couples. In urban India and Pakistan, little is known about couple concordance in diabetes, hypertension, and dyslipidaemia and associated socioeconomic characteristics and modifiable risk factors. METHODS We analysed cross-sectional data from 2548 couples from the Centre for cArdio-metabolic Risk Reduction in South Asia cohort in Chennai, Delhi and Karachi. We estimated couple concordance in presence of ≥1 of diabetes, hypertension and dyslipidaemia (positive concordance: both spouses (W+H+); negative concordance: neither spouse (W-H-); discordant wife: only wife (W+H-); or discordant husband: only husband (W-H+)). We assessed associations of five socioeconomic and household characteristics, and six modifiable risk factors with couple concordance using multinomial logistic regression models with couples as the unit of analysis (reference: W-H-). RESULTS Of the couples, 59.4% (95% CI 57.4% to 61.3%) were concordant in chronic conditions (W+H+: 29.2% (95% CI 27.4% to 31.0%); W-H-: 30.2% (95% CI 28.4%- to 32.0%)); and 40.6% (95% CI 38.7% to 42.6%) discordant (W+H-: 13.1% (95% CI 11.8% to 14.4%); W-H+: 27.6% (95% CI 25.9% to 29.4%)). Compared with couples with no conditions (W-H-), couples had higher relative odds of both having at least one condition if they had higher versus lower levels of: income (OR 2.03 (95% CI 1.47 to 2.80)), wealth (OR 2.66 (95% CI 1.98 to 3.58)) and education (wives' education: OR 1.92 (95% CI 1.29 to 2.86); husbands' education: OR 2.98 (95% CI 1.92 to 4.66)) or weight status (overweight or obesity in both spouses ORs 7.17 (95% CI 4.99 to 10.30)). CONCLUSIONS Positive couple concordance in major chronic conditions is high in urban India and Pakistan, especially among couples with relatively higher socioeconomic position. This suggests that prevention and management focusing on couples at high risk for concordant chronic conditions may be effective and more so in higher socioeconomic groups.
Collapse
Affiliation(s)
- Jannie Nielsen
- Emory Global Diabetes Research Center, Hubert Department of GlobalHealth, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
- Section of Social Medicine, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Roopa Shivashankar
- Division of Non Communicable Diseases', Indian Council of Medical Research, New Delhi, India
- Centre for Chronic Disease Control, New Delhi, India
| | - Solveig A Cunningham
- Emory Global Diabetes Research Center, Hubert Department of GlobalHealth, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Dorairaj Prabhakaran
- Centre for Chronic Disease Control, New Delhi, India
- Research Division, Public Health Foundation of India, New Delhi, India
| | - Nikhil Tandon
- Department of Endocrinology, Metabolism & Diabetes, All India Institute of Medical Sciences, New Delhi, India
| | - Viswanathan Mohan
- Epidemiology & Diabetology, Madras Diabetes Research Foundation & Dr.Mohan's Diabetes Specialities Centre, Chennai, Tamilnadu, India
| | - Romaina Iqbal
- Department of Community Health Sciences, The Aga Khan University, Karachi, Pakistan
| | - Km Venkat Narayan
- Emory Global Diabetes Research Center, Hubert Department of GlobalHealth, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| | - Mohammed K Ali
- Emory Global Diabetes Research Center, Hubert Department of GlobalHealth, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
- Department of Family and Preventive Medicine, School of Medicine, Emory University, Atlanta, Georgia, USA
| | - Shivani Anil Patel
- Emory Global Diabetes Research Center, Hubert Department of GlobalHealth, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA
| |
Collapse
|
21
|
Keys MT, Thinggaard M, Larsen LA, Pedersen DA, Hallas J, Christensen K. Reassessing the evidence of a survival advantage in Type 2 diabetes treated with metformin compared with controls without diabetes: a retrospective cohort study. Int J Epidemiol 2022; 51:1886-1898. [PMID: 36287641 DOI: 10.1093/ije/dyac200] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 10/05/2022] [Indexed: 01/21/2023] Open
Abstract
BACKGROUND Previous research has suggested that individuals with Type 2 diabetes and initiated on metformin monotherapy present with a survival advantage compared with the general population without diabetes. This finding has generated considerable interest in the prophylactic use of metformin against age-related morbidity. METHODS Utilizing Danish National Health Registers, we assessed differences in survival associated with metformin monotherapy for Type 2 diabetes compared with no diagnosis of diabetes in both singleton and discordant twin populations between 1996 and 2012. Data were analysed in both nested case-control and matched cohort study designs, with incidence rate ratios (IRRs) and hazard ratios estimated using conditional logistic regression and Cox proportional hazards regression, respectively. RESULTS In case-control pairs matched on birth year and sex or co-twin (sex, birth year and familial factors), incident Type 2 diabetes with treatment by metformin monotherapy initiation compared with no diagnosis of diabetes was associated with increased mortality in both singletons (IRR = 1.52, 95% CI: 1.37, 1.68) and discordant twin pairs (IRR = 1.90, 95% CI: 1.35, 2.67). After adjusting for co-morbidities and social indicators, these associations were attenuated to 1.32 (95% CI: 1.16, 1.50) and 1.64 (95% CI: 1.10, 2.46), respectively. Increased mortality was observed across all levels of cumulative use and invariant to a range of study designs and sensitivity analyses. CONCLUSIONS Treatment initiation by metformin monotherapy in Type 2 diabetes was not associated with survival equal or superior to that of the general population without diabetes. Our contrasting findings compared with previous research are unlikely to be the result of differences in epidemiological or methodological parameters.
Collapse
Affiliation(s)
- Matthew Thomas Keys
- Department of Epidemiology, Biostatistics, and Biodemography, University of Southern Denmark, Odense, Denmark.,The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Mikael Thinggaard
- Department of Epidemiology, Biostatistics, and Biodemography, University of Southern Denmark, Odense, Denmark.,The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Lisbeth Aagaard Larsen
- Department of Epidemiology, Biostatistics, and Biodemography, University of Southern Denmark, Odense, Denmark.,The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Dorthe Almind Pedersen
- Department of Epidemiology, Biostatistics, and Biodemography, University of Southern Denmark, Odense, Denmark.,The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Jesper Hallas
- Clinical Pharmacology and Pharmacy, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Kaare Christensen
- Department of Epidemiology, Biostatistics, and Biodemography, University of Southern Denmark, Odense, Denmark.,The Danish Twin Registry, Department of Public Health, University of Southern Denmark, Odense, Denmark.,Danish Ageing Research Centre, Department of Public Health, University of Southern Denmark, Odense, Denmark
| |
Collapse
|
22
|
Abstract
PURPOSE OF REVIEW Type 2 diabetes (T2D) is a multifactorial, heritable syndrome characterized by dysregulated glucose homeostasis that results from impaired insulin secretion and insulin resistance. Genetic association studies have successfully identified hundreds of T2D risk loci implicating many genes in disease pathogenesis. In this review, we provide an overview of the recent T2D genetic studies from the past 3 years with particular focus on the effects of sample size and ancestral diversity on genetic discovery as well as discuss recent work on the use and limitations of genetic risk scores (GRS) for T2D risk prediction. RECENT FINDINGS Recent large-scale, multi-ancestry genetic studies of T2D have identified over 500 novel risk loci. The genetic variants (i.e., single nucleotide polymorphisms (SNPs)) marking these novel loci in general have smaller effect sizes than previously discovered loci. Inclusion of samples from diverse ancestral backgrounds shows a few ancestry specific loci marked by common variants, but overall, the majority of loci discovered are common across ancestries. Inclusion of common variant GRS, even with hundreds of loci, does not substantially increase T2D risk prediction over standard clinical risk factors such as age and family history. Common variant association studies of T2D have now identified over 700 T2D risk loci, half of which have been discovered in the past 3 years. These recent studies demonstrate that inclusion of ancestrally diverse samples can enhance locus discovery and improve accuracy of GRS for T2D risk prediction. GRS based on common variants, however, only minimally enhances risk prediction over standard clinical risk factors.
Collapse
Affiliation(s)
- Natalie DeForest
- Department of Medicine, Division of Endocrinology, University of California San Diego, La Jolla, CA, USA
- Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA
| | - Amit R Majithia
- Department of Medicine, Division of Endocrinology, University of California San Diego, La Jolla, CA, USA.
| |
Collapse
|
23
|
Cunningham SA, Beckles GL, Nielsen J. Declines in Health and Support Between Parents and Adult Children: Insights from Diabetes. POPULATION RESEARCH AND POLICY REVIEW 2022. [DOI: 10.1007/s11113-022-09708-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
|
24
|
DNA Methylation and Type 2 Diabetes: Novel Biomarkers for Risk Assessment? Int J Mol Sci 2021; 22:ijms222111652. [PMID: 34769081 PMCID: PMC8584054 DOI: 10.3390/ijms222111652] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 10/25/2021] [Accepted: 10/25/2021] [Indexed: 12/15/2022] Open
Abstract
Diabetes is a severe threat to global health. Almost 500 million people live with diabetes worldwide. Most of them have type 2 diabetes (T2D). T2D patients are at risk of developing severe and life-threatening complications, leading to an increased need for medical care and reduced quality of life. Improved care for people with T2D is essential. Actions aiming at identifying undiagnosed diabetes and at preventing diabetes in those at high risk are needed as well. To this end, biomarker discovery and validation of risk assessment for T2D are critical. Alterations of DNA methylation have recently helped to better understand T2D pathophysiology by explaining differences among endophenotypes of diabetic patients in tissues. Recent evidence further suggests that variations of DNA methylation might contribute to the risk of T2D even more significantly than genetic variability and might represent a valuable tool to predict T2D risk. In this review, we focus on recent information on the contribution of DNA methylation to the risk and the pathogenesis of T2D. We discuss the limitations of these studies and provide evidence supporting the potential for clinical application of DNA methylation marks to predict the risk and progression of T2D.
Collapse
|
25
|
Wang N, Tong R, Xu J, Tian Y, Pan J, Cui J, Chen H, Peng Y, Fei S, Yang S, Wang L, Yao J, Cui W. PDX1 and MC4R genetic polymorphisms are associated with type 2 diabetes mellitus risk in the Chinese Han population. BMC Med Genomics 2021; 14:249. [PMID: 34696776 PMCID: PMC8543917 DOI: 10.1186/s12920-021-01037-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 06/01/2021] [Indexed: 11/17/2022] Open
Abstract
BACKGROUND Diabetes mellitus (DM) is a complex metabolic disease that is caused by a complex interplay between genetic and environmental factors. This research aimed to investigate the association of genetic polymorphisms in PDX1 and MC4R with T2DM risk. METHODS The genotypes of 10 selected SNPs in PDX1 and MC4R were identified using the Agena MassARRAY platform. We utilized odds ratio (OR) and 95% confidence intervals (CIs) to assess the correlation between genetic polymorphisms and T2DM risk. RESULTS We found that PDX1-rs9581943 decreased susceptibility to T2DM among in a Chinese Han population (OR = 0.76, p = 0.045). We also found that selected genetic polymorphisms in PDX1 and MC4R could modify the risk of T2DM, which might also be influenced by age, sex, BMI, smoking status, and drinking status (p < 0.05). CONCLUSIONS We concluded that PDX1 and MC4R genetic variants were significantly associated with T2DM risk in a Chinese Han population. These single polymorphic markers may be considered to be new targets in the assessment and prevention of T2DM among Chinese Han people.
Collapse
Affiliation(s)
- Ning Wang
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Rui Tong
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Jing Xu
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Yanni Tian
- Department of Oncology, East Branch of the First Affiliated Hospital of Xi'an Jiaotong University, Xi'an, 710089, Shaanxi, China
| | - Juan Pan
- Department of Endocrinology, Xianyang Central Hospital, Xianyang, 712000, Shaanxi, China
| | - Jiaqi Cui
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Huan Chen
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Yanqi Peng
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Sijia Fei
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Shujun Yang
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Lu Wang
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Juanchuan Yao
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China
| | - Wei Cui
- Department of Endocrinology and Second Department of Geriatrics, The First Affiliated Hospital of Xi'an Jiaotong University, 277 West Yanta Road, Xi'an, 710061, Shaanxi, China.
| |
Collapse
|
26
|
Cheng H, Zhu W, Zhu M, Sun Y, Sun X, Jia D, Yang C, Yu H, Zhang C. Susceptibility of six polymorphisms in the receptor for advanced glycation end products to type 2 diabetes: a systematic review and meta-analysis. Endocr J 2021; 68:993-1010. [PMID: 33840670 DOI: 10.1507/endocrj.ej21-0130] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/23/2022] Open
Abstract
We did a systematic review and meta-analysis, aiming to examine the association of available polymorphisms in the receptor for advanced glycation end products (AGER) gene with the risk of type 2 diabetes. Literature search, eligibility assessment, and data extraction were independently performed by two authors. Risk was expressed as by odds ratio (OR) and 95% confidence interval (CI) under the random-effects model. A total of 26 publications, involving 29 independent studies (8,318 patients with type 2 diabetes and 5,589 healthy or orthoglycemic controls) were included in this meta-analysis. Six polymorphisms in AGER gene, rs2070600, rs1800624, rs1800625, rs184003, rs3134940, and rs55640627, were eligible for inclusion. Overall analyses indicated that the mutations of rs1800624 (-374A) and rs55640627 (2245A) were associated with a significantly increased risk of type 2 diabetes (OR = 1.17 and 1.55, 95% CI: 1.00 to 1.38 and 1.21 to 1.98, respectively). Subsidiary analyses revealed that the mutation of rs2070600 was associated with 2.13-folded increased risk of type 2 diabetes in Caucasians (95% CI: 1.28 to 3.55), and the mutation of rs1800624 was associated with 1.57-folded increased risk in South Asians (95% CI: 1.09 to 2.25), with no evidence of heterogeneity (I2: 42.5% and 44.5%). There were low probabilities of publication bias for all studied polymorphisms. Taken together, our findings indicate an ethnicity-dependent contribution of AGER gene in the pathogenesis of type 2 diabetes, that is, rs2070600 was a susceptibility locus in Caucasians, yet rs1800624 in South Asians.
Collapse
Affiliation(s)
- Hao Cheng
- Department of Clinics, Qiqihar Medical University, Qiqihar, Heilongjiang, 161006, China
| | - Wenbin Zhu
- Department of Molecular Biology Laboratory, Qiqihar Medical University, Qiqihar, Heilongjiang, 161006, China
| | - Mou Zhu
- Department of Biochemistry and Molecular Biology, Qiqihar Medical University, Qiqihar, Heilongjiang, 161006, China
| | - Yan Sun
- Department of Clinical Pathogen Microbiology, Qiqihar Medical University, Qiqihar, Heilongjiang, 161006, China
| | - Xiaojie Sun
- Department of Clinical Biochemistry, Qiqihar Medical University, Qiqihar, Heilongjiang, 161006, China
| | - Di Jia
- Department of Biochemistry and Molecular Biology, Qiqihar Medical University, Qiqihar, Heilongjiang, 161006, China
| | - Chao Yang
- Department of Biochemistry and Molecular Biology, Qiqihar Medical University, Qiqihar, Heilongjiang, 161006, China
| | - Haitao Yu
- Department of Cell Biology, Qiqihar Medical University, Qiqihar, Heilongjiang, 161006, China
| | - Chunjing Zhang
- Department of Biochemistry and Molecular Biology, Qiqihar Medical University, Qiqihar, Heilongjiang, 161006, China
| |
Collapse
|
27
|
Polfus LM, Darst BF, Highland H, Sheng X, Ng MC, Below JE, Petty L, Bien S, Sim X, Wang W, Fontanillas P, Patel Y, The 23andMe Research Team, DIAMANTE Hispanic/Latino Consortium, MEta-analysis of type 2 DIabetes in African Americans Consortium, Preuss M, Schurmann C, Du Z, Lu Y, Rhie SK, Mercader JM, Tusie-Luna T, González-Villalpando C, Orozco L, Spracklen CN, Cade BE, Jensen RA, Sun M, Joo YY, An P, Yanek LR, Bielak LF, Tajuddin S, Nicolas A, Chen G, Raffield L, Guo X, Chen WM, Nadkarni GN, Graff M, Tao R, Pankow JS, Daviglus M, Qi Q, Boerwinkle EA, Liu S, Phillips LS, Peters U, Carlson C, Wikens LR, Le Marchand L, North KE, Buyske S, Kooperberg C, Loos RJ, Stram DO, Haiman CA. Genetic discovery and risk characterization in type 2 diabetes across diverse populations. HGG ADVANCES 2021; 2:100029. [PMID: 34604815 PMCID: PMC8486151 DOI: 10.1016/j.xhgg.2021.100029] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2020] [Accepted: 03/04/2021] [Indexed: 11/23/2022] Open
Abstract
Genomic discovery and characterization of risk loci for type 2 diabetes (T2D) have been conducted primarily in individuals of European ancestry. We conducted a multiethnic genome-wide association study of T2D among 53,102 cases and 193,679 control subjects from African, Hispanic, Asian, Native Hawaiian, and European population groups in the Population Architecture Genomics and Epidemiology (PAGE) and Diabetes Genetics Replication and Meta-analysis (DIAGRAM) Consortia. In individuals of African ancestry, we discovered a risk variant in the TGFB1 gene (rs11466334, risk allele frequency (RAF) = 6.8%, odds ratio [OR] = 1.27, p = 2.06 × 10-8), which replicated in independent studies of African ancestry (p = 6.26 × 10-23). We identified a multiethnic risk variant in the BACE2 gene (rs13052926, RAF = 14.1%, OR = 1.08, p = 5.75 × 10-9), which also replicated in independent studies (p = 3.45 × 10-4). We also observed a significant difference in the performance of a multiethnic genetic risk score (GRS) across population groups (pheterogeneity = 3.85 × 10-20). Comparing individuals in the top GRS risk category (40%-60%), the OR was highest in Asians (OR = 3.08) and European (OR = 2.94) ancestry populations, followed by Hispanic (OR = 2.39), Native Hawaiian (OR = 2.02), and African ancestry (OR = 1.57) populations. These findings underscore the importance of genetic discovery and risk characterization in diverse populations and the urgent need to further increase representation of non-European ancestry individuals in genetics research to improve genetic-based risk prediction across populations.
Collapse
Affiliation(s)
- Linda M. Polfus
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - Burcu F. Darst
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - Heather Highland
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Xin Sheng
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - Maggie C.Y. Ng
- Division of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Jennifer E. Below
- The Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Lauren Petty
- The Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | | | | | - Yesha Patel
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - The 23andMe Research Team
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Division of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- The Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Adaptive Biotechnologies Corporation, Seattle, WA, USA
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- 23andMe, Sunnyvale, CA, USA
- Icahn School of Medicine at Mount Sinai, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA
- Department of Biochemistry and Molecular Medicine, University of Southern California, Los Angeles, CA, USA
- Program in Metabolism, Broad Institute, Cambridge, MA, USA
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Universidad Nacional Autónoma de Mexico, Mexico City, Mexico
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Pública, Mexico City, Mexico
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
- Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK, USA
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Division of Statistical Genomics, School of Medicine, Washington University, St. Louis, MO, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Center for Research on Genomics and Global Health, National Human Genome Institute, National Institutes of Health, Bethesda, MD, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
- Department of Biostatistics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
- Institute for Minority Health Research, University of Illinois Chicago, Chicago, IL, USA
- Center for Population Cohorts, Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Human Genetics Center, University of Texas Health Science Center, Houston, TX, USA
- School of Public Health, Brown University, Providence, RI, USA
- Atlanta VA Medical Center, Decatur, GA, USA
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
- Division of Public Health Sciences, University of Washington, Department of Epidemiology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
- Department of Statistics, Rutgers University, Piscataway, NJ, USA
- Icahn School of Medicine at Mount Sinai, The Mindich Child Health and Development Institute, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA
| | - DIAMANTE Hispanic/Latino Consortium
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Division of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- The Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Adaptive Biotechnologies Corporation, Seattle, WA, USA
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- 23andMe, Sunnyvale, CA, USA
- Icahn School of Medicine at Mount Sinai, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA
- Department of Biochemistry and Molecular Medicine, University of Southern California, Los Angeles, CA, USA
- Program in Metabolism, Broad Institute, Cambridge, MA, USA
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Universidad Nacional Autónoma de Mexico, Mexico City, Mexico
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Pública, Mexico City, Mexico
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
- Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK, USA
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Division of Statistical Genomics, School of Medicine, Washington University, St. Louis, MO, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Center for Research on Genomics and Global Health, National Human Genome Institute, National Institutes of Health, Bethesda, MD, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
- Department of Biostatistics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
- Institute for Minority Health Research, University of Illinois Chicago, Chicago, IL, USA
- Center for Population Cohorts, Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Human Genetics Center, University of Texas Health Science Center, Houston, TX, USA
- School of Public Health, Brown University, Providence, RI, USA
- Atlanta VA Medical Center, Decatur, GA, USA
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
- Division of Public Health Sciences, University of Washington, Department of Epidemiology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
- Department of Statistics, Rutgers University, Piscataway, NJ, USA
- Icahn School of Medicine at Mount Sinai, The Mindich Child Health and Development Institute, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA
| | - MEta-analysis of type 2 DIabetes in African Americans Consortium
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Division of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- The Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
- Adaptive Biotechnologies Corporation, Seattle, WA, USA
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
- 23andMe, Sunnyvale, CA, USA
- Icahn School of Medicine at Mount Sinai, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA
- Department of Biochemistry and Molecular Medicine, University of Southern California, Los Angeles, CA, USA
- Program in Metabolism, Broad Institute, Cambridge, MA, USA
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Universidad Nacional Autónoma de Mexico, Mexico City, Mexico
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Pública, Mexico City, Mexico
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
- Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, MA, USA
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK, USA
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
- Division of Statistical Genomics, School of Medicine, Washington University, St. Louis, MO, USA
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
- Center for Research on Genomics and Global Health, National Human Genome Institute, National Institutes of Health, Bethesda, MD, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
- Department of Biostatistics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
- Institute for Minority Health Research, University of Illinois Chicago, Chicago, IL, USA
- Center for Population Cohorts, Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
- Human Genetics Center, University of Texas Health Science Center, Houston, TX, USA
- School of Public Health, Brown University, Providence, RI, USA
- Atlanta VA Medical Center, Decatur, GA, USA
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
- Division of Public Health Sciences, University of Washington, Department of Epidemiology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
- University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
- Department of Statistics, Rutgers University, Piscataway, NJ, USA
- Icahn School of Medicine at Mount Sinai, The Mindich Child Health and Development Institute, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA
| | - Michael Preuss
- Icahn School of Medicine at Mount Sinai, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA
| | - Claudia Schurmann
- Icahn School of Medicine at Mount Sinai, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA
| | - Zhaohui Du
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - Yingchang Lu
- Division of Genetic Medicine, Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Suhn K. Rhie
- Department of Biochemistry and Molecular Medicine, University of Southern California, Los Angeles, CA, USA
| | | | - Teresa Tusie-Luna
- Unidad de Biología Molecular y Medicina Genómica, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, Universidad Nacional Autónoma de Mexico, Mexico City, Mexico
| | - Clicerio González-Villalpando
- Centro de Estudios en Diabetes, Unidad de Investigacion en Diabetes y Riesgo Cardiovascular, Centro de Investigacion en Salud Poblacional, Instituto Nacional de Salud Pública, Mexico City, Mexico
| | - Lorena Orozco
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Cassandra N. Spracklen
- Department of Biostatistics and Epidemiology, University of Massachusetts, Amherst, MA, USA
| | - Brian E. Cade
- Division of Sleep and Circadian Disorders, Brigham and Women’s Hospital, Boston, MA, USA
| | - Richard A. Jensen
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Meng Sun
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK, USA
| | - Yoonjung Yoonie Joo
- Division of Endocrinology, Metabolism, and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Ping An
- Division of Statistical Genomics, School of Medicine, Washington University, St. Louis, MO, USA
| | - Lisa R. Yanek
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Lawrence F. Bielak
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA
| | - Salman Tajuddin
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - Aude Nicolas
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - Guanjie Chen
- Center for Research on Genomics and Global Health, National Human Genome Institute, National Institutes of Health, Bethesda, MD, USA
| | - Laura Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Xiuqing Guo
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Wei-Min Chen
- Department of Public Health Sciences and Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Girish N. Nadkarni
- Icahn School of Medicine at Mount Sinai, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ran Tao
- Department of Biostatistics, Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - James S. Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois Chicago, Chicago, IL, USA
| | - Qibin Qi
- Center for Population Cohorts, Department of Epidemiology & Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Eric A. Boerwinkle
- Human Genetics Center, University of Texas Health Science Center, Houston, TX, USA
| | - Simin Liu
- School of Public Health, Brown University, Providence, RI, USA
| | - Lawrence S. Phillips
- Atlanta VA Medical Center, Decatur, GA, USA
- Division of Endocrinology and Metabolism, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Ulrike Peters
- Division of Public Health Sciences, University of Washington, Department of Epidemiology, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Chris Carlson
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Lynne R. Wikens
- University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Loic Le Marchand
- University of Hawaii Cancer Center, University of Hawaii at Manoa, Honolulu, HI, USA
| | - Kari E. North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Steven Buyske
- Department of Statistics, Rutgers University, Piscataway, NJ, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Ruth J.F. Loos
- Icahn School of Medicine at Mount Sinai, The Mindich Child Health and Development Institute, The Charles Bronfman Institute for Personalized Medicine, New York, NY, USA
| | - Daniel O. Stram
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| | - Christopher A. Haiman
- Department of Preventive Medicine, Center for Genetic Epidemiology, University of Southern California, Los Angeles, CA, USA
| |
Collapse
|
28
|
Wang W, Jiang H, Zhang Z, Duan W, Han T, Sun C. Interaction between dietary branched-chain amino acids and genetic risk score on the risk of type 2 diabetes in Chinese. GENES & NUTRITION 2021; 16:4. [PMID: 33663374 PMCID: PMC7934387 DOI: 10.1186/s12263-021-00684-6] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/14/2020] [Accepted: 02/17/2021] [Indexed: 01/22/2023]
Abstract
BACKGROUND AND OBJECTIVES Previous studies have found the important gene-diet interactions on type 2 diabetes (T2D) incident but have not followed branched-chain amino acids (BCAAs), even though they have shown heterogeneous effectiveness in diabetes-related factors. So in this study, we aim to investigate whether dietary BCAAs interact with the genetic predisposition in relation to T2D risk and fasting glucose in Chinese adults. METHODS In a case-control study nested in the Harbin Cohort Study on Diet, Nutrition and Chronic Non-Communicable Diseases, we obtained data for 434 incident T2D cases and 434 controls matched by age and sex. An unweighted genetic risk score (GRS) was calculated for 25 T2D-related single nucleotide polymorphisms by summation of the number of risk alleles for T2D. Multivariate logistic regression models and general linear regression models were used to assess the interaction between dietary BCAAs and GRS on T2D risk and fasting glucose. RESULTS Significant interactions were found between GRS and dietary BCAAs on T2D risk and fasting glucose (p for interaction = 0.001 and 0.004, respectively). Comparing with low GRS, the odds ratio of T2D in high GRS were 2.98 (95% CI 1.54-5.76) among those with the highest tertile of total BCAA intake but were non-significant among those with the lowest intake, corresponding to 0.39 (0.12) mmol/L versus - 0.07 (0.10) mmol/L fasting glucose elevation per tertile. Viewed differently, comparing extreme tertiles of dietary BCAAs, the odds ratio (95% CIs) of T2D risk were 0.46 (0.22-0.95), 2.22 (1.15-4.31), and 2.90 (1.54-5.47) (fasting glucose elevation per tertile: - 0.23 (0.10), 0.18 (0.10), and 0.26 (0.13) mmol/L) among participants with low, intermediate, and high genetic risk, respectively. CONCLUSIONS This study indicated that dietary BCAAs could amplify the genetic association with T2D risk and fasting glucose. Moreover, higher BCAA intake showed positive association with T2D when genetic predisposition was also high but changed to negative when genetic predisposition was low.
Collapse
Affiliation(s)
- Weiqi Wang
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, People's Republic of China
| | - Haiyang Jiang
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, People's Republic of China
| | - Ziwei Zhang
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, People's Republic of China
| | - Wei Duan
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, People's Republic of China
| | - Tianshu Han
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, People's Republic of China
| | - Changhao Sun
- National Key Discipline, Department of Nutrition and Food Hygiene, School of Public Health, Harbin Medical University, 157 Baojian Road, Harbin, 150081, People's Republic of China.
| |
Collapse
|
29
|
Minami T, Matsumoto T, Tabara Y, Gozal D, Smith D, Murase K, Tanizawa K, Takahashi N, Nakatsuka Y, Hamada S, Handa T, Takeyama H, Oga T, Nakamoto I, Wakamura T, Komenami N, Setoh K, Tsutsumi T, Kawaguchi T, Kamatani Y, Takahashi Y, Morita S, Nakayama T, Hirai T, Matsuda F, Chin K. Impact of sleep-disordered breathing on glucose metabolism among individuals with a family history of diabetes: the Nagahama study. J Clin Sleep Med 2021; 17:129-140. [PMID: 32955012 DOI: 10.5664/jcsm.8796] [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] [Indexed: 12/25/2022]
Abstract
STUDY OBJECTIVES It is well known that a family history of diabetes (FHD) is a definitive risk factor for type 2 diabetes. It has not been known whether sleep-disordered breathing (SDB) increases the prevalence of diabetes in those with an FHD. METHODS We assessed SDB severity in 7,477 study participants by oximetry corrected by objective sleep duration determined by wrist actigraphy. Glycated hemoglobin ≥6.5% and/or current medication for diabetes indicated the presence of diabetes. In addition to the overall prevalence, the prevalence of recent-onset diabetes during the nearly 5 years before the SDB measurements were made was investigated. RESULTS Of the 7,477 participants (mean age: 57.9; range: 34.2-80.7; SD: 12.1 years; 67.7% females), 1,569 had an FHD. The prevalence of diabetes in FHD participants with moderate-to-severe SDB (MS-SDB) was higher than in those without SDB (MS-SDB vs without SDB: all, 29.3% vs 3.3% [P < .001]; females, 32.6% vs 1.9% [P < .001]; males, 26.2% vs 11.7% [P = .037]). However, multivariate analysis showed that MS-SDB was significantly associated with a higher prevalence of diabetes only in FHD-positive females (odds ratio [95% confidence interval]: females, 7.43 [3.16-17.45]; males, 0.92 [0.37-2.31]). Among the FHD-positive participants, the prevalence of recent-onset diabetes was higher in those with MS-SDB than those without SDB, but only in females (MS-SDB vs without SDB: 21.4% vs 1.1%; P < 0.001). CONCLUSIONS MS-SDB was associated with diabetes risk in females with an FHD, and future studies are needed on whether treatment of SDB in females with an FHD would prevent the onset of diabetes.
Collapse
Affiliation(s)
- Takuma Minami
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takeshi Matsumoto
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan.,Department of Respiratory Medicine, Osaka Saiseikai Noe Hospital, Osaka, Japan
| | - Yasuharu Tabara
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - David Gozal
- Department of Child Health and Child Health Research Institute, University of Missouri School of Medicine, Columbia, Missouri
| | - Dale Smith
- Department of Behavioral Sciences, Olivet Nazarene University, Bourbonnais, Illinois
| | - Kimihiko Murase
- Department of Respiratory Care and Sleep Control Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Kiminobu Tanizawa
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Naomi Takahashi
- Department of Respiratory Care and Sleep Control Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yoshinari Nakatsuka
- Department of Respiratory Care and Sleep Control Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Satoshi Hamada
- Department of Advance Medicine for Respiratory Failure, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tomohiro Handa
- Department of Advance Medicine for Respiratory Failure, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Hirofumi Takeyama
- Department of Respiratory Care and Sleep Control Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Toru Oga
- Department of Respiratory Medicine, Kawasaki Medical School, Kurashiki, Japan
| | - Isuzu Nakamoto
- Nursing Science, Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Tomoko Wakamura
- Nursing Science, Human Health Sciences, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Naoko Komenami
- Department of Food and Nutrition, Kyoto Women's University, Kyoto, Japan
| | - Kazuya Setoh
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takanobu Tsutsumi
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takahisa Kawaguchi
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Yoichiro Kamatani
- Kyoto-McGill International Collaborative School in Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, Japan
| | - Yoshimitsu Takahashi
- Department of Health Informatics, Kyoto University School of Public Health, Kyoto, Japan
| | - Satoshi Morita
- Department of Biomedical Statistics and Bioinformatics, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Takeo Nakayama
- Department of Health Informatics, Kyoto University School of Public Health, Kyoto, Japan
| | - Toyohiro Hirai
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | - Kazuo Chin
- Department of Respiratory Care and Sleep Control Medicine, Graduate School of Medicine, Kyoto University, Kyoto, Japan
| | | |
Collapse
|
30
|
Xiong X, Wei L, Xiao Y, Han Y, Yang J, Zhao H, Yang M, Sun L. Effects of family history of diabetes on pancreatic β-cell function and diabetic ketoacidosis in newly diagnosed patients with type 2 diabetes: a cross-sectional study in China. BMJ Open 2021; 11:e041072. [PMID: 33431489 PMCID: PMC7802721 DOI: 10.1136/bmjopen-2020-041072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/02/2022] Open
Abstract
OBJECTIVE To investigate the association between a parental and/or sibling history of diabetes and clinical characteristics. DESIGN A cross-sectional study. SETTING The data were collected from the endocrinology department of The Second Xiangya Hospital of Central South University from June 2017 to October 2019. PARTICIPANTS A total of 894 newly diagnosed patients with type 2 diabetes were recruited. Data on clinical characteristics were collected from patient medical records. Pancreatic β-cell function and insulin resistance were calculated with the homeostatic model assessment. SPSS V.25.0 was used to perform the analysis. RESULTS The percentages of patients with parental and sibling histories of diabetes were 14.8% and 9.8%, respectively. The prevalence of diabetic ketoacidosis (DKA) was 3.9%. Compared with those with no parental history of diabetes, patients with a parental history of diabetes were characterised by early-onset disease (41.70±10.88 vs 51.17±14.09 years), poor glycaemic control of fasting blood glucose (10.84±5.21 vs 8.91±4.38 mmol/L) and a high prevalence of DKA (7.6% vs 3.3%). The patients with a sibling history of diabetes had later disease onset (56.05±9.86 vs 49.09±14.29 years) and lower BMI (24.49±3.48 vs 25.69±3.86 kg/m2) than those with no sibling history of diabetes. Univariate regression suggested that both parental history (p=0.037) and sibling history (p=0.011) of diabetes were associated with β-cell function; however, multiple regression analysis showed that only a sibling history of diabetes was associated with β-cell function (p=0.038). Univariate regression revealed a positive correlation between parental history of diabetes (p=0.023, OR=2.416, 95% CI 1.132 to 5.156) and DKA. Unfortunately, this correlation was not statistically significant for either patients with a parental history (p=0.234, OR=1.646, 95% CI 0.724 to 3.743) or those with a sibling history (p=0.104, OR=2.319, 95% CI 0.841 to 6.389) after adjustments for confounders. CONCLUSION A sibling history of diabetes was associated with poor β-cell function, and a parental history of diabetes was associated with poor glycaemic control and a high prevalence of DKA.
Collapse
Affiliation(s)
- Xiaofen Xiong
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ling Wei
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ying Xiao
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Yachun Han
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Jinfei Yang
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Hao Zhao
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Ming Yang
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, China
| | - Lin Sun
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, China
| |
Collapse
|
31
|
Wang Y, Zhang Y, Wang K, Su Y, Zhuge J, Li W, Wang S, Yao H. Nomogram Model for Screening the Risk of Type II Diabetes in Western Xinjiang, China. Diabetes Metab Syndr Obes 2021; 14:3541-3553. [PMID: 34393494 PMCID: PMC8357405 DOI: 10.2147/dmso.s313838] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2021] [Accepted: 06/29/2021] [Indexed: 12/13/2022] Open
Abstract
OBJECTIVE A simple type 2 diabetes mellitus (T2DM) screening model was established preciously based on easily available variables for identifying high-risk individuals in western Xinjiang, China. METHODS A total of 458,153 cases participating in the national health examination were recruited. Logistic regression and the least absolute shrinkage and selection operator (LASSO) models were used for univariate analysis, factors selection, and the establishment of prediction model. Receiver operating characteristic (ROC) curve, Hosmer-Lemeshow test and clinical decision curve (CDA) were applied for evaluating the discrimination, calibration and clinical validity, respectively. The optimal threshold for predicting risk factors for T2DM has been estimated as well. RESULTS The nomogram depicted the risk of T2DM based on different genders, the factors mainly consisted of age, family history of T2DM (FHOT), waist circumference (WC), total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDLc), body mass index (BMI), high-density lipoprotein cholesterol (HDLc), etc. The area under ROC of men and women was 0.864 and 0.816 in the development group, similarly in the validation group, which was 0.865 and 0.815, respectively. The calibration curve showed that the nomogram was accurate for predicting the risk of T2DM, and the CDA proved great clinical application value of the nomogram. Threshold values of the age, WC, TC, TG, HDLc, BMI in different genders were 52.5 years old (men) and 48.5 years old (women), 85.50 cm (men) and 89.9 cm (women), 4.94 mmol/L (men) and 4.94mmol/L (women), 1.26mmol/L (men) and 1.67mmol/L (women), 1.40mmol/L (men) and 1.40mmol/L (women), 24.70kg/m2 (men) and 24.95kg/m2 (women), respectively. CONCLUSION Our results give a clue that the nomogram may be useful for identifying adults who have high risk for diabetes, which is simple, affordable, with high credibility and can be widely implemented. Further studies are needed to evaluate the utility and feasibility of this model in various settings.
Collapse
Affiliation(s)
- Yushan Wang
- Center of Health Management, The First Affiliated Hospital, Xinjiang Medical University, Urumqi, People’s Republic of China
| | - Yushan Zhang
- College of Public Health, Xinjiang Medical University, Urumqi, People’s Republic of China
| | - Kai Wang
- Department of Medical Engineering and Technology, Xinjiang Medical University, Urumqi, People’s Republic of China
| | - Yinxia Su
- Center of Health Management, The First Affiliated Hospital, Xinjiang Medical University, Urumqi, People’s Republic of China
| | - Jinhui Zhuge
- College of Public Health, Xinjiang Medical University, Urumqi, People’s Republic of China
| | - Wenli Li
- College of Public Health, Xinjiang Medical University, Urumqi, People’s Republic of China
| | - Shuxia Wang
- Center of Health Management, The First Affiliated Hospital, Xinjiang Medical University, Urumqi, People’s Republic of China
| | - Hua Yao
- Center of Health Management, The First Affiliated Hospital, Xinjiang Medical University, Urumqi, People’s Republic of China
- Correspondence: Hua Yao; Shuxia Wang Center of Health Management, The First Affiliated Hospital of Xinjiang Medical University, No. 137 Liyushan South Road, Urumqi, 830011, People’s Republic of ChinaTel +86-13999180161; +86-13579901672 Email ;
| |
Collapse
|
32
|
Chiu H, Lee MY, Wu PY, Huang JC, Chen SC, Chang JM. Comparison of the effects of sibling and parental history of type 2 diabetes on metabolic syndrome. Sci Rep 2020; 10:22131. [PMID: 33335312 PMCID: PMC7747734 DOI: 10.1038/s41598-020-79382-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 12/07/2020] [Indexed: 02/07/2023] Open
Abstract
The aim of this study was to investigate the associations between sibling history, parental history and simultaneous sibling and parental history of diabetes, and the presence of the metabolic syndrome (MetS) and its components. Our study comprised 5000 participants from Taiwan Biobank until April, 2014. The participants were stratified into four groups according to sibling and/or parental family history (FH) of DM. MetS was defined as having 3 of the following 5 abnormalities based on the standard of the NCEP ATP III and modified criteria for Asians. The prevalence of MetS and its traits was estimated and compared among the four familial risk strata. Multivariate logistic regression analysis showed participants with sibling FH of DM [vs. no FH of DM; odds ratio (OR) 1.815; 95% confidence interval (CI) 1.293 to 2.548; p = 0.001], participants with parental FH of DM (vs. no FH of DM; OR 1.771; 95% CI 1.468 to 2.135; p < 0.001), and participants with simultaneous sibling and parental FH of DM (vs. no FH of DM; OR 2.961; 95% CI 2.108 to 4.161; p < 0.001) were significantly associated with MetS. A synergistic effect of sibling FH of DM and parental FH of DM on the association of MetS was also observed. In a nationally representative sample of Taiwan adults, a simultaneous sibling and parental history of diabetes shows a significant, independent association with MetS and its components, except for abdominal obesity. The association highlights the importance of obtaining stratified FH information in clinical practice and may help to identify individuals who should be targeted for screening and early prevention of MetS.
Collapse
Affiliation(s)
- Hsuan Chiu
- Department of General Medicine, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Mei-Yueh Lee
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Pei-Yu Wu
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Department of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, 482, Shan-Ming Rd., Hsiao-Kang Dist., Kaohsiung, 812, Taiwan, ROC
| | - Jiun-Chi Huang
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Department of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, 482, Shan-Ming Rd., Hsiao-Kang Dist., Kaohsiung, 812, Taiwan, ROC.,Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Szu-Chia Chen
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan. .,Department of Internal Medicine, Kaohsiung Municipal Siaogang Hospital, Kaohsiung Medical University, 482, Shan-Ming Rd., Hsiao-Kang Dist., Kaohsiung, 812, Taiwan, ROC. .,Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan. .,Research Center for Environmental Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan.
| | - Jer-Ming Chang
- Division of Nephrology, Department of Internal Medicine, Kaohsiung Medical University Hospital, Kaohsiung Medical University, Kaohsiung, Taiwan.,Faculty of Medicine, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| |
Collapse
|
33
|
Yang CH, Mangiafico SP, Waibel M, Loudovaris T, Loh K, Thomas HE, Morahan G, Andrikopoulos S. E2f8 and Dlg2 genes have independent effects on impaired insulin secretion associated with hyperglycaemia. Diabetologia 2020; 63:1333-1348. [PMID: 32356104 DOI: 10.1007/s00125-020-05137-0] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2019] [Accepted: 02/14/2020] [Indexed: 12/11/2022]
Abstract
AIMS/HYPOTHESIS Reduced insulin secretion results in hyperglycaemia and diabetes involving a complex aetiology that is yet to be fully elucidated. Genetic susceptibility is a key factor in beta cell dysfunction and hyperglycaemia but the responsible genes have not been defined. The Collaborative Cross (CC) is a recombinant inbred mouse panel with diverse genetic backgrounds allowing the identification of complex trait genes that are relevant to human diseases. The aim of this study was to identify and characterise genes associated with hyperglycaemia. METHODS Using an unbiased genome-wide association study, we examined random blood glucose and insulin sensitivity in 53 genetically unique mouse strains from the CC population. The influences of hyperglycaemia susceptibility quantitative trait loci (QTLs) were investigated by examining glucose tolerance, insulin secretion, pancreatic histology and gene expression in the susceptible mice. Expression of candidate genes and their association with insulin secretion were examined in human islets. Mechanisms underlying reduced insulin secretion were studied in MIN6 cells using RNA interference. RESULTS Wide variations in blood glucose levels and the related metabolic traits (insulin sensitivity and body weight) were observed in the CC population. We showed that elevated blood glucose in the CC strains was not due to insulin resistance nor obesity but resulted from reduced insulin secretion. This insulin secretory defect was demonstrated to be independent of abnormalities in islet morphology, beta cell mass and pancreatic insulin content. Gene mapping identified the E2f8 (p = 2.19 × 10-15) and Dlg2 loci (p = 3.83 × 10-8) on chromosome 7 to be significantly associated with hyperglycaemia susceptibility. Fine mapping the implicated regions using congenic mice demonstrated that these two loci have independent effects on insulin secretion in vivo. Significantly, our results revealed that increased E2F8 and DLG2 gene expression are correlated with enhanced insulin secretory function in human islets. Furthermore, loss-of-function studies in MIN6 cells demonstrated that E2f8 is involved in insulin secretion through an ATP-sensitive K+ channel-dependent pathway, which leads to a 30% reduction in Abcc8 expression. Similarly, knockdown of Dlg2 gene expression resulted in impaired insulin secretion in response to glucose and non-glucose stimuli. CONCLUSIONS/INTERPRETATION Collectively, these findings suggest that E2F transcription factor 8 (E2F8) and discs large homologue 2 (DLG2) regulate insulin secretion. The CC resource enables the identification of E2f8 and Dlg2 as novel genes associated with hyperglycaemia due to reduced insulin secretion in pancreatic beta cells. Taken together, our results provide better understanding of the molecular control of insulin secretion and further support the use of the CC resource to identify novel genes relevant to human diseases.
Collapse
Affiliation(s)
- Chieh-Hsin Yang
- Department of Medicine (Austin Health), Austin Hospital, University of Melbourne, Level 7, Lance Townsend Building, Studley Road, Heidelberg, VIC, 3084, Australia.
- St Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, VIC, 3065, Australia.
| | - Salvatore P Mangiafico
- Department of Medicine (Austin Health), Austin Hospital, University of Melbourne, Level 7, Lance Townsend Building, Studley Road, Heidelberg, VIC, 3084, Australia
| | - Michaela Waibel
- St Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, VIC, 3065, Australia
| | - Thomas Loudovaris
- St Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, VIC, 3065, Australia
| | - Kim Loh
- St Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, VIC, 3065, Australia
| | - Helen E Thomas
- St Vincent's Institute of Medical Research, 9 Princes Street, Fitzroy, VIC, 3065, Australia
| | - Grant Morahan
- Harry Perkins Institute of Medical Research, Nedlands, WA, Australia
| | - Sofianos Andrikopoulos
- Department of Medicine (Austin Health), Austin Hospital, University of Melbourne, Level 7, Lance Townsend Building, Studley Road, Heidelberg, VIC, 3084, Australia.
| |
Collapse
|
34
|
Combined Tuberculosis and Diabetes Mellitus Screening and Assessment of Glycaemic Control among Household Contacts of Tuberculosis Patients in Yangon, Myanmar. Trop Med Infect Dis 2020; 5:tropicalmed5030107. [PMID: 32610514 PMCID: PMC7558353 DOI: 10.3390/tropicalmed5030107] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2020] [Revised: 06/03/2020] [Accepted: 06/19/2020] [Indexed: 01/21/2023] Open
Abstract
Background: This study aimed to identify the prevalence of diabetes mellitus (DM) and tuberculosis (TB) among household contacts of index TB patients in Yangon, Myanmar. Method: Household contacts were approached at their home. Chest X-ray and capillary blood glucose tests were offered based on World Health Organization and American Diabetes Association guidelines. Crude prevalence and odds ratios of DM and TB among household contacts of TB patients with and without DM were calculated. Results: The overall prevalence of DM and TB among household contacts were (14.0%, 95% CI: 10.6–18.4) and (5%, 95% CI: 3.2–7.6), respectively. More than 25% of DM cases and almost 95% of TB cases among household contacts were newly diagnosed. Almost 64% of known DM cases among household contacts had poor glycaemic control. The risk of getting DM among household contacts of TB patients with DM was significantly higher (OR—2.13, 95% CI: 1.10–4.12) than those of TB patients without DM. There was no difference in prevalence of TB among household contacts of TB patients with and without DM. Conclusion: Significant proportions of the undetected and uncontrolled DM among household contacts of index TB patients indicate a strong need for DM screening and intervention in this TB–DM dual high-risk population.
Collapse
|
35
|
Ding M, Ahmad S, Qi L, Hu Y, Bhupathiraju SN, Guasch-Ferré M, Jensen MK, Chavarro JE, Ridker PM, Willett WC, Chasman DI, Hu FB, Kraft P. Additive and Multiplicative Interactions Between Genetic Risk Score and Family History and Lifestyle in Relation to Risk of Type 2 Diabetes. Am J Epidemiol 2020; 189:445-460. [PMID: 31647510 DOI: 10.1093/aje/kwz251] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2019] [Revised: 11/09/2018] [Accepted: 10/17/2019] [Indexed: 12/28/2022] Open
Abstract
We examined interactions between lifestyle factors and genetic risk of type 2 diabetes (T2D-GR), captured by genetic risk score (GRS) and family history (FH). Our initial study cohort included 20,524 European-ancestry participants, of whom 1,897 developed incident T2D, in the Nurses' Health Study (1984-2016), Nurses' Health Study II (1989-2016), and Health Professionals Follow-up Study (1986-2016). The analyses were replicated in 19,183 European-ancestry controls and 2,850 incident T2D cases in the Women's Genome Health Study (1992-2016). We defined 2 categories of T2D-GR: high GRS (upper one-third) with FH and low GRS or without FH. Compared with participants with the healthiest lifestyle and low T2D-GR, the relative risk of T2D for participants with the healthiest lifestyle and high T2D-GR was 2.24 (95% confidence interval (CI): 1.76, 2.86); for participants with the least healthy lifestyle and low T2D-GR, it was 4.05 (95% CI: 3.56, 4.62); and for participants with the least healthy lifestyle and high T2D-GR, it was 8.72 (95% CI: 7.46, 10.19). We found a significant departure from an additive risk difference model in both the initial and replication cohorts, suggesting that adherence to a healthy lifestyle could lead to greater absolute risk reduction among those with high T2D-GR. The public health implication is that a healthy lifestyle is important for diabetes prevention, especially for individuals with high GRS and FH of T2D.
Collapse
|
36
|
Silverman-Retana O, Hulman A, Nielsen J, Ekstrøm CT, Carstensen B, Simmons RK, Bjerg L, Johnston LW, Witte DR. Effect of familial diabetes status and age at diagnosis on type 2 diabetes risk: a nation-wide register-based study from Denmark. Diabetologia 2020; 63:934-943. [PMID: 32076733 DOI: 10.1007/s00125-020-05113-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 01/31/2020] [Indexed: 12/14/2022]
Abstract
AIMS/HYPOTHESIS We assessed whether the risk of developing type 2 diabetes and the age of onset varied with the age at diabetes diagnosis of affected family members. METHODS We performed a national register-based open cohort study of individuals living in Denmark between 1995 and 2012. The population under study consisted of all individuals aged 30 years or older without diagnosed diabetes at the start date of the cohort (1 January 1995) and who had information about their parents' identity. Individuals who turned 30 years of age during the observation period and had available parental identity information were also added to the cohort from that date (open cohort design). These criteria restricted the study population mostly to people born between 1960 and 1982. Multivariable Poisson regression models adjusted for current age and highest educational attainment were used to estimate incidence rate ratios (IRRs) of type 2 diabetes. RESULTS We followed 2,000,552 individuals for a median of 14 years (24,034,059 person-years) and observed 76,633 new cases of type 2 diabetes. Compared with individuals of the same age and sex who did not have a parent or full sibling with diabetes, the highest risk of developing type 2 diabetes was observed in individuals with family members diagnosed at an early age. The IRR was progressively lower with a higher age at diabetes diagnosis in family members: 3.9 vs 1.4 for those with a parental age at diagnosis of 50 or 80 years, respectively; and 3.3 vs 2.0 for those with a full sibling's age at diagnosis of 30 or 60 years, respectively. CONCLUSIONS/INTERPRETATION People with a family member diagnosed with diabetes at an earlier age are more likely to develop diabetes and also to develop it at an earlier age than those with a family member diagnosed in later life. This finding highlights the importance of expanding our understanding of the interplay between genetic diabetes determinants and the social, behavioural and environmental diabetes determinants that track in families across generations. Accurate registration of age at diagnosis should form an integral part of recording a diabetes family history, as it provides easily obtainable and highly relevant detail that may improve identification of individuals at increased risk of younger onset of type 2 diabetes. In particular, these individuals may benefit from closer risk factor assessment and follow-up, as well as prevention strategies that may involve the family.
Collapse
Affiliation(s)
- Omar Silverman-Retana
- Department of Public Health, Aarhus University, Building 1260, Barthollins Allé 2, 8000 Aarhus C, Aarhus, Denmark.
- Danish Diabetes Academy, Odense, Denmark.
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark.
| | - Adam Hulman
- Department of Public Health, Aarhus University, Building 1260, Barthollins Allé 2, 8000 Aarhus C, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
| | - Jannie Nielsen
- Global Health Section, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Claus T Ekstrøm
- Section of Biostatistics, Department of Public Health, University of Copenhagen, Copenhagen, Denmark
| | - Bendix Carstensen
- Clinical Epidemiology Department, Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Rebecca K Simmons
- Department of Public Health, Aarhus University, Building 1260, Barthollins Allé 2, 8000 Aarhus C, Aarhus, Denmark
| | - Lasse Bjerg
- Department of Public Health, Aarhus University, Building 1260, Barthollins Allé 2, 8000 Aarhus C, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
| | - Luke W Johnston
- Department of Public Health, Aarhus University, Building 1260, Barthollins Allé 2, 8000 Aarhus C, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
| | - Daniel R Witte
- Department of Public Health, Aarhus University, Building 1260, Barthollins Allé 2, 8000 Aarhus C, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
- Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus, Denmark
| |
Collapse
|
37
|
Iwata M, Kamura Y, Honoki H, Kobayashi K, Ishiki M, Yagi K, Fukushima Y, Takano A, Kato H, Murakami S, Higuchi K, Kobashi C, Fukuda K, Koshimizu Y, Tobe K. Family history of diabetes in both parents is strongly associated with impaired residual β-cell function in Japanese type 2 diabetes patients. J Diabetes Investig 2020; 11:564-572. [PMID: 31705736 PMCID: PMC7232274 DOI: 10.1111/jdi.13176] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2019] [Revised: 11/05/2019] [Accepted: 11/06/2019] [Indexed: 12/14/2022] Open
Abstract
AIMS/INTRODUCTION The objective of the present study was to clarify the association of the type and number of first-degree family history of diabetes (FHD) with the clinical characteristics, especially with residual β-cell function, in type 2 diabetes patients. MATERIALS AND METHODS A total of 1,131 type 2 diabetes patients were recruited and divided into four groups according to FHD information as follows: (i) patients without FHD (FHD-); (ii) those with at least one sibling who had diabetes without parental diabetes (FHD+); (iii) those with one parent (FHD++); or (iv) those with both parents (FHD+++) who had diabetes with or without a sibling with diabetes. RESULTS The percentages of the FHD-, FHD+, FHD++ and FHD+++ groups were 49.4%, 13.4%, 34.0% and 3.2%, respectively. Patients in the FHD++ and FHD+++ groups were significantly younger at the time of diabetes diagnosis (P < 0.001) than those in the FHD- and FHD+ groups, even after adjusting for confounding factors. In addition, the levels of insulin secretion were significantly lower in the patients in the FHD+, FHD++ and FHD+++ groups than those in the FHD- group (P < 0.05) after adjusting for confounding factors, and the patients in the FHD+++ group presented with the lowest levels of insulin secretion among the four groups. CONCLUSIONS Our results showed that in type 2 diabetes patients, the degree of the associations between FHD and clinical characteristics differs according to the number and the type of FHD. In particular, FHD in both parents is most strongly associated with impaired residual β-cell function.
Collapse
Affiliation(s)
- Minoru Iwata
- First Department of Internal MedicineFaculty of MedicineUniversity of ToyamaToyamaJapan
- Itoigawa Community Medical UnitToyama University HospitalToyamaJapan
| | - Yutaka Kamura
- First Department of Internal MedicineFaculty of MedicineUniversity of ToyamaToyamaJapan
| | - Hisae Honoki
- First Department of Internal MedicineFaculty of MedicineUniversity of ToyamaToyamaJapan
| | - Kaori Kobayashi
- First Department of Internal MedicineFaculty of MedicineUniversity of ToyamaToyamaJapan
| | - Manabu Ishiki
- First Department of Internal MedicineFaculty of MedicineUniversity of ToyamaToyamaJapan
- Center for Medical Education and Career DevelopmentUniversity of ToyamaToyamaJapan
| | - Kunimasa Yagi
- First Department of Internal MedicineFaculty of MedicineUniversity of ToyamaToyamaJapan
| | - Yasuo Fukushima
- Department of Internal MedicineAsahi General HospitalAsahi‐machiJapan
| | - Atsuko Takano
- Division of Endocrinology and MetabolismDepartment of Internal MedicineSaiseikai Takaoka HospitalTakaokaJapan
| | - Hiromi Kato
- Department of Internal MedicineJapan Community Health care Organization Takaoka Fushiki HospitalTakaokaJapan
| | - Shihou Murakami
- Division of Endocrinology and MetabolismDepartment of Internal MedicineToyama Rosai HospitalUozuJapan
| | - Kiyohiro Higuchi
- Department of Internal MedicineJA Niigata Kouseiren Itoigawa General HospitalItoigawaJapan
| | - Chikaaki Kobashi
- Department of Internal MedicineKamiichi General HospitalKamiichi‐machiJapan
| | | | | | - Kazuyuki Tobe
- First Department of Internal MedicineFaculty of MedicineUniversity of ToyamaToyamaJapan
| |
Collapse
|
38
|
Lin Z, Guo D, Chen J, Zheng B. A nomogram for predicting 5-year incidence of type 2 diabetes in a Chinese population. Endocrine 2020; 67:561-568. [PMID: 31820309 DOI: 10.1007/s12020-019-02154-x] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Accepted: 11/27/2019] [Indexed: 02/08/2023]
Abstract
PURPOSE To develop a nomogram for predicting 5-year incidence of type 2 diabetes (T2D) in Chinese adults. METHODS This is a retrospective cohort study from a prospectively collected database. We included a total 32,766 adults free of T2D at baseline with a median follow-up of 3 years. Univariate and multivariate Cox regression analyses were applied to identify independent predictors. A nomogram was constructed to predict 5-year incident rate of T2D based on the multivariate analysis results. Harrell's C-indexes and calibration plots were used to evaluate the accuracy of the nomogram in both internal and external validations. RESULTS The overall prevalence of T2D was 2.1%. Participants were randomly divided into a training set (n = 21,844) and a validation set (n = 10,922). After multivariate analysis in the training set, age, sex, BMI, hypertension, dyslipidemia, smoking status, and family history were found as risk predictors and integrated into the nomogram. Harrell's C-indexes were 0.815 (95% CI: 0.797-0.834) and 0.779 (95% CI: 0.747-0.811) in the training and validation sets, respectively. The calibration plots demonstrated good agreement between the estimated probability and the actual observation. CONCLUSION Our nomogram could be a simple and reliable tool for predicting 5-year risk of developing T2D in high-risk Chinese. Through the model, early identifying high-risk individuals is helpful for timely intervention to reduce the incidence of T2D.
Collapse
Affiliation(s)
- Zeyin Lin
- Department of Ultrasound, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Dongming Guo
- Department of General Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Juntian Chen
- Department of General Surgery, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China
| | - Baoqun Zheng
- Department of Ultrasound, The First Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, China.
| |
Collapse
|
39
|
Almehmadi AH, Alzaid G, Quqandi S, Almalki G, Bannan A, AlHindi A, Idrees A, Habiballah A, Al-Shareef K, Alhazzazi T. Awareness of the Effect of Diabetes on Oral Health among a Population in Jeddah, Saudi Arabia. ORAL HEALTH & PREVENTIVE DENTISTRY 2020; 18:27-34. [PMID: 32051968 PMCID: PMC11654492 DOI: 10.3290/j.ohpd.a44115] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Received: 03/17/2018] [Accepted: 12/16/2018] [Indexed: 11/06/2022]
Abstract
PURPOSE Diabetes is an ever-growing health issue in the Kingdom of Saudi Arabia. It has several oral health implications and oral health in turn affects diabetes control. The primary objective of this research was to study the awareness of the effect of diabetes on oral health among the general population in the city of Jeddah, Saudi Arabia. MATERIALS AND METHODS A closed-ended, validated questionnaire was distributed to 506 randomly selected shopping-mall-goers. Responses were coded and entered into spreadsheet (SPSS, IBM) and frequency distribution of the responses was calculated. RESULTS The majority of the respondents were females (62.5%), non-diabetic (80.2%) and reported a positive family history of diabetes (87.9%). Most of them (63.4%) understood the importance of discussing one's diabetes status with the dentist as it affected the treatment plan, and also knew (84.4%) that diabetes affects oral health in some way. A majority also correctly responded to how diabetes affects oral health (66.3%) and to the sequelae of untreated gum disease (87.2%). The majority of the respondents had not received any tips or information regarding the connection between diabetes and oral health. CONCLUSION This study reported adequate knowledge of the sample with respect to diabetes-related oral health. An important finding of this study was that the majority of the study participants did not receive information leading to diabetes-related oral health awareness or knowledge from anyone, which implies that health professionals and health media do not play the requisite role in dissemination of this important aspect of public health.
Collapse
Affiliation(s)
- Ahmad H. Almehmadi
- Assistant Professor, Department of Oral Biology, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia. Study idea, hypothesis, questionnaire design and validation, evaluation of the results, wrote manuscript
| | - Ghada Alzaid
- Physician, Department of Family Medicine, King Abdulaziz University Hospital, Jeddah, Saudi Arabia. Helped in questionnaire design, wrote manuscript, interpreting results
| | - Sarah Quqandi
- Dentist, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia. Helped formulate questions and determine suitability for the study, participant recruitment, data collection, contributed to the results section
| | - Ghaidaa Almalki
- Dentist, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia. Helped formulate questions and determine suitability for the study, participant recruitment, data collection, contributed to the results section
| | - Abraar Bannan
- Dentist, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia. Helped formulate questions and determine suitability for the study, participant recruitment, data collection, contributed to the results section
| | - Areej AlHindi
- Dentist, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia. Helped formulate questions and determine suitability for the study, participant recruitment, data collection, contributed to the results section
| | - Abdulrahman Idrees
- Dentist, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia. Helped formulate questions and determine suitability for the study, participant recruitment, data collection, contributed to the results section
| | - Anas Habiballah
- Dentist, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia. Helped formulate questions and determine suitability for the study, participant recruitment, data collection, contributed to the results section
| | - Khalid Al-Shareef
- Dentist, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia. Helped formulate questions and determine suitability for the study, participant recruitment, data collection, contributed to the results section
| | - Turki Alhazzazi
- Assistant Professor, Department of Oral Biology, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia. Helped prepare the study, manuscript editing, and contributed to the discussion
| |
Collapse
|
40
|
Aasbjerg K, Nørgaard CH, Vestergaard N, Søgaard P, Køber L, Weeke P, Gislason G, Torp-Pedersen C. Risk of diabetes among related and unrelated family members. Diabetes Res Clin Pract 2020; 160:107997. [PMID: 31901471 DOI: 10.1016/j.diabres.2019.107997] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Revised: 12/13/2019] [Accepted: 12/30/2019] [Indexed: 01/07/2023]
Abstract
AIMS The aim was to explore familial aggregation of diabetes in genetically related and unrelated individuals. METHODS We included citizens from Danish nationwide registries between 1995 and 2018 and calculated rate ratios (RR) of diabetes based on family relation using Poisson regression. RESULTS Of 7.3 million individuals eligible for inclusion, we identified 343,237 (4.7%) with diabetes. The RR of diabetes was 2.02 (95% CI: 1.99-2.05; p < 0.0001) if any relative had diabetes, 1.79 (95% CI: 1.76-1.83) if a father had diabetes, and 2.06 (95% CI: 2.02-2.10) if a mother had diabetes. If both parents had diabetes, the RR was 3.40 (95% CI: 3.24-3.56). Among full siblings, the RR for developing diabetes was 2.77 (95% CI: 2.71-2.84) and 5.76 (95% CI: 5.00-6.63) for twins. For second-degree relatives, half siblings with a common mother had a RR of 2.35 (95% CI: 2.15-2.56), and with a common father 1.99 (95% CI: 1.81-2.17). Furthermore, the RR was 1.60 (95% CI: 1.56-1.64) if a wife had diabetes, and 1.41 (95% CI: 1.38-1.44) if a husband had diabetes. A subgroup analysis of individuals receiving insulin only treatment (N = 23,054) demonstrated a similar risk pattern, although with slightly higher risk estimates. CONCLUSIONS/INTERPRETATION Family aggregation of diabetes is associated with genetic disposition with maternal status being the predominant factor. Furthermore, we observed increased risk of diabetes in second-degree relatives, and between unrelated spouses, indicating that environmental factors influence diabetes risk substantially.
Collapse
Affiliation(s)
- Kristian Aasbjerg
- Department of Ophthalmology, Aarhus University Hospital, DK-8200 Aarhus N, Denmark; Aalborg University Hospital, Unit of Epidemiology and Biostatistics, Hobrovej 18-22, PO-box 365, DK-9000 Aalborg, Denmark.
| | - Caroline Holm Nørgaard
- Department of Cardiology and Clinical Research, Nordsjællands University Hospital, Hillerød, Denmark
| | - Nanna Vestergaard
- Department of Ophthalmology, Aarhus University Hospital, DK-8200 Aarhus N, Denmark; Aalborg University Hospital, Unit of Epidemiology and Biostatistics, Hobrovej 18-22, PO-box 365, DK-9000 Aalborg, Denmark
| | - Peter Søgaard
- Department of Cardiology, Aalborg University Hospital, DK-9000 Aalborg, Denmark
| | - Lars Køber
- Department of Cardiology, Copenhagen University Hospital, Rigshospitalet, Denmark
| | - Peter Weeke
- Department of Cardiology, Copenhagen University Hospital, Rigshospitalet, Denmark
| | - Gunnar Gislason
- Copenhagen University Hospital Herlev and Gentofte, Department of Cardiology, Kildegårdsvej 28, DK-2900 Hellerup, Denmark; The Danish Heart Foundation, Vognmagergade 7, 1120 Copenhagen, Denmark; The National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
| | - Christian Torp-Pedersen
- Department of Cardiology and Clinical Research, Nordsjællands University Hospital, Hillerød, Denmark
| |
Collapse
|
41
|
Wang(a) J, Wang S, Wang(b) J, Xiao M, Guo Y, Tang Y, Zhang J, Gu J. Epigenetic Regulation Associated With Sirtuin 1 in Complications of Diabetes Mellitus. Front Endocrinol (Lausanne) 2020; 11:598012. [PMID: 33537003 PMCID: PMC7848207 DOI: 10.3389/fendo.2020.598012] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Accepted: 11/27/2020] [Indexed: 01/19/2023] Open
Abstract
Diabetes mellitus (DM) has been one of the largest health concerns of the 21st century due to the serious complications associated with the disease. Therefore, it is essential to investigate the pathogenesis of DM and develop novel strategies to reduce the burden of diabetic complications. Sirtuin 1 (SIRT1), a nicotinamide adenosine dinucleotide (NAD+)-dependent deacetylase, has been reported to not only deacetylate histones to modulate chromatin function but also deacetylate numerous transcription factors to regulate the expression of target genes, both positively and negatively. SIRT1 also plays a crucial role in regulating histone and DNA methylation through the recruitment of other nuclear enzymes to the chromatin. Furthermore, SIRT1 has been verified as a direct target of many microRNAs (miRNAs). Recently, numerous studies have explored the key roles of SIRT1 and other related epigenetic mechanisms in diabetic complications. Thus, this review aims to present a summary of the rapidly growing field of epigenetic regulatory mechanisms, as well as the epigenetic influence of SIRT1 on the development and progression of diabetic complications, including cardiomyopathy, nephropathy, and retinopathy.
Collapse
Affiliation(s)
- Jie Wang(a)
- School of Nursing, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Shudong Wang
- Department of Cardiology at the First Hospital of Jilin University, Changchun, China
| | - Jie Wang(b)
- School of Nursing, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Mengjie Xiao
- School of Nursing, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Yuanfang Guo
- School of Nursing, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Yufeng Tang
- Department of Orthopedic Surgery, The First Affiliated Hospital of Shandong First Medical University, Jinan, China
| | - Jingjing Zhang
- Department of Cardiology at the First Hospital of China Medical University, and Department of Cardiology at the People’s Hospital of Liaoning Province, Shenyang, China
| | - Junlian Gu
- School of Nursing, Cheeloo College of Medicine, Shandong University, Jinan, China
- *Correspondence: Junlian Gu,
| |
Collapse
|
42
|
Santos CESD, Rech CR, Antes DL, Schneider IJC, d’Orsi E, Benedetti TRB. Incidence and prevalence of diabetes self-reported on elderly in south of Brazil: results of EpiFloripa Ageing Study. CIENCIA & SAUDE COLETIVA 2019; 24:4191-4200. [DOI: 10.1590/1413-812320182411.31092017] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2017] [Accepted: 04/17/2018] [Indexed: 11/22/2022] Open
Abstract
Abstract This study investigated the prevalence and incidence of diabetes self-referred in the elderly. Longitudinal population-based study (EpiFloripa Ageing Study), with 1.702 elderly in 2009/10 and 1.197 in 2013/14 of Florianópolis, SC. Self-reported and anthropometric data were collected at home. The prevalence of diabetes self-referred in 2009/10 was 22.1% (95%CI 20.1-24.1). The characteristics were: no formal schooling (2.30; CI95% 1.32-4.00); 5 to 8 years of schooling (OR = 1.70, CI95% 1.07-2.69); increased waist circumference (OR = 3.31, CI95% 2.05-5.34) and hypertension (OR = 2.38, CI95%: 1.68-3.36). The incidence of diabetes self-reported after four years of follow-up was 8.3% (95% CI, 6.7-10.3). After adjustment: increased waist circumference (OR= 2.23, CI95% 1.09-4.57) at baseline was associated with the incidence of diabetes. The prevalence and incidence of diabetes were high among the elderly. Interventions must be performed especially with elderly with low and without formal schooling, with increased waist circumference and hypertension, thus they were the subgroups with higher odds ratio of reporting and developing diabetes.
Collapse
|
43
|
Genes associated with Type 2 Diabetes and vascular complications. Aging (Albany NY) 2019; 10:178-196. [PMID: 29410390 PMCID: PMC5842840 DOI: 10.18632/aging.101375] [Citation(s) in RCA: 36] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2017] [Accepted: 01/30/2018] [Indexed: 12/20/2022]
Abstract
Type 2 Diabetes (T2D) is a chronic disease associated with a number of micro- and macrovascular complications that increase the morbidity and mortality of patients. The risk of diabetic complications has a strong genetic component. To this end, we sought to evaluate the association of 40 single nucleotide polymorphisms (SNPs) in 21 candidate genes with T2D and its vascular complications in 503 T2D patients and 580 healthy controls. The genes were chosen because previously reported to be associated with T2D complications and/or with the aging process. We replicated the association of T2D risk with IGF2BP rs4402960 and detected novel associations with TERT rs2735940 and rs2736098. The addition of these SNPs to a model including traditional risk factors slightly improved risk prediction. After stratification of patients according to the presence/absence of vascular complications, we found significant associations of variants in the CAT, FTO, and UCP1 genes with diabetic retinopathy and nephropathy. Additionally, a variant in the ADIPOQ gene was found associated with macrovascular complications. Notably, these genes are involved in some way in mitochondrial biology and reactive oxygen species regulation. Hence, our findings strongly suggest a potential link between mitochondrial oxidative homeostasis and individual predisposition to diabetic vascular complications.
Collapse
|
44
|
Almehmadi AH. Awareness of population regarding the effects of diabetes on dental implant treatment in Jeddah, Saudi Arabia. Heliyon 2019; 5:e02407. [PMID: 31687541 PMCID: PMC6819952 DOI: 10.1016/j.heliyon.2019.e02407] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2019] [Revised: 06/28/2019] [Accepted: 08/29/2019] [Indexed: 11/30/2022] Open
Abstract
OBJECTIVE Diabetes mellitus (DM) has several complications. Delayed wound healing, microvascular disease and an impaired response to infections are complications that can have a direct bearing on dental implant therapy. This paper studies the awareness of the population with regard to the effect of DM on dental implant treatment. MATERIALS AND METHODS A validated, close-ended questionnaire was distributed to 506 randomly selected mall-goers in the city of Jeddah. Responses were coded and entered into spreadsheet software (SPSS, IBM). The frequency distribution of the responses was calculated, and inferences were drawn. RESULTS The study revealed that the majority of the sample were females (62.8%), did not have diabetes (80.4%) and reported a positive family history of diabetes (87.4%). Most of the respondents (56%) believed that uncontrolled diabetes can lead to implant loss and that diabetes affects the healing process (91.6%). Many patients (42%) responded that diabetes could be treated with dental implants if the blood sugar level was controlled. CONCLUSION The studied sample revealed a satisfactory level of awareness regarding the association of diabetes and oral hygiene in dental implant therapy. However, there is less than adequate knowledge about the effects of diabetes on dental implants, as the majority of the respondents believe that only controlled diabetics can avail dental implant treatment.
Collapse
Affiliation(s)
- Ahmad H. Almehmadi
- Department of Oral Biology, Faculty of Dentistry, King Abdulaziz University, Jeddah, Saudi Arabia
| |
Collapse
|
45
|
Ramezankhani A, Guity K, Azizi F, Hadaegh F. Sex differences in the association between spousal metabolic risk factors with incidence of type 2 diabetes: a longitudinal study of the Iranian population. Biol Sex Differ 2019; 10:41. [PMID: 31439024 PMCID: PMC6704543 DOI: 10.1186/s13293-019-0255-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2019] [Accepted: 08/12/2019] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND We investigated whether metabolic risk factors in one spouse were associated with an excessive risk of type 2 diabetes in the other. METHODS The study cohort (1999-2018) included 1833 men and 1952 women, aged ≥ 20 years with information on both their own and their spouse's diabetes status and metabolic risk factors including body mass index (BMI), waist circumference, systolic and diastolic blood pressure, triglyceride to high-density lipoprotein cholesterol ratio, and type 2 diabetes. The associations between spousal metabolic risk factors and type 2 diabetes were estimated using Cox regression models adjusted for the three nested sets of covariates. RESULTS We found 714 (360 men and 354 women) incident cases of type 2 diabetes, after more than 15 years of follow-up. Among women, having a husband with diabetes was associated with a 38% (hazard ratio (HR) 1.38; 95% confidence interval (CI) 1.03, 1. 84) increased risk of type 2 diabetes, adjusted for age, socioeconomic status, individual's own value of the respective spousal exposure variable, family history of diabetes, and physical activity level. After further adjustment for the woman's own BMI level, the husband's diabetes was associated with 23% (HR 1.23; 0.92, 1.64) higher risk of type 2 diabetes in wives, values which did not reach statistical significance. No significant associations were found between spousal metabolic risk factors and incidence of type 2 diabetes among index men. CONCLUSION We found a sex-specific effect of spousal diabetes on the risk of type 2 diabetes. Having a husband with diabetes increased an individual's risk of type 2 diabetes. Our results might contribute to the early detection of individuals at high risk of developing type 2 diabetes, particularly, in women adversely affected by their partner's diabetes.
Collapse
Affiliation(s)
- Azra Ramezankhani
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Kamran Guity
- Cellular and Molecular Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Fereidoun Azizi
- Endocrine Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Farzad Hadaegh
- Prevention of Metabolic Disorders Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
| |
Collapse
|
46
|
Appiah D, Schreiner PJ, Selvin E, Demerath EW, Pankow JS. Spousal diabetes status as a risk factor for incident type 2 diabetes: a prospective cohort study and meta-analysis. Acta Diabetol 2019; 56:619-629. [PMID: 30888538 PMCID: PMC6520150 DOI: 10.1007/s00592-019-01311-y] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2019] [Accepted: 02/19/2019] [Indexed: 12/31/2022]
Abstract
AIMS It is unclear if the presence of type-2 diabetes in one spouse is associated with the development of diabetes in the other spouse. We studied the concordance of diabetes among black and white participants in the Atherosclerosis Risk in Communities (ARIC) study and summarized existing studies in a meta-analysis. METHODS We conducted a prospective cohort analysis of ARIC data from 8077 married men and women (mean age 54 years) without diabetes at baseline (1987-1989). Complementary log-log models that accounted for interval censoring was used to model the hazard ratio (HR) for the association of spousal diabetes status with the incidence of diabetes. For the meta-analysis, we searched MEDLINE and EMBASE for observational studies published through December 2018 that evaluated spousal concordance for diabetes. RESULTS During a median follow-up of 22 years, 2512 incident cases of diabetes were recorded. In models with adjustment for general adiposity, spousal cardiometabolic factors and other diabetes risk factors, adults who had a spouse with diabetes had elevated risk for incident diabetes compared to those without a spouse diagnosed with diabetes (HR 1.20, 95% confidence interval 1.02-1.41). This association did not differ by sex or race. Summarized estimates from the 17 studies (489,798 participants from 9 countries) included in the meta-analysis showed a positive association between spousal diabetes status and the development of diabetes (Pooled odds ratio 1.88, 95% CI 1.52-2.33). CONCLUSIONS Results from this large prospective biracial cohort and meta-analysis provides evidence that spouses of persons with diabetes are a high-risk group for diabetes.
Collapse
Affiliation(s)
- Duke Appiah
- Department of Public Health, Texas Tech University Health Sciences Center, 3601 4th Street, STOP 9430, Lubbock, TX, 79430, USA.
| | - Pamela J Schreiner
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Elizabeth Selvin
- Department of Epidemiology, Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Ellen W Demerath
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - James S Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| |
Collapse
|
47
|
Alharithy MK, Alobaylan MM, Alsugair ZO, Alswat KA. Impact of Family History of Diabetes on Diabetes Control and Complications. Endocr Pract 2018; 24:773-779. [PMID: 30308135 DOI: 10.4158/ep-2018-0071] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
OBJECTIVE Our aim was to assess the impact of parental and sibling history of type 2 diabetes (T2D) on patient characteristics, glycemic control, and T2D complications. METHODS This cross-sectional study included adults with T2D. Type 1 diabetes and gestational diabetes patients were excluded. The laboratory data were retrieved from the patients' electronic files, and baseline measurements were obtained by the researchers. RESULTS The study included a total of 511 T2D patients, with a mean age of 60.1 ± 10.9 years and mean hemoglobin A1c of 8.94 ± 2.1% (74.2 ± 22.9 mmol/mol). Of these patients, 54% were male and 49.7% had a parental history of T2D. The patients with parental history of T2D were diagnosed at a younger age and had a higher body mass index (BMI) ( P = .035) and higher waist circumference (WC) ( P = .013) than those T2D patients with no parental history. Approximately 60% of the participants had siblings with a history of T2D, and in comparison with those with no sibling history, they had higher prevalence of cerebrovascular accidents ( P = .02). CONCLUSION Having a parental history of T2D is significantly associated with diagnosis at a younger age and a higher BMI and WC. Having a sibling history of T2D is significantly associated with worse cerebrovascular outcome. ABBREVIATIONS ACR = albumin to creatinine ratio; BMI = body mass index; DBP = diastolic blood pressure; DM = diabetes mellitus; FBG = fasting blood glucose; GFR = glomerular filtration rate; HbA1c = hemoglobin A1c; LDL = low-density lipoprotein; SBP = systolic blood pressure; T2D = type 2 diabetes; TG = triglyceride; WC = waist circumference.
Collapse
|
48
|
Nielsen J, Hulman A, Witte DR. Spousal cardiometabolic risk factors and incidence of type 2 diabetes: a prospective analysis from the English Longitudinal Study of Ageing. Diabetologia 2018. [PMID: 29520580 DOI: 10.1007/s00125-018-4587-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
AIMS/HYPOTHESIS In the UK, more than one million people have undiagnosed diabetes and an additional five million are at high risk of developing the disease. Given that early identification of these people is key for both primary and secondary prevention, new screening approaches are needed. Since spouses resemble each other in cardiometabolic risk factors related to type 2 diabetes, we aimed to investigate whether diabetes and cardiometabolic risk factors in one spouse can be used as an indicator of incident type 2 diabetes in the other spouse. METHODS We analysed data from 3649 men and 3478 women from the English Longitudinal Study of Ageing with information on their own and their spouse's diabetes status and cardiometabolic risk factors. We modelled incidence rates and incidence rate ratios with Poisson regression, using spousal diabetes status or cardiometabolic risk factors (i.e. BMI, waist circumference, systolic and diastolic BP, HDL- and LDL-cholesterol and triacylglycerols) as exposures and type 2 diabetes incidence in the index individual as the outcome. Models were adjusted for two nested sets of covariates. RESULTS Spousal BMI and waist circumference were associated with incident type 2 diabetes, but with different patterns for men and women. A man's risk of type 2 diabetes increased more steeply with his wife's obesity level, and the association remained statistically significant even after adjustment for the man's own obesity level. Having a wife with a 5 kg/m2 higher BMI (30 kg/m2 vs 25 kg/m2) was associated with a 21% (95% CI 11%, 33%) increased risk of type 2 diabetes. In contrast, the association between incident type 2 diabetes in a woman and her husband's BMI was attenuated after adjusting for the woman's own obesity level. Findings for waist circumference were similar to those for BMI. Regarding other risk factors, we found a statistically significant association only between the risk of type 2 diabetes in women and their husbands' triacylglycerol levels. CONCLUSIONS/INTERPRETATION The main finding of this study is the sex-specific effect of spousal obesity on the risk of type 2 diabetes. Having an obese spouse increases an individual's risk of type 2 diabetes over and above the effect of the individual's own obesity level among men, but not among women. Our results suggest that a couples-focused approach may be beneficial for the early detection of type 2 diabetes and individuals at high risk of developing type 2 diabetes, especially in men, who are less likely than women to attend health checks. DATA AVAILABILITY Data were accessed via the UK Data Service under the data-sharing agreement no. 91400 ( https://discover.ukdataservice.ac.uk/catalogue/?sn=5050&type=Data%20catalogue ).
Collapse
Affiliation(s)
- Jannie Nielsen
- Global Health Section, Department of Public Health, University of Copenhagen, Oester Farimagsgade 5, Building 9, Mailbox 2099, 1014, Copenhagen K., Denmark.
- Hubert Department of Global Health, Rollins School of Public Health, Emory University, Atlanta, GA, USA.
| | - Adam Hulman
- Department of Public Health, Aarhus University, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
| | - Daniel R Witte
- Department of Public Health, Aarhus University, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
| |
Collapse
|
49
|
Schmittdiel JA, Cunningham SA, Adams SR, Nielsen J, Ali MK. Influence of a New Diabetes Diagnosis on the Health Behaviors of the Patient's Partner. Ann Fam Med 2018; 16:290-295. [PMID: 29987075 PMCID: PMC6037527 DOI: 10.1370/afm.2259] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/28/2017] [Revised: 02/23/2018] [Accepted: 03/21/2018] [Indexed: 11/09/2022] Open
Abstract
PURPOSE When a person is given a diagnosis of diabetes, the changes in his or her health behaviors may influence the behaviors of his or her partner. The diabetes diagnosis may affect household members' perceptions of their own health risks, which could trigger behavioral change. The purpose of this study was to assess whether partners of persons with newly diagnosed diabetes changed their health behaviors compared with partners of persons without diabetes. METHODS The study population consisted of Kaiser Permanente Northern California health plan members from 2007 to 2011. This cohort study assessed differences in change of 8 health behaviors. The study compared coresiding partners of persons with newly diagnosed diabetes before and after a diabetes diagnosis with a 5 to 1 matched sample of coresiding partners of persons without diabetes. RESULTS A total of 180,910 couples were included in the analysis. After adjusting for baseline characteristics, partners of persons with newly diagnosed diabetes had significantly higher rates of participation in weight management-related health education classes (risk ratio [RR] = 1.50; 95% CI, 1.39-1.63); smoking cessation medication use (RR = 1.25; 95% CI, 1.05-1.50); glucose screening (RR = 1.07; 95% CI, 1.05-1.08); clinically meaningful weight loss (RR = 1.06; 95% CI, 1.02-1.11); lipid screening (RR = 1.05; 95% CI, 1.04-1.07); influenza vaccination (RR = 1.03; 95% CI, 1.02-1.04); and blood pressure screening (RR = 1.02; 95% CI, 1.02-1.03) compared with partners of persons without diabetes. CONCLUSIONS There were small but significant differences in health-related behavioral changes among partners of persons with newly diagnosed diabetes compared with partners of persons without diabetes, even when no intervention occurred. This finding suggests a diabetes diagnosis within a family may be a teachable moment to improve health behaviors at the household level.
Collapse
Affiliation(s)
- Julie A Schmittdiel
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | | | - Sara R Adams
- Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Jannie Nielsen
- Hubert Department of Global Health, Emory University, Atlanta, Georgia.,Global Health Section, Department of Public Health, University of Copenhagen, Denmark
| | | |
Collapse
|
50
|
Örnolfsson KT, Olafsson S, Bergmann OM, Gershwin ME, Björnsson ES. Using the Icelandic genealogical database to define the familial risk of primary biliary cholangitis. Hepatology 2018; 68:166-171. [PMID: 29159924 DOI: 10.1002/hep.29675] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Revised: 10/17/2017] [Accepted: 11/17/2017] [Indexed: 12/13/2022]
Abstract
UNLABELLED Hereditary factors in primary biliary cholangitis (PBC) have been well defined in genome-wide association studies, but there are few direct data available that define the relative risk (RR) for family members with an affected proband. An increased risk in first-degree relatives has been demonstrated in a variety of studies, but data have been lacking on further detailed associations for subsequent generations. The objective of this study was to use the unique Icelandic genealogical database to study the familiality of PBC. All patients with positive antimitochondrial antibody measurements in Iceland during the period 1991-2015 who fulfilled diagnostic criteria for PBC were included. The Icelandic genealogical database was used to assess familial relations. For each case of PBC, 10,000 control subjects matched for age, sex, and number of known relatives were randomly chosen from this database to calculate the familial RR of PBC. The average kinship coefficient (KC) of the patients was calculated and compared with the average KC of controls. Overall, 222 PBC patients were identified (182 females, 40 males; median age, 62 years). First-, second- and third-degree relatives of the PBC patients had a high RR of the disease: 9.13 (P < 0.0001), 3.61 (P = 0.014) and 2.59 (P = 0.008), respectively. In fourth- and fifth-degree relatives, the RR was also increased to 1.66 (P = 0.08) and 1.42 (P = 0.08), respectively. The average KC of the patients was also higher than that of the control subjects, with 21.34 × 10-5 versus 9.56 × 10-5 (P < 0.0001). CONCLUSION Relatives of PBC patients had markedly higher risk for development of the disease compared with controls and importantly our data demonstrate that the risk was significantly increased even in second- and third-degree relatives. (Hepatology 2018;68:166-171).
Collapse
Affiliation(s)
- Kristjan T Örnolfsson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland.,Division of Gastroenterology and Hepatology, Landspitali, The National University Hospital of Iceland, Reykjavik, Iceland
| | - Sigurdur Olafsson
- Division of Gastroenterology and Hepatology, Landspitali, The National University Hospital of Iceland, Reykjavik, Iceland
| | - Ottar M Bergmann
- Division of Gastroenterology and Hepatology, Landspitali, The National University Hospital of Iceland, Reykjavik, Iceland
| | - M Eric Gershwin
- Department of Rheumatology, University of California, Davis, CA
| | - Einar S Björnsson
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland.,Division of Gastroenterology and Hepatology, Landspitali, The National University Hospital of Iceland, Reykjavik, Iceland
| |
Collapse
|