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García-Hermoso A, Ramírez-Vélez R, Díez J, González A, Izquierdo M. Exercise training-induced changes in exerkine concentrations may be relevant to the metabolic control of type 2 diabetes mellitus patients: A systematic review and meta-analysis of randomized controlled trials. JOURNAL OF SPORT AND HEALTH SCIENCE 2023; 12:147-157. [PMID: 36351545 PMCID: PMC10105032 DOI: 10.1016/j.jshs.2022.11.003] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 09/24/2022] [Accepted: 10/17/2022] [Indexed: 06/01/2023]
Abstract
BACKGROUND This study investigates the effects of exercise training on exerkines in patients with type 2 diabetes mellitus to determine the optimal exercise prescription. METHODS A systematic search for relevant studies was performed in 3 databases. Randomized controlled trials investigating the effects of exercise training on at least one of the following exerkines were included: adiponectin, apelin, brain-derived neurotrophic factor, fetuin-A, fibroblast growth factor-21, follistatin, ghrelin, interleukin (IL)-6, IL-8, IL-10, IL-15, IL-18, leptin, myostatin, omentin, resistin, retinol-binding protein 4, tumor necrosis factor-α, and visfatin. RESULTS Forty randomized controlled trials were selected for data extraction (n = 2160). Exercise training induces changes in adiponectin, fetuin-A, fibroblast growth factor-21, IL-6, IL-10, leptin, resistin, and tumor necrosis factor-α levels but has no significant effects on apelin, IL-18, and ghrelin compared to controls. Physical exercise training favored large and positive changes in pooled exerkines (i.e., an overall effect size calculated from several exerkines) (Hedge's g = 1.02, 95% confidence interval (95%CI): 0.76-1.28), which in turn were related to changes in glycated hemoglobin (mean difference (MD) = -0.81%, 95%CI: -0.95% to -0.67%), fasting glucose (MD = -23.43 mg/dL, 95%CI: -30.07 mg/dL to -16.80 mg/dL), waist circumference (MD = -3.04 cm, 95%CI: -4.02 cm to -2.07 cm), and body mass (MD = -1.93 kg, 95%CI: -2.00 kg to -1.86 kg). Slightly stronger effects were observed with aerobic, resistance, or high-intensity interval protocols at moderate- to vigorous-intensity and with programs longer than 24 weeks that comprise at least 3 sessions per week and more than 60 min per session. CONCLUSION Exercise training represents an anti-inflammatory therapy and metabolism-improving strategy with minimal side effects for patients with type 2 diabetes mellitus.
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Affiliation(s)
- Antonio García-Hermoso
- Navarrabiomed, Public University of Navarra (UPNA), Health Research Institute of Navarra (IdiSNA), University Hospital of Navarra, Pamplona 310008, Spain; CIBER of Frailty and Healthy Aging (CIBERFES), Carlos III Institute of Health, Madrid 28029, Spain.
| | - Robinson Ramírez-Vélez
- Navarrabiomed, Public University of Navarra (UPNA), Health Research Institute of Navarra (IdiSNA), University Hospital of Navarra, Pamplona 310008, Spain; CIBER of Frailty and Healthy Aging (CIBERFES), Carlos III Institute of Health, Madrid 28029, Spain; Institute for Health Research of Navarra (IDISNA), Pamplona 31008, Spain
| | - Javier Díez
- Institute for Health Research of Navarra (IDISNA), Pamplona 31008, Spain; Program of Cardiovascular Diseases, Center for Applied Medical Research, University of Navarra, Pamplona 31008, Spain; Centre for Biomedical Research in Cardiovascular Disease Network, Carlos III Institute of Health, Madrid 28029, Spain; Departments of Nephrology and Cardiology, University of Navarra Clinic, Pamplona 31008, Spain
| | - Arantxa González
- Institute for Health Research of Navarra (IDISNA), Pamplona 31008, Spain; Program of Cardiovascular Diseases, Center for Applied Medical Research, University of Navarra, Pamplona 31008, Spain; Centre for Biomedical Research in Cardiovascular Disease Network, Carlos III Institute of Health, Madrid 28029, Spain
| | - Mikel Izquierdo
- Navarrabiomed, Public University of Navarra (UPNA), Health Research Institute of Navarra (IdiSNA), University Hospital of Navarra, Pamplona 310008, Spain; CIBER of Frailty and Healthy Aging (CIBERFES), Carlos III Institute of Health, Madrid 28029, Spain; Institute for Health Research of Navarra (IDISNA), Pamplona 31008, Spain
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Yoshimoto M, Sakuma Y, Ogino J, Iwai R, Watanabe S, Inoue T, Takahashi H, Suzuki Y, Kinoshita D, Takemura K, Takahashi H, Shimura H, Babazono T, Yoshida S, Hashimoto N. Sex differences in predictive factors for onset of type 2 diabetes in Japanese individuals: A 15-year follow-up study. J Diabetes Investig 2022; 14:37-47. [PMID: 36200977 PMCID: PMC9807159 DOI: 10.1111/jdi.13918] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 08/25/2022] [Accepted: 09/19/2022] [Indexed: 02/07/2023] Open
Abstract
AIMS/INTRODUCTION The increase in the number of patients with type 2 diabetes mellitus is an important concern worldwide. The goal of this study was to investigate factors involved in the onset of type 2 diabetes mellitus, and sex differences in long-term follow up of people with normal glucose tolerance. MATERIALS AND METHODS Of 1,309 individuals who underwent screening at our facility in 2004, 748 individuals without diabetes were enrolled. Correlations of metabolic markers including serum adiponectin (APN) with onset of type 2 diabetes mellitus were examined over 15 years in these individuals. RESULTS The Kaplan-Meier curve for onset of type 2 diabetes mellitus for 15 years in the decreased APN group was examined. Hazard ratios for the APN concentration for onset of diabetes were 1.78 (95% confidence interval [CI] 1.20-2.63, P = 0.004) in all participants, 1.48 (95% CI 0.96-2.29, P = 0.078) for men and 3.01 (95% CI 1.37-6.59, P = 0.006) for women. During the follow-up period of 15 years, body mass index, estimated glomerular filtration rate, fatty liver, C-reactive protein and alanine aminotransferase in men were significant in univariate analysis, but only estimated glomerular filtration rate and fatty liver were significantly related to onset of type 2 diabetes mellitus in multivariate analysis. In women, body mass index, systolic blood pressure, triglyceride, fatty liver and APN were significant in univariate analysis, and APN was the only significant risk factor in multivariate analysis (P < 0.05). CONCLUSIONS There are differences between men and women with regard to targets for intervention to prevent the onset of type 2 diabetes mellitus. Individuals requiring intensive intervention should be selected with this finding to maximize the use of limited social and economic resources.
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Affiliation(s)
- Mei Yoshimoto
- Department of Diabetes, Endocrine and Metabolic Diseases, Yachiyo Medical CenterTokyo Women's Medical UniversityYachiyo, ChibaJapan
| | - Yukie Sakuma
- Clinical Research Support CenterAsahi General HospitalAsahi, ChibaJapan
| | - Jun Ogino
- Department of Diabetes and Metabolic DiseasesAsahi General HospitalAsahi, ChibaJapan
| | - Rie Iwai
- Department of Clinical LaboratoryAsahi General HospitalAsahi, ChibaJapan
| | - Saburo Watanabe
- Clinical Research Support CenterAsahi General HospitalAsahi, ChibaJapan
| | - Takeshi Inoue
- Clinical Research Support CenterAsahi General HospitalAsahi, ChibaJapan
| | - Haruo Takahashi
- Clinical Research Support CenterAsahi General HospitalAsahi, ChibaJapan
| | - Yoshifumi Suzuki
- Department of Diabetes and Metabolic DiseasesAsahi General HospitalAsahi, ChibaJapan
| | - Daisuke Kinoshita
- Department of Diabetes and Metabolic DiseasesAsahi General HospitalAsahi, ChibaJapan
| | - Koji Takemura
- Department of Diabetes and Metabolic DiseasesAsahi General HospitalAsahi, ChibaJapan
| | - Hidenori Takahashi
- Preventive Medicine Research CenterAsahi General HospitalAsahi, ChibaJapan
| | - Haruhisa Shimura
- Preventive Medicine Research CenterAsahi General HospitalAsahi, ChibaJapan,Department of Internal MedicineAsahi General HospitalAsahi, ChibaJapan
| | - Tetsuya Babazono
- Department of Medicine, Diabetes Center, School of MedicineTokyo Women's Medical UniversityTokyoJapan
| | - Shouji Yoshida
- Department of Internal MedicineAsahi General HospitalAsahi, ChibaJapan
| | - Naotake Hashimoto
- Preventive Medicine Research CenterAsahi General HospitalAsahi, ChibaJapan
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Liu D, Wu L, Gao Q, Long X, Hou X, Qian L, Ni J, Fang Q, Li H, Jia W. FGF21/adiponectin ratio predicts deterioration in glycemia: a 4.6-year prospective study in China. Cardiovasc Diabetol 2021; 20:157. [PMID: 34321008 PMCID: PMC8320224 DOI: 10.1186/s12933-021-01351-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/21/2021] [Accepted: 07/21/2021] [Indexed: 12/29/2022] Open
Abstract
Background The fibroblast growth factor (FGF) 21-adiponectin pathway is involved in the regulation of insulin resistance. However, the relationship between the FGF21-adiponectin pathway and type 2 diabetes in humans is unclear. Here, we investigated the association of FGF21/adiponectin ratio with deterioration in glycemia in a prospective cohort study. Methods We studied 6361 subjects recruited from the prospective Shanghai Nicheng Cohort Study in China. The association between baseline FGF21/adiponectin ratio and new-onset diabetes and incident prediabetes was evaluated using multiple logistic regression analysis. Results At baseline, FGF21/adiponectin ratio levels increased progressively with the deterioration in glycemic control from normal glucose tolerance to prediabetes and diabetes (p for trend < 0.001). Over a median follow-up of 4.6 years, 195 subjects developed new-onset diabetes and 351 subjects developed incident prediabetes. Elevated baseline FGF21/adiponectin ratio was a significant predictor of new-onset diabetes independent of traditional risk factors, especially in subjects with prediabetes (odds ratio, 1.367; p = 0.001). Moreover, FGF21/adiponectin ratio predicted incident prediabetes (odds ratio, 1.185; p = 0.021) while neither FGF21 nor adiponectin were independent predictors of incident prediabetes (both p > 0.05). Furthermore, net reclassification improvement and integrated discrimination improvement analyses showed that FGF21/adiponectin ratio provided a better performance in diabetes risk prediction than the use of FGF21 or adiponectin alone. Conclusions FGF21/adiponectin ratio independently predicted the onset of prediabetes and diabetes, with the potential to be a useful biomarker of deterioration in glycemia. Supplementary Information The online version contains supplementary material available at 10.1186/s12933-021-01351-1.
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Affiliation(s)
- Dan Liu
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China.,Department of Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Liang Wu
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Qiongmei Gao
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Xiaoxue Long
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China.,Department of Medicine, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xuhong Hou
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Lingling Qian
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Jiacheng Ni
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Qichen Fang
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China
| | - Huating Li
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China.
| | - Weiping Jia
- Department of Endocrinology and Metabolism, Shanghai Diabetes Institute, Shanghai Clinical Center for Diabetes, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, 600 Yishan Road, Shanghai, 200233, China.
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Dias GD, Cartolano FC, Freitas MCP, Santa-Helena E, Markus MRP, Santos RD, Damasceno NRT. Adiponectin predicts the antioxidant capacity and size of high-density lipoprotein (HDL) in individuals with diabetes mellitus. J Diabetes Complications 2021; 35:107856. [PMID: 33627254 DOI: 10.1016/j.jdiacomp.2021.107856] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/19/2020] [Revised: 12/09/2020] [Accepted: 01/03/2021] [Indexed: 01/13/2023]
Abstract
AIMS The relationship between adiponectin and type 2 diabetes mellitus (T2DM) is established; however the evidence on its role in high-density lipoprotein (HDL) functionality is still scant. The aim of this study was to assess the association of adiponectin with HDL functionality especially on the antioxidant capacity and HDL subfractions in individuals with T2DM. METHODS This case-control study enrolled 356 individuals who were divided into two groups: diabetics [T2DM (n = 188)] and non-diabetic [nT2DM (n = 168)]. The association of adiponectin level on HDL functionality parameters was done in function of the cut-off point for adiponectin [percentile p < 75 = 12.9 μg/mL versus p ≥ 75 = 12.9 μg/mL] and multiple adjustments applied in the logistic regression models. RESULTS Body mass index (BMI), waist circumference (WC) and body fat mass (FM) were higher in T2DM. The larger HDL particles (HDLLARGE) were lower in T2DM group in comparison with nT2DM (28.20% versus 30.40%; p = 0.016). Individuals with T2DM and simultaneous highest adiponectin (p ≥ 75) had 2.25 OR (95% CI = 1.03-4.91) and 5.14 OR (95% CI = 2.37-11.15) to present higher HDL-C and HDLLARGE concentrations. After adjustment for multiple confounders, high level of adiponectin was independently related with improvement of the HDL antioxidant capacity (OR = 2.78; 95% CI = 1.16-6.67). CONCLUSIONS High adiponectin level associates with a lesser negative impact of T2DM on HDL functionality by increase in APO AI, particles size, and cholesterol content. On the same token, higher adiponectin was associated with greater odds to have high antioxidant capacity.
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Affiliation(s)
- G D Dias
- Department of Nutrition, Faculty of Public Health, University of Sao Paulo (FSP-USP), Sao Paulo, Brazil
| | - F C Cartolano
- Department of Nutrition, Faculty of Public Health, University of Sao Paulo (FSP-USP), Sao Paulo, Brazil
| | - M C P Freitas
- Department of Nutrition, Faculty of Public Health, University of Sao Paulo (FSP-USP), Sao Paulo, Brazil
| | | | - M R P Markus
- Universitatsklinikum Greifswald, Greifswald, Germany
| | - R D Santos
- Lipid Clinic, Heart Institute (InCor), University of Sao Paulo Medical School Hospital (HC-FMUSP), Sao Paulo, Brazil
| | - N R T Damasceno
- Department of Nutrition, Faculty of Public Health, University of Sao Paulo (FSP-USP), Sao Paulo, Brazil.
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Wu X, Xuan W, You L, Lian H, Li F, Zhang X, Chen Q, Sun K, Chen C, Xu M, Li Y, Yan L, Zhang X, Ren M. Associations of GDF-15 and GDF-15/adiponectin ratio with odds of type 2 diabetes in the Chinese population. Endocrine 2021; 72:423-436. [PMID: 33713014 DOI: 10.1007/s12020-021-02632-1] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 01/09/2021] [Indexed: 01/23/2023]
Abstract
PURPOSE We elucidate the effect of Growth differentiation factor-15(GDF-15)/adiponectin ratio in improving the assessment value for odds of type 2 diabetes. METHODS Cross-sectional design. A total of 405 participants (135 patients with newly diagnosed type 2 diabetes, 135 age- and sex-matched participants with prediabetes, and 135 healthy controls) were collected from Guangzhou and Dongguan, China. The serum GDF-15 and adiponectin levels were measured by ELISA and latex-enhanced immunoturbidimetry. Logistic regression analysis and restricted cubic splines were used to evaluate the associations between diabetes and the indicators. RESULTS The low level of adiponectin and high GDF-15/adiponectin ratio were significantly associated with increased odds of type 2 diabetes, but not for GDF-15. Three clusters were identified based on the K-means clustering analysis. Compared to the lowest quartiles of adiponectin, the OR and 95% CI of the highest adiponectin with type 2 diabetes was 0.24 (0.07-0.74, p trend = 0.004) after adjusting for sex, age, BMI, and DBP only in cluster 1. After adjusting for confounding factors, subjects with the highest GDF-15/adiponectin ratio quartiles had 3.9 times (OR = 3.85, 95% CI = 0.76-24.25) and 3.8 times (OR = 3.80, 95% CI = 1.02-14.68) higher odds of type 2 diabetes in cluster 2 and cluster 3, respectively. The association between the GDF-15/adiponectin ratio and type 2 diabetes was attenuated, but still remarkable (OR = 3.18, 95% CI = 1.11-10.18), in cluster 1. CONCLUSIONS Higher GDF-15/adiponectin ratio is independently associated with increased odds of type 2 diabetes for all study populations, suggesting that the GDF-15/adiponectin ratio may be a better indicator of type 2 diabetes.
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Affiliation(s)
- Xiaoying Wu
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou, 510120, People's Republic of China
| | - Wenting Xuan
- Department of Endocrinology, Dongguan People's Hospital, No. 3 South, Xinguyongwan Road, Wanjiang District, Dongguan, 523059, People's Republic of China
| | - Lili You
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou, 510120, People's Republic of China
| | - Hong Lian
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou, 510120, People's Republic of China
| | - Feng Li
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou, 510120, People's Republic of China
| | - Xiaoyun Zhang
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou, 510120, People's Republic of China
| | - Qingyu Chen
- Boji Healthcare Center, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou, 510120, People's Republic of China
| | - Kan Sun
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou, 510120, People's Republic of China
| | - Chaogang Chen
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou, 510120, People's Republic of China
| | - Mingtong Xu
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou, 510120, People's Republic of China
| | - Yan Li
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou, 510120, People's Republic of China
| | - Li Yan
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou, 510120, People's Republic of China
| | - Xiuwei Zhang
- Department of Endocrinology, Dongguan People's Hospital, No. 3 South, Xinguyongwan Road, Wanjiang District, Dongguan, 523059, People's Republic of China.
| | - Meng Ren
- Department of Endocrinology, Sun Yat-sen Memorial Hospital, Sun Yat-sen University, 107 Yanjiang West Road, Guangzhou, 510120, People's Republic of China.
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Circulating Adiponectin and Its Association with Metabolic Traits and Type 2 Diabetes: Gene-Diet Interactions Focusing on Selected Gene Variants and at the Genome-Wide Level in High-Cardiovascular Risk Mediterranean Subjects. Nutrients 2021; 13:nu13020541. [PMID: 33562295 PMCID: PMC7914877 DOI: 10.3390/nu13020541] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 01/26/2021] [Accepted: 02/02/2021] [Indexed: 12/27/2022] Open
Abstract
Adiponectin is gaining renewed interest since, in addition to its possible protective role against insulin resistance and arteriosclerosis, recent studies suggest other additional favorable effects. However, the influence of gene-diet interactions on plasma adiponectin levels is still little understood. We analyzed the association between plasma adiponectin levels and various metabolic traits in a high-cardiovascular risk Mediterranean population, as well as the genetic effect of four candidate single-nucleotide polymorphisms (SNPs) in the adiponectin gene (ADIPOQ) and their interactions with the Mediterranean dietary pattern. Additionally, we explored, at the genome-wide level, the SNPs most associated with plasma adiponectin levels, as well as gene-diet interactions with the Mediterranean diet. In the 954 participants studied (aged 55-80 years), plasma adiponectin levels were strongly associated with plasma HDL-C concentrations (p = 6.6 × 10-36) and inversely related to triglycerides (p = 4.7 × 10-18), fasting glucose (p = 3.5 × 10-16) and type 2 diabetes (p = 1.4 × 10-7). Of the four pre-selected ADIPOQ candidate SNPs, the one most associated with plasma adiponectin was the -11391G > A (rs17300539) promoter SNP (p = 7.2 × 10-5, in the multivariable adjusted model). No significant interactions with the Mediterranean diet pattern were observed for these SNPs. Additionally, in the exploratory genome-wide association study (GWAS), we found new SNPs associated with adiponectin concentrations at the suggestive genome-wide level (p < 1 × 10-5) for the whole population, including the lead SNP rs9738548 (intergenic) and rs11647294 in the VAT1L (Vesicle Amine Transport 1 Like) gene. We also found other promising SNPs on exploring different strata such as men, women, diabetics and non-diabetics (p = 3.5 × 10-8 for rs2850066). Similarly, we explored gene-Mediterranean diet interactions at the GWAS level and identified several SNPs with gene-diet interactions at p < 1 × 10-5. A remarkable gene-diet interaction was revealed for the rs2917570 SNP in the OPCML (Opioid Binding Protein/Cell Adhesion Molecule Like) gene, previously reported to be associated with adiponectin levels in some populations. Our results suggest that, in this high-cardiovascular risk Mediterranean population, and even though adiponectin is favorably associated with metabolic traits and lower type 2 diabetes, the gene variants more associated with adiponectin may be population-specific, and some suggestive gene-Mediterranean diet interactions were detected.
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Tagi VM, Giannini C, Chiarelli F. Insulin Resistance in Children. Front Endocrinol (Lausanne) 2019; 10:342. [PMID: 31214120 PMCID: PMC6558106 DOI: 10.3389/fendo.2019.00342] [Citation(s) in RCA: 94] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2019] [Accepted: 05/13/2019] [Indexed: 12/28/2022] Open
Abstract
Insulin resistance (IR) is a pathological condition strongly associated with obesity. However, corticosteroids or growth hormone therapy and genetic diseases may affect insulin sensitivity lifelong. In obese children and adolescents of any age there is an evident association between IR and an increased prevalence of type 2 diabetes (T2D) and other elements contributing to the metabolic syndrome, leading to a higher cardiovascular risk. Therefore, early diagnosis and interventions in the attempt to prevent T2D when glycemia values are still normal is fundamental. The gold standard technique used to evaluate IR is the hyperinsulinemic euglycemic clamp, however it is costly and difficult to perform in clinical and research sets. Therefore, several surrogate markers have been proposed. Although the treatment of insulin resistance in children is firstly targeted to lifestyle interventions, in selected cases the integration of a pharmacological intervention might be taken into consideration. The aim of this review is to present the current knowledge on IR in children, starting with an outline of the recent evidences about the congenital forms of deficiency in insulin functioning and therefore focusing on the physiopathology of IR, its appropriate measurement, consequences, treatment options and prevention strategies.
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Wang Y, Meng RW, Kunutsor SK, Chowdhury R, Yuan JM, Koh WP, Pan A. Plasma adiponectin levels and type 2 diabetes risk: a nested case-control study in a Chinese population and an updated meta-analysis. Sci Rep 2018; 8:406. [PMID: 29321603 PMCID: PMC5762808 DOI: 10.1038/s41598-017-18709-9] [Citation(s) in RCA: 58] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Accepted: 12/15/2017] [Indexed: 01/12/2023] Open
Abstract
Results from previous prospective studies assessing the relation between adiponectin and type 2 diabetes (T2D) were not entirely consistent, and evidence in Chinese population is scarce. Moreover, the last meta-analysis did not examine the impact of metabolic variables on the adiponectin-T2D association. Therefore, we prospectively evaluated the adiponectin-T2D association among 571 T2D cases and 571 age-sex-matched controls nested within the Singapore Chinese Health Study (SCHS). Furthermore, we conducted an updated meta-analysis by searching prospective studies on Pubmed till September 2016. In the SCHS, the odds ratio of T2D, comparing the highest versus lowest tertile of adiponectin levels, was 0.30 (95% confidence interval: 0.17, 0.55) in the fully-adjusted model. The relation was stronger among heavier participants (body mass index ≥23 kg/m2) compared to their leaner counterparts (P for interaction = 0.041). In a meta-analysis of 34 prospective studies, the pooled relative risk was 0.53 (95% confidence interval: 0.47, 0.61) comparing the extreme tertiles of adiponectin with moderate heterogeneity (I2 = 48.7%, P = 0.001). The adiponectin-T2D association remained unchanged after adjusting for inflammation and dyslipidemia markers, but substantially attenuated with adjustment for insulin sensitivity and/or glycaemia markers. Overall evidence indicates that higher adiponectin levels are associated with decreased T2D risk in Chinese and other populations.
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Affiliation(s)
- Yeli Wang
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore
| | - Rui-Wei Meng
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health and State Key Laboratory of Environmental Health (incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China
| | - Setor K Kunutsor
- Translational Health Sciences, Bristol Medical School, University of Bristol Southmead Hospital, Bristol, United Kingdom
| | - Rajiv Chowdhury
- Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Jian-Min Yuan
- UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.,Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Woon-Puay Koh
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore, Singapore. .,Duke-NUS Medical School, Singapore, Singapore.
| | - An Pan
- Department of Epidemiology and Biostatistics, Ministry of Education Key Laboratory of Environment and Health and State Key Laboratory of Environmental Health (incubation), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China.
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von Frankenberg AD, Reis AF, Gerchman F. Relationships between adiponectin levels, the metabolic syndrome, and type 2 diabetes: a literature review. ARCHIVES OF ENDOCRINOLOGY AND METABOLISM 2017; 61:614-622. [PMID: 29412387 PMCID: PMC10522055 DOI: 10.1590/2359-3997000000316] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/09/2016] [Accepted: 08/09/2017] [Indexed: 11/22/2022]
Abstract
Elevated hepatic glucose production, impaired insulin secretion, and insulin resistance - abnormalities of glucose metabolism typically found in subjects with obesity - are major factors underlying the pathogenesis of type 2 diabetes (DM2) and the metabolic syndrome (MS). Adiponectin is a major regulator of glucose and lipid homeostasis via its insulin-sensitizing properties, and lower levels seems to be associated with the development of DM2 and MS. The purpose of this review is to clarify the mechanisms whereby adiponectin relates to the development of DM2 and MS and the association between polymorphisms of the adiponectin gene, circulating levels of the hormone, and its relationships with DM2. In addition, the impact of dietary lipids in the circulating levels of adiponectin will be addressed. According to the literature, circulating adiponectin levels seem to decrease as the number of MS components increases. Lower adiponectin concentrations are associated with higher intra-abdominal fat content. Therefore, adiponectin could link intra-abdominal fat with insulin resistance and development of MS. Therapeutic strategies that target the MS and its components, such as lifestyle modification through physical activity and weight loss, have been shown to increase adiponectin concentrations. Possible roles of diets containing either low or high amounts of fat, or different types of fat, have been analyzed in several studies, with heterogeneous results. Supplementation with n-3 PUFA modestly increases adiponectin levels, whereas conjugated linoleic acid supplementation appears to reduce concentrations when compared with unsaturated fatty acid supplementation used as an active placebo.
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Affiliation(s)
- Anize Delfino von Frankenberg
- Universidade Federal do Rio Grande do SulFaculdade de MedicinaPorto AlegreRSBrasilPrograma de Pós-Graduação em Endocrinología, Faculdade de Medicina, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brasil
- Universidade Federal de Ciências da Saúde de Porto AlegreDepartamento de NutriçãoPorto AlegreRSBrasilDepartamento de Nutrição, Universidade Federal de Ciências da Saúde de Porto Alegre (UFCSPA), Porto Alegre, RS, Brasil
| | - André F. Reis
- Universidade Federal de São PauloDepartamento de MedicinaSão PauloSPBrasilUniversidade Federal de São Paulo (Unifesp), Departamento de Medicina, Disciplina de Endocrinologia, São Paulo, SP, Brasil
| | - Fernando Gerchman
- Universidade Federal do Rio Grande do SulFaculdade de MedicinaPorto AlegreRSBrasilPrograma de Pós-Graduação em Endocrinología, Faculdade de Medicina, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, RS, Brasil
- Hospital de Clínicas de Porto Alegre (HCPA)Porto AlegreRSBrasilUnidade de Metabolismo, Divisão de Endocrinologia, Hospital de Clínicas de Porto Alegre (HCPA), Porto Alegre, RS, Brasil
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10
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Wichmann HE. Epidemiology in Germany-general development and personal experience. Eur J Epidemiol 2017; 32:635-656. [PMID: 28815360 DOI: 10.1007/s10654-017-0290-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2017] [Accepted: 07/27/2017] [Indexed: 12/19/2022]
Abstract
Did you ever hear about epidemiology in Germany? Starting from an epidemiological desert the discipline has grown remarkably, especially during the last 10-15 years: research institutes have been established, research funding has improved, multiple curriculae in Epidemiology and Public Health are offered. This increase has been quite steep, and now the epidemiological infrastructure is much better. Several medium-sized and even big population cohorts are ongoing, and the number and quality of publications from German epidemiologists has reached a respectable level. My own career in epidemiology started in the field of environmental health. After German reunification I concentrated for many years on environmental problems in East Germany and observed the health benefits after improvement of the situation. Later, I concentrated on population-based cohorts in newborns (GINI/LISA) and adults (KORA, German National Cohort), and on biobanking. This Essay describes the development in Germany after worldwar 2, illustrated by examples of research results and build-up of epidemiological infractructures worth mentioning.
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Affiliation(s)
- Heinz-Erich Wichmann
- Institute of Epidemiology, 2, Helmholtz Center Munich, Munich, Germany. .,Chair of Epidemiology, University of Munich, Munich, Germany.
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11
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Hivert MF, Scholtens DM, Allard C, Nodzenski M, Bouchard L, Brisson D, Lowe LP, McDowell I, Reddy T, Dastani Z, Richards JB, Hayes MG, Lowe WL. Genetic determinants of adiponectin regulation revealed by pregnancy. Obesity (Silver Spring) 2017; 25:935-944. [PMID: 28317342 PMCID: PMC5404994 DOI: 10.1002/oby.21805] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2016] [Revised: 12/25/2016] [Accepted: 01/18/2017] [Indexed: 11/10/2022]
Abstract
OBJECTIVE This study investigated genetic determinants of adiponectin during pregnancy to reveal novel biology of adipocyte regulation. METHODS A genome-wide association study was conducted in 1,322 pregnant women from the Hyperglycemia and Adverse Pregnancy Outcome Study with adiponectin measured at ∼28 weeks of gestation. Variants reaching P < 5×10-5 for de novo genotyping in two replication cohorts (Genetics of Glycemic regulation in Gestation and Growth N = 522; ECOGENE-21 N = 174) were selected. RESULTS In the combined meta-analysis, the maternal T allele of rs900400 located on chr3q25 (near LEKR1/CCNL1) was associated with lower maternal adiponectin (β ± standard error [SE] = -0.18 ± 0.03 standard deviation [SD] of adiponectin per risk allele; P = 1.5 ×10-8 ; N = 2,004; multivariable adjusted models). In contrast, rs900400 showed only nominal association with adiponectin in a large sample of nonpregnant women (β ± SE = -0.012 ± 0.006; P = 0.05; N = 16,678 women from the ADIPOgen consortium). The offspring rs900400 T risk allele was associated with greater neonatal skinfold thickness (β ±SE = 0.19 ± 0.04 SD per risk allele; P = 4.1×10-8 ; N = 1,489) and higher cord blood leptin (β ± SE = 0.28 ± 0.05 log-leptin per risk allele; P = 8.2 ×10-9 ; N = 502), but not with cord blood adiponectin (P = 0.23; N = 495). The T allele of rs900400 was associated with higher expression of TIPARP in adipocytes. CONCLUSIONS These investigations of adipokines during pregnancy and early life suggest that rs900400 has a role in adipocyte function.
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Affiliation(s)
- Marie-France Hivert
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA, USA
- Diabetes Unit, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Denise M. Scholtens
- Department of Preventive Medicine, Division of Biostatistics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Catherine Allard
- Department of Mathematics, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Michael Nodzenski
- Department of Preventive Medicine, Division of Biostatistics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Luigi Bouchard
- Department of Biochemistry, Université de Sherbrooke, Sherbrooke, QC, Canada
| | - Diane Brisson
- Department of Medicine, Université de Montréal, ECOGENE-21 and Lipid Clinic, Chicoutimi, QC, Canada
| | - Lynn P. Lowe
- Department of Preventive Medicine, Division of Epidemiology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Ian McDowell
- Department of Biostatistics and Bioinformatics, Duke Institute for Genome Sciences and Policy, Durham, NC, USA
| | - Tim Reddy
- Department of Biostatistics and Bioinformatics, Duke Institute for Genome Sciences and Policy, Durham, NC, USA
| | - Zari Dastani
- Department of Internal Medicine, Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, QC, Canada
| | - J. Brent Richards
- Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada
- Department of Twin Research, King’s College London, London, UK
| | - M. Geoffrey Hayes
- Division of Endocrinology, Metabolism and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - William L. Lowe
- Division of Endocrinology, Metabolism and Molecular Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
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12
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Farooq R, Amin S, Hayat Bhat M, Malik R, Wani HA, Majid S. Type 2 diabetes and metabolic syndrome - adipokine levels and effect of drugs. Gynecol Endocrinol 2017; 33:75-78. [PMID: 27705028 DOI: 10.1080/09513590.2016.1207165] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Type 2 diabetes mellitus (T2DM) is a consequence of complex interactions among multiple genetic variants and environmental risk factors. This complex disorder is also characterized by changes in various adipokines. In this study, our objective was to estimate the levels of adiponectin, leptin, and resistin (ALR) in T2DM patients, besides studying the effect of various drugs on their levels. Study participants included 400 diabetic and 300 normal patients from the Department of Endocrinology and Department of Biochemistry, Govt Medical College Srinagar. Subjects were categorized under various groups, i.e., Group 1 (metformin treated) and Group 2 (glimepiride treated), and cases were also categorized as obese with T2DM (Group A), obese without T2DM (Group B), and T2DM only (Group C). The serum ALR levels were estimated by ELISA (Alere), and biochemical parameters were also evaluated before and after treatment. Adiponectin levels were found to be significantly lower in T2DM cases as compared to controls (12 ± 5.5 versus 22.5 ± 7.9 μg/ml), while leptin and resistin levels were found to be significantly higher than controls (14.3 ± 7.4 versus 7.36 ± 3.73 ng/ml) (13.4 ± 1.56 versus 7.236 ± 2.129 pg/ml). Taking the effect of drugs into consideration, the effect on adiponectin and resistin levels was found to be highly significant in Group 2 before and after treatment (11 ± 5 versus 19.2 ± 4.5 μg/ml) (13.6 ± 2.5 versus 7.3 ± 2.9 pg/ml), while more effect was observed in leptin among Group 1 (metformin)-treated cases (27 ± 15 ng/ml versus 15 ± 15 ng/ml). Further the adiponectin levels were found to be significantly lower in Group B, while leptin and resistin levels were found to be significantly higher among obese cases when compared to T2DM cases only. Glimepiride also shows more effect on FBG, HbA1c% levels, while metformin shows more effect on Lipid profile levels. From the study, it can be concluded that ALR levels are affected by use of antidiabetic drugs among which glimepiride shows more effect on adiponectin and resistin levels, while leptin gets affected more by metformin. It can also be proposed that ALR levels are not affected by diabetes only, suggesting that their alterations in T2DM may be due to obesity as we observed more ALR changes in obese cases when compared to T2DM cases, and so there might be an important link between adiposity and insulin resistance.
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Affiliation(s)
- Rabia Farooq
- a Department of Biochemistry , Govt Medical College , Srinagar , India
| | - Shajrul Amin
- b Department of Biochemistry , University of Kashmir , Srinagar , India , and
| | - M Hayat Bhat
- c Department of Medicine , Govt Medical College , Srinagar , India
| | - Rawoof Malik
- a Department of Biochemistry , Govt Medical College , Srinagar , India
| | - Hilal Ahmad Wani
- a Department of Biochemistry , Govt Medical College , Srinagar , India
| | - Sabhiya Majid
- a Department of Biochemistry , Govt Medical College , Srinagar , India
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Zemlin AE, Matsha TE, Kengne AP, Hon G, Erasmus RT. High Molecular Weight Adiponectin Levels are Neither Influenced by Adiponectin Polymorphisms Nor Associated with Insulin Resistance in Mixed-ancestry Hyperglycemic Subjects from South Africa. J Med Biochem 2016; 35:416-427. [PMID: 28670194 PMCID: PMC5471637 DOI: 10.1515/jomb-2016-0024] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2016] [Accepted: 07/09/2016] [Indexed: 12/28/2022] Open
Abstract
Background High molecular weight (HMW) adiponectin has antiatherogenic, antiinflammatory and antidiabetic properties and these effects have been linked to its effect on high density lipoprotein cholesterol (HDL-c). Single nucleotide polymorphisms (SNPs) in the adiponectin gene influence adiponectin levels. We examined the relationship between HMW-adiponectin levels and cardiometabolic traits in normo- and hyperglycemic mixed ancestry South Africans and correlated these levels to two common polymorphisms. Methods HMW-adiponectin was determined in 101 subjects from the Cape Town Bellville South community-based study on a mixed ancestry population. Comparisons were made between individuals with normo- and hyperglycemia. Two common SNPs, ADIPOQ SNPs rs17300539 and rs266729, known to affect adiponectin levels were also tested for. Levels of HMW-adiponectin were then correlated with cardiometabolic traits in all groups. Results Levels of HMW-adiponectin were not significantly different in the normo- and hyperglycemic groups (median 11.6 vs. 10.5 μg/mL, p=0.3060) and in men and women (8.44 vs. 11.34 μg/mL, p=0.67). ADIPOQ SNPs rs17300539 and rs266729 did not influence levels of HMW-adiponectin. Robust correlation analyses revealed a significant positive correlation between HMW-adiponectin and HDL-c (r=0.45; 95%CI: 0.27–0.59), similarly in normo- and hyperglycemic participants (p > 0.99). This association was substantially attenuated in robust linear regressions adjusted for age, gender and adiposity. Conclusions Adiponectin levels in this population were not determined by the commonest SNPs of the adiponectin gene, were unaffected by glycemic status; but were significantly correlated with HDL-c levels. Previous studies have attributed some of the beneficial effects of adiponectin to its effect on HDL-c.
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Affiliation(s)
- Annalise E Zemlin
- Division of Chemical Pathology, Faculty of Medicine and Health Sciences, National Health Laboratory Service (NHLS) and University of Stellenbosch, Cape Town, South Africa
- (AEZ)
| | - Tandi E Matsha
- Department of Biomedical Sciences, Faculty of Health and Wellness Science, Cape Peninsula University of Technology, Cape Town, South Africa
| | - Andre P Kengne
- Non-Communicable Diseases Research Unit, South Africa Medical Research Council, University of Cape Town and University of Stellenbosch, Cape Town, South Africa
| | - Gloudina Hon
- Department of Biomedical Sciences, Faculty of Health and Wellness Science, Cape Peninsula University of Technology, Cape Town, South Africa
| | - Rajiv T Erasmus
- Division of Chemical Pathology, Faculty of Medicine and Health Sciences, National Health Laboratory Service (NHLS) and University of Stellenbosch, Cape Town, South Africa
- Division of Chemical Pathology, Tygerberg Hospital National Health Laboratory Service (NHLS) and University of Stellenbosch PO Box 19113, Tygerberg 7505 South Africa e-mail: (RTE)
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14
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Neville CE, Patterson CC, Linden GJ, Love K, McKinley MC, Kee F, Blankenberg S, Evans A, Yarnell J, Woodside JV. The relationship between adipokines and the onset of type 2 diabetes in middle-aged men: The PRIME study. Diabetes Res Clin Pract 2016; 120:24-30. [PMID: 27500548 DOI: 10.1016/j.diabres.2016.07.010] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2015] [Revised: 05/06/2016] [Accepted: 07/16/2016] [Indexed: 01/17/2023]
Abstract
AIMS Epidemiological evidence suggests that adipokines may be associated with the onset of type 2 diabetes, but the evidence to date is limited and inconclusive. This study examined the association between adiponectin and leptin and the subsequent diagnosis of type 2 diabetes in a UK population based cohort of non-diabetic middle-aged men. METHODS Baseline serum levels of leptin and adiponectin were measured in 1839 non-diabetic men aged 50-60years who were participating in the prospective population-based PRIME study. Over a mean follow-up of 14.7years, new cases of type 2 diabetes were determined from self-reported clinical information with subsequent validation by general practitioners. RESULTS 151 Participants developed type 2 diabetes during follow-up. In Cox regression models adjusted for age, men in the top third of the leptin distribution were at increased risk (hazard ratio (HR) 4.27, 95% CI 2.67-6.83) and men in the top third of the adiponectin distribution at reduced risk (HR 0.24, 95% CI 0.14-0.42) relative to men in the bottom third. However, significance was lost for leptin after additional adjustment for BMI, waist to hip ratio, lifestyle factors and biological risk factors, including C-reactive protein (CRP). Further adjustment for HOMA-IR also resulted in loss of significance for adiponectin. CONCLUSIONS This study provides evidence that adipokines are associated with men's future type 2 diabetes risk but not independently of other risk factors.
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Affiliation(s)
- Charlotte E Neville
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Institute of Clinical Science B, Queen's University Belfast, Belfast, BT12 6BJ, United Kingdom.
| | - Christopher C Patterson
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Institute of Clinical Science B, Queen's University Belfast, Belfast, BT12 6BJ, United Kingdom; UKCRC Centre of Excellence for Public Health (Northern Ireland), Queen's University Belfast, Belfast, BT12 6BJ, United Kingdom.
| | - Gerard J Linden
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Institute of Clinical Science B, Queen's University Belfast, Belfast, BT12 6BJ, United Kingdom.
| | - Karl Love
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Institute of Clinical Science B, Queen's University Belfast, Belfast, BT12 6BJ, United Kingdom.
| | - Michelle C McKinley
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Institute of Clinical Science B, Queen's University Belfast, Belfast, BT12 6BJ, United Kingdom; UKCRC Centre of Excellence for Public Health (Northern Ireland), Queen's University Belfast, Belfast, BT12 6BJ, United Kingdom.
| | - Frank Kee
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Institute of Clinical Science B, Queen's University Belfast, Belfast, BT12 6BJ, United Kingdom; UKCRC Centre of Excellence for Public Health (Northern Ireland), Queen's University Belfast, Belfast, BT12 6BJ, United Kingdom.
| | - Stefan Blankenberg
- Department of Medicine II, Johannes Gutenberg-University Mainz, Mainz, Germany.
| | - Alun Evans
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Institute of Clinical Science B, Queen's University Belfast, Belfast, BT12 6BJ, United Kingdom.
| | - John Yarnell
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Institute of Clinical Science B, Queen's University Belfast, Belfast, BT12 6BJ, United Kingdom.
| | - Jayne V Woodside
- Centre for Public Health, School of Medicine, Dentistry and Biomedical Sciences, Institute of Clinical Science B, Queen's University Belfast, Belfast, BT12 6BJ, United Kingdom; UKCRC Centre of Excellence for Public Health (Northern Ireland), Queen's University Belfast, Belfast, BT12 6BJ, United Kingdom.
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15
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Wang WD, Xing L, Teng JR, Li S, Mi NA. Effects of basal insulin application on serum visfatin and adiponectin levels in type 2 diabetes. Exp Ther Med 2015; 9:2219-2224. [PMID: 26136963 DOI: 10.3892/etm.2015.2428] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2014] [Accepted: 10/28/2014] [Indexed: 12/15/2022] Open
Abstract
The aim of this study was to investigate the effects of basal insulin application on the serum visfatin and adiponectin (APN) levels of patients with type 2 diabetes mellitus (T2DM). A total of 200 patients with T2DM, who were diagnosed in The Third People's Hospital of Jinan (glycosylated hemoglobin ≥7%), were randomly divided into treatment and control groups. The patients used only oral hypoglycemic drugs and had never received insulin therapy. In the treatment group, basal insulin was administered in combination with the original application of oral hypoglycemic drugs, whereas the control group maintained the original use of oral hypoglycemic drugs or took other oral hypoglycemic agents. The body mass index and fasting blood glucose, postprandial blood glucose, glycosylated hemoglobin, visfatin, APN and blood lipid levels of the patients were examined prior to the treatment and six months later. The drug and insulin doses in the treatment group were adjusted according to the patients' blood glucose, which allowed the fasting and postprandial blood glucose levels to attain the standards. The fasting and postprandial blood glucose levels in the control group also achieved the standards. It was found that the six-month application of basal insulin could significantly decrease the glycosylated hemoglobin and significantly increase the serum APN levels; the serum visfatin levels, however, remained unchanged. The immediate application of basal insulin could facilitate the attainment of glycosylated hemoglobin standards in T2DM and could increase the plasma APN levels, preventing diabetic vascular complications.
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Affiliation(s)
- Wei-Dong Wang
- Department of Endocrinology, The Third People's Hospital of Jinan, Jinan, Shandong 250132, P.R. China
| | - Lin Xing
- Department of Endocrinology, The Third People's Hospital of Jinan, Jinan, Shandong 250132, P.R. China
| | - Jun-Ru Teng
- Department of Clinical Laboratory, The Third People's Hospital of Jinan, Jinan, Shandong 250132, P.R. China
| | - Shuo Li
- Department of Endocrinology, The Third People's Hospital of Jinan, Jinan, Shandong 250132, P.R. China
| | - N A Mi
- Department of Endocrinology, The Third People's Hospital of Jinan, Jinan, Shandong 250132, P.R. China
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The role of circulating adiponectin in prostate cancer: a meta-analysis. Int J Biol Markers 2015; 30:e22-31. [PMID: 25450645 DOI: 10.5301/jbm.5000124] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/03/2014] [Indexed: 01/11/2023]
Abstract
PURPOSE Emerging evidence suggests that adiponectin may play a protective role in tumor progression and prognosis. However, available evidence in prostate cancer is conflicting. Therefore, we carried out a meta-analysis to evaluate the role of circulating adiponectin and prostate cancer. METHODS AND RESULTS An extensive search was performed on Google, PubMed, Elsevier Science and Springer from the date of the inception of those services to December 2013. Eleven studies with 2,504 patients and 3,565 controls concerning this association were included in our analysis. Standard mean difference (SMD) with 95% confidence intervals (95% CIs) was used to estimate this association. The pooled analysis showed that circulating adiponectin concentrations were lower in patients with prostate cancer than controls, with a pooled SMD of -0.893 μg/mL (95% CI, -1.345 to -0.440, p=0.000). Dose-response relationships between concentrations of adiponectin and risk of prostate cancer were evaluated. We found that decreased concentrations of adiponectin were associated with a significantly greater risk of prostate cancer (p for nonlinearity = 0.043). CONCLUSIONS The results of our analysis indicated that concentration of adiponectin in cancer patients was significantly lower than in controls. Thus, adiponectin may serve as a potential biomarker for early diagnosis of this disease. We also found that decreased concentration of adiponectin was associated with a significantly greater risk of prostate cancer. However, more studies in future, especially larger, prospective studies, are needed to confirm this association with underlying biological mechanisms.
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Jung CC, Tsai YS, Chang CC, Cheng TJ, Chang CW, Liu PY, Chiu YJ, Su HJ. Allergen exposure induces adipose tissue inflammation and insulin resistance. Int Immunopharmacol 2014; 23:104-12. [DOI: 10.1016/j.intimp.2014.07.033] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2014] [Revised: 07/29/2014] [Accepted: 07/30/2014] [Indexed: 12/17/2022]
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18
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Baziar N, Jafarian K, Shadman Z, Qorbani M, Khoshniat Nikoo M, Abd Mishani M. Effect of therapeutic dose of vitamin d on serum adiponectin and glycemia in vitamin d-insufficient or deficient type 2 diabetic patients. IRANIAN RED CRESCENT MEDICAL JOURNAL 2014; 16:e21458. [PMID: 25593737 PMCID: PMC4270651 DOI: 10.5812/ircmj.21458] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/22/2014] [Revised: 08/16/2014] [Accepted: 08/30/2014] [Indexed: 12/17/2022]
Abstract
Background: Lower vitamin D status has been reported in diabetic patients. Serum 25-hydroxyvitamin D and adiponectin were inversely associated with type 2 diabetes and insulin resistance. Vitamin D may involve in regulation of the adiponectin levels, which is directly related to insulin sensitivity. Objectives: The aim of this study was to investigate the effect of therapeutic dose of vitamin D on serum adiponectin and insulin resistance in vitamin D-insufficient or deficient type 2 diabetic patients. Materials and Methods: This double-blind, randomized, clinical trial was conducted on 81 type 2 diabetic patients with vitamin D level of 10-30 ng/mL. Intervention was 50000 IU vitamin D or placebo once a week for 8 weeks. At the beginning and end of the study, blood samples were collected after 12 hours of fasting and serum glucose, insulin, 25-hydroxyvitamin D, and adiponectin were measured. Insulin resistance was calculated by homeostasis model assessment (HOMA-IR). Results: After 8-week intervention, serum 25-hydroxyvitamin D significantly increased and reached the normal levels in patients receiving vitamin D (P < 0.001) and the levels of fasting serum glucose, insulin, and HOMA-IR were significantly decreased (P = 0.04, 0.02 and 0.007, respectively). No significant changes were observed in these levels in the placebo group. Significant differences were observed in mean changes in the above-mentioned variables between the two groups (P = 0.01, 0.04 and 0.006, respectively). No significant changes were found in serum adiponectin in the vitamin D and placebo groups (P = 0.83). Conclusions: Therapeutic dose of vitamin D can improve vitamin D status and glycemic indicators. But it seems that an 8-week intervention period was not sufficient to reveal the possible effects of vitamin D on serum adiponectin levels.
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Affiliation(s)
- Nima Baziar
- Department of Clinical Nutrition and Dietetics Therapy, Faculty of Nutrition Sciences and Food Technology, Tehran University of Medical Sciences, Tehran, IR Iran
| | - Kurosh Jafarian
- Department of Clinical Nutrition and Dietetics Therapy, Faculty of Nutrition Sciences and Food Technology, Tehran University of Medical Sciences, Tehran, IR Iran
| | - Zhaleh Shadman
- Research Center of Endocrinology and Metabolism, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, IR Iran
| | - Mostafa Qorbani
- Department of Community Medicine, Alborz University of Medical Sciences, Karaj, IR Iran
- Non Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, IR Iran
| | - Mohsen Khoshniat Nikoo
- Research Center of Endocrinology and Metabolism, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, IR Iran
- Corresponding Author: Mohsen Khoshniat Nikoo, Research Center of Endocrinology and Metabolism, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, IR Iran. Tel: +98-2188220094; Ext: 5; Fax: +98-2188220052, E-mail:
| | - Mahshid Abd Mishani
- Research Center of Endocrinology and Metabolism, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, IR Iran
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Abbasi A, Corpeleijn E, Gansevoort RT, Gans ROB, Struck J, Schulte J, Hillege HL, van der Harst P, Stolk RP, Navis G, Bakker SJL. Circulating peroxiredoxin 4 and type 2 diabetes risk: the Prevention of Renal and Vascular Endstage Disease (PREVEND) study. Diabetologia 2014; 57:1842-9. [PMID: 24893865 PMCID: PMC4119240 DOI: 10.1007/s00125-014-3278-9] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2014] [Accepted: 05/08/2014] [Indexed: 02/07/2023]
Abstract
AIMS/HYPOTHESIS Oxidative stress plays a key role in the development of type 2 diabetes mellitus. We previously showed that the circulating antioxidant peroxiredoxin 4 (Prx4) is associated with cardiometabolic risk factors. We aimed to evaluate the association of Prx4 with type 2 diabetes risk in the general population. METHODS We analysed data on 7,972 individuals from the Prevention of Renal and Vascular End-stage Disease (PREVEND) study (49% men, aged 28-75 years) with no diabetes at baseline. Logistic regression models adjusted for age, sex, smoking, waist circumference, hypertension and family history of diabetes were used to estimate the ORs for type 2 diabetes. RESULTS During a median follow up of 7.7 years, 496 individuals (288 men; 58%) developed type 2 diabetes. The median (Q1-Q3) Prx4 level was 0.84 (0.53-1.40) U/l in individuals who developed type 2 diabetes and 0.68 (0.43-1.08) U/l in individuals who did not develop type 2 diabetes. For every doubling of Prx4 levels, the adjusted OR (95% CI) for type 2 diabetes was 1.16 (1.05-1.29) in the whole population; by sex, it was 1.31 (1.14-1.50) for men and 1.03 (0.87-1.21) for women. Further adjustment for other clinical measures did not materially change the results. The addition of Prx4 to a validated diabetes risk score significantly improved the prediction of type 2 diabetes in men (p = 0.002 for reclassification improvement). CONCLUSIONS/INTERPRETATION Our findings suggest that elevated serum Prx4 levels are associated with a higher risk of incident type 2 diabetes. For men, taking Prx4 into consideration can improve type 2 diabetes prediction over a validated diabetes risk score; in contrast, there is no improvement in risk prediction for women.
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Affiliation(s)
- Ali Abbasi
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands,
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Circulating adiponectin levels and risk of type 2 diabetes in the Japanese. Nutr Diabetes 2014; 4:e130. [PMID: 25133442 PMCID: PMC4151175 DOI: 10.1038/nutd.2014.27] [Citation(s) in RCA: 48] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/08/2014] [Revised: 06/22/2014] [Accepted: 07/10/2014] [Indexed: 12/22/2022] Open
Abstract
Background: Adiponectin has anti-inflammatory and insulin-sensitizing properties. Prospective studies have consistently shown a lower risk of type 2 diabetes among those with higher circulating adiponectin levels. Objective: We examined prospectively the association between serum adiponectin levels and type 2 diabetes risk among Japanese workers, taking visceral fat mass into account. Subjects and methods: Subjects were 4591 Japanese employees who attended a comprehensive health screening in 2008; had biochemical data including serum adiponectin; were free of diabetes at baseline; and received health screening in 2011. Multiple logistic regression analysis was used to examine the association between adiponectin and incidence of diabetes among overall subjects, as well as subgroups. Stratified analyses were carried out according to variables including visceral fat area (VFA). Results: During 3 years of follow-up, 217 diabetic cases were newly identified. Of these, 87% had a prediabetes at baseline. Serum adiponectin level was significantly, inversely associated with incidence of diabetes, with odds ratios (95% confidence interval) adjusted for age, sex, family history, smoking, alcohol drinking, physical activity and body mass index (BMI) for the lowest through highest quartile of adiponectin of 1 (reference), 0.79 (0.55–1.12), 0.60 (0.41–0.88) and 0.40 (0.25–0.64), respectively (P-value for trend <0.01). This association was materially unchanged with adjustment for VFA instead of BMI. After further adjustment for both homeostasis model assessment of insulin resistance and hemoglobin A1c, however, the association became statistically nonsignificant (P-value for trend=0.18). Risk reduction associated with higher adiponectin levels was observed in both participants with and without obesity or insulin resistance at baseline. Conclusions: Results suggest that higher levels of circulating adiponectin are associated with a lower risk of type 2 diabetes, independently of overall and intra-abdominal fat deposition, and that adiponectin may confer a benefit in both persons with and without insulin resistance.
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Abstract
BACKGROUND AND AIMS The initial disturbance of insulin resistance seems to focus on adipose tissue is a dynamic organ involved in many physiological and metabolic processes. Expresses and secretes a variety of active peptides, adipocytokines. To evaluate the prevalence of insulin-resistance in an healthy urban middle age population and to explore the role of adiponectin, inflammatory biomarkers (hs-CRP) and traditional cardiovascular risk factors as predictors of the insulin-resistance state. MATERIALS AND METHODS We studied of 176 participants (117 women and 59 men, 25-74 years), individuals with diabetes, hypothyroidism or hyperthyroidism, infectious disease, renal, or hepatic neoplasms and pregnant women were excluded. We evaluated glucose, insulin, adiponectin and hs-CRP. RESULTS We found that 17.2% of individuals presented insulin-resistance. Correlation was found between waist circumference, body mass index, blood pressure and HOMA index (p<0.01). Adiponectin was associated with the insulin-resistance (p<0.001) but not hs-CRP. Adiponectin (β=0.385, p=0.004) and waist circumference (β=0.116, p=0.02) were predictors of IR only in women, meanwhile none of the analyzed biomarkers predicted insulin-resistance in men. Besides, postmenopausal women presented higher adiponectin levels than premenopausal 7.63 (4.46-9.58) vs 5.50 (3.83-7.40) μg/ml, p=0.01. CONCLUSIONS Adiponectin and waist circumference are important predictors of insulin-resistance even in healthy non-diabetic women, they may open a new opportunity to improve current risk estimation.
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Affiliation(s)
- Graciela A Bonneau
- Ministerio de Salud Pública de la Provincia de Misiones, Argentina; Facultad de Ciencias Exactas, Químicas y Naturales, Universidad Nacional de Misiones, Argentina.
| | | | - Gabriela Berg
- Lipids and Lipoproteins Laboratory, Faculty of Pharmacy and Biochemistry, INFIBIOC, University of Buenos Aires, Argentina
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Herder C, Carstensen M, Ouwens DM. Anti-inflammatory cytokines and risk of type 2 diabetes. Diabetes Obes Metab 2013; 15 Suppl 3:39-50. [PMID: 24003920 DOI: 10.1111/dom.12155] [Citation(s) in RCA: 114] [Impact Index Per Article: 10.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/21/2013] [Accepted: 05/12/2013] [Indexed: 12/12/2022]
Abstract
Proinflammatory processes have been investigated extensively in the development of type 2 diabetes, but our knowledge on anti-inflammatory proteins is rather limited. This article summarizes studies that investigated associations between circulating levels of anti-inflammatory cytokines and incident type 2 diabetes preferably in prospective epidemiological studies. Adiponectin is the only known anti-inflammatory protein whose circulating levels are decreased before type 2 diabetes. In contrast, concentrations of interleukin-1 receptor antagonist (IL-1RA), transforming growth factor-β1 (TGF-β1) and growth differentiation factor-15 (GDF-15) are increased and indicate the presence of a compensatory, but eventually futile, counter-regulation of proinflammatory stimuli. Importantly, a proof-of-principle study using recombinant IL-1RA to improve metabolic control in patients with type 2 diabetes demonstrated that a more pronounced upregulation of this protein than that found in the natural course of diabetes development may have clinical relevance. Other interesting candidates like omentin (which shows similar associations with metabolic parameters as adiponectin), interleukin-10 (IL-10) and secreted frizzled-related protein-5 (Sfrp5) are currently less well studied with sometimes conflicting results regarding their association with type 2 diabetes. Thus, further research is required to better understand the causal role of proinflammatory cytokines, hypoadiponectinaemia and the upregulation of anti-inflammatory proteins before the onset of type 2 diabetes.
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Affiliation(s)
- C Herder
- Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.
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Lacroix M, Battista MC, Doyon M, Ménard J, Ardilouze JL, Perron P, Hivert MF. Lower adiponectin levels at first trimester of pregnancy are associated with increased insulin resistance and higher risk of developing gestational diabetes mellitus. Diabetes Care 2013; 36:1577-83. [PMID: 23300287 PMCID: PMC3661817 DOI: 10.2337/dc12-1731] [Citation(s) in RCA: 90] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/25/2012] [Accepted: 11/30/2012] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To evaluate the associations between adiponectin levels and 1) the risk of developing gestational diabetes mellitus (GDM), and 2) insulin resistance/sensitivity, β-cell function, and compensation indices in a prospective cohort representative of the general population of pregnant women. RESEARCH DESIGN AND METHODS We performed anthropometric measurements and collected blood samples at 1st (6-13 weeks) and 2nd (24-28 weeks) trimesters. Diagnosis of GDM was made at 2nd trimester based on a 75-g oral glucose tolerance test (International Association of the Diabetes and Pregnancy Study Groups criteria). Insulin was measured (ELISA; Luminex) to estimate homeostasis model assessment of insulin resistance (HOMA-IR), β-cell function (HOMA-B), insulin sensitivity (Matsuda index), insulin secretion (AUC(insulin/glucose)), and β-cell compensation (insulin secretion sensitivity index-2). Adiponectin was measured by radioimmunoassay. RESULTS Among the 445 participants included in this study, 38 women developed GDM. Women who developed GDM had lower 1st-trimester adiponectin levels (9.67 ± 3.84 vs. 11.92 ± 4.59 µg/mL in women with normal glucose tolerance). Lower adiponectin levels were associated with higher risk of developing GDM (OR, 1.12 per 1 µg/mL decrease of adiponectin levels; P = 0.02, adjusted for BMI and HbA1c at 1st trimester). Adiponectin levels at 1st and 2nd trimesters were associated with HOMA-IR (both: r = -0.22, P < 0.0001) and Matsuda index (r = 0.28, P < 0.0001, and r = 0.29, P < 0.0001). After adjustment for confounding factors, we found no significant association with HOMA-B and AUC(insulin/glucose). CONCLUSIONS Pregnant women with lower adiponectin levels at 1st trimester have higher levels of insulin resistance and are more likely to develop GDM independently of adiposity or glycemic measurements.
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Affiliation(s)
- Marilyn Lacroix
- Faculty of Medicine, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | | | - Myriam Doyon
- Centre de Recherche Clinique Étienne-Le Bel, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Québec, Canada
| | - Julie Ménard
- Centre de Recherche Clinique Étienne-Le Bel, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Québec, Canada
| | - Jean-Luc Ardilouze
- Faculty of Medicine, Université de Sherbrooke, Sherbrooke, Québec, Canada
- Centre de Recherche Clinique Étienne-Le Bel, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Québec, Canada
| | - Patrice Perron
- Faculty of Medicine, Université de Sherbrooke, Sherbrooke, Québec, Canada
- Centre de Recherche Clinique Étienne-Le Bel, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Québec, Canada
| | - Marie-France Hivert
- Faculty of Medicine, Université de Sherbrooke, Sherbrooke, Québec, Canada
- Centre de Recherche Clinique Étienne-Le Bel, Centre Hospitalier Universitaire de Sherbrooke, Sherbrooke, Québec, Canada
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts
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Sans S, Padró T, Tuomilehto J, Badimon L. Incidence of diabetes and serum adipokines in Catalonian men: the ADIPOCAT study. Ann Med 2013; 45:97-102. [PMID: 22497253 DOI: 10.3109/07853890.2012.679958] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/04/2023] Open
Abstract
AIMS To investigate the relationship of body mass index and serum adipokines with incidence of diabetes in men. MATERIAL AND METHODS Ten-year cohort study of a random population sample of 1011 men aged 35-69 years from the MONICA-Catalonia survey (1986-1988). WHO-MONICA protocol and the US Hispanic NHANES diabetes questionnaire were applied. Fasting serum glucose and lipids were measured by enzymatic methods, adipokines and insulin by Luminex xMAP technology,and hs-CRP by nephelometry in stored baseline samples (-80°C). Type2 diabetes was defined as fasting glucose ≥ 7.0 mmol/L or diagnosed diabetes. Incident diabetes was defined as absence of these criteria at baseline but presence at re-examination. Cox regression analysis was used. RESULTS Incidence of diabetes (n = 85) was 10.3/1000 person-years, increasing significantly with BMI but decreasing by quartiles of adiponectin. Incidence increased above median BMI and glucose (45.3/1000 person-years, OR = 19.97). Log-adiponectin associated with reduced risk of diabetes after multivariate adjustment (HR = 0.24, 95% CI 0.08-0.72), with significant modification of this effect by baseline glycaemia. C-reactive protein was not a significant factor. Leptin lost strength when adjusted for BMI. CONCLUSIONS In a population with relatively high diabetes incidence, BMI and glucose were strong risk factors, while adiponectin protected against diabetes, especially in men with high glycaemic level.
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Affiliation(s)
- Susana Sans
- Institute of Health Studies, Barcelona 08005, Spain.
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Zhang J, Hochwald SN. Plasma adiponectin: a possible link between fat metabolism and pancreatic cancer risk. J Natl Cancer Inst 2012; 105:79-80. [PMID: 23243204 DOI: 10.1093/jnci/djs522] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
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Jia T, Carrero JJ, Lindholm B, Stenvinkel P. The complex role of adiponectin in chronic kidney disease. Biochimie 2012; 94:2150-6. [DOI: 10.1016/j.biochi.2012.02.024] [Citation(s) in RCA: 36] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2011] [Accepted: 02/17/2012] [Indexed: 12/25/2022]
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Ho JSK, Germer S, Tam CHT, So WY, Martin M, Ma RCW, Chan JCN, Ng MCY. Association of the PPARG Pro12Ala polymorphism with type 2 diabetes and incident coronary heart disease in a Hong Kong Chinese population. Diabetes Res Clin Pract 2012; 97:483-91. [PMID: 22515931 DOI: 10.1016/j.diabres.2012.03.012] [Citation(s) in RCA: 25] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2012] [Revised: 03/04/2012] [Accepted: 03/15/2012] [Indexed: 11/18/2022]
Abstract
AIMS We examined the risk association between single nucleotide polymorphisms (SNPs) in eleven candidate genes with type 2 diabetes (T2D). T2D-associated polymorphisms were also examined for prediction of incident CHD. METHODS 113 tagging SNPs were genotyped in stage 1 (467 T2D cases, 290 controls), and 15 SNPs were analyzed in the final cohort (1462 T2D cases, 600 controls). Three T2D-associated SNPs were further tested for prediction of CHD within a subset of 1417 T2D cases free of CHD at enrolment. RESULTS In the case-control analysis, PPARG rs1801282 (Pro12Ala) (OR=1.48 (1.02-2.16)), ADIPOQ rs1063539 (OR=1.17 (1.01-1.35)), and HNF4A rs1884614 (OR=1.16 (1.00-1.32) were associated with T2D (P(allelic)<0.05). Joint analysis of rs1801282-C, rs1063539-G, and rs1884614-T risk alleles showed an additive dosage effect (P for trend=0.001). Moreover, carriers with two PPARG rs1801282-C risk alleles were associated with an increased risk of incident CHD (HR=4.38 (1.03-18.57), P=0.045) in T2D patients in the prospective analysis. CONCLUSIONS Genetic variants of PPARG, ADIPOQ and HNF4A were individually and jointly associated with T2D in Hong Kong Chinese. The PPARG Pro12 risk allele contributed to increased risk for both T2D and CHD.
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Affiliation(s)
- Janice S K Ho
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Prince of Wales Hospital, Shatin, Hong Kong
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Manning AK, Hivert MF, Scott RA, Grimsby JL, Bouatia-Naji N, Chen H, Rybin D, Liu CT, Bielak LF, Prokopenko I, Amin N, Barnes D, Cadby G, Hottenga JJ, Ingelsson E, Jackson AU, Johnson T, Kanoni S, Ladenvall C, Lagou V, Lahti J, Lecoeur C, Liu Y, Martinez-Larrad MT, Montasser ME, Navarro P, Perry JRB, Rasmussen-Torvik LJ, Salo P, Sattar N, Shungin D, Strawbridge RJ, Tanaka T, van Duijn CM, An P, de Andrade M, Andrews JS, Aspelund T, Atalay M, Aulchenko Y, Balkau B, Bandinelli S, Beckmann JS, Beilby JP, Bellis C, Bergman RN, Blangero J, Boban M, Boehnke M, Boerwinkle E, Bonnycastle LL, Boomsma DI, Borecki IB, Böttcher Y, Bouchard C, Brunner E, Budimir D, Campbell H, Carlson O, Chines PS, Clarke R, Collins FS, Corbatón-Anchuelo A, Couper D, de Faire U, Dedoussis GV, Deloukas P, Dimitriou M, Egan JM, Eiriksdottir G, Erdos MR, Eriksson JG, Eury E, Ferrucci L, Ford I, Forouhi NG, Fox CS, Franzosi MG, Franks PW, Frayling TM, Froguel P, Galan P, de Geus E, Gigante B, Glazer NL, Goel A, Groop L, Gudnason V, Hallmans G, Hamsten A, Hansson O, Harris TB, Hayward C, Heath S, Hercberg S, Hicks AA, Hingorani A, Hofman A, Hui J, Hung J, Jarvelin MR, Jhun MA, Johnson PC, Jukema JW, Jula A, Kao W, Kaprio J, Kardia SLR, Keinanen-Kiukaanniemi S, Kivimaki M, Kolcic I, Kovacs P, Kumari M, Kuusisto J, Kyvik KO, Laakso M, Lakka T, Lannfelt L, Lathrop GM, Launer LJ, Leander K, Li G, Lind L, Lindstrom J, Lobbens S, Loos RJF, Luan J, Lyssenko V, Mägi R, Magnusson PKE, Marmot M, Meneton P, Mohlke KL, Mooser V, Morken MA, Miljkovic I, Narisu N, O’Connell J, Ong KK, Oostra BA, Palmer LJ, Palotie A, Pankow JS, Peden JF, Pedersen NL, Pehlic M, Peltonen L, Penninx B, Pericic M, Perola M, Perusse L, Peyser PA, Polasek O, Pramstaller PP, Province MA, Räikkönen K, Rauramaa R, Rehnberg E, Rice K, Rotter JI, Rudan I, Ruokonen A, Saaristo T, Sabater-Lleal M, Salomaa V, Savage DB, Saxena R, Schwarz P, Seedorf U, Sennblad B, Serrano-Rios M, Shuldiner AR, Sijbrands EJ, Siscovick DS, Smit JH, Small KS, Smith NL, Smith AV, Stančáková A, Stirrups K, Stumvoll M, Sun YV, Swift AJ, Tönjes A, Tuomilehto J, Trompet S, Uitterlinden AG, Uusitupa M, Vikström M, Vitart V, Vohl MC, Voight BF, Vollenweider P, Waeber G, Waterworth DM, Watkins H, Wheeler E, Widen E, Wild SH, Willems SM, Willemsen G, Wilson JF, Witteman JC, Wright AF, Yaghootkar H, Zelenika D, Zemunik T, Zgaga L, Wareham NJ, McCarthy MI, Barroso I, Watanabe RM, Florez JC, Dupuis J, Meigs JB, Langenberg C. A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance. Nat Genet 2012; 44:659-69. [PMID: 22581228 PMCID: PMC3613127 DOI: 10.1038/ng.2274] [Citation(s) in RCA: 599] [Impact Index Per Article: 49.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2011] [Accepted: 04/13/2012] [Indexed: 12/15/2022]
Abstract
Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and β-cell dysfunction but have contributed little to the understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways might be uncovered by accounting for differences in body mass index (BMI) and potential interactions between BMI and genetic variants. We applied a joint meta-analysis approach to test associations with fasting insulin and glucose on a genome-wide scale. We present six previously unknown loci associated with fasting insulin at P < 5 × 10(-8) in combined discovery and follow-up analyses of 52 studies comprising up to 96,496 non-diabetic individuals. Risk variants were associated with higher triglyceride and lower high-density lipoprotein (HDL) cholesterol levels, suggesting a role for these loci in insulin resistance pathways. The discovery of these loci will aid further characterization of the role of insulin resistance in T2D pathophysiology.
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Affiliation(s)
- Alisa K. Manning
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
- Department of Molecular Biology, Massachusetts General Hospital, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts
| | - Marie-France Hivert
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Medicine, Universite de Sherbrooke, Sherbrooke, Québec, Canada
| | - Robert A. Scott
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Jonna L. Grimsby
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Nabila Bouatia-Naji
- Institut Pasteur de Lille, Lille, France
- Lille Nord de France University, Lille, France
| | - Han Chen
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Denis Rybin
- Boston University Data Coordinating Center, Boston, Massachusetts, USA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Lawrence F. Bielak
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Inga Prokopenko
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Daniel Barnes
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Gemma Cadby
- Genetic Epidemiology and Biostatistics Platform, Ontario Institute for Cancer Research. Toronto, Canada
- Prosserman Centre for Health Research, Samuel Lunenfeld Research Institute, Toronto, Canada
| | - Jouke-Jan Hottenga
- Netherlands Twin Register, Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Erik Ingelsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anne U. Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Toby Johnson
- Clinical Pharmacology and The Genome Centre, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Stavroula Kanoni
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hixton, Cambridge, UK
| | - Claes Ladenvall
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden
- Lund University Diabetes Centre, Malmö, Sweden
| | - Vasiliki Lagou
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Jari Lahti
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - Cecile Lecoeur
- Institut Pasteur de Lille, Lille, France
- Lille Nord de France University, Lille, France
| | - Yongmei Liu
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Maria Teresa Martinez-Larrad
- Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, Madrid, Spain
| | - May E. Montasser
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland, School of Medicine, Baltimore, Maryland, USA
| | - Pau Navarro
- MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Edinburgh, UK
| | - John R. B. Perry
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Genetics of Complex Traits, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter, UK
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
| | - Laura J. Rasmussen-Torvik
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Perttu Salo
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Naveed Sattar
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, UK
| | - Dmitry Shungin
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden
- Lund University Diabetes Centre, Malmö, Sweden
- Department of Public Health & Clinical Medicine, Genetic Epidemiology & Clinical Research Group, Umeå University Hospital, Umeå, Sweden
- Department of Odontology, Umeå University, Sweden
| | - Rona J. Strawbridge
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Toshiko Tanaka
- Clinical Research Branch, National Institute on Aging, Baltimore, Maryland, USA
| | - Cornelia M. van Duijn
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Centre for medical systems biology, Netherlands Genomics Initiative, The Hague
- Netherlands Genomics Initiative and the Netherlands Consortium for Healthy Aging, Rotterdam, The Netherlands
| | - Ping An
- Department of Genetics Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Mariza de Andrade
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Jeanette S. Andrews
- Department of Biostatistical Sciences, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Thor Aspelund
- Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Mustafa Atalay
- Institute of Biomedicine/Physiology, University of Eastern Finland, Kuopio Campus, Kuopio, Finland
| | - Yurii Aulchenko
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Beverley Balkau
- Inserm, CESP Centre for research in Epidemiology and Population Health, Villejuif, France
- University Paris Sud 11, Villejuif, France
| | | | - Jacques S. Beckmann
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- Service of Medical Genetics, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - John P. Beilby
- PathWest Laboratory Medicine of WA, J Block, QEII Medical Centre, Nedlands, Australia
- School of Pathology and Laboratory Medicine, The University of Western Australia, Nedlands, Australia
- Busselton Population Medical Research Foundation, B Block, QEII Medical Centre, Nedlands, Australia
| | - Claire Bellis
- Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Richard N. Bergman
- Department of Physiology & Biophysics, Keck School of Medicine of the University of Southern California, Los Angeles, California, USA
| | - John Blangero
- Texas Biomedical Research Institute, San Antonio, Texas, USA
| | - Mladen Boban
- Department of Pharmacology, Faculty of Medicine, University of Split, Croatia
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, Texas, USA
| | - Lori L. Bonnycastle
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland, USA
| | - Dorret I. Boomsma
- Netherlands Twin Register, Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Ingrid B. Borecki
- Department of Genetics Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Yvonne Böttcher
- IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
| | - Claude Bouchard
- Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA
| | - Eric Brunner
- University College London, Department of Epidemiology & Public Health, London, UK
| | - Danijela Budimir
- Department of Pharmacology, Faculty of Medicine, University of Split, Croatia
| | - Harry Campbell
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - Olga Carlson
- Laboratory of Clinical Investigation, National Institute of Aging, Baltimore, Maryland, USA
| | - Peter S. Chines
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland, USA
| | - Robert Clarke
- Clinical Trial Service Unit, University of Oxford, Oxford, UK
| | - Francis S. Collins
- Genome Technology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland, USA
| | - Arturo Corbatón-Anchuelo
- Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, Madrid, Spain
| | - David Couper
- Department of Biostatistics, University of North Carolina Gillings School of Global Public Health, Chapel Hill, North Carolina, USA
| | - Ulf de Faire
- Division of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - George V Dedoussis
- Department of Nutrition - Dietetics, Harokopio University, Athens, Greece
| | - Panos Deloukas
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hixton, Cambridge, UK
| | - Maria Dimitriou
- Department of Nutrition - Dietetics, Harokopio University, Athens, Greece
| | - Josephine M Egan
- Laboratory of Clinical Investigation, National Institute of Aging, Baltimore, Maryland, USA
| | | | - Michael R. Erdos
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland, USA
| | - Johan G. Eriksson
- Department of General Practice and Primary health Care, University of Helsinki, Finland
- Helsinki University Central Hospital, Unit of General Practice, Helsinki, Finland
- Folkhalsan Research Centre, Helsinki, Finland
- Vaasa Central Hospital, Vaasa, Finland
- National Institute for Health and Welfare, Helsinki, Finland
| | - Elodie Eury
- Institut Pasteur de Lille, Lille, France
- Lille Nord de France University, Lille, France
| | - Luigi Ferrucci
- Longitudinal Studies Section, Clinical Research Branch, National Institute on Aging, Baltimore, Maryland, USA
| | - Ian Ford
- Robertson Centre for Biostatistics, University of Glasgow, UK
| | - Nita G. Forouhi
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Caroline S Fox
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts, USA
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, USA
| | - Maria Grazia Franzosi
- Department of Cardiovascular Research, Mario Negri Institute for Pharmacological Research, Milan, Italy
| | - Paul W Franks
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden
- Lund University Diabetes Centre, Malmö, Sweden
- Department of Public Health & Clinical Medicine, Genetic Epidemiology & Clinical Research Group, Umeå University Hospital, Umeå, Sweden
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts, USA
- Institut National de la Recherche Agronomique, Université Paris, Bobigny Cedex, France
| | - Timothy M Frayling
- Genetics of Complex Traits, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter, UK
| | - Philippe Froguel
- Institut Pasteur de Lille, Lille, France
- Lille Nord de France University, Lille, France
- Genomic Medicine, Hammersmith Hospital, Imperial College London, London, UK
| | - Pilar Galan
- Institut National de la Santé et de la Recherche Médicale, Université Paris, Bobigny Cedex, France
| | - Eco de Geus
- Netherlands Twin Register, Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - Bruna Gigante
- Division of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Nicole L. Glazer
- Department of Medicine, Section of Preventive Medicine and Epidemiology, BU School of Medicine, Boston, Massachusetts, USA
- Department of Epidemiology, BU School of Public Health, Boston, Massachusetts, USA
| | - Anuj Goel
- Department of Cardiovascular Medicine and Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Leif Groop
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden
- Lund University Diabetes Centre, Malmö, Sweden
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Göran Hallmans
- Department of Public Health & Clinical Medicine, Nutrition Research, Umeå University, Sweden
| | - Anders Hamsten
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Ola Hansson
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden
- Lund University Diabetes Centre, Malmö, Sweden
| | - Tamara B. Harris
- Intramural Research Program, Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Bethesda, Maryland, USA
| | - Caroline Hayward
- MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Edinburgh, UK
| | - Simon Heath
- Centre National de Génotypage, Commissariat à L’Energie Atomique, Institut de Génomique, Evry, France
| | - Serge Hercberg
- Institut National de la Santé et de la Recherche Médicale, Université Paris, Bobigny Cedex, France
| | - Andrew A. Hicks
- Center for Biomedicine, European Academy Bozen/Bolzano, Bolzano, Italy - Affiliated Institute of the University of Lübeck, Lübeck, Germany
| | - Aroon Hingorani
- Genetic epidemiology group, University College London, Department of Epidemiology & Public Health, London, UK
| | - Albert Hofman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative and the Netherlands Consortium for Healthy Aging, Rotterdam, The Netherlands
| | - Jennie Hui
- PathWest Laboratory Medicine of WA, J Block, QEII Medical Centre, Nedlands, Australia
- School of Pathology and Laboratory Medicine, The University of Western Australia, Nedlands, Australia
- Busselton Population Medical Research Foundation, B Block, QEII Medical Centre, Nedlands, Australia
- School of Population Health, The University of Western Australia, Nedlands, Australia
| | - Joseph Hung
- Busselton Population Medical Research Foundation, B Block, QEII Medical Centre, Nedlands, Australia
- Sir Charles Gairdner Hospital Unit, School of Medicine & Pharmacology, University of Western Australia, Australia
| | - Marjo Riitta Jarvelin
- Department of Epidemiology and Biostatistics, School of Public Health, MRC-HPA Centre for Environment and Health, Faculty of Medicine, Imperial College London, UK
- Institute of Health Sciences, University of Oulu, Oulu, Finland
- Biocenter Oulu, University of Oulu, Oulu, Finland
- National Institute of Health and Welfare, Oulu, Finland
| | - Min A. Jhun
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA
| | | | - J Wouter Jukema
- Department of Cardiology C5-P, Leiden University Medical Center, Leiden, the Netherlands
- Durrer Center for Cardiogenetic Research, Amsterdam, The Netherlands
| | - Antti Jula
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - W.H. Kao
- Division of Epidemiology, Johns Hopkins School of Public Health, Baltimore, Maryland, USA
| | - Jaakko Kaprio
- National Institute for Health and Welfare, Helsinki, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Hjelt Institute, Dept of Public Health, University of Helsinki, Finland
| | - Sharon L. R. Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Sirkka Keinanen-Kiukaanniemi
- Faculty of Medicine, Institute of Health Sciences, University of Oulu, Oulu, Finland
- Unit of General Practice, Oulu University Hospital, Oulu, Finland
| | - Mika Kivimaki
- University College London, Department of Epidemiology & Public Health, London, UK
| | - Ivana Kolcic
- Department of Public Health, Faculty of Medicine, University of Split, Croatia
| | - Peter Kovacs
- Interdisciplinary Centre for Clinical Research, University of Leipzig, Leipzig, Germany
| | - Meena Kumari
- Genetic epidemiology group, University College London, Department of Epidemiology & Public Health, London, UK
| | - Johanna Kuusisto
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Kirsten Ohm Kyvik
- Institute of Regional Health Services Research and Professor Odense Patient data Explorative Network (OPEN)
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Timo Lakka
- Institute of Biomedicine/Physiology, University of Eastern Finland, Kuopio Campus, Kuopio, Finland
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
| | - Lars Lannfelt
- Department of Public Health and Caring Sciences, Uppsala University, Rudbecklaboratoriet, Uppsala, Sweden
| | - G Mark Lathrop
- Centre National de Génotypage, Commissariat à L’Energie Atomique, Institut de Génomique, Evry, France
| | - Lenore J. Launer
- Intramural Research Program, Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, Bethesda, Maryland, USA
| | - Karin Leander
- Division of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Guo Li
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, USA
| | - Lars Lind
- Department of Medical Sciences, University Hospital, Uppsala University, Uppsala, Sweden
| | - Jaana Lindstrom
- Diabetes Prevention Unit, Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Stéphane Lobbens
- Institut Pasteur de Lille, Lille, France
- Lille Nord de France University, Lille, France
| | - Ruth J. F. Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Jian’an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Valeriya Lyssenko
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Malmö, Sweden
- Lund University Diabetes Centre, Malmö, Sweden
| | - Reedik Mägi
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Patrik K. E. Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Michael Marmot
- University College London, Department of Epidemiology & Public Health, London, UK
| | - Pierre Meneton
- Institut National de la Santé et de la Recherche Médicale, Centre de Recherche des Cordeliers, Paris, France
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Vincent Mooser
- Division of Genetics, GlaxoSmithKline, Philadelphia, Pennsylvania, USA
| | - Mario A. Morken
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland, USA
| | - Iva Miljkovic
- Department of Epidemiology, Center for Aging and Population Health, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
| | - Narisu Narisu
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland, USA
| | - Jeff O’Connell
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland, School of Medicine, Baltimore, Maryland, USA
| | - Ken K. Ong
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Ben A. Oostra
- Department of Clinical Genetics, Erasmus MC, Rotterdam, The Netherlands
| | - Lyle J. Palmer
- Genetic Epidemiology and Biostatistics Platform, Ontario Institute for Cancer Research. Toronto, Canada
- Prosserman Centre for Health Research, Samuel Lunenfeld Research Institute, Toronto, Canada
| | - Aarno Palotie
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hixton, Cambridge, UK
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
- Department of Medical Genetics, University of Helsinki and Helsinki University Central Hospital, Finland
| | - James S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, Minnesota, USA
| | - John F. Peden
- Department of Cardiovascular Medicine and Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Marina Pehlic
- Department of Biology, Faculty of Medicine, University of Split, Croatia
| | - Leena Peltonen
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hixton, Cambridge, UK
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Brenda Penninx
- Department of Psychiatry, Leiden University Medical Center, Leiden, The Netherlands
- Department of Psychiatry, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
- Department Psychiatry, EMGO Institute for Health and Care Research and Institute for Neurosciences, VU University Medical Center, Amsterdam, The Netherlands
| | | | - Markus Perola
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Louis Perusse
- Department of Preventive Medicine, Laval University, Quebec, Canada
| | - Patricia A Peyser
- Department of Epidemiology, University of Michigan, Ann Arbor, Michigan, USA
| | - Ozren Polasek
- Department of Public Health, Faculty of Medicine, University of Split, Croatia
| | - Peter P. Pramstaller
- Center for Biomedicine, European Academy Bozen/Bolzano, Bolzano, Italy - Affiliated Institute of the University of Lübeck, Lübeck, Germany
| | - Michael A. Province
- Department of Genetics Division of Statistical Genomics, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Katri Räikkönen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - Rainer Rauramaa
- Kuopio Research Institute of Exercise Medicine, Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Emil Rehnberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ken Rice
- Department of Biostatistics, University of Washington, Seattle, Washington, USA
| | | | - Igor Rudan
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
- Centre for Global Health, University of Split, Croatia
| | - Aimo Ruokonen
- Institute of Clinical Medicine, University of Oulu, Finland
| | - Timo Saaristo
- Finnish Diabetes Association, Tampere, Finland
- Pirkanmaa Hospital District, Tampere, Finland
| | - Maria Sabater-Lleal
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Veikko Salomaa
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - David B. Savage
- Metabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Addenbrooke’s Hospital, Cambridge, UK
| | - Richa Saxena
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Peter Schwarz
- Department of Medicine, Division Prevention and Care of Diabetes, University of Dresden, Dresden, Germany
| | - Udo Seedorf
- Leibniz Institute for Arteriosclerosis Research, University of Munster, Germany
| | - Bengt Sennblad
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Manuel Serrano-Rios
- Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders, Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, Madrid, Spain
| | - Alan R. Shuldiner
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland, School of Medicine, Baltimore, Maryland, USA
- Geriatric Research and Education Clinical Center, Veterans Administration Medical Center, Baltimore, Maryland, USA
| | | | - David S. Siscovick
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington, USA
- Department of Medicine, University of Washington, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
| | - Johannes H. Smit
- Department of Psychiatry, Neuroscience Campus Amsterdam, VU University Medical Centre, Amsterdam, The Netherlands
| | - Kerrin S. Small
- Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK
| | - Nicholas L. Smith
- Department of Medicine, University of Washington, Seattle, Washington, USA
- Department of Epidemiology, University of Washington, Seattle, Washington, USA
- Group Health Research Institute, Group Health Cooperative, Seattle, Washington, USA
- Seattle Epidemiologic Research and Information Center, Veterans Affairs Office of Research and Development, Seattle, WA, USA
| | - Albert Vernon Smith
- Icelandic Heart Association, Kopavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - Alena Stančáková
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Kathleen Stirrups
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hixton, Cambridge, UK
| | - Michael Stumvoll
- IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
- Department of Medicine, University of Leipzig, Division of Endocrinology and Diabetes, Leipzig, Germany
| | - Yan V. Sun
- Department of Epidemiology, Emory University, Atlanta, Georgia, US
| | - Amy J. Swift
- Genome Technology Branch, National Human Genome Research Institute, Bethesda, Maryland, USA
| | - Anke Tönjes
- IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
- Department of Medicine, University of Leipzig, Division of Endocrinology and Diabetes, Leipzig, Germany
| | - Jaakko Tuomilehto
- Diabetes Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland
- South Ostrobothnia Central Hospital, Seinäjoki, Finland
- Hospital Universitario La Paz, Madrid, Spain
- Centre for Vascular Prevention, Danube-University Krems, Krems, Austria
| | - Stella Trompet
- Department of Cardiology C5-P, Leiden University Medical Center, Leiden, the Netherlands
| | - Andre G. Uitterlinden
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative and the Netherlands Consortium for Healthy Aging, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - Matti Uusitupa
- Institute of Public Health and Clinical Nutrition, University of Easten Finland, Kuopio, Finland
- Research Unit, Kuopio University Hospital, Kuopio, Finland
| | - Max Vikström
- Division of Cardiovascular Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Veronique Vitart
- MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Edinburgh, UK
| | - Marie-Claude Vohl
- Department of Food Science and Nutrition, Laval University, Quebec, Canada
| | - Benjamin F. Voight
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
| | - Peter Vollenweider
- Department of Internal Medicine, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Gerard Waeber
- Department of Internal Medicine, Centre Hospitalier Universitaire Vaudois, Lausanne, Switzerland
| | - Dawn M Waterworth
- Division of Genetics, GlaxoSmithKline, Philadelphia, Pennsylvania, USA
| | - Hugh Watkins
- Department of Cardiovascular Medicine and Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Eleanor Wheeler
- Metabolic Disease Group, Wellcome Trust Sanger Institute, Hinxton, UK
| | - Elisabeth Widen
- Institute for Molecular Medicine Finland, University of Helsinki, Finland
| | - Sarah H. Wild
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - Sara M. Willems
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - Gonneke Willemsen
- Netherlands Twin Register, Department of Biological Psychology, VU University, Amsterdam, The Netherlands
| | - James F. Wilson
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
| | - Jacqueline C.M. Witteman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative and the Netherlands Consortium for Healthy Aging, Rotterdam, The Netherlands
| | - Alan F. Wright
- MRC Human Genetics Unit, MRC IGMM, University of Edinburgh, Edinburgh, UK
| | - Hanieh Yaghootkar
- Genetics of Complex Traits, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter, UK
| | - Diana Zelenika
- Centre National de Génotypage, Commissariat à L’Energie Atomique, Institut de Génomique, Evry, France
| | - Tatijana Zemunik
- Department of Biology, Faculty of Medicine, University of Split, Croatia
| | - Lina Zgaga
- Centre for Population Health Sciences, University of Edinburgh, Edinburgh, UK
- Department of medical statistics, epidemiology and medical informatics, University of Zagreb, Zagreb, Croatia
| | | | | | - Nicholas J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Mark I. McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
| | - Ines Barroso
- Metabolic Disease Group, Wellcome Trust Sanger Institute, Hinxton, UK
- University of Cambridge, Metabolic Research Laboratories, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
| | - Richard M. Watanabe
- Department of Physiology & Biophysics, Keck School of Medicine of the University of Southern California, Los Angeles, California, USA
- Department of Preventive Medicine, Keck School of Medicine of the University of Southern California, Los Angeles, California, USA
| | - Jose C. Florez
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts, USA
- Diabetes Research Center, Diabetes Unit, Massachusetts General Hospital, Boston, Massachusetts, USA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts, USA
| | - James B. Meigs
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts, USA
- Department of Medicine, Harvard Medical School, Boston, Massachusetts, USA
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge, UK
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Oliveira CSV, Saddi-Rosa P, Crispim F, Canani LH, Gerchman F, Giuffrida FMA, Vieira JGH, Velho G, Reis AF. Association of ADIPOQ variants, total and high molecular weight adiponectin levels with coronary artery disease in diabetic and non-diabetic Brazilian subjects. J Diabetes Complications 2012; 26:94-8. [PMID: 22459242 DOI: 10.1016/j.jdiacomp.2012.02.008] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2011] [Revised: 01/20/2012] [Accepted: 02/24/2012] [Indexed: 01/13/2023]
Abstract
OBJECTIVE To investigate the association of ADIPOQ variants, total and high molecular weight adiponectin (HMW) adiponectin levels with the prevalence of diabetes mellitus and coronary artery disease (CAD) diagnosed by coronary angiography in Brazilian subjects with high cardiovascular risk. METHODS 603 subjects undergoing coronary angiography were studied in regard to their glycemic status and presence of CAD (lesions >0%). We evaluated baseline concentrations of total and HMW adiponectin and three ADIPOQ variants: -11391G>A (rs17300539), +45T>G (rs2241766) and+276G>T (rs1501299). RESULTS The G-allele of rs2241766 was associated with higher levels of total and HMW adiponectin, and the A-allele of rs17300539 was associated with higher levels of HMW adiponectin. Lower levels of total and HMW adiponectin were independently associated with CAD. The G-allele of rs2241766 (OR 2.45, 95% C.I. 1.05-6.04, p=0.04) and the G-allele of rs1501299 (OR 1.89, 95% C.I. 1.04-3.45, p=0.03) were associated with CAD, and these associations were independent of circulating levels of adiponectin. CONCLUSIONS In Brazilian subjects with high cardiovascular risk, CAD was associated with lower total and HMW adiponectin levels. The rs2241766 and rs1501299 polymorphisms were associated with CAD. The rs2241766 variant was associated with total and HMW adiponectin levels, while rs17300539 was associated with HMW adiponectin levels.
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Kizer JR, Arnold AM, Benkeser D, Ix JH, Djousse L, Zieman SJ, Barzilay JI, Tracy RP, Mantzoros CS, Siscovick DS, Mukamal KJ. Total and high-molecular-weight adiponectin and risk of incident diabetes in older people. Diabetes Care 2012; 35:415-23. [PMID: 22148099 PMCID: PMC3263897 DOI: 10.2337/dc11-1519] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To delineate the associations of total adiponectin, high-molecular-weight (HMW) adiponectin, and the HMW-to-total adiponectin ratio with diabetes in older adults. RESEARCH DESIGN AND METHODS Total and HMW adiponectin were measured in a population-based study of older adults. The relations of total adiponectin, HMW adiponectin, and their ratio with incident diabetes (n = 309) were assessed in 3,802 individuals. RESULTS Total and HMW adiponectin were highly correlated (r = 0.94). Analysis using cubic splines revealed that the associations between total and HMW adiponectin and new-onset diabetes were not linear. Specifically, after adjustment for confounders, there were similar inverse relationships for total (hazard ratio per SD 0.49 [95% CI 0.39-0.63]) and HMW adiponectin (0.42 [0.32-0.56]) with diabetes up to values of 20 and 10 mg/L, respectively, above which the associations plateaued. These associations persisted after adjustment for potential mediators (blood pressure, lipids, C-reactive protein, and homeostasis model assessment of insulin resistance [HOMA-IR]). There was, however, evidence of interaction by HOMA-IR in the lower range of adiponectin, with stronger inverse associations among insulin-sensitive than insulin-resistant participants. HMW-to-total adiponectin ratio showed a linear adjusted association with outcome, but this was abolished by inclusion of mediating variables. CONCLUSIONS In this older cohort, increasing concentrations of total and HMW adiponectin were associated with comparably lower risks of diabetes, but these associations leveled off with further increases above concentrations of 20 and 10 mg/L, respectively. The more pronounced risk decreases at the lower range among participants without insulin resistance support a role for adiponectin that is independent of baseline hyperinsulinemia, but this will require further investigation.
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Affiliation(s)
- Jorge R Kizer
- Department of Medicine, Weill Cornell Medical College, New York, New York, USA.
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Lilja M, Rolandsson O, Norberg M, Söderberg S. The impact of leptin and adiponectin on incident type 2 diabetes is modified by sex and insulin resistance. Metab Syndr Relat Disord 2012; 10:143-51. [PMID: 22283633 DOI: 10.1089/met.2011.0123] [Citation(s) in RCA: 29] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Adiponectin and leptin and their ratio have been associated with incident type 2 diabetes (T2DM), although the data presented are conflicting and the populations studied have been small. In this large, prospective, nested, case referent study, we hypothesized that these associations are sex specific and may be modified by insulin resistance. METHODS Men and women aged 30-60 years with incident T2DM (n=640) and a prior health survey within the Västerbotten Intervention Programme (VIP) and matched referents (n=1564) were identified. Using conditional logistic regression analyses, we tested whether baseline plasma adiponectin and leptin levels and their ratio independently predicted incident T2DM, stratified for gender and insulin resistance. RESULTS Adjusted for traditional risk factors, fourth-quartile levels of adiponectin were associated with a reduced risk of T2DM in men [odds ratio (OR) 0.55 (0.36-0.86)] and women [OR 0.47 (0.27-0.83)]. Quartile four of the leptin/adiponectin ratio predicted T2DM in both men [OR 3.08 (1.68-5.67)] and women [OR 3.31 (1.56-7.03)], whereas quartile-four levels of leptin predicted T2DM only in men [OR 2.30 (1.32-4.02)]. When stratified for insulin sensitivity and adjusted for body mass index (BMI), log(e)-transformed leptin predicted T2DM in insulin-sensitive men [OR 1.56 (1.13-2.17)] but not in insulin-resistant men [OR 1.03 (0.76-1.39)]. The effect of adiponectin and the leptin/adiponectin ratio was not influenced by the insulin sensitivity status. CONCLUSIONS Leptin in men and adiponectin in both sexes were independent predictors of T2DM. The association was modified by the degree of insulin sensitivity. The leptin/adiponectin ratio may add predictive information beyond the separate hormones.
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Affiliation(s)
- Mikael Lilja
- The Research and Development Unit, Jämtland County Council, Östersund, Sweden.
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Current World Literature. Curr Opin Nephrol Hypertens 2012; 21:106-18. [DOI: 10.1097/mnh.0b013e32834ee42b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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Hanley AJG, Wagenknecht LE, Norris JM, Bergman R, Anderson A, Chen YI, Lorenzo C, Haffner SM. Adiponectin and the incidence of type 2 diabetes in Hispanics and African Americans: the IRAS Family Study. Diabetes Care 2011; 34:2231-6. [PMID: 21816973 PMCID: PMC3177725 DOI: 10.2337/dc11-0531] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
OBJECTIVE A recent meta-analysis of 13 prospective studies reported that higher levels of adiponectin were significantly associated with lower risk of type 2 diabetes. Most previous studies, however, were limited in their ability to adjust for appropriate confounding variables. Our objective, therefore, was to study this association after adjustment for directly measured adiposity and insulin sensitivity, expressed as the insulin sensitivity index (S(I)). RESEARCH DESIGN AND METHODS The study included 1,096 Hispanic and African American participants free of diabetes at baseline (2000-2002) who returned for follow-up after 5 years. S(I) was determined from frequently sampled intravenous glucose tolerance tests with minimal model analysis. Visceral adipose tissue (VAT) area was determined by computed tomography. Diabetes and impaired fasting glucose (IFG) were defined using American Diabetes Association criteria. Multivariate generalized estimating equation logistic regression models were used to account for correlations within families. RESULTS A total of 82 subjects met criteria for incident diabetes. After adjustment for age, sex, ethnicity, and smoking, adiponectin was significantly inversely associated with diabetes (odds ratio [OR] 0.54 per 1 SD difference [95% CI 0.38-0.76]). The association remained significant after additional adjustment in individual models for BMI, homeostasis model assessment of insulin resistance, or VAT (all P < 0.05). However, adiponectin was no longer associated in separate models adjusted for S(I) or IFG (OR 0.81 [0.56-1.16] and 0.75 [0.53-1.06], respectively). CONCLUSIONS Adiponectin was inversely associated with incident diabetes after adjustment for conventional anthropometric and metabolic variables or VAT. Adjustment for detailed measures of S(I) attenuated this relationship, however, suggesting that the link between adiponectin and diabetes may operate at least in part through insulin resistance.
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Affiliation(s)
- Anthony J G Hanley
- Department of Nutritional Sciences and Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada.
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Oliveira CSV, Giuffrida FMA, Crispim F, Saddi-Rosa P, Reis AF. ADIPOQ and adiponectin: the common ground of hyperglycemia and coronary artery disease? ACTA ACUST UNITED AC 2011; 55:446-54. [DOI: 10.1590/s0004-27302011000700003] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2011] [Accepted: 10/30/2011] [Indexed: 01/02/2023]
Abstract
Plasma adiponectin and the coding gene for adiponectin, ADIPOQ, are thought to explain part of the interaction between obesity, insulin resistance, type 2 diabetes (T2DM) and coronary artery disease (CAD). Here, we illustrate the role that adiponectin and ADIPOQ variants might play in the modulation of CAD, especially in the occurrence of hyperglycemia. Recent evidence suggests that total and high molecular weight (HMW) adiponectin levels are apparent markers of better cardiovascular prognosis in patients with low risk of CAD. However, in subjects with established or high risk of CAD, these levels are associated with poorer prognosis. We also provide recent evidences relating to the genetic control of total and HMW adiponectin levels, especially evidence regarding ADIPOQ. Accumulated data suggest that both adiponectin levels and polymorphisms in the ADIPOQ gene are linked to the risk of CAD in patients with hyperglycemia, and that these associations seem to be independent from each other, even if adiponectin levels are partly dependent on ADIPOQ.
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