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Nielsen MB, Çolak Y, Benn M, Mason A, Burgess S, Nordestgaard BG. Plasma adiponectin levels and risk of heart failure, atrial fibrillation, aortic valve stenosis, and myocardial infarction: large-scale observational and Mendelian randomization evidence. Cardiovasc Res 2024; 120:95-107. [PMID: 37897683 PMCID: PMC10898934 DOI: 10.1093/cvr/cvad162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 09/07/2023] [Accepted: 09/23/2023] [Indexed: 10/30/2023] Open
Abstract
AIMS Adiponectin may play an important protective role in heart failure and associated cardiovascular diseases. We hypothesized that plasma adiponectin is associated observationally and causally, genetically with risk of heart failure, atrial fibrillation, aortic valve stenosis, and myocardial infarction. METHODS AND RESULTS In the Copenhagen General Population Study, we examined 30 045 individuals with plasma adiponectin measurements observationally and 96 903 individuals genetically in one-sample Mendelian randomization analyses using five genetic variants explaining 3% of the variation in plasma adiponectin. In the HERMES, UK Biobank, The Nord-Trøndelag Health Study (HUNT), deCODE, the Michigan Genomics Initiative (MGI), DiscovEHR, and the AFGen consortia, we performed two-sample Mendelian randomization analyses in up to 1 030 836 individuals using 12 genetic variants explaining 14% of the variation in plasma adiponectin.In observational analyses modelled linearly, a 1 unit log-transformed higher plasma adiponectin was associated with a hazard ratio of 1.51 (95% confidence interval: 1.37-1.66) for heart failure, 1.63 (1.50-1.78) for atrial fibrillation, 1.21 (1.03-1.41) for aortic valve stenosis, and 1.03 (0.93-1.14) for myocardial infarction; levels above the median were also associated with an increased risk of myocardial infarction, and non-linear U-shaped associations were more apparent for heart failure, aortic valve stenosis, and myocardial infarction in less-adjusted models. Corresponding genetic, causal risk ratios were 0.92 (0.65-1.29), 0.87 (0.68-1.12), 1.55 (0.87-2.76), and 0.93 (0.67-1.30) in one-sample Mendelian randomization analyses, and no significant associations were seen for non-linear one-sample Mendelian randomization analyses; corresponding causal risk ratios were 0.99 (0.89-1.09), 1.00 (0.92-1.08), 1.01 (0.79-1.28), and 0.99 (0.86-1.13) in two-sample Mendelian randomization analyses, respectively. CONCLUSION Observationally, elevated plasma adiponectin was associated with an increased risk of heart failure, atrial fibrillation, aortic valve stenosis, and myocardial infarction. However, genetic evidence did not support causality for these associations.
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Affiliation(s)
- Maria Booth Nielsen
- Department of Clinical Biochemistry, Copenhagen University Hospital—Herlev and Gentofte, Borgmester Ib Juuls Vej 73, Entrance 7, 4. Floor, M3, DK-2730 Herlev, Copenhagen, Denmark
- The Copenhagen General Population Study, Copenhagen University Hospital—Herlev and Gentofte, Borgmester Ib Juuls Vej 73, Entrance 7, 4. Floor, M3, DK-2730 Herlev, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen N, Copenhagen, Denmark
| | - Yunus Çolak
- The Copenhagen General Population Study, Copenhagen University Hospital—Herlev and Gentofte, Borgmester Ib Juuls Vej 73, Entrance 7, 4. Floor, M3, DK-2730 Herlev, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen N, Copenhagen, Denmark
- Department of Respiratory Medicine, Copenhagen University Hospital—Herlev and Gentofte, Copenhagen, Denmark
| | - Marianne Benn
- The Copenhagen General Population Study, Copenhagen University Hospital—Herlev and Gentofte, Borgmester Ib Juuls Vej 73, Entrance 7, 4. Floor, M3, DK-2730 Herlev, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen N, Copenhagen, Denmark
- Department of Clinical Biochemistry, Copenhagen University Hospital—Rigshospitalet, Copenhagen, Denmark
| | - Amy Mason
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- Heart and Lung Research Institute, University of Cambridge, Cambridge, United Kingdom
| | - Stephen Burgess
- Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom
- British Heart Foundation Cardiovascular Epidemiology Unit, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
- Heart and Lung Research Institute, University of Cambridge, Cambridge, United Kingdom
| | - Børge Grønne Nordestgaard
- Department of Clinical Biochemistry, Copenhagen University Hospital—Herlev and Gentofte, Borgmester Ib Juuls Vej 73, Entrance 7, 4. Floor, M3, DK-2730 Herlev, Copenhagen, Denmark
- The Copenhagen General Population Study, Copenhagen University Hospital—Herlev and Gentofte, Borgmester Ib Juuls Vej 73, Entrance 7, 4. Floor, M3, DK-2730 Herlev, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, DK-2200 Copenhagen N, Copenhagen, Denmark
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2
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Bai Y, Bentley L, Ma C, Naveenan N, Cleak J, Wu Y, Simon MM, Westerberg H, Cañas RC, Horner N, Pandey R, Paphiti K, Schulze U, Mianné J, Hough T, Teboul L, de Baaij JH, Cox RD. Cleft palate and minor metabolic disturbances in a mouse global Arl15 gene knockout. FASEB J 2023; 37:e23211. [PMID: 37773757 PMCID: PMC10631251 DOI: 10.1096/fj.202201918r] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 07/27/2023] [Accepted: 09/08/2023] [Indexed: 10/01/2023]
Abstract
ARL15, a small GTPase protein, was linked to metabolic traits in association studies. We aimed to test the Arl15 gene as a functional candidate for metabolic traits in the mouse. CRISPR/Cas9 germline knockout (KO) of Arl15 showed that homozygotes were postnatal lethal and exhibited a complete cleft palate (CP). Also, decreased cell migration was observed from Arl15 KO mouse embryonic fibroblasts (MEFs). Metabolic phenotyping of heterozygotes showed that females had reduced fat mass on a chow diet from 14 weeks of age. Mild body composition phenotypes were also observed in heterozygous mice on a high-fat diet (HFD)/low-fat diet (LFD). Females on a HFD showed reduced body weight, gonadal fat depot weight and brown adipose tissue (BAT) weight. In contrast, in the LFD group, females showed increased bone mineral density (BMD), while males showed a trend toward reduced BMD. Clinical biochemistry analysis of plasma on HFD showed transient lower adiponectin at 20 weeks of age in females. Urinary and plasma Mg2+ concentrations were not significantly different. Our phenotyping data showed that Arl15 is essential for craniofacial development. Adult metabolic phenotyping revealed potential roles in brown adipose tissue and bone development.
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Affiliation(s)
- Ying Bai
- Mammalian Genetics Unit and Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxon OX11 0RD, UK
| | - Liz Bentley
- Mammalian Genetics Unit and Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxon OX11 0RD, UK
| | - Chao Ma
- Department of Physiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Nijmegen, The Netherlands
| | | | - James Cleak
- Mammalian Genetics Unit and Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxon OX11 0RD, UK
| | - Yixing Wu
- Mammalian Genetics Unit and Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxon OX11 0RD, UK
| | - Michelle M Simon
- Mammalian Genetics Unit and Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxon OX11 0RD, UK
| | - Henrik Westerberg
- Mammalian Genetics Unit and Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxon OX11 0RD, UK
| | - Ramón Casero Cañas
- Mammalian Genetics Unit and Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxon OX11 0RD, UK
| | - Neil Horner
- Mammalian Genetics Unit and Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxon OX11 0RD, UK
| | - Rajesh Pandey
- Mammalian Genetics Unit and Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxon OX11 0RD, UK
| | - Keanu Paphiti
- Mammalian Genetics Unit and Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxon OX11 0RD, UK
| | | | - Joffrey Mianné
- Mammalian Genetics Unit and Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxon OX11 0RD, UK
| | - Tertius Hough
- Mammalian Genetics Unit and Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxon OX11 0RD, UK
| | - Lydia Teboul
- Mammalian Genetics Unit and Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxon OX11 0RD, UK
| | - Jeroen H.F. de Baaij
- Department of Physiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Centre, Nijmegen, The Netherlands
| | - Roger D. Cox
- Mammalian Genetics Unit and Mary Lyon Centre, MRC Harwell Institute, Didcot, Oxon OX11 0RD, UK
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3
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Mahbub L, Kozlov G, Zong P, Lee EL, Tetteh S, Nethramangalath T, Knorn C, Jiang J, Shahsavan A, Yue L, Runnels L, Gehring K. Structural insights into regulation of CNNM-TRPM7 divalent cation uptake by the small GTPase ARL15. eLife 2023; 12:e86129. [PMID: 37449820 PMCID: PMC10348743 DOI: 10.7554/elife.86129] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 07/02/2023] [Indexed: 07/18/2023] Open
Abstract
Cystathionine-β-synthase (CBS)-pair domain divalent metal cation transport mediators (CNNMs) are an evolutionarily conserved family of magnesium transporters. They promote efflux of Mg2+ ions on their own and influx of divalent cations when expressed with the transient receptor potential ion channel subfamily M member 7 (TRPM7). Recently, ADP-ribosylation factor-like GTPase 15 (ARL15) has been identified as CNNM-binding partner and an inhibitor of divalent cation influx by TRPM7. Here, we characterize ARL15 as a GTP and CNNM-binding protein and demonstrate that ARL15 also inhibits CNNM2 Mg2+ efflux. The crystal structure of a complex between ARL15 and CNNM2 CBS-pair domain reveals the molecular basis for binding and allowed the identification of mutations that specifically block binding. A binding deficient ARL15 mutant, R95A, failed to inhibit CNNM and TRPM7 transport of Mg2+ and Zn2+ ions. Structural analysis and binding experiments with phosphatase of regenerating liver 2 (PRL2 or PTP4A2) showed that ARL15 and PRLs compete for binding CNNM to coordinate regulation of ion transport by CNNM and TRPM7.
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Affiliation(s)
- Luba Mahbub
- Department of Biochemistry, McGill UniversityMontrealCanada
- Centre de recherche en biologie structurale, McGill UniversityMontréalCanada
| | - Guennadi Kozlov
- Department of Biochemistry, McGill UniversityMontrealCanada
- Centre de recherche en biologie structurale, McGill UniversityMontréalCanada
| | - Pengyu Zong
- Department of Cell Biology, UCONN Health CenterFarmingtonUnited States
| | - Emma L Lee
- Department of Biochemistry, McGill UniversityMontrealCanada
- Centre de recherche en biologie structurale, McGill UniversityMontréalCanada
| | - Sandra Tetteh
- Rutgers-Robert Wood Johnson Medical SchoolPiscatawayUnited States
| | | | - Caroline Knorn
- Department of Biochemistry, McGill UniversityMontrealCanada
- Centre de recherche en biologie structurale, McGill UniversityMontréalCanada
| | - Jianning Jiang
- Department of Biochemistry, McGill UniversityMontrealCanada
- Centre de recherche en biologie structurale, McGill UniversityMontréalCanada
| | - Ashkan Shahsavan
- Department of Biochemistry, McGill UniversityMontrealCanada
- Centre de recherche en biologie structurale, McGill UniversityMontréalCanada
| | - Lixia Yue
- Department of Cell Biology, UCONN Health CenterFarmingtonUnited States
| | - Loren Runnels
- Rutgers-Robert Wood Johnson Medical SchoolPiscatawayUnited States
| | - Kalle Gehring
- Department of Biochemistry, McGill UniversityMontrealCanada
- Centre de recherche en biologie structurale, McGill UniversityMontréalCanada
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4
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Mollahosseini M, Yazdanpanah Z, Nadjarzadeh A, Mirzaei M, Kalantar SM, Mirzaei K, Mozaffari-Khosravi H. Study Protocol for the Interactions between Dietary Patterns and ARL15 and ADIPOQ Genes Polymorphisms on Cardiometabolic Risk Factors. Int J Prev Med 2023; 14:62. [PMID: 37351048 PMCID: PMC10284236 DOI: 10.4103/ijpvm.ijpvm_17_22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 06/15/2022] [Indexed: 06/24/2023] Open
Abstract
Background Cardiovascular diseases (CVDs) are recognized as one of the leading causes of death worldwide. Studies have shown the impact of genetic predisposition and dietary factors on developing these diseases. Dietary patterns and genetic factors such as polymorphisms related to the level of adiponectin may also interact with each other and produce variances in the effects of these factors on different individuals. The purpose of this study is to investigate the interactions between food intake patterns and polymorphisms on ADIPOQ and ARL15 genes in relation to cardiometabolic risk factors. Methods This cross-sectional study is conducted on 380 adults (20 to 70 years old) living in Yazd, Iran. Individuals were selected from the participants in Yazd Health Study (YaHS) and its sub-study called Taghziyeh Mardom-e Yazd (TAMYZ) after reviewing the inclusion and exclusion criteria. YaHS is a population-based cohort study which has been conducted on 9962 adults living in Yazd since 2014. In the present study, rotated principle component analysis (PCA) with Varimax rotation is used to identify the major dietary patterns. The polymerase chain reaction-restricted fragment length polymorphism (PCR-RFLP) method is used in order to identify rs1501299 and rs6450176 variants (on ADIPOQ and ARL15 genes, respectively). General linear models (GLM) as well as regression models are used to investigate the interactions between the studied genotypes and the extracted dietary patterns. Conclusions The results of this study can help to personalize dietary recommendations for the prevention of CVDs according to the genetic predisposition of individuals.
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Affiliation(s)
- Mehdi Mollahosseini
- Nutrition and Food Security Research Center, Yazd, Iran
- Department of Nutrition, School of Public Health, Yazd, Iran
| | - Zeinab Yazdanpanah
- Nutrition and Food Security Research Center, Yazd, Iran
- Department of Nutrition, School of Public Health, Yazd, Iran
| | - Azadeh Nadjarzadeh
- Nutrition and Food Security Research Center, Yazd, Iran
- Department of Nutrition, School of Public Health, Yazd, Iran
| | | | - Seyed Mehdi Kalantar
- Department of Medical Genetics, Reproduction Sciences Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
- Research and Clinical Center for Infertility, Reproduction Sciences Institute, Shahid Sadoughi University of Medical Sciences, Yazd, Iran
| | - Khadijeh Mirzaei
- Department of Community Nutrition, School of Nutritional Sciences and Dietetics, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Hassan Mozaffari-Khosravi
- Nutrition and Food Security Research Center, Yazd, Iran
- Department of Nutrition, School of Public Health, Yazd, Iran
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5
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Mahbub L, Kozlov G, Zong P, Tetteh S, Nethramangalath T, Knorn C, Jiang J, Shahsavan A, Lee E, Yue L, Runnels LW, Gehring K. Structural insights into regulation of TRPM7 divalent cation uptake by the small GTPase ARL15. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.19.524765. [PMID: 36711628 PMCID: PMC9882303 DOI: 10.1101/2023.01.19.524765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Cystathionine-β-synthase (CBS)-pair domain divalent metal cation transport mediators (CNNMs) are an evolutionarily conserved family of magnesium transporters. They promote efflux of Mg 2+ ions on their own or uptake of divalent cations when coupled to the transient receptor potential ion channel subfamily M member 7 (TRPM7). Recently, ADP-ribosylation factor-like GTPase 15 (ARL15) has been identified as CNNM binding partner and an inhibitor of divalent cation influx by TRPM7. Here, we characterize ARL15 as a GTP-binding protein and demonstrate that it binds the CNNM CBS-pair domain with low micromolar affinity. The crystal structure of the complex between ARL15 GTPase domain and CNNM2 CBS-pair domain reveals the molecular determinants of the interaction and allowed the identification of mutations in ARL15 and CNNM2 mutations that abrogate binding. Loss of CNNM binding prevented ARL15 suppression of TRPM7 channel activity in support of previous reports that the proteins function as a ternary complex. Binding experiments with phosphatase of regenerating liver 2 (PRL2 or PTP4A2) revealed that ARL15 and PRLs compete for binding CNNM, suggesting antagonistic regulation of divalent cation transport by the two proteins.
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Affiliation(s)
- Luba Mahbub
- Department of Biochemistry, McGill University, Montréal, Canada,Centre de recherche en biologie structurale, McGill University, Montréal, Canada
| | - Guennadi Kozlov
- Department of Biochemistry, McGill University, Montréal, Canada,Centre de recherche en biologie structurale, McGill University, Montréal, Canada
| | - Pengyu Zong
- Dept. of Cell Biology. UCONN Health Center, Farmington, Connecticut, United States
| | - Sandra Tetteh
- Rutgers-Robert Wood Johnson Medical School, Piscataway, New Jersey, United States
| | | | - Caroline Knorn
- Department of Biochemistry, McGill University, Montréal, Canada,Centre de recherche en biologie structurale, McGill University, Montréal, Canada
| | - Jianning Jiang
- Department of Biochemistry, McGill University, Montréal, Canada,Centre de recherche en biologie structurale, McGill University, Montréal, Canada
| | - Ashkan Shahsavan
- Department of Biochemistry, McGill University, Montréal, Canada,Centre de recherche en biologie structurale, McGill University, Montréal, Canada
| | - Emma Lee
- Department of Biochemistry, McGill University, Montréal, Canada,Centre de recherche en biologie structurale, McGill University, Montréal, Canada
| | - Lixia Yue
- Dept. of Cell Biology. UCONN Health Center, Farmington, Connecticut, United States
| | - Loren W. Runnels
- Rutgers-Robert Wood Johnson Medical School, Piscataway, New Jersey, United States
| | - Kalle Gehring
- Department of Biochemistry, McGill University, Montréal, Canada,Centre de recherche en biologie structurale, McGill University, Montréal, Canada,Corresponding author:
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6
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Kim D, Justice AE, Chittoor G, Blanco E, Burrows R, Graff M, Howard AG, Wang Y, Rohde R, Buchanan VL, Voruganti VS, Almeida M, Peralta J, Lehman DM, Curran JE, Comuzzie AG, Duggirala R, Blangero J, Albala C, Santos JL, Angel B, Lozoff B, Gahagan S, North KE. Genetic determinants of metabolic biomarkers and their associations with cardiometabolic traits in Hispanic/Latino adolescents. Pediatr Res 2022; 92:563-571. [PMID: 34645953 PMCID: PMC9005573 DOI: 10.1038/s41390-021-01729-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2021] [Revised: 06/08/2021] [Accepted: 08/17/2021] [Indexed: 01/05/2023]
Abstract
BACKGROUND Metabolic regulation plays a significant role in energy homeostasis, and adolescence is a crucial life stage for the development of cardiometabolic disease (CMD). This study aims to investigate the genetic determinants of metabolic biomarkers-adiponectin, leptin, ghrelin, and orexin-and their associations with CMD risk factors. METHODS We characterized the genetic determinants of the biomarkers among Hispanic/Latino adolescents of the Santiago Longitudinal Study (SLS) and identified the cumulative effects of genetic variants on adiponectin and leptin using biomarker polygenic risk scores (PRS). We further investigated the direct and indirect effect of the biomarker PRS on downstream body fat percent (BF%) and glycemic traits using structural equation modeling. RESULTS We identified putatively novel genetic variants associated with the metabolic biomarkers. A substantial amount of biomarker variance was explained by SLS-specific PRS, and the prediction was improved by including the putatively novel loci. Fasting blood insulin and insulin resistance were associated with PRS for adiponectin, leptin, and ghrelin, and BF% was associated with PRS for adiponectin and leptin. We found evidence of substantial mediation of these associations by the biomarker levels. CONCLUSIONS The genetic underpinnings of metabolic biomarkers can affect the early development of CMD, partly mediated by the biomarkers. IMPACT This study characterized the genetic underpinnings of four metabolic hormones and investigated their potential influence on adiposity and insulin biology among Hispanic/Latino adolescents. Fasting blood insulin and insulin resistance were associated with polygenic risk score (PRS) for adiponectin, leptin, and ghrelin, with evidence of some degree of mediation by the biomarker levels. Body fat percent (BF%) was also associated with PRS for adiponectin and leptin. This provides important insight on biological mechanisms underlying early metabolic dysfunction and reveals candidates for prevention efforts. Our findings also highlight the importance of ancestrally diverse populations to facilitate valid studies of the genetic architecture of metabolic biomarker levels.
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Affiliation(s)
- Daeeun Kim
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Anne E. Justice
- Department of Population Health Sciences, Geisinger, Danville, PA
| | - Geetha Chittoor
- Department of Population Health Sciences, Geisinger, Danville, PA
| | - Estela Blanco
- Division of Academic General Pediatrics, Child Development and Community Health at the Center for Community Health, University of California at San Diego, San Diego, CA,Department of Public Health, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Raquel Burrows
- Department of Public Health Nutrition, Institute of Nutrition and Food Technology (INTA), University of Chile, Santiago, Chile
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Annie Green Howard
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Yujie Wang
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Rebecca Rohde
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Victoria L. Buchanan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - V. Saroja Voruganti
- Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis NC
| | - Marcio Almeida
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX
| | - Juan Peralta
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX
| | - Donna M. Lehman
- Departments of Medicine and Epidemiology and Biostatistics, University of Texas Health San Antonio, San Antonio, TX
| | - Joanne E. Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX
| | | | - Ravindranath Duggirala
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, TX
| | - Cecilia Albala
- Department of Public Health Nutrition, Institute of Nutrition and Food Technology (INTA), University of Chile, Santiago, Chile
| | - José L. Santos
- Department of Nutrition, Diabetes and Metabolism, School of Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Bárbara Angel
- Department of Public Health Nutrition, Institute of Nutrition and Food Technology (INTA), University of Chile, Santiago, Chile
| | - Betsy Lozoff
- Department of Pediatrics, University of Michigan, Ann Arbor, MI
| | - Sheila Gahagan
- Division of Academic General Pediatrics, Child Development and Community Health at the Center for Community Health, University of California at San Diego, San Diego, CA
| | - Kari E. North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC
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7
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Shi M, Tie HC, Divyanshu M, Sun X, Zhou Y, Boh BK, Vardy LA, Lu L. Arl15 upregulates the TGFβ family signaling by promoting the assembly of the Smad-complex. eLife 2022; 11:76146. [PMID: 35834310 PMCID: PMC9352346 DOI: 10.7554/elife.76146] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Accepted: 07/12/2022] [Indexed: 11/13/2022] Open
Abstract
The hallmark event of the canonical transforming growth factor β (TGFβ) family signaling is the assembly of the Smad-complex, consisting of the common Smad, Smad4, and phosphorylated receptor-regulated Smads. How the Smad-complex is assembled and regulated is still unclear. Here, we report that active Arl15, an Arf-like small G protein, specifically binds to the MH2 domain of Smad4 and colocalizes with Smad4 at the endolysosome. The binding relieves the autoinhibition of Smad4, which is imposed by the intramolecular interaction between its MH1 and MH2 domains. Activated Smad4 subsequently interacts with phosphorylated receptor-regulated Smads, forming the Smad-complex. Our observations suggest that Smad4 functions as an effector and a GTPase activating protein (GAP) of Arl15. Assembly of the Smad-complex enhances the GAP activity of Smad4 toward Arl15, therefore dissociating Arl15 before the nuclear translocation of the Smad-complex. Our data further demonstrate that Arl15 positively regulates the TGFβ family signaling.
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Affiliation(s)
- Meng Shi
- Skin Research Laboratory, A*STAR, Singapore, singapore, Singapore
| | - Hieng Chiong Tie
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Mahajan Divyanshu
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Xiuping Sun
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Yan Zhou
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Boon Kim Boh
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Leah A Vardy
- Skin Research Laboratory, A*STAR, Singapore, singapore, Singapore
| | - Lei Lu
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
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8
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Trends in insulin resistance: insights into mechanisms and therapeutic strategy. Signal Transduct Target Ther 2022; 7:216. [PMID: 35794109 PMCID: PMC9259665 DOI: 10.1038/s41392-022-01073-0] [Citation(s) in RCA: 159] [Impact Index Per Article: 79.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2022] [Revised: 06/15/2022] [Accepted: 06/20/2022] [Indexed: 02/06/2023] Open
Abstract
The centenary of insulin discovery represents an important opportunity to transform diabetes from a fatal diagnosis into a medically manageable chronic condition. Insulin is a key peptide hormone and mediates the systemic glucose metabolism in different tissues. Insulin resistance (IR) is a disordered biological response for insulin stimulation through the disruption of different molecular pathways in target tissues. Acquired conditions and genetic factors have been implicated in IR. Recent genetic and biochemical studies suggest that the dysregulated metabolic mediators released by adipose tissue including adipokines, cytokines, chemokines, excess lipids and toxic lipid metabolites promote IR in other tissues. IR is associated with several groups of abnormal syndromes that include obesity, diabetes, metabolic dysfunction-associated fatty liver disease (MAFLD), cardiovascular disease, polycystic ovary syndrome (PCOS), and other abnormalities. Although no medication is specifically approved to treat IR, we summarized the lifestyle changes and pharmacological medications that have been used as efficient intervention to improve insulin sensitivity. Ultimately, the systematic discussion of complex mechanism will help to identify potential new targets and treat the closely associated metabolic syndrome of IR.
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9
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Tagi VM, Samvelyan S, Chiarelli F. An update of the consensus statement on insulin resistance in children 2010. Front Endocrinol (Lausanne) 2022; 13:1061524. [PMID: 36465645 PMCID: PMC9709113 DOI: 10.3389/fendo.2022.1061524] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/04/2022] [Accepted: 10/14/2022] [Indexed: 11/17/2022] Open
Abstract
In our modern society, where highly palatable and calorie-rich foods are readily available, and sedentary lifestyle is common among children and adolescents, we face the pandemic of obesity, nonalcoholic fatty liver disease, hypertension, atherosclerosis, and T2D. Insulin resistance (IR) is known to be the main underlying mechanism of all these associated health consequences; therefore, the early detection of IR is fundamental for preventing them.A Consensus Statement, internationally supported by all the major scientific societies in pediatric endocrinology, was published in 2010, providing all the most recent reliable evidence to identify the definition of IR in children, its measurement, its risk factors, and the effective strategies to prevent and treat it. However, the 2010 Consensus concluded that further research was necessary to assess some of the discussed points, in particular the best way to measure insulin sensitivity, standardization of insulin measurements, identification of strong surrogate biomarkers of IR, and the effective role of lifestyle intervention and medications in the prevention and treatment of IR.The aim of this review is to update each point of the consensus with the most recent available studies, with the goal of giving a picture of the current state of the scientific literature regarding IR in children, with a particular regard for issues that are not yet fully clarified.
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Affiliation(s)
- Veronica Maria Tagi
- Department of Pediatrics, University of Chieti, Chieti, Italy
- *Correspondence: Veronica Maria Tagi,
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10
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Nielsen MB, Nordestgaard BG, Benn M, Çolak Y. Plasma adiponectin and risk of asthma: observational analysis, genetic Mendelian randomisation and meta-analysis. Thorax 2021; 77:1070-1077. [PMID: 34949725 DOI: 10.1136/thoraxjnl-2021-217675] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 11/18/2021] [Indexed: 11/03/2022]
Abstract
BACKGROUND Adiponectin, an adipocyte-secreted protein-hormone with inflammatory properties, has a potentially important role in the development and progression of asthma. Unravelling whether adiponectin is a causal risk factor for asthma is an important issue to clarify as adiponectin could be a potential novel drug target for the treatment of asthma. OBJECTIVE We tested the hypothesis that plasma adiponectin is associated observationally and causally (using genetic variants as instrumental variables) with risk of asthma. METHODS In the Copenhagen General Population Study, we did an observational analysis in 28 845 individuals (2278 asthma cases) with plasma adiponectin measurements, and a genetic one-sample Mendelian randomisation analysis in 94 868 individuals (7128 asthma cases) with 4 genetic variants. Furthermore, in the UK Biobank, we did a genetic two-sample Mendelian randomisation analysis in 462 933 individuals (53 598 asthma cases) with 12 genetic variants. Lastly, we meta-analysed the genetic findings. RESULTS While a 1 unit log-transformed higher plasma adiponectin in the Copenhagen General Population Study was associated with an observational OR of 1.65 (95% CI 1.29 to 2.08) for asthma, the corresponding genetic causal OR was 1.03 (95% CI 0.75 to 1.42). The genetic causal OR for asthma in the UK Biobank was 1.00 (95% CI 0.99 to 1.00). Lastly, genetic meta-analysis confirmed lack of association between genetically high plasma adiponectin and causal OR for asthma. CONCLUSION Observationally, high plasma adiponectin is associated with increased risk of asthma; however, genetic evidence could not support a causal association between plasma adiponectin and asthma.
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Affiliation(s)
- Maria Booth Nielsen
- Department of Clinical Biochemistry, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark.,The Copenhagen General Population Study, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Børge G Nordestgaard
- Department of Clinical Biochemistry, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark.,The Copenhagen General Population Study, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marianne Benn
- The Copenhagen General Population Study, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark.,Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.,Department of Clinical Biochemistry, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Yunus Çolak
- The Copenhagen General Population Study, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark .,Department of Clinical Medicine, Faculty of Health and Medical Sciences, Copenhagen University Hospital, Copenhagen, Denmark.,Department of Respiratory Medicine, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark
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11
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Orchard P, Manickam N, Ventresca C, Vadlamudi S, Varshney A, Rai V, Kaplan J, Lalancette C, Mohlke KL, Gallagher K, Burant CF, Parker SCJ. Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits. Genome Res 2021; 31:2258-2275. [PMID: 34815310 PMCID: PMC8647829 DOI: 10.1101/gr.268482.120] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Accepted: 09/16/2021] [Indexed: 12/12/2022]
Abstract
Skeletal muscle accounts for the largest proportion of human body mass, on average, and is a key tissue in complex diseases and mobility. It is composed of several different cell and muscle fiber types. Here, we optimize single-nucleus ATAC-seq (snATAC-seq) to map skeletal muscle cell-specific chromatin accessibility landscapes in frozen human and rat samples, and single-nucleus RNA-seq (snRNA-seq) to map cell-specific transcriptomes in human. We additionally perform multi-omics profiling (gene expression and chromatin accessibility) on human and rat muscle samples. We capture type I and type II muscle fiber signatures, which are generally missed by existing single-cell RNA-seq methods. We perform cross-modality and cross-species integrative analyses on 33,862 nuclei and identify seven cell types ranging in abundance from 59.6% to 1.0% of all nuclei. We introduce a regression-based approach to infer cell types by comparing transcription start site-distal ATAC-seq peaks to reference enhancer maps and show consistency with RNA-based marker gene cell type assignments. We find heterogeneity in enrichment of genetic variants linked to complex phenotypes from the UK Biobank and diabetes genome-wide association studies in cell-specific ATAC-seq peaks, with the most striking enrichment patterns in muscle mesenchymal stem cells (∼3.5% of nuclei). Finally, we overlay these chromatin accessibility maps on GWAS data to nominate causal cell types, SNPs, transcription factor motifs, and target genes for type 2 diabetes signals. These chromatin accessibility profiles for human and rat skeletal muscle cell types are a useful resource for nominating causal GWAS SNPs and cell types.
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Affiliation(s)
- Peter Orchard
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Nandini Manickam
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Christa Ventresca
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Swarooparani Vadlamudi
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Arushi Varshney
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Vivek Rai
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Jeremy Kaplan
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Claudia Lalancette
- Epigenomics Core, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Katherine Gallagher
- Department of Surgery, University of Michigan, Ann Arbor, Michigan 48109, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Charles F Burant
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Stephen C J Parker
- Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan 48109, USA
- Department of Human Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA
- Department of Biostatistics, University of Michigan, Ann Arbor, Michigan 48109, USA
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12
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Wu Y, Bai Y, McEwan DG, Bentley L, Aravani D, Cox RD. Palmitoylated small GTPase ARL15 is translocated within Golgi network during adipogenesis. Biol Open 2021; 10:273707. [PMID: 34779483 PMCID: PMC8689486 DOI: 10.1242/bio.058420] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 11/10/2021] [Indexed: 11/20/2022] Open
Abstract
The small GTPase ARF family member ARL15 gene locus is associated in population studies with increased risk of type 2 diabetes, lower adiponectin and higher fasting insulin levels. Previously, loss of ARL15 was shown to reduce insulin secretion in a human β-cell line and loss-of-function mutations are found in some lipodystrophy patients. We set out to understand the role of ARL15 in adipogenesis and showed that endogenous ARL15 palmitoylated and localised in the Golgi of mouse liver. Adipocyte overexpression of palmitoylation-deficient ARL15 resulted in redistribution to the cytoplasm and a mild reduction in expression of some adipogenesis-related genes. Further investigation of the localisation of ARL15 during differentiation of a human white adipocyte cell line showed that ARL15 was predominantly co-localised with a marker of the cis face of Golgi at the preadipocyte stage and then translocated to other Golgi compartments after differentiation was induced. Finally, co-immunoprecipitation and mass spectrometry identified potential interacting partners of ARL15, including the ER-localised protein ARL6IP5. Together, these results suggest a palmitoylation dependent trafficking-related role of ARL15 as a regulator of adipocyte differentiation via ARL6IP5 interaction. This article has an associated First Person interview with the first author of the paper. Summary: ARL15 (GTPase ARF family) is associated with adipose traits. ARL15 is palmitoylated, localised to Golgi in preadipocytes and translocated to other Golgi compartments during differentiation. ARL15 interacts with ER-localised ARL6IP5.
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Affiliation(s)
- Yixing Wu
- Mammalian Genetics Unit, MRC Harwell Institute, Harwell Oxford, Oxfordshire, OX11 0RD, UK
| | - Ying Bai
- Mammalian Genetics Unit, MRC Harwell Institute, Harwell Oxford, Oxfordshire, OX11 0RD, UK
| | - David G McEwan
- Division of Cell Signalling & Immunology, School of Life Sciences, University of Dundee, Dundee, UK.,Cancer Research UK Beatson Institute, Garscube Estate, Switchback Road, Glasgow, G61 1BD, UK
| | - Liz Bentley
- Mammalian Genetics Unit, MRC Harwell Institute, Harwell Oxford, Oxfordshire, OX11 0RD, UK
| | - Dimitra Aravani
- Mammalian Genetics Unit, MRC Harwell Institute, Harwell Oxford, Oxfordshire, OX11 0RD, UK
| | - Roger D Cox
- Mammalian Genetics Unit, MRC Harwell Institute, Harwell Oxford, Oxfordshire, OX11 0RD, UK
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13
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Kollewe A, Chubanov V, Tseung FT, Correia L, Schmidt E, Rössig A, Zierler S, Haupt A, Müller CS, Bildl W, Schulte U, Nicke A, Fakler B, Gudermann T. The molecular appearance of native TRPM7 channel complexes identified by high-resolution proteomics. eLife 2021; 10:68544. [PMID: 34766907 PMCID: PMC8616561 DOI: 10.7554/elife.68544] [Citation(s) in RCA: 27] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Accepted: 11/08/2021] [Indexed: 12/22/2022] Open
Abstract
The transient receptor potential melastatin-subfamily member 7 (TRPM7) is a ubiquitously expressed membrane protein consisting of ion channel and protein kinase domains. TRPM7 plays a fundamental role in the cellular uptake of divalent cations such as Zn2+, Mg2+, and Ca2+, and thus shapes cellular excitability, plasticity, and metabolic activity. The molecular appearance and operation of TRPM7 channels in native tissues have remained unresolved. Here, we investigated the subunit composition of endogenous TRPM7 channels in rodent brain by multi-epitope affinity purification and high-resolution quantitative mass spectrometry (MS) analysis. We found that native TRPM7 channels are high-molecular-weight multi-protein complexes that contain the putative metal transporter proteins CNNM1-4 and a small G-protein ADP-ribosylation factor-like protein 15 (ARL15). Heterologous reconstitution experiments confirmed the formation of TRPM7/CNNM/ARL15 ternary complexes and indicated that complex formation effectively and specifically impacts TRPM7 activity. These results open up new avenues towards a mechanistic understanding of the cellular regulation and function of TRPM7 channels.
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Affiliation(s)
- Astrid Kollewe
- Institute of Physiology II, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Vladimir Chubanov
- Walther-Straub Institute of Pharmacology and Toxicology, LMU Munich, Munich, Germany
| | - Fong Tsuen Tseung
- Walther-Straub Institute of Pharmacology and Toxicology, LMU Munich, Munich, Germany
| | - Leonor Correia
- Walther-Straub Institute of Pharmacology and Toxicology, LMU Munich, Munich, Germany
| | - Eva Schmidt
- Walther-Straub Institute of Pharmacology and Toxicology, LMU Munich, Munich, Germany
| | - Anna Rössig
- Walther-Straub Institute of Pharmacology and Toxicology, LMU Munich, Munich, Germany
| | - Susanna Zierler
- Walther-Straub Institute of Pharmacology and Toxicology, LMU Munich, Munich, Germany.,Institute of Pharmacology, Johannes Kepler University Linz, Linz, Austria
| | - Alexander Haupt
- Institute of Physiology II, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Catrin Swantje Müller
- Institute of Physiology II, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Wolfgang Bildl
- Institute of Physiology II, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Uwe Schulte
- Institute of Physiology II, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Signalling Research Centres BIOSS and CIBSS, Freiburg, Germany
| | - Annette Nicke
- Walther-Straub Institute of Pharmacology and Toxicology, LMU Munich, Munich, Germany
| | - Bernd Fakler
- Institute of Physiology II, Faculty of Medicine, University of Freiburg, Freiburg, Germany.,Signalling Research Centres BIOSS and CIBSS, Freiburg, Germany
| | - Thomas Gudermann
- Walther-Straub Institute of Pharmacology and Toxicology, LMU Munich, Munich, Germany.,German Center for Lung Research, Munich, Germany
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14
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Nielsen MB, Çolak Y, Benn M, Nordestgaard BG. Low Plasma Adiponectin in Risk of Type 2 Diabetes: Observational Analysis and One- and Two-Sample Mendelian Randomization Analyses in 756,219 Individuals. Diabetes 2021; 70:2694-2705. [PMID: 34426507 DOI: 10.2337/db21-0131] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Accepted: 08/16/2021] [Indexed: 12/12/2022]
Abstract
We tested the hypothesis that low plasma adiponectin is associated observationally and causally with increased risk of type 2 diabetes. Observational analyses are prone to confounding and reverse causation, while genetic Mendelian randomization (MR) analyses are much less influenced by these biases. We examined 30,045 individuals from the Copenhagen General Population Study observationally (plasma adiponectin [1,751 individuals with type 2 diabetes]), 96,903 Copenhagen individuals using one-sample MR (5 genetic variants [5,012 individuals with type 2 diabetes]), and 659,316 Europeans (ADIPOGen, GERA, DIAGRAM, UK Biobank) using two-sample MR (10 genetic variants [62,892 individuals type 2 diabetes]). Observationally, and in comparisons with individuals with median plasma adiponectin of 28.9 μg/mL (4th quartile), multivariable adjusted hazard ratios (HRs) for type 2 diabetes were 1.42 (95% CI 1.18-1.72) for 19.2 μg/mL (3rd quartile), 2.21 (1.84-2.66) for 13.9 μg/mL (2nd quartile), and 4.05 (3.38-4.86) for 9.2 μg/mL (1st quartile). Corresponding cumulative incidence for type 2 diabetes at age 70 years was 3%, 7%, 11%, and 20%, respectively. A 1 μg/mL lower plasma adiponectin conferred an HR for type 2 diabetes of 1.07 (1.06-1.09), while genetic, causal risk ratio per 1 unit log-transformed lower plasma adiponectin was 1.13 (95% CI 0.83-1.53) in one-sample MR and 1.26 (1.01-1.57) in two-sample MR. In conclusion, low plasma adiponectin is associated with increased risk of type 2 diabetes, an association that could represent a causal relationship.
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Affiliation(s)
- Maria B Nielsen
- Department of Clinical Biochemistry, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark
- The Copenhagen General Population Study, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Yunus Çolak
- Department of Clinical Biochemistry, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark
- The Copenhagen General Population Study, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Section of Respiratory Medicine, Department of Internal Medicine, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark
| | - Marianne Benn
- The Copenhagen General Population Study, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Biochemistry, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
| | - Børge G Nordestgaard
- Department of Clinical Biochemistry, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark
- The Copenhagen General Population Study, Copenhagen University Hospital - Herlev and Gentofte, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
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15
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Correlation between an intronic SNP genotype and ARL15 level in rheumatoid arthritis. J Genet 2021. [DOI: 10.1007/s12041-021-01286-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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16
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Nam GE, Zhang ZF, Rao J, Zhou H, Jung SY. Interactions Between Adiponectin-Pathway Polymorphisms and Obesity on Postmenopausal Breast Cancer Risk Among African American Women: The WHI SHARe Study. Front Oncol 2021; 11:698198. [PMID: 34367982 PMCID: PMC8335565 DOI: 10.3389/fonc.2021.698198] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2021] [Accepted: 07/02/2021] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND A decreased level of serum adiponectin is associated with obesity and an increased risk of breast cancer among postmenopausal women. Yet, the interplay between genetic variants associated with adiponectin phenotype, obesity, and breast cancer risk is unclear in African American (AA) women. METHODS We examined 32 single-nucleotide polymorphisms (SNPs) previously identified in genome-wide association and replication studies of serum adiponectin levels using data from 7,991 AA postmenopausal women in the Women's Health Initiative SNP Health Association Resource. RESULTS Stratifying by obesity status, we identified 18 adiponectin-related SNPs that were associated with breast cancer risk. Among women with BMI ≥ 30 kg/m2, the minor TT genotype of FER rs10447248 had an elevated breast cancer risk. Interaction was observed between obesity and the CT genotype of ADIPOQ rs6773957 on the additive scale for breast cancer risk (relative excess risk due to interaction, 0.62; 95% CI, 0.32-0.92). The joint effect of BMI ≥ 30 kg/m2 and the TC genotype of OR8S1 rs11168618 was larger than the sum of the independent effects on breast cancer risk. CONCLUSIONS We demonstrated that obesity plays a significant role as an effect modifier in an increased effect of the SNPs on breast cancer risk using one of the most extensive data on postmenopausal AA women. IMPACT The results suggest the potential use of adiponectin genetic variants as obesity-associated biomarkers for informing AA women who are at greater risk for breast cancer and also for promoting behavioral interventions, such as weight control, to those with risk genotypes.
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Affiliation(s)
- Gina E. Nam
- Department of Epidemiology, Fielding School of Public Health, University of California at Los Angeles (UCLA), Los Angeles, CA, United States
| | - Zuo-Feng Zhang
- Department of Epidemiology, Fielding School of Public Health, University of California at Los Angeles (UCLA), Los Angeles, CA, United States
- Center for Human Nutrition, Department of Medicine, UCLA David Geffen School of Medicine, University of California at Los Angeles (UCLA), Los Angeles, CA, United States
| | - Jianyu Rao
- Department of Epidemiology, Fielding School of Public Health, University of California at Los Angeles (UCLA), Los Angeles, CA, United States
| | - Hua Zhou
- Department of Biostatistics, Fielding School of Public Health, University of California at Los Angeles (UCLA), Los Angeles, CA, United States
| | - Su Yon Jung
- Translational Sciences Section, School of Nursing, University of California at Los Angeles (UCLA), Los Angeles, CA, United States
- Jonsson Comprehensive Cancer Center, University of California at Los Angeles (UCLA), Los Angeles, CA, United States
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17
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ARL15 modulates magnesium homeostasis through N-glycosylation of CNNMs. Cell Mol Life Sci 2021; 78:5427-5445. [PMID: 34089346 PMCID: PMC8257531 DOI: 10.1007/s00018-021-03832-8] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Revised: 03/23/2021] [Accepted: 03/30/2021] [Indexed: 02/06/2023]
Abstract
Cyclin M (CNNM1-4) proteins maintain cellular and body magnesium (Mg2+) homeostasis. Using various biochemical approaches, we have identified members of the CNNM family as direct interacting partners of ADP-ribosylation factor-like GTPase 15 (ARL15), a small GTP-binding protein. ARL15 interacts with CNNMs at their carboxyl-terminal conserved cystathionine-β-synthase (CBS) domains. In silico modeling of the interaction between CNNM2 and ARL15 supports that the small GTPase specifically binds the CBS1 and CNBH domains. Immunocytochemical experiments demonstrate that CNNM2 and ARL15 co-localize in the kidney, with both proteins showing subcellular localization in the endoplasmic reticulum, Golgi apparatus and the plasma membrane. Most importantly, we found that ARL15 is required for forming complex N-glycosylation of CNNMs. Overexpression of ARL15 promotes complex N-glycosylation of CNNM3. Mg2+ uptake experiments with a stable isotope demonstrate that there is a significant increase of 25Mg2+ uptake upon knockdown of ARL15 in multiple kidney cancer cell lines. Altogether, our results establish ARL15 as a novel negative regulator of Mg2+ transport by promoting the complex N-glycosylation of CNNMs.
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18
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Chalazan B, Palm D, Sridhar A, Lee C, Argos M, Daviglus M, Rehman J, Konda S, Darbar D. Common genetic variants associated with obesity in an African-American and Hispanic/Latino population. PLoS One 2021; 16:e0250697. [PMID: 33983957 PMCID: PMC8118531 DOI: 10.1371/journal.pone.0250697] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2020] [Accepted: 04/12/2021] [Indexed: 11/18/2022] Open
Abstract
INTRODUCTION Over 35% of all adults in the world are currently obese and risk of obesity in racial or ethnic minority groups exist in the US, but the causes of these differences are not all known. As obesity is a leading cause of cardiovascular disease, an improved understanding of risk factors across racial and ethnic groups may improve outcomes. OBJECTIVE The objective of this study was to determine if susceptibility to obesity is associated with genetic variation in candidate single nucleotide polymorphisms (SNPs) in African Americans and Hispanic/Latinos. MATERIALS AND METHODS We examined data from 534 African Americans and 557 Hispanic/Latinos participants from the UIC Cohort of Patients, Family and Friends. Participants were genotyped for the top 26 obesity-associated SNPs within FTO, MC4R, TUB, APOA2, APOA5, ADIPOQ, ARL15, CDH13, KNG1, LEPR, leptin, and SCG3 genes. RESULTS The mean (SD) age of participants was 49±13 years, 55% were female, and mean body mass index (BMI) was 31±7.5 kg/m2. After adjusting for age and sex, we found that rs8050136 in FTO (odds ratio [OR] 1.40, 95% confidence interval [CI] 1.1-1.8; P = 0.01) among African Americans and rs2272383 in TUB (OR 1.34, 95% CI 1.04-1.71; P = 0.02) among Hispanic/Latinos were associated with obesity. However, none of the SNPs in multivariable analysis of either AA or H/L cohorts were significant when adjusted for multiple correction. CONCLUSIONS We show that candidate SNPs in the FTO and TUB genes are associated with obesity in African Americans and Hispanic/Latinos individuals respectively. While the underlying pathophysiological mechanisms by which common genetic variants cause obesity remain unclear, we have identified novel therapeutic targets across racial and ethnic groups.
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Affiliation(s)
- Brandon Chalazan
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, United States of America
| | - Denada Palm
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, United States of America
| | - Arvind Sridhar
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, United States of America
| | - Christina Lee
- Broad Institute of MIT and Harvard, Boston, Massachusetts, United States of America
| | - Maria Argos
- Division of Epidemiology and Biostatics, School of Public Health, University of Illinois at Chicago, Chicago, Illinois, United States of America
| | - Martha Daviglus
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, United States of America
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, Illinois, United States of America
| | - Jalees Rehman
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, United States of America
- Department of Pharmacology, University of Illinois at Chicago, Chicago, Illinois, United States of America
| | - Sreenivas Konda
- Division of Epidemiology and Biostatics, School of Public Health, University of Illinois at Chicago, Chicago, Illinois, United States of America
| | - Dawood Darbar
- Department of Medicine, University of Illinois at Chicago, Chicago, Illinois, United States of America
- Department of Pharmacology, University of Illinois at Chicago, Chicago, Illinois, United States of America
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19
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Dimou NL, Papadimitriou N, Mariosa D, Johansson M, Brennan P, Peters U, Chanock SJ, Purdue M, Bishop DT, Gago‐Dominquez M, Giles GG, Moreno V, Platz EA, Tangen CM, Wolk A, Zheng W, Wu X, Campbell PT, Giovannucci E, Lin Y, Gunter MJ, Murphy N. Circulating adipokine concentrations and risk of five obesity-related cancers: A Mendelian randomization study. Int J Cancer 2021; 148:1625-1636. [PMID: 33038280 PMCID: PMC7894468 DOI: 10.1002/ijc.33338] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Revised: 08/27/2020] [Accepted: 09/17/2020] [Indexed: 12/20/2022]
Abstract
Obesity is considered a chronic inflammatory state characterized by continued secretion of adipokines and cytokines. Experimental and epidemiological evidence indicates that circulating adipokines may be associated with the development of obesity-related cancers, but it is unclear if these associations are causal or confounded. We examined potential causal associations of specific adipokines (adiponectin, leptin, soluble leptin receptor [sOB-R] and plasminogen activator inhibitor-1 [PAI-1]) with five obesity-related cancers (colorectal, pancreatic, renal cell carcinoma [RCC], ovarian and endometrial) using Mendelian randomization (MR) methods. We used summary-level data from large genetic consortia for 114 530 cancer cases and 245 284 controls. We constructed genetic instruments using 18 genetic variants for adiponectin, 2 for leptin and 4 for both sOB-R and PAI-1 (P value for inclusion<5 × 10-8 ). Causal estimates were obtained using two-sample MR methods. In the inverse-variance weighted models, we found an inverse association between adiponectin and risk of colorectal cancer (odds ratio per 1 μg/mL increment in adiponectin concentration: 0.90 [95% confidence interval = 0.84-0.97]; P = .01); but, evidence of horizontal pleiotropy was detected and the association was not present when this was taken into consideration. No association was found for adiponectin and risks of pancreatic cancer, RCC, ovarian cancer and endometrial cancer. Leptin, sOB-R and PAI-1 were also similarly unrelated to risk of obesity-related cancers. Despite the large sample size, our MR analyses do not support causal effects of circulating adiponectin, leptin, sOB-R and PAI-1 concentrations on the development of five obesity-related cancers.
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Affiliation(s)
- Niki L. Dimou
- Section of Nutrition and Metabolism, International Agency for Research on CancerLyonFrance
| | - Nikos Papadimitriou
- Section of Nutrition and Metabolism, International Agency for Research on CancerLyonFrance
| | - Daniela Mariosa
- Section of Genetics, International Agency for Research on CancerLyonFrance
| | - Mattias Johansson
- Section of Genetics, International Agency for Research on CancerLyonFrance
| | - Paul Brennan
- Section of Genetics, International Agency for Research on CancerLyonFrance
| | - Ulrike Peters
- Fred Hutchinson Cancer Research CenterSeattleWashingtonUSA
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
| | - Mark Purdue
- Division of Cancer Epidemiology and Genetics, National Cancer InstituteNational Institutes of HealthBethesdaMarylandUSA
| | | | - Manuela Gago‐Dominquez
- Fundación Gallega de Medicina Genómica, Grupo de Genéticadel CáncerInstituto de Investigación Sanitaria de Santiago IDISComplejo Hospitalario Univ. Santiago‐CHUS, SERGAS, Santiago de CompostelaSpain
- Moores Cancer CenterUniversity of California San DiegoLa JollaCaliforniaUSA
| | - Graham G. Giles
- Cancer Epidemiology DivisionCancer Council VictoriaMelbourneVictoriaAustralia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global HealthThe University of MelbourneMelbourneVictoriaAustralia
- Precision MedicineSchool of Clinical Sciences at Monash Health, Monash UniversityClaytonVictoriaAustralia
| | - Victor Moreno
- Oncology Data Analytics ProgramCatalan Institute of Oncology‐IDIBELL, L'Hospitalet de LlobregatBarcelonaSpain
- CIBER Epidemiología y SaludPública (CIBERESP)MadridSpain
- Department of Clinical Sciences, Faculty of MedicineUniversity of BarcelonaBarcelonaSpain
- ONCOBEL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de LlobregatBarcelonaSpain
| | - Elizabeth A. Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public HealthBaltimoreMarylandUSA
| | - Catherine M. Tangen
- SWOG Statistical Center, Fred Hutchinson Cancer Research CenterSeattleWashingtonUSA
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska InstitutetStockholmSweden
- Department of Surgical SciencesUppsala UniversityUppsalaSweden
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt‐Ingram Cancer CenterVanderbilt UniversityNashvilleTennesseeUSA
| | - Xifeng Wu
- Department of EpidemiologyThe University of Texas MD Anderson Cancer CenterHoustonTexasUSA
- Department of Precision Health and Data Science, School of Public Health and the Second Affiliated HospitalZhejiang University School of MedicineHangzhouChina
| | - Peter T. Campbell
- Behavioral and Epidemiology Research Group, American Cancer SocietyAtlantaGeorgiaUSA
| | - Edward Giovannucci
- Department of Epidemiology, Harvard T.H. Chan School of Public HealthHarvard UniversityBostonMassachusettsUSA
- Department of NutritionT.H. Chan School of Public HealthBostonMassachusettsUSA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical SchoolBostonMassachusettsUSA
| | - Yi Lin
- Public Health Sciences Division, Fred Hutchinson Cancer Research CenterSeattleWashingtonUSA
| | | | - Marc J. Gunter
- Section of Nutrition and Metabolism, International Agency for Research on CancerLyonFrance
| | - Neil Murphy
- Section of Nutrition and Metabolism, International Agency for Research on CancerLyonFrance
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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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21
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Sharma A, Saini M, Kundu S, Thelma BK. Computational insight into the three-dimensional structure of ADP ribosylation factor like protein 15, a novel susceptibility gene for rheumatoid arthritis. J Biomol Struct Dyn 2020; 40:4626-4641. [PMID: 33356902 DOI: 10.1080/07391102.2020.1860826] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
Abstract
The ARL15 gene (ADP ribosylation factor like protein 15) encodes for an uncharacterized small GTP-binding protein. Its exact role in human physiology remains unknown, but a number of genetic association studies have recognised different variants in this gene to be statistically associated with numerous traits and complex diseases. We have previously reported a novel association of ARL15 with rheumatoid arthritis (RA) based on a genome-wide association study in a north Indian cohort. Subsequent investigations have provided leads for its involvement in RA pathophysiology, especially its potential as a novel therapeutic target. However, the absence of an experimentally determined tertiary structure for ARL15 significantly hinders the understanding of its biochemical and physiological functions, as well as development of potential lead molecules. We, therefore, aimed to derive a high quality, refined model of the three dimensional structure of human ARL15 protein using two different computational protein structure prediction methods - template-based threading and ab initio modelling. The best model each from among the five each derived from both the approaches was selected based on stringent quality assessment and refinement. Molecular dynamics simulations over long timescales revealed the ab initio model to be relatively more stable, and it marginally outperformed the template-based model in the quality assessment as well. A putative GTP-binding site was also predicted using homology for the ARL15 protein, where potential competitive inhibitors can be targeted. This high quality predicted model may provide insights to the biological role(s) of ARL15 and inform and guide further experimental, structural and biochemical characterization efforts.Communicated by Ramaswamy H. Sarma.
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Affiliation(s)
- Aditya Sharma
- Department of Genetics, University of Delhi South Campus, New Delhi, India
| | - Manisha Saini
- Department of Biochemistry, University of Delhi South Campus, New Delhi, India
| | - Suman Kundu
- Department of Biochemistry, University of Delhi South Campus, New Delhi, India
| | - B K Thelma
- Department of Genetics, University of Delhi South Campus, New Delhi, India
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Abstract
A growing body of evidence indicates that obesity is strongly and independently associated with adverse outcomes of COVID-19, including death. By combining emerging knowledge of the pathological processes involved in COVID-19 with insights into the mechanisms underlying the adverse health consequences of obesity, we present some hypotheses regarding the deleterious impact of obesity on the course of COVID-19. These hypotheses are testable and could guide therapeutic and preventive interventions. As obesity is now almost ubiquitous and no vaccine for COVID-19 is currently available, even a modest reduction in the impact of obesity on mortality and morbidity from this viral infection could have profound consequences for public health.
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Affiliation(s)
- Sam M Lockhart
- MRC Metabolic Diseases Unit, Wellcome Trust-Medical Research Council Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Stephen O'Rahilly
- MRC Metabolic Diseases Unit, Wellcome Trust-Medical Research Council Institute of Metabolic Science and NIHR Cambridge Biomedical Research Centre, University of Cambridge, Cambridge CB2 0QQ, UK
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23
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Williams PT. Quantile-dependent expressivity of plasma adiponectin concentrations may explain its sex-specific heritability, gene-environment interactions, and genotype-specific response to postprandial lipemia. PeerJ 2020; 8:e10099. [PMID: 33088620 PMCID: PMC7568478 DOI: 10.7717/peerj.10099] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 09/14/2020] [Indexed: 12/22/2022] Open
Abstract
Background "Quantile-dependent expressivity" occurs when the effect size of a genetic variant depends upon whether the phenotype (e.g. adiponectin) is high or low relative to its distribution. We have previously shown that the heritability (h2 ) of adiposity, lipoproteins, postprandial lipemia, pulmonary function, and coffee and alcohol consumption are quantile-specific. Whether adiponectin heritability is quantile specific remains to be determined. Methods Plasma adiponectin concentrations from 4,182 offspring-parent pairs and 1,662 sibships from the Framingham Heart Study were analyzed. Quantile-specific heritability from offspring-parent (β OP,h2 = 2β OP/(1 + rspouse)) and full-sib regression slopes (β FS, h2 = {(1 + 8rspouse β FS)0.05-1}/(2rspouse)) were robustly estimated by quantile regression with nonparametric significance assigned from 1,000 bootstrap samples. Results Quantile-specific h2 (± SE) increased with increasing percentiles of the offspring's age- and sex-adjusted adiponectin distribution when estimated from β OP (P trend = 2.2 × 10-6): 0.30 ± 0.03 at the 10th, 0.33 ± 0.04 at the 25th, 0.43 ± 0.04 at the 50th, 0.55 ± 0.05 at the 75th, and 0.57 ± 0.08 at the 90th percentile, and when estimated from β FS (P trend = 7.6 × 10-7): 0.42 ± 0.03 at the 10th, 0.44 ± 0.04 at the 25th, 0.56 ± 0.05 at the 50th, 0.73 ± 0.08 at the 75th, and 0.79 ± 0.11 at the 90th percentile. Consistent with quantile-dependent expressivity, adiponectin's: (1) heritability was greater in women in accordance with their higher adiponection concentrations; (2) relationships to ADIPOQ polymorphisms were modified by adiposity in accordance with its adiponectin-lowering effect; (3) response to rosiglitazone was predicted by the 45T> G ADIPOQ polymorphism; (4) difference by ADIPOQ haplotypes increased linearly with increasing postprandial adiponectin concentrations. Conclusion Adiponectin heritability is quantile dependent, which may explain sex-specific heritability, gene-environment and gene-drug interactions, and postprandial response by haplotypes.
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Affiliation(s)
- Paul T Williams
- Molecular Biophysics & Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, United States of America
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24
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Francischetti EA, Dezonne RS, Pereira CM, de Moraes Martins CJ, Celoria BMJ, de Oliveira PAC, de Abreu VG. Insights Into the Controversial Aspects of Adiponectin in Cardiometabolic Disorders. Horm Metab Res 2020; 52:695-707. [PMID: 32927496 DOI: 10.1055/a-1239-4349] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
In 2016, the World Health Organization estimated that more than 1.9 billion adults were overweight or obese. This impressive number shows that weight excess is pandemic. Overweight and obesity are closely associated with a high risk of comorbidities, such as insulin resistance and its most important outcomes, including metabolic syndrome, type 2 diabetes mellitus, and cardiovascular disease. Adiponectin has emerged as a salutary adipocytokine, with insulin-sensitizing, anti-inflammatory, and cardiovascular protective properties. However, under metabolically unfavorable conditions, visceral adipose tissue-derived inflammatory cytokines might reduce the transcription of the adiponectin gene and consequently its circulating levels. Low circulating levels of adiponectin are negatively associated with various conditions, such as insulin resistance, type 2 diabetes mellitus, metabolic syndrome, and cardiovascular disease. In contrast, several recent clinical trials and meta-analyses have reported high circulating adiponectin levels positively associated with cardiovascular mortality and all-cause mortality. These results are biologically intriguing and counterintuitive, and came to be termed "the adiponectin paradox". Adiponectin paradox is frequently associated with adiponectin resistance, a concept related with the downregulation of adiponectin receptors in insulin-resistant states. We review this contradiction between the apparent role of adiponectin as a health promoter and the recent evidence from Mendelian randomization studies indicating that circulating adiponectin levels are an unexpected predictor of increased morbidity and mortality rates in several clinical conditions. We also critically review the therapeutic perspective of synthetic peptide adiponectin receptors agonist that has been postulated as a promising alternative for the treatment of metabolic syndrome and type 2 diabetes mellitus.
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Affiliation(s)
- Emilio Antonio Francischetti
- Laboratory of Clinical and Experimental Pathophysiology, Rio de Janeiro State University, Rio de Janeiro, Brazil
| | - Rômulo Sperduto Dezonne
- Postgraduate Program in Translational Biomedicine, Grande Rio University, Duque de Caxias, Brazil
| | - Cláudia Maria Pereira
- Postgraduate Program in Translational Biomedicine, Grande Rio University, Duque de Caxias, Brazil
| | - Cyro José de Moraes Martins
- Laboratory of Clinical and Experimental Pathophysiology, Rio de Janeiro State University, Rio de Janeiro, Brazil
| | | | | | - Virgínia Genelhu de Abreu
- Laboratory of Clinical and Experimental Pathophysiology, Rio de Janeiro State University, Rio de Janeiro, Brazil
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Fischer J, Völzke H, Kassubek J, Müller HP, Kühn JP, Nauck M, Friedrich N, Zylla S. Associations of a Panel of Adipokines with Fat Deposits and Metabolic Phenotypes in a General Population. Obesity (Silver Spring) 2020; 28:1550-1559. [PMID: 32627926 DOI: 10.1002/oby.22871] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 03/31/2020] [Accepted: 04/21/2020] [Indexed: 01/24/2023]
Abstract
OBJECTIVE This study provides a comprehensive overview of the associations of five adipokines (adiponectin, chemerin, galectin-3, leptin, and resistin) with fat deposits, behavioral risk factors, and metabolic phenotypes. METHODS Using multivariable linear and logistic regression models, cross-sectional data from 4,116 participants of the population-based Study of Health in Pomerania were analyzed. RESULTS Participants with obesity showed higher chemerin, galectin-3, and leptin but showed lower adiponectin concentrations. Independently of other fat compounds, liver fat content, visceral adipose tissue, and subcutaneous adipose tissue (SAT) were inversely associated with adiponectin. Independent positive associations of liver fat content and SAT with chemerin as well as of SAT with galectin-3 and leptin were observed. Physically inactive participants had higher chemerin and leptin concentrations. Smokers had higher chemerin and galectin-3 as well as lower leptin. Alcohol consumption was associated with adiponectin (positive) and resistin (inverse). All adipokines were associated with at least one lipid marker. Associations with glucose metabolism were seen for adiponectin, chemerin, galectin-3, and leptin. CONCLUSIONS High adiponectin concentrations were related to favorable metabolic conditions, whereas high chemerin, galectin-3, and leptin were associated with an unfavorable metabolic profile. High leptin seems to be primarily indicative of obesity, whereas high adiponectin and chemerin are associated with a broader range of metabolic phenotypes.
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Affiliation(s)
- Julian Fischer
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research, Partner Site Greifswald, Greifswald, Germany
- German Center for Diabetes Research, Partner Site Greifswald, Greifswald, Germany
| | - Jan Kassubek
- Department of Neurology, University of Ulm, Ulm, Germany
| | | | - Jens-Peter Kühn
- Department of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
- Institute and Policlinic of Diagnostic and Interventional Radiology, University of Dresden, Dresden, Germany
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research, Partner Site Greifswald, Greifswald, Germany
| | - Nele Friedrich
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research, Partner Site Greifswald, Greifswald, Germany
| | - Stephanie Zylla
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research, Partner Site Greifswald, Greifswald, Germany
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26
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Genetic variation, adipokines, and cardiometabolic disease. Curr Opin Pharmacol 2020; 52:33-39. [PMID: 32480034 DOI: 10.1016/j.coph.2020.04.006] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Revised: 04/21/2020] [Accepted: 04/22/2020] [Indexed: 11/24/2022]
Abstract
Adipokines are adipocyte-secreted cell signalling proteins that travel to distant target organs and tissues, where they regulate a variety of biological actions implicated in cardiometabolic health. In the past decade, genome-wide association studies have identified multiple genetic variants associated with circulating levels of adipokines, providing new instruments for examining the role of adipokines in cardiometabolic pathologies. Currently, there is limited genetic evidence of causal relationships between adipokines and cardiometabolic disease, which is consistent with findings from randomized clinical trials that have thus far shown limited success for adipokine-based treatments in improving cardiometabolic health. Incorporating human genetic data in early phases of target selection is essential for enhancing the success of adipokine-based therapies for cardiometabolic disease.
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27
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Adiyaman SC, Ozer M, Saydam BO, Akinci B. The Role of Adiponectin in Maintaining Metabolic Homeostasis. Curr Diabetes Rev 2020; 16:95-103. [PMID: 31267874 DOI: 10.2174/1573399815666190702155733] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2018] [Revised: 03/22/2019] [Accepted: 06/20/2019] [Indexed: 01/01/2023]
Abstract
BACKGROUND Adiponectin is an adipocyte-derived cytokine closely associated with obesity, altered body adipose tissue distribution, insulin resistance, and cardiovascular diseases. INTRODUCTION Evidence from animal and human studies demonstrate that adiponectin plays an important role in the regulation of glucose and lipid metabolism. Adiponectin increases insulin sensitivity and improves systemic lipid metabolism. Although research efforts on adiponectin mostly aim towards its endocrine functions, this adipocyte-derived molecule also has profound autocrine and paracrine functions. CONCLUSION In this review, our aim is to discuss the role of adiponectin in maintaining metabolic homeostasis and its association with cardiovascular health. The proper identification of these roles is of great importance, which has the potential to identify a wealth of novel targets for the treatment of diabetes and related cardio-metabolic diseases.
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Affiliation(s)
| | - Muhammet Ozer
- Department of Internal Medicine, Dokuz Eylul University, Izmir, Turkey
| | - Basak Ozgen Saydam
- Division of Endocrinology and Metabolism, Dokuz Eylul University, Izmir, Turkey
| | - Baris Akinci
- Division of Endocrinology and Metabolism, Dokuz Eylul University, Izmir, Turkey
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Bains V, Kaur H, Badaruddoza. Association study of the single‐nucleotide polymorphisms −3971G/A and +276G/T in the adiponectin gene with type 2 diabetes in a North Indian Punjabi population. Ann Hum Genet 2019; 84:235-248. [DOI: 10.1111/ahg.12366] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2018] [Revised: 07/16/2019] [Accepted: 10/28/2019] [Indexed: 12/18/2022]
Affiliation(s)
- Veena Bains
- Department of Human Genetics Guru Nanak Dev University Amritsar Punjab India
| | - Harjit Kaur
- Department of Human Genetics Guru Nanak Dev University Amritsar Punjab India
| | - Badaruddoza
- Department of Human Genetics Guru Nanak Dev University Amritsar Punjab India
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Awofala AA, Ogundele OE, Adekoya KO, Osundina SA. Adiponectin and human eating behaviour: a Mendelian randomization study. EGYPTIAN JOURNAL OF MEDICAL HUMAN GENETICS 2019. [DOI: 10.1186/s43042-019-0022-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Abstract
Background
Adiponectin plays key roles in regulating appetite and food intake. Altered circulating adiponectin levels have been observed in human eating disorders such as anorexia nervosa, bulimia nervosa or binge eating. In addition, an association between circulating adiponectin levels and human eating behaviour (EB) has been reported. Interestingly, a disturbance in eating behaviour is the defining characteristic of human eating disorders. However, it is unknown whether adiponectin is causally implicated in human EB. We therefore aimed to investigate the causal effect of adiponectin on EB.
Results
Mendelian randomization (MR) analysis estimated the influence of blood adiponectin on EB by combining data on the association of adiponectin gene (ADIPOQ) variants with adiponectin levels and with three EB factors involving disinhibition, restraint and hunger. Using inverse-variance weighted (IVW) regression method and other complementary MR techniques (weighted median regression, MR Egger and weighted modal regression), the MR analysis revealed a broadly consistent evidence that higher blood adiponectin concentration was significantly associated with increased EB factor disinhibition (beta coefficient for IVW regression [βIVW], 3.05; 95% confidence interval [CI] 1.10, 5.00) but non-significantly associated with increased EB factor restraint (βIVW, 0.17; 95% CI − 1.85, 2.18), and increased EB factor hunger (βIVW, 1.63; 95% CI − 0.75, 4.01).
Conclusions
Overall, our findings indicate a causal role of adiponectin levels in eating disinhibition but not in eating restraint and hunger.
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30
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Purfield DC, Evans RD, Berry DP. Reaffirmation of known major genes and the identification of novel candidate genes associated with carcass-related metrics based on whole genome sequence within a large multi-breed cattle population. BMC Genomics 2019; 20:720. [PMID: 31533623 PMCID: PMC6751660 DOI: 10.1186/s12864-019-6071-9] [Citation(s) in RCA: 31] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2018] [Accepted: 08/29/2019] [Indexed: 12/25/2022] Open
Abstract
Background The high narrow sense heritability of carcass traits suggests that the underlying additive genetic potential of an individual should be strongly correlated with both animal carcass quality and quantity, and therefore, by extension, carcass value. Therefore, the objective of the present study was to detect genomic regions associated with three carcass traits, namely carcass weight, conformation and fat cover, using imputed whole genome sequence in 28,470 dairy and beef sires from six breeds with a total of 2,199,926 phenotyped progeny. Results Major genes previously associated with carcass performance were identified, as well as several putative novel candidate genes that likely operate both within and across breeds. The role of MSTN in carcass performance was re-affirmed with the segregating Q204X mutation explaining 1.21, 1.11 and 5.95% of the genetic variance in carcass weight, fat and conformation, respectively in the Charolais population. In addition, a genomic region on BTA6 encompassing the NCAPG/LCORL locus, which is a known candidate locus associated with body size, was associated with carcass weight in Angus, Charolais and Limousin. Novel candidate genes identified included ZFAT in Angus, and SLC40A1 and the olfactory gene cluster on BTA15 in Charolais. Although the majority of associations were breed specific, associations that operated across breeds included SORCS1 on BTA26, MCTP2 on BTA21 and ARL15 on BTA20; these are of particular interest due to their potential informativeness in across-breed genomic evaluations. Genomic regions affecting all three carcass traits were identified in each of the breeds, although these were mainly concentrated on BTA2 and BTA6, surrounding MSTN and NCAPG/LCORL, respectively. This suggests that although major genes may be associated with all three carcass traits, the majority of genes containing significant variants (unadjusted p-value < 10− 4) may be trait specific associations of small effect. Conclusions Although plausible novel candidate genes were identified, the proportion of variance explained by these candidates was minimal thus reaffirming that while carcass performance may be affected by major genes in the form of MSTN and NCAPG/LCORL, the majority of variance is attributed to the additive (and possibly multiplicative) effect of many polymorphisms of small effect. Electronic supplementary material The online version of this article (10.1186/s12864-019-6071-9) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- D C Purfield
- Animal & Grassland Research and Innovation Center, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland.
| | - R D Evans
- Irish Cattle Breeding Federation, Bandon, Co. Cork, Ireland
| | - D P Berry
- Animal & Grassland Research and Innovation Center, Teagasc, Moorepark, Fermoy, Co. Cork, Ireland
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Spracklen CN, Karaderi T, Yaghootkar H, Schurmann C, Fine RS, Kutalik Z, Preuss MH, Lu Y, Wittemans LBL, Adair LS, Allison M, Amin N, Auer PL, Bartz TM, Blüher M, Boehnke M, Borja JB, Bork-Jensen J, Broer L, Chasman DI, Chen YDI, Chirstofidou P, Demirkan A, van Duijn CM, Feitosa MF, Garcia ME, Graff M, Grallert H, Grarup N, Guo X, Haesser J, Hansen T, Harris TB, Highland HM, Hong J, Ikram MA, Ingelsson E, Jackson R, Jousilahti P, Kähönen M, Kizer JR, Kovacs P, Kriebel J, Laakso M, Lange LA, Lehtimäki T, Li J, Li-Gao R, Lind L, Luan J, Lyytikäinen LP, MacGregor S, Mackey DA, Mahajan A, Mangino M, Männistö S, McCarthy MI, McKnight B, Medina-Gomez C, Meigs JB, Molnos S, Mook-Kanamori D, Morris AP, de Mutsert R, Nalls MA, Nedeljkovic I, North KE, Pennell CE, Pradhan AD, Province MA, Raitakari OT, Raulerson CK, Reiner AP, Ridker PM, Ripatti S, Roberston N, Rotter JI, Salomaa V, Sandoval-Zárate AA, Sitlani CM, Spector TD, Strauch K, Stumvoll M, Taylor KD, Thuesen B, Tönjes A, Uitterlinden AG, Venturini C, Walker M, Wang CA, Wang S, Wareham NJ, Willems SM, Willems van Dijk K, Wilson JG, Wu Y, Yao J, Young KL, Langenberg C, Frayling TM, Kilpeläinen TO, Lindgren CM, Loos RJF, Mohlke KL. Exome-Derived Adiponectin-Associated Variants Implicate Obesity and Lipid Biology. Am J Hum Genet 2019; 105:15-28. [PMID: 31178129 DOI: 10.1016/j.ajhg.2019.05.002] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/26/2019] [Accepted: 04/30/2019] [Indexed: 12/25/2022] Open
Abstract
Circulating levels of adiponectin, an adipocyte-secreted protein associated with cardiovascular and metabolic risk, are highly heritable. To gain insights into the biology that regulates adiponectin levels, we performed an exome array meta-analysis of 265,780 genetic variants in 67,739 individuals of European, Hispanic, African American, and East Asian ancestry. We identified 20 loci associated with adiponectin, including 11 that had been reported previously (p < 2 × 10-7). Comparison of exome array variants to regional linkage disequilibrium (LD) patterns and prior genome-wide association study (GWAS) results detected candidate variants (r2 > .60) spanning as much as 900 kb. To identify potential genes and mechanisms through which the previously unreported association signals act to affect adiponectin levels, we assessed cross-trait associations, expression quantitative trait loci in subcutaneous adipose, and biological pathways of nearby genes. Eight of the nine loci were also associated (p < 1 × 10-4) with at least one obesity or lipid trait. Candidate genes include PRKAR2A, PTH1R, and HDAC9, which have been suggested to play roles in adipocyte differentiation or bone marrow adipose tissue. Taken together, these findings provide further insights into the processes that influence circulating adiponectin levels.
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Affiliation(s)
- Cassandra N Spracklen
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Tugce Karaderi
- The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7FZ, UK; Department of Biological Sciences, Faculty of Arts and Sciences, Eastern Mediterranean University, Famagusta, Cyprus; Novo Nordisk Foundation Center for Protein Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark; DTU Health Technology, Technical University of Denmark, Lyngby 2800, Denmark
| | - Hanieh Yaghootkar
- Genetics of Complex Traits, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter EX2 5DW, UK; Research Centre for Optimal Health, School of Life Sciences, University of Westminster, London, UK
| | - Claudia Schurmann
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Rebecca S Fine
- Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, MA 02115, USA; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Zoltan Kutalik
- Genetics of Complex Traits, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter EX2 5DW, UK; University Center for Primary Care and Public Health, University of Lausanne, Lausanne 1010, Switzerland; Swiss Institute of Bioinformatics, Lausanne 1015, Switzerland
| | - Michael H Preuss
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Yingchang Lu
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Division of Epidemiology, Department of Medicine, Vanderbilt-Ingram Cancer Center, Vanderbilt Epidemiology Center, Vanderbilt University School of Medicine, Nashville, TN 37203-1738, USA; Genetics of Obesity and Related Metabolic Traits Program, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Laura B L Wittemans
- The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7FZ, UK; MRC Epidemiology Unit, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Linda S Adair
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC 27516, USA
| | - Matthew Allison
- Department of Family Medicine and Public Health, University of California, San Diego, CA 92093, USA
| | - Najaf Amin
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3015CN, the Netherlands
| | - Paul L Auer
- Joseph J. Zilber School of Public Health, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA
| | - Traci M Bartz
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101, USA; Department of Biostatistics, University of Washington, Seattle, WA 98101, USA
| | - Matthias Blüher
- Medical Department III - Endocrinology, Nephrology, Rheumatology, University of Leipzig, Leipzig 4103, Germany
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Judith B Borja
- Office of Population Studies Foundation, Inc, Cebu City, Philippines; Department of Nutrition and Dietetics, University of San Carlos, Cebu City, Philippines
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Linda Broer
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam 3000 CA, the Netherlands
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, LABioMed at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Paraskevi Chirstofidou
- Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK
| | - Ayse Demirkan
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3015CN, the Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3015CN, the Netherlands
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Melissa E Garcia
- National Heart, Lung, and Blood Institute, Bethesda, MD 20892, USA
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA; Carolina Center for Genome Sciences, Chapel Hill, NC 27599, USA
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, München-Neuherberg 85764, Germany; German Center for Diabetes Research, München-Neuherberg 85765, Germany
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, LABioMed at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Jeffrey Haesser
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Bethesda, MD 20892, USA
| | - Heather M Highland
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jaeyoung Hong
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 2118, USA
| | - M Arfan Ikram
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam 3000 CA, the Netherlands; Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam 3000 CA, the Netherlands
| | - Erik Ingelsson
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Palo Alto, CA 94304, USA; Stanford Cardiovascular Institute, Stanford University of Medicine, Palo Alto, CA 94304, USA; Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala 75185, Sweden; Stanford Diabetes Research Center, Stanford University, Stanford, CA 94305, USA
| | - Rebecca Jackson
- Division of Endocrinology, Diabetes, and Metabolism, Ohio State University, Columbus, OH 43210, USA
| | - Pekka Jousilahti
- Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki 00271, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere 33522, Finland; Department of Clinical Physiology, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33522, Finland
| | - Jorge R Kizer
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Peter Kovacs
- Medical Department III - Endocrinology, Nephrology, Rheumatology, University of Leipzig, Leipzig 4103, Germany
| | - Jennifer Kriebel
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, München-Neuherberg 85764, Germany; German Center for Diabetes Research, München-Neuherberg 85765, Germany
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland and Kuopio University of Hospital, Kuopio 70029 KYS, Finland
| | - Leslie A Lange
- Division of Biomedical Informatics and Personalized Medicine, Department of Medicine, University of Colorado-Denver, Denver, CO 80045, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33520, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33522, Finland
| | - Jin Li
- Department of Medicine, Division of Cardiovascular Medicine, Stanford University, Palo Alto, CA 94304, USA
| | - Ruifang Li-Gao
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden 2333 ZA, the Netherlands
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala 75185, Sweden
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, Tampere 33522, Finland; Department of Clinical Chemistry, Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere 33521, Finland
| | - Stuart MacGregor
- QIMR Berghofer Medical Research Institute, Brisbane, QLD 4006, Australia
| | - David A Mackey
- Faculty of Health and Medical Sciences, The University of Western Australia, Perth, WA 6009, Australia; Centre for Ophthalmology and Visual Science, Lions Eye Institute, The University of Western Australia, Perth, WA 6009, Australia
| | - Anubha Mahajan
- The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7FZ, UK; Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7FZ, UK
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK; NIHR Biomedical Research Centre, Guy's and St Thomas' Foundation Trust, London SE1 9RT, UK
| | - Satu Männistö
- Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki 00271, Finland
| | - Mark I McCarthy
- The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7FZ, UK; Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7FZ, UK; Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford OX3 7FZ, UK
| | - Barbara McKnight
- Department of Biostatistics, University of Washington, Seattle, WA 98101, USA
| | - Carolina Medina-Gomez
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam 3000 CA, the Netherlands; Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam 3000 CA, the Netherlands
| | - James B Meigs
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Medicine, Harvard Medical School, Boston, MA 02115, USA; Program in Population and Medical Genetics, Broad Institute, Cambridge, MA 02114, USA
| | - Sophie Molnos
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München Research Center for Environmental Health, München-Neuherberg 85764, Germany; German Center for Diabetes Research, München-Neuherberg 85765, Germany
| | - Dennis Mook-Kanamori
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden 2333 ZA, the Netherlands; Department of Public Health and Primary Care, Leiden University Medical Center, Leiden 2334 ZA, the Netherlands
| | - Andrew P Morris
- The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7FZ, UK; Department of Biostatistics, University of Liverpool, Liverpool L69 3GL, UK
| | - Renee de Mutsert
- Department of Clinical Epidemiology, Leiden University Medical Center, Leiden 2333 ZA, the Netherlands
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, NIH, Bethesda, MD 20892, USA; Data Tecnica International, Glen Echo, MD 20812, USA
| | - Ivana Nedeljkovic
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam 3015CN, the Netherlands
| | - Kari E North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Craig E Pennell
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Newcastle, NSW 2305, Australia
| | - Aruna D Pradhan
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Olli T Raitakari
- Centre for Population Health Research, University of Turku and Turku University Hospital, Turku, Finland; Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland; Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
| | - Chelsea K Raulerson
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Alex P Reiner
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA 02215, USA; Harvard Medical School, Boston, MA 02115, USA
| | - Samuli Ripatti
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Public Health, University of Helsinki, Helsinki 00014, Finland; Institute for Molecular Medicine Finland, Helsinki 00014, Finland
| | - Neil Roberston
- The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7FZ, UK; Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 7FZ, UK
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, LABioMed at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Veikko Salomaa
- Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki 00271, Finland
| | | | - Colleen M Sitlani
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98101, USA
| | - Tim D Spector
- Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München - German Research Center for Environmental Health, Neuherberg 85764, Germany; Chair of Genetic Epidemiology, Institute of Medical Informatics, Biometry and Epidemiology, Ludwig-Maximilians-Universität, Munich 81377, Germany
| | - Michael Stumvoll
- Medical Department III - Endocrinology, Nephrology, Rheumatology, University of Leipzig, Leipzig 4103, Germany
| | - Kent D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, LABioMed at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Betina Thuesen
- Center for Clinical Research and Disease Prevention, Bispebjerg and Frederiksberg Hospital, The Capital Region, Copenhagen 2400, Denmark
| | - Anke Tönjes
- Medical Department III - Endocrinology, Nephrology, Rheumatology, University of Leipzig, Leipzig 4103, Germany
| | - Andre G Uitterlinden
- Department of Internal Medicine, Erasmus MC University Medical Center Rotterdam, Rotterdam 3000 CA, the Netherlands; Department of Epidemiology, Erasmus MC University Medical Center Rotterdam, Rotterdam 3000 CA, the Netherlands
| | - Cristina Venturini
- Department of Twin Research and Genetic Epidemiology, Kings College London, London SE1 7EH, UK
| | - Mark Walker
- Institute of Cellular Medicine, The Medical School, Newcastle University, Newcastle, UK
| | - Carol A Wang
- School of Medicine and Public Health, Faculty of Medicine and Health, The University of Newcastle, Newcastle, NSW 2305, Australia
| | - Shuai Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 2118, USA
| | | | - Sara M Willems
- MRC Epidemiology Unit, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Ko Willems van Dijk
- Department of Internal Medicine, Division of Endocrinology, Leiden University Medical Center, Leiden 2333 ZA, the Netherlands; Einthoven Laboratory for Experimental Vascular Medicine, Leiden 2333 ZA, the Netherlands; Department of Human Genetics, Leiden University Medical Center, Leiden 2333 ZA, the Netherlands
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS 39216, USA
| | - Ying Wu
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, LABioMed at Harbor-UCLA Medical Center, Torrance, CA 90502, USA
| | - Kristin L Young
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | | | - Timothy M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, Royal Devon & Exeter Hospital, Exeter EX2 5DW, UK
| | - Tuomas O Kilpeläinen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark; Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Cecilia M Lindgren
- The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7FZ, UK; Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA; Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford OX3 7LF, UK
| | - Ruth J F Loos
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; The Mindich Child Health and Development Institute, Ichan School of Medicine at Mount Sinai, New York, NY 10029, USA.
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
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Shen J, Liu M, Xu J, Sun B, Xu H, Zhang W. ARL15 overexpression attenuates high glucose-induced impairment of insulin signaling and oxidative stress in human umbilical vein endothelial cells. Life Sci 2019; 220:127-135. [DOI: 10.1016/j.lfs.2019.01.030] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Revised: 01/10/2019] [Accepted: 01/18/2019] [Indexed: 02/07/2023]
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He J, Stryjecki C, Reddon H, Peralta-Romero J, Karam-Araujo R, Suarez F, Gomez-Zamudio J, Burguete-Garcia A, Alyass A, Cruz M, Meyre D. Adiponectin is associated with cardio-metabolic traits in Mexican children. Sci Rep 2019; 9:3084. [PMID: 30816311 PMCID: PMC6395686 DOI: 10.1038/s41598-019-39801-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2018] [Accepted: 12/31/2018] [Indexed: 02/07/2023] Open
Abstract
The adipocyte-derived adiponectin hormone bridges obesity and its cardio-metabolic complications. Genetic variants at the ADIPOQ locus, in ADIPOR1, and ADIPOR2 have been associated with adiponectin concentrations and cardio-metabolic complications in diverse ethnicities. However, no studies have examined these associations in Mexican children. We recruited 1 457 Mexican children from Mexico City. Six genetic variants in or near ADIPOQ (rs182052, rs2241766, rs266729, rs822393), ADIPOR1 (rs10920533), and ADIPOR2 (rs11061971) were genotyped. Associations between serum adiponectin, genetic variants, and cardio-metabolic traits were assessed using linear and logistic regressions adjusted for age, sex, and recruitment center. Serum adiponectin concentration was negatively associated with body mass index, waist to hip ratio, low-density lipoprotein cholesterol, total cholesterol, triglycerides, fasting glucose, fasting insulin, homeostatic model assessment of insulin resistance, dyslipidemia and overweight/obesity status (7.76 × 10−40 ≤ p ≤ 3.00 × 10−3). No significant associations between genetic variants in ADIPOQ, ADIPOR1, and ADIPOR2 and serum adiponectin concentration were identified (all p ≥ 0.30). No significant associations between the six genetic variants and cardio-metabolic traits were observed after Bonferroni correction (all p < 6.9 × 10−4). Our study suggests strong associations between circulating adiponectin concentration and cardio-metabolic traits in Mexican children.
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Affiliation(s)
- Juehua He
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Carolina Stryjecki
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Hudson Reddon
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Jesus Peralta-Romero
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Roberto Karam-Araujo
- Health Promotion Division, Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Fernando Suarez
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Jaime Gomez-Zamudio
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico
| | - Ana Burguete-Garcia
- Centro de investigación sobre enfermedades infecciosas. Instituto Nacional de Salud Pública. Cuernavaca, Morelos, Mexico
| | - Akram Alyass
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada
| | - Miguel Cruz
- Medical Research Unit in Biochemistry, Hospital de Especialidades, Centro Médico Nacional Siglo XXI del Instituto Mexicano del Seguro Social, Mexico City, Mexico.
| | - David Meyre
- Department of Health Research Methods, Evidence, and Impact, McMaster University, Hamilton, Canada. .,Department of Pathology and Molecular Medicine, McMaster University, Hamilton, Canada.
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Taneera J, Prasad RB, Dhaiban S, Mohammed AK, Haataja L, Arvan P, Hamad M, Groop L, Wollheim CB. Silencing of the FTO gene inhibits insulin secretion: An in vitro study using GRINCH cells. Mol Cell Endocrinol 2018; 472:10-17. [PMID: 29890211 PMCID: PMC6559235 DOI: 10.1016/j.mce.2018.06.003] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/22/2018] [Revised: 05/14/2018] [Accepted: 06/07/2018] [Indexed: 01/01/2023]
Abstract
Expression of fat mass and obesity-associated gene (FTO) and ADP-ribosylation factor-like 15 (ARL15) in human islets is inversely correlated with HbA1c. However, their impact on insulin secretion is still ambiguous. Here in, we investigated the role of FTO and ARL15 using GRINCH (Glucose-Responsive Insulin-secreting C-peptide-modified Human proinsulin) clonal rat β-cells. GRINCH cells have inserted GFP into the human C-peptide insulin gene. Hence, secreted CpepGFP served to monitor insulin secretion. mRNA silencing of FTO in GRINCH cells showed a significant reduction in glucose but not depolarization-stimulated insulin secretion, whereas ARL15 silencing had no effect. A significant down-regulation of insulin mRNA was observed in FTO knockdown cells. Type-2 Diabetic islets revealed a reduced expression of FTO mRNA. In conclusion, our data suggest that fluorescent CpepGFP released from GRINCH cells may serve as a convenient marker for insulin secretion. Silencing of FTO expression, but not ARL15, inhibits insulin secretion by affecting metabolic signaling.
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Affiliation(s)
- Jalal Taneera
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates; Lund University Diabetes Center, Malmoe, Lund University, Sweden.
| | - Rashmi B Prasad
- Lund University Diabetes Center, Malmoe, Lund University, Sweden
| | - Sarah Dhaiban
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates
| | - Abdul Khader Mohammed
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates
| | - Leena Haataja
- Endocrinology and Diabetes, University of Michigan Medical School, Ann Arbor, USA
| | - Peter Arvan
- Endocrinology and Diabetes, University of Michigan Medical School, Ann Arbor, USA
| | - Mawieh Hamad
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates
| | - Leif Groop
- Lund University Diabetes Center, Malmoe, Lund University, Sweden; Finnish Institute for Molecular Medicine (FIMM), Helsinki University, Finland
| | - Claes B Wollheim
- Lund University Diabetes Center, Malmoe, Lund University, Sweden; Department of Cell Physiology and Metabolism, University Medical Center. Geneva, Switzerland
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Peters KE, Davis WA, Beilby J, Hung J, Bruce DG, Davis TME. The relationship between circulating adiponectin, ADIPOQ variants and incident cardiovascular disease in type 2 diabetes: The Fremantle Diabetes Study. Diabetes Res Clin Pract 2018; 143:62-70. [PMID: 29969725 DOI: 10.1016/j.diabres.2018.06.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2018] [Revised: 05/25/2018] [Accepted: 06/13/2018] [Indexed: 01/23/2023]
Abstract
AIMS To investigate the relationship between serum adiponectin, ADIPOQ variants and haplotypes, and cardiovascular disease (CVD) in type 2 diabetes (T2D). METHODS Baseline data including serum total adiponectin and 21 ADIPOQ polymorphisms were available for 1076 participants (mean age 64.0 years, 49.4% males) in a community-based cohort followed for an average of 12 years. RESULTS During 8843 patient-years of follow-up for coronary heart disease (CHD), 13,494 patient-years for ischaemic stroke (IS) and 12,028 patient-years for heart failure (HF), 40.4%, 11.8% and 31.9% of patients experienced a first episode of CHD, IS or HF, respectively. In Cox regression after adjustment for the most parsimonious models, loge(serum adiponectin) and the ADIPOQ variant rs12495941 were inversely associated with incident CHD (hazard ratio [95% confidence interval] 0.79 [0.65-0.98] and 0.64 [0.44-0.94], respectively), while rs1648707 was positively associated with incident IS (2.05 [1.37-3.06]; all P ≤ 0.028). In males, rs9860747 and rs17366568 predicted CHD (0.22 [0.05-0.92] and 1.50 [1.01-2.20]; P ≤ 0.042), while rs1648707 and rs1063537 predicted IS (2.36 [1.32-4.23] and 2.09 [1.17-3.72]; P ≤ 0.012). In females, rs10937273 predicted CHD via an interaction with serum adiponectin (0.43 [0.21-0.91]; P = 0.027), while rs864265 predicted IS (0.43 [0.21-0.88], P = 0.021). The associations between ADIPOQ variants and outcomes were supported by haplotype block analysis. Neither serum adiponectin nor ADIPOQ variants predicted HF. CONCLUSIONS Serum total adiponectin and gender-specific ADIPOQ variants predict CHD and IS, but not HF, independently of other risk factors in community-based patients with T2D. In contrast to some previous studies, there was no relationship between a high serum total adiponectin and CVD.
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Affiliation(s)
- Kirsten E Peters
- Medical School, University of Western Australia, Crawley, Western Australia, Australia.
| | - Wendy A Davis
- Medical School, University of Western Australia, Crawley, Western Australia, Australia.
| | - John Beilby
- Department of Diagnostic Molecular Genomics, PathWest, Queen Elizabeth II Medical Centre, Nedlands, Western Australia, Australia; School of Biomedical Sciences, University of Western Australia, Crawley, Western Australia, Australia.
| | - Joe Hung
- Medical School, University of Western Australia, Crawley, Western Australia, Australia.
| | - David G Bruce
- Medical School, University of Western Australia, Crawley, Western Australia, Australia.
| | - Timothy M E Davis
- Medical School, University of Western Australia, Crawley, Western Australia, Australia.
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Pilot genome-wide association study identifying novel risk loci for type 2 diabetes in a Maya population. Gene 2018; 677:324-331. [PMID: 30130595 DOI: 10.1016/j.gene.2018.08.041] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Revised: 07/27/2018] [Accepted: 08/08/2018] [Indexed: 12/20/2022]
Abstract
Type 2 diabetes mellitus (T2D) is one of the two leading causes of mortality in Mexico. However, most studies have focused on Caucasians or Asians, and there are a small number of studies investigating Maya populations. Furthermore, to the best of our knowledge, there is no information on isolated Maya communities with T2D frequencies of 20% that are primarily attributed to ethnicity. Consequently, this study focused on assessing which genetic risk variants could be involved in the high rates of T2D in 92 individuals with Maya ancestry; 47 were diagnosed with T2D, and 45 were classified as healthy individuals. A pilot genome-wide association study was performed using the Affymetrix Axiom Genome-wide LAT1 array. The population structure was determined with the ADMIXTURE software using 1289 Latin American selected polymorphisms, and 39 polymorphisms associated with T2D were included for replication. Association tests were performed using the Statistical Analysis System (SAS) using the allelic, genotype and Armitage trend tests. The results indicated that population structure analysis displayed no differences between T2D patients and healthy individuals; 24 loci located were identified for probable association with T2D (p > 1.288 × 10-7 and p < 1.348 × 10-4); the polymorphism AGTR2 rs1914711 in chromosome X was identified by the allele test (OR = 6.824; p = 1.448 × 10-9) as a candidate gene for association with T2D; and ARL15 rs4311394 was associated as a T2D protector by genotype and the Armitage trend test (OR = 0.318; p = 0.001). In conclusion, this study proposes 24 candidate SNPs associated with T2D for replication studies and one for protective association with T2D.
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Lundbäck V, Kulyte A, Strawbridge RJ, Ryden M, Arner P, Marcus C, Dahlman I. FAM13A and POM121C are candidate genes for fasting insulin: functional follow-up analysis of a genome-wide association study. Diabetologia 2018; 61:1112-1123. [PMID: 29487953 PMCID: PMC6448992 DOI: 10.1007/s00125-018-4572-8] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/18/2017] [Accepted: 12/20/2017] [Indexed: 01/09/2023]
Abstract
AIMS/HYPOTHESIS By genome-wide association meta-analysis, 17 genetic loci associated with fasting serum insulin (FSI), a marker of systemic insulin resistance, have been identified. To define potential culprit genes in these loci, in a cross-sectional study we analysed white adipose tissue (WAT) expression of 120 genes in these loci in relation to systemic and adipose tissue variables, and functionally evaluated genes demonstrating genotype-specific expression in WAT (eQTLs). METHODS Abdominal subcutaneous adipose tissue biopsies were obtained from 114 women. Basal lipolytic activity was measured as glycerol release from adipose tissue explants. Adipocytes were isolated and insulin-stimulated incorporation of radiolabelled glucose into lipids was used to quantify adipocyte insulin sensitivity. Small interfering RNA-mediated knockout in human mesenchymal stem cells was used for functional evaluation of genes. RESULTS Adipose expression of 48 of the studied candidate genes associated significantly with FSI, whereas expression of 24, 17 and 2 genes, respectively, associated with adipocyte insulin sensitivity, lipolysis and/or WAT morphology (i.e. fat cell size relative to total body fat mass). Four genetic loci contained eQTLs. In one chromosome 4 locus (rs3822072), the FSI-increasing allele associated with lower FAM13A expression and FAM13A expression associated with a beneficial metabolic profile including decreased WAT lipolysis (regression coefficient, R = -0.50, p = 5.6 × 10-7). Knockdown of FAM13A increased lipolysis by ~1.5-fold and the expression of LIPE (encoding hormone-sensitive lipase, a rate-limiting enzyme in lipolysis). At the chromosome 7 locus (rs1167800), the FSI-increasing allele associated with lower POM121C expression. Consistent with an insulin-sensitising function, POM121C expression associated with systemic insulin sensitivity (R = -0.22, p = 2.0 × 10-2), adipocyte insulin sensitivity (R = 0.28, p = 3.4 × 10-3) and adipose hyperplasia (R = -0.29, p = 2.6 × 10-2). POM121C knockdown decreased expression of all adipocyte-specific markers by 25-50%, suggesting that POM121C is necessary for adipogenesis. CONCLUSIONS/INTERPRETATION Gene expression and adipocyte functional studies support the notion that FAM13A and POM121C control adipocyte lipolysis and adipogenesis, respectively, and might thereby be involved in genetic control of systemic insulin sensitivity.
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Affiliation(s)
- Veroniqa Lundbäck
- Department of Clinical Science, Intervention and Technology, Division of Paediatrics, Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Agne Kulyte
- Department of Medicine, Huddinge, Karolinska Institutet, C2:94, SE-141 86, Stockholm, Sweden
| | - Rona J Strawbridge
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, UK
- Department of Medicine, Solna, Karolinska Institute, Stockholm, Sweden
| | - Mikael Ryden
- Department of Medicine, Huddinge, Karolinska Institutet, C2:94, SE-141 86, Stockholm, Sweden
| | - Peter Arner
- Department of Medicine, Huddinge, Karolinska Institutet, C2:94, SE-141 86, Stockholm, Sweden
| | - Claude Marcus
- Department of Clinical Science, Intervention and Technology, Division of Paediatrics, Huddinge, Karolinska Institutet, Stockholm, Sweden
| | - Ingrid Dahlman
- Department of Medicine, Huddinge, Karolinska Institutet, C2:94, SE-141 86, Stockholm, Sweden.
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BDNF Val66Met polymorphism, life stress and depression: A meta-analysis of gene-environment interaction. J Affect Disord 2018; 227:226-235. [PMID: 29102837 DOI: 10.1016/j.jad.2017.10.024] [Citation(s) in RCA: 92] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2017] [Revised: 09/25/2017] [Accepted: 10/04/2017] [Indexed: 02/07/2023]
Abstract
BACKGROUND Depression is thought to be multifactorial in etiology, including genetic and environmental components. While a number of gene-environment interaction studies have been carried out, meta-analyses are scarce. The present meta-analysis aimed to quantify evidence on the interaction between brain-derived neurotrophic factor (BDNF) Val66Met polymorphism and stress in depression. METHODS Included were 31 peer-reviewed with a pooled total of 21060 participants published before October 2016 and literature searches were conducted using PubMed, Wolters Kluwer, Web of Science, EBSCO, Elsevier Science Direct and Baidu Scholar databases. RESULTS The results indicated that the Met allele of BDNF Val66Met polymorphism significantly moderated the relationship between stress and depression (Z=2.666, p = 0.003). The results of subgroup analysis concluded that stressful life events and childhood adversity separately interacted with the Met allele of BDNF Val66Met polymorphism in depression (Z = 2.552, p = 0.005; Z = 1.775, p = 0.03). LIMITATIONS The results could be affected by errors or bias in primary studies which had small sample sizes with relatively lower statistic power. We could not estimate how strong the interaction effect between gene and environment was. CONCLUSIONS We found evidence that supported the hypothesis that BDNF Val66Met polymorphism moderated the relationship between stress and depression, despite the fact that many included individual studies did not show this effect.
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Rocha N, Payne F, Huang-Doran I, Sleigh A, Fawcett K, Adams C, Stears A, Saudek V, O’Rahilly S, Barroso I, Semple RK. The metabolic syndrome- associated small G protein ARL15 plays a role in adipocyte differentiation and adiponectin secretion. Sci Rep 2017; 7:17593. [PMID: 29242557 PMCID: PMC5730586 DOI: 10.1038/s41598-017-17746-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2017] [Accepted: 11/30/2017] [Indexed: 02/02/2023] Open
Abstract
Common genetic variants at the ARL15 locus are associated with plasma adiponectin, insulin and HDL cholesterol concentrations, obesity, and coronary atherosclerosis. The ARL15 gene encodes a small GTP-binding protein whose function is currently unknown. In this study adipocyte-autonomous roles for ARL15 were investigated using conditional knockdown of Arl15 in murine 3T3-L1 (pre)adipocytes. Arl15 knockdown in differentiated adipocytes impaired adiponectin secretion but not adipsin secretion or insulin action, while in preadipocytes it impaired adipogenesis. In differentiated adipocytes GFP-tagged ARL15 localized predominantly to the Golgi with lower levels detected at the plasma membrane and intracellular vesicles, suggesting involvement in intracellular trafficking. Sequencing of ARL15 in 375 severely insulin resistant patients identified four rare heterozygous variants, including an early nonsense mutation in a proband with femorogluteal lipodystrophy and non classical congenital adrenal hyperplasia, and an essential splice site mutation in a proband with partial lipodystrophy and a history of childhood yolk sac tumour. No nonsense or essential splice site mutations were found in 2,479 controls, while five such variants were found in the ExAC database. These findings provide evidence that ARL15 plays a role in adipocyte differentiation and adiponectin secretion, and raise the possibility that human ARL15 haploinsufficiency predisposes to lipodystrophy.
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Affiliation(s)
- Nuno Rocha
- 0000 0004 0369 9638grid.470900.aThe University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Cambridge, UK ,grid.454369.9The National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, UK
| | - Felicity Payne
- 0000 0004 0606 5382grid.10306.34Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Isabel Huang-Doran
- 0000 0004 0369 9638grid.470900.aThe University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Cambridge, UK ,grid.454369.9The National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, UK
| | - Alison Sleigh
- 0000000121885934grid.5335.0Wolfson Brain Imaging Centre, University of Cambridge School of Clinical Medicine, Cambridge Biomedical Campus, Cambridge, UK ,0000 0004 0383 8386grid.24029.3dNational Institute for Health Research/Wellcome Trust Clinical Research Facility, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, UK
| | - Katherine Fawcett
- 0000 0004 0606 5382grid.10306.34Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Claire Adams
- 0000 0004 0369 9638grid.470900.aThe University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Cambridge, UK ,grid.454369.9The National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, UK
| | - Anna Stears
- 0000 0004 0383 8386grid.24029.3dWolfson Diabetes and Endocrine Clinic, Institute of Metabolic Science, Addenbrooke’s Hospital, Cambridge University Hospitals NHS Foundation Trust, Cambridge, UK
| | - Vladimir Saudek
- 0000 0004 0369 9638grid.470900.aThe University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Cambridge, UK ,grid.454369.9The National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, UK
| | - Stephen O’Rahilly
- 0000 0004 0369 9638grid.470900.aThe University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Cambridge, UK ,grid.454369.9The National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, UK
| | - Inês Barroso
- 0000 0004 0369 9638grid.470900.aThe University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Cambridge, UK ,0000 0004 0606 5382grid.10306.34Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, UK
| | - Robert K. Semple
- 0000 0004 0369 9638grid.470900.aThe University of Cambridge Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, Cambridge, UK ,grid.454369.9The National Institute for Health Research Cambridge Biomedical Research Centre, Cambridge, UK ,0000 0004 1936 7988grid.4305.2Centre for Cardiovascular Sciences, University of Edinburgh, Queen’s Medical Research Institute, Edinburgh, UK
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40
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Corre T, Arjona FJ, Hayward C, Youhanna S, de Baaij JHF, Belge H, Nägele N, Debaix H, Blanchard MG, Traglia M, Harris SE, Ulivi S, Rueedi R, Lamparter D, Macé A, Sala C, Lenarduzzi S, Ponte B, Pruijm M, Ackermann D, Ehret G, Baptista D, Polasek O, Rudan I, Hurd TW, Hastie ND, Vitart V, Waeber G, Kutalik Z, Bergmann S, Vargas-Poussou R, Konrad M, Gasparini P, Deary IJ, Starr JM, Toniolo D, Vollenweider P, Hoenderop JGJ, Bindels RJM, Bochud M, Devuyst O. Genome-Wide Meta-Analysis Unravels Interactions between Magnesium Homeostasis and Metabolic Phenotypes. J Am Soc Nephrol 2017; 29:335-348. [PMID: 29093028 DOI: 10.1681/asn.2017030267] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/11/2017] [Accepted: 07/19/2017] [Indexed: 12/15/2022] Open
Abstract
Magnesium (Mg2+) homeostasis is critical for metabolism. However, the genetic determinants of the renal handling of Mg2+, which is crucial for Mg2+ homeostasis, and the potential influence on metabolic traits in the general population are unknown. We obtained plasma and urine parameters from 9099 individuals from seven cohorts, and conducted a genome-wide meta-analysis of Mg2+ homeostasis. We identified two loci associated with urinary magnesium (uMg), rs3824347 (P=4.4×10-13) near TRPM6, which encodes an epithelial Mg2+ channel, and rs35929 (P=2.1×10-11), a variant of ARL15, which encodes a GTP-binding protein. Together, these loci account for 2.3% of the variation in 24-hour uMg excretion. In human kidney cells, ARL15 regulated TRPM6-mediated currents. In zebrafish, dietary Mg2+ regulated the expression of the highly conserved ARL15 ortholog arl15b, and arl15b knockdown resulted in renal Mg2+ wasting and metabolic disturbances. Finally, ARL15 rs35929 modified the association of uMg with fasting insulin and fat mass in a general population. In conclusion, this combined observational and experimental approach uncovered a gene-environment interaction linking Mg2+ deficiency to insulin resistance and obesity.
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Affiliation(s)
- Tanguy Corre
- Institute of Social and Preventive Medicine.,Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Francisco J Arjona
- Department of Physiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Caroline Hayward
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine
| | - Sonia Youhanna
- Institute of Physiology, University of Zürich, Zurich, Switzerland
| | - Jeroen H F de Baaij
- Department of Physiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Hendrica Belge
- Institute of Physiology, University of Zürich, Zurich, Switzerland
| | - Nadine Nägele
- Institute of Physiology, University of Zürich, Zurich, Switzerland
| | - Huguette Debaix
- Institute of Physiology, University of Zürich, Zurich, Switzerland
| | - Maxime G Blanchard
- Department of Physiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Michela Traglia
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology.,Medical Genetics Section, University of Edinburgh Centre for Genomic and Experimental Medicine and Medical Research Council Institute of Genetics and Molecular Medicine, Western General Hospital, Edinburgh, Scotland, UK
| | - Sheila Ulivi
- Department of Medical Genetics, Institute for Maternal and Child Health, Istituto di Ricovero e Cura a Carattere Scientifico "Burlo Garofolo," Trieste, Italy
| | - Rico Rueedi
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - David Lamparter
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Aurélien Macé
- Institute of Social and Preventive Medicine.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Cinzia Sala
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | - Stefania Lenarduzzi
- Department of Medical Genetics, Institute for Maternal and Child Health, Istituto di Ricovero e Cura a Carattere Scientifico "Burlo Garofolo," Trieste, Italy
| | | | - Menno Pruijm
- Service of Nephrology, University Hospital of Lausanne, Lausanne, Switzerland
| | - Daniel Ackermann
- University Clinic for Nephrology and Hypertension, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Georg Ehret
- Division of Cardiology, Department of Internal Medicine Specialties, University Hospital of Geneva, Geneva, Switzerland
| | - Daniela Baptista
- Division of Cardiology, Department of Internal Medicine Specialties, University Hospital of Geneva, Geneva, Switzerland
| | - Ozren Polasek
- Faculty of Medicine, University of Split, Split, Croatia
| | - Igor Rudan
- Usher Institute of Population Health Sciences and Informatics
| | - Toby W Hurd
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine
| | - Nicholas D Hastie
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine
| | - Veronique Vitart
- Medical Research Council Human Genetics Unit, Institute of Genetics and Molecular Medicine
| | | | - Zoltán Kutalik
- Institute of Social and Preventive Medicine.,Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland.,Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Rosa Vargas-Poussou
- Department of Genetics, Hôpital Européen Georges Pompidou, Assistance Publique Hôpitaux de Paris, Paris, France.,Centre de Référence des Maladies Rénales Héréditaires de l'Enfant et de l'Adulte, Paris, France
| | - Martin Konrad
- Department of General Pediatrics, University Hospital Münster, Munster, Germany
| | - Paolo Gasparini
- Department of Medical, Surgical and Health Sciences, University of Trieste, Trieste, Italy; and.,Department of Experimental Genetics, Sidra, Doha, Qatar
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology.,Department of Psychology, and
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology.,Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, Scotland, UK
| | - Daniela Toniolo
- Division of Genetics and Cell Biology, San Raffaele Scientific Institute, Milan, Italy
| | | | - Joost G J Hoenderop
- Department of Physiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | - René J M Bindels
- Department of Physiology, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, The Netherlands
| | | | - Olivier Devuyst
- Institute of Physiology, University of Zürich, Zurich, Switzerland;
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Abstract
Insulin resistance and the metabolic syndrome are complex metabolic traits and key risk factors for the development of cardiovascular disease. They result from the interplay of environmental and genetic factors but the full extent of the genetic background to these conditions remains incomplete. Large-scale genome-wide association studies have helped advance the identification of common genetic variation associated with insulin resistance and the metabolic syndrome, and more recently, exome sequencing has allowed the identification of rare variants associated with the pathogenesis of these conditions. Many variants associated with insulin resistance are directly involved in glucose metabolism; however, functional studies are required to assess the contribution of other variants to the development of insulin resistance. Many genetic variants involved in the pathogenesis of the metabolic syndrome are associated with lipid metabolism.
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Affiliation(s)
- Audrey E Brown
- Institute of Cellular Medicine, William Leech Building, Medical School, Newcastle University, Newcastle, NE2 4HH, UK
| | - Mark Walker
- Institute of Cellular Medicine, William Leech Building, Medical School, Newcastle University, Newcastle, NE2 4HH, UK.
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Cilek EE, Ozturk H, Gur Dedeoglu B. Construction of miRNA-miRNA networks revealing the complexity of miRNA-mediated mechanisms in trastuzumab treated breast cancer cell lines. PLoS One 2017; 12:e0185558. [PMID: 28981542 PMCID: PMC5628841 DOI: 10.1371/journal.pone.0185558] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2017] [Accepted: 09/14/2017] [Indexed: 12/02/2022] Open
Abstract
Trastuzumab is a monoclonal antibody frequently used to prevent the progression of HER2+ breast cancers, which constitute approximately 20% of invasive breast cancers. microRNAs (miRNAs) are small, non-coding RNA molecules that are known to be involved in gene regulation. With their emerging roles in cancer, they are recently promoted as potential candidates to mediate therapeutic actions by targeting genes associated with drug response. In this study we explored miRNA-mediated regulation of trastuzumab mechanisms by identifying the important miRNAs responsible for the drug response via homogenous network analysis. Our network model enabled us to simplify the complexity of miRNA interactions by connecting them through their common pathways. We outlined the functionally relevant miRNAs by constructing pathway-based miRNA-miRNA networks in SKBR3 and BT474 cells, respectively. Identification of the most targeted genes revealed that trastuzumab responsive miRNAs favourably regulate the repression of targets with longer 3’UTR than average considered to be key elements, while the miRNA-miRNA networks highlighted central miRNAs such as hsa-miR-3976 and hsa-miR-3671 that showed strong interactions with the remaining members of the network. Furthermore, the clusters of the miRNA-miRNA networks showed that trastuzumab response was mostly established through cancer related and metabolic pathways. hsa-miR-216b was found to be the part of the most powerful interactions of metabolic pathways, which was defined in the largest clusters in both cell lines. The network based representation of miRNA-miRNA interactions through their shared pathways provided a better understanding of miRNA-mediated drug response and could be suggested for further characterization of miRNA functions.
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Affiliation(s)
| | - Hakime Ozturk
- Department of Computer Engineering, Bogazici University, Istanbul, Turkey
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43
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Deguchi H, Navarro S, Payne AB, Elias DJ, Dowling NF, Austin HD, España F, Medina P, Hooper WC, Griffin JH. Low level of the plasma sphingolipid, glucosylceramide, is associated with thrombotic diseases. Res Pract Thromb Haemost 2017; 1:33-40. [PMID: 29202121 PMCID: PMC5703432 DOI: 10.1002/rth2.12018] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Essentials Minor abundance plasma lipids, eg, glucosylceramide, can modulate blood coagulation reactions This lipid was measured in plasmas of 1 myocardial infarction and 2 venous thrombosis populations Low plasma glucosylceramide levels were found in each population compared to matched controls Low plasma glucosylceramide levels are associated with venous and arterial thrombosis
Background One previous pilot study suggested the association of low plasma glucosylceramide (GlcCer) levels with venous thrombosis (VTE) risk. Objective We aimed to confirm and evaluate the association of low plasma GlcCer levels with VTE and myocardial infarction (MI) occurrence, respectively. Patients and Methods We evaluated the association of GlcCer in two independent case‐control studies of Caucasian VTE populations (N=210 and 636) and one case‐control study of Caucasian MI patients (N=345). Result Plasma GlcCer levels in VTE patients were lower compared to controls in two independent VTE populations (5.0 vs 5.8 μg/mL, P=.003 for the Scripps registry, and 5.6 vs 6.0 μg/mL, P=.001 for the Valencia registry, respectively). A low plasma GlcCer level (below tenth percentile of controls) was associated with increased VTE occurrence (odds ratio [OR]=3.7 [95% CI, 1.8‐7.9] for Scripps registry and OR=2.1 [95% CI, 1.3‐3.3] for Valencia registry, respectively). For the MI study, the median GlcCer plasma level was lower in MI patients than in controls (4.3 vs 5.6 μg/mL, P<.001), and a low level of GlcCer (below tenth percentile of control) was associated with higher MI occurrence (OR=7.7, [95% CI, 4.3‐13.8]). Conclusion Lower concentration of GlcCer was associated with VTE occurrence in 2 independent studies and also with MI occurrence in 1 study.
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Affiliation(s)
- Hiroshi Deguchi
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA
| | - Silvia Navarro
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA.,Haemostasis, Thrombosis, Atherosclerosis and Vascular Biology Research Group, La Fe Medical Research Institute, Valencia, Spain
| | - Amanda B Payne
- Rollins School of Public Health, Emory University, Atlanta, GA, USA.,Division of Blood Disorders, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Darlene J Elias
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA.,Scripps Clinic and Scripps Green Hospital, La Jolla, CA, USA
| | - Nicole F Dowling
- Rollins School of Public Health, Emory University, Atlanta, GA, USA.,Division of Blood Disorders, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Harland D Austin
- Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Francisco España
- Haemostasis, Thrombosis, Atherosclerosis and Vascular Biology Research Group, La Fe Medical Research Institute, Valencia, Spain
| | - Pilar Medina
- Haemostasis, Thrombosis, Atherosclerosis and Vascular Biology Research Group, La Fe Medical Research Institute, Valencia, Spain
| | - W Craig Hooper
- Division of Blood Disorders, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - John H Griffin
- Department of Molecular Medicine, The Scripps Research Institute, La Jolla, CA, USA
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An Updated Systematic Review and Meta-analysis of Association Between Adiponectin Gene Polymorphisms and Coronary Artery Disease. ACTA ACUST UNITED AC 2017; 21:340-351. [DOI: 10.1089/omi.2017.0007] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
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Nimptsch K, Song M, Aleksandrova K, Katsoulis M, Freisling H, Jenab M, Gunter MJ, Tsilidis KK, Weiderpass E, Bueno-De-Mesquita HB, Chong DQ, Jensen MK, Wu C, Overvad K, Kühn T, Barrdahl M, Melander O, Jirström K, Peeters PH, Sieri S, Panico S, Cross AJ, Riboli E, Van Guelpen B, Myte R, Huerta JM, Rodriguez-Barranco M, Quirós JR, Dorronsoro M, Tjønneland A, Olsen A, Travis R, Boutron-Ruault MC, Carbonnel F, Severi G, Bonet C, Palli D, Janke J, Lee YA, Boeing H, Giovannucci EL, Ogino S, Fuchs CS, Rimm E, Wu K, Chan AT, Pischon T. Genetic variation in the ADIPOQ gene, adiponectin concentrations and risk of colorectal cancer: a Mendelian Randomization analysis using data from three large cohort studies. Eur J Epidemiol 2017; 32:419-430. [PMID: 28550647 PMCID: PMC5535815 DOI: 10.1007/s10654-017-0262-y] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Accepted: 05/18/2017] [Indexed: 12/20/2022]
Abstract
Higher levels of circulating adiponectin have been related to lower risk of colorectal cancer in several prospective cohort studies, but it remains unclear whether this association may be causal. We aimed to improve causal inference in a Mendelian Randomization meta-analysis using nested case-control studies of the European Prospective Investigation into Cancer and Nutrition (EPIC, 623 cases, 623 matched controls), the Health Professionals Follow-up Study (HPFS, 231 cases, 230 controls) and the Nurses' Health Study (NHS, 399 cases, 774 controls) with available data on pre-diagnostic adiponectin concentrations and selected single nucleotide polymorphisms in the ADIPOQ gene. We created an ADIPOQ allele score that explained approximately 3% of the interindividual variation in adiponectin concentrations. The ADIPOQ allele score was not associated with risk of colorectal cancer in logistic regression analyses (pooled OR per score-unit unit 0.97, 95% CI 0.91, 1.04). Genetically determined twofold higher adiponectin was not significantly associated with risk of colorectal cancer using the ADIPOQ allele score as instrumental variable (pooled OR 0.73, 95% CI 0.40, 1.34). In a summary instrumental variable analysis (based on previously published data) with higher statistical power, no association between genetically determined twofold higher adiponectin and risk of colorectal cancer was observed (0.99, 95% CI 0.93, 1.06 in women and 0.94, 95% CI 0.88, 1.01 in men). Thus, our study does not support a causal effect of circulating adiponectin on colorectal cancer risk. Due to the limited genetic determination of adiponectin, larger Mendelian Randomization studies are necessary to clarify whether adiponectin is causally related to lower risk of colorectal cancer.
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Affiliation(s)
- Katharina Nimptsch
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine (MDC), Robert-Rössle-Straße 10, 13125, Berlin, Germany.
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Mingyang Song
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Krasimira Aleksandrova
- Nutrition, Immunity and Metabolism Start-up Lab, Department of Epidemiology, German Institute of Human Nutrition (DIfE), Potsdam-Rehbruecke, Nuthetal, Germany
| | - Michail Katsoulis
- Hellenic Health Foundation, Athens, Greece
- Farr Institute of Health Informatics Research at London, UCL, London, UK
| | - Heinz Freisling
- International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Mazda Jenab
- International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Marc J Gunter
- International Agency for Research on Cancer (IARC-WHO), Lyon, France
| | - Konstantinos K Tsilidis
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, Ioannina, Greece
| | - Elisabete Weiderpass
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, The Arctic University of Norway, Tromsø, Norway
- Department of Research, Cancer Registry of Norway, Oslo, Norway
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
- Samfundet Folkhälsan, Helsinki, Finland
| | - H Bas Bueno-De-Mesquita
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
- Department for Determinants of Chronic Diseases (DCD), National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
- Department of Social and Preventive Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Dawn Q Chong
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Division of Medical Oncology, National Cancer Centre Singapore, Singapore, Singapore
| | - Majken K Jensen
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Chunsen Wu
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark
- Institute of Clinical Research, University of Southern Denmark, Odense, Denmark
- Odense University Hospital, Odense, Denmark
| | - Kim Overvad
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Tilman Kühn
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Myrto Barrdahl
- Division of Cancer Epidemiology, German Cancer Research Center, Heidelberg, Germany
| | - Olle Melander
- Department of Clinical Sciences Lund, Lund University, Malmö, Sweden
| | - Karin Jirström
- Department of Clinical Sciences Lund, Lund University, Malmö, Sweden
| | - Petra H Peeters
- Department of Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands
- MRC-PHE Centre for Environment and Health, Department of Epidemiology and Biostatistics, School of Public Health, Imperial College, London, UK
| | - Sabina Sieri
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
| | - Amanda J Cross
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
| | - Elio Riboli
- Department of Epidemiology and Biostatistics, The School of Public Health, Imperial College London, London, UK
| | | | - Robin Myte
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - José María Huerta
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Miguel Rodriguez-Barranco
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs, GRANADA, Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain
| | | | - Miren Dorronsoro
- Public Health Direction and Biodonostia Research Institute- Ciberesp, Basque Regional Health Department, San Sebastian, Spain
| | | | - Anja Olsen
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Ruth Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Marie-Christine Boutron-Ruault
- Université Paris-Sud, UVSQ, CESP, INSERM, Université Paris-Saclay, Villejuif, France
- Gustave Roussy, 94805, Villejuif, France
| | - Franck Carbonnel
- Université Paris-Sud, UVSQ, CESP, INSERM, Université Paris-Saclay, Villejuif, France
- Gustave Roussy, 94805, Villejuif, France
- Department of Gastroenterology, Assistance Publique-Hôpitaux de Paris (AP-HP), University hospitals Paris-Sud, Site de Bicêtre, Paris Sud University, Paris XI, Le Kremlin Bicêtre, Villejuif, France
| | - Gianluca Severi
- Université Paris-Sud, UVSQ, CESP, INSERM, Université Paris-Saclay, Villejuif, France
- Gustave Roussy, 94805, Villejuif, France
- Human Genetics Foundation (HuGeF), Turin, Italy
- Cancer Council Victoria, Melbourne, Australia
- University of Melbourne, Melbourne, Australia
| | - Catalina Bonet
- Unit of Nutrition and Cancer, Cancer Epidemiology Research Programme, Catalan Institute of Oncology (ICO), Barcelona, Spain
| | - Domenico Palli
- Cancer Research and Prevention Institute (ISPO), Florence, Italy
| | - Jürgen Janke
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine (MDC), Robert-Rössle-Straße 10, 13125, Berlin, Germany
| | - Young-Ae Lee
- Genetics of Allergic Disease Research Group, Max Delbrück Center for Molecular Medicine (MDC), Berlin, Germany
| | - Heiner Boeing
- Department of Epidemiology, German Institute of Human Nutrition (DIfE), Potsdam-Rehbruecke, Nuthetal, Germany
| | - Edward L Giovannucci
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Shuji Ogino
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
- Division of MPE Molecular Pathological Epidemiology, Department of Pathology, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Charles S Fuchs
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
- Department of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical School, Boston, MA, USA
| | - Eric Rimm
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
| | - Kana Wu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Andrew T Chan
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, and Harvard Medical School, Boston, MA, USA
- Broad Institute, Cambridge, MA, USA
| | - Tobias Pischon
- Molecular Epidemiology Research Group, Max Delbrück Center for Molecular Medicine (MDC), Robert-Rössle-Straße 10, 13125, Berlin, Germany
- Charité Universitätsmedizin, Berlin, Germany
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Civelek M, Wu Y, Pan C, Raulerson CK, Ko A, He A, Tilford C, Saleem NK, Stančáková A, Scott LJ, Fuchsberger C, Stringham HM, Jackson AU, Narisu N, Chines PS, Small KS, Kuusisto J, Parks BW, Pajukanta P, Kirchgessner T, Collins FS, Gargalovic PS, Boehnke M, Laakso M, Mohlke KL, Lusis AJ. Genetic Regulation of Adipose Gene Expression and Cardio-Metabolic Traits. Am J Hum Genet 2017; 100:428-443. [PMID: 28257690 DOI: 10.1016/j.ajhg.2017.01.027] [Citation(s) in RCA: 114] [Impact Index Per Article: 16.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2016] [Accepted: 01/12/2017] [Indexed: 12/15/2022] Open
Abstract
Subcutaneous adipose tissue stores excess lipids and maintains energy balance. We performed expression quantitative trait locus (eQTL) analyses by using abdominal subcutaneous adipose tissue of 770 extensively phenotyped participants of the METSIM study. We identified cis-eQTLs for 12,400 genes at a 1% false-discovery rate. Among an approximately 680 known genome-wide association study (GWAS) loci for cardio-metabolic traits, we identified 140 coincident cis-eQTLs at 109 GWAS loci, including 93 eQTLs not previously described. At 49 of these 140 eQTLs, gene expression was nominally associated (p < 0.05) with levels of the GWAS trait. The size of our dataset enabled identification of five loci associated (p < 5 × 10-8) with at least five genes located >5 Mb away. These trans-eQTL signals confirmed and extended the previously reported KLF14-mediated network to 55 target genes, validated the CIITA regulation of class II MHC genes, and identified ZNF800 as a candidate master regulator. Finally, we observed similar expression-clinical trait correlations of genes associated with GWAS loci in both humans and a panel of genetically diverse mice. These results provide candidate genes for further investigation of their potential roles in adipose biology and in regulating cardio-metabolic traits.
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Affiliation(s)
- Mete Civelek
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Center for Public Health Genomics, University of Virginia, Charlottesville, VA 22908, USA; Department of Biomedical Engineering, University of Virginia, Charlottesville, VA 22908, USA
| | - Ying Wu
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Calvin Pan
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Chelsea K Raulerson
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA
| | - Arthur Ko
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA; Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Aiqing He
- Bristol-Myers Squibb, Pennington, NJ 08534, USA
| | | | - Niyas K Saleem
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio 70210, Finland
| | - Alena Stančáková
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio 70210, Finland
| | - Laura J Scott
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Christian Fuchsberger
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Heather M Stringham
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Narisu Narisu
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Peter S Chines
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | - Kerrin S Small
- Department of Twin Research and Genetic Epidemiology, School of Medicine, King's College London, London SE1 7EH, UK
| | - Johanna Kuusisto
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio 70210, Finland
| | - Brian W Parks
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | - Päivi Pajukanta
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA; Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA
| | | | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | | | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI 48109, USA
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio 70210, Finland
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC 27599, USA.
| | - Aldons J Lusis
- Department of Medicine, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA; Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA 90095, USA; Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA 90095, USA.
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Ma W, Huang T, Heianza Y, Wang T, Sun D, Tong J, Williamson DA, Bray GA, Sacks FM, Qi L. Genetic Variations of Circulating Adiponectin Levels Modulate Changes in Appetite in Response to Weight-Loss Diets. J Clin Endocrinol Metab 2017; 102:316-325. [PMID: 27841942 PMCID: PMC5413100 DOI: 10.1210/jc.2016-2909] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/05/2016] [Accepted: 11/10/2016] [Indexed: 01/06/2023]
Abstract
CONTEXT Adiponectin plays key roles in regulating appetite and food intake. OBJECTIVE To investigate interactions between the genetic risk score (GRS) for adiponectin levels and weight-loss diets varying in macronutrient intake on long-term changes in appetite and adiponectin levels. DESIGN, SETTING, AND PARTICIPANTS A GRS was calculated based on 5 adiponectin-associated variants in 692 overweight adults from the 2-year Preventing Overweight Using Novel Dietary Strategies trial. MAIN OUTCOME MEASURES Repeated measurements of plasma adiponectin levels and appetite-related traits, including cravings, fullness, prospective consumption, and hunger. RESULTS Dietary fat showed nominally significant interactions with the adiponectin GRS on changes in appetite score and prospective consumption from baseline to 6 months (P for interaction = 0.014 and 0.017, respectively) after adjusting for age, sex, ethnicity, baseline body mass index, and baseline respective outcome values. The GRS for lower adiponectin levels was associated with a greater decrease in appetite (P < 0.001) and prospective consumption (P = 0.008) among participants consuming a high-fat diet, whereas no significant associations were observed in the low-fat group. Additionally, a significant interaction was observed between the GRS and dietary fat on 6-month changes in adiponectin levels (P for interaction = 0.021). The lower GRS was associated with a greater increase in adiponectin in the low-fat group (P = 0.02), but it was not associated with adiponectin changes in the high-fat group (P = 0.31). CONCLUSIONS Our findings suggest that individuals with varying genetic architecture of circulating adiponectin may respond divergently in appetite and adiponectin levels to weight-loss diets varying in fat intake.
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Affiliation(s)
| | - Tao Huang
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana 70112;
| | - Yoriko Heianza
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana 70112;
| | - Tiange Wang
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana 70112;
| | - Dianjianyi Sun
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana 70112;
| | - Jenny Tong
- Department of Medicine, Duke University School of Medicine, Durham, North Carolina 27703;
| | - Donald A. Williamson
- Pennington Biomedical Research Center of the Louisiana State University System, Baton Rouge, Louisiana 70808; and
| | - George A. Bray
- Pennington Biomedical Research Center of the Louisiana State University System, Baton Rouge, Louisiana 70808; and
| | - Frank M. Sacks
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115;
| | - Lu Qi
- Department of Epidemiology and
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, Massachusetts 02115;
- Department of Epidemiology, School of Public Health and Tropical Medicine, Tulane University, New Orleans, Louisiana 70112;
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, Massachusetts 02115
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48
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Ried JS, Jeff M. J, Chu AY, Bragg-Gresham JL, van Dongen J, Huffman JE, Ahluwalia TS, Cadby G, Eklund N, Eriksson J, Esko T, Feitosa MF, Goel A, Gorski M, Hayward C, Heard-Costa NL, Jackson AU, Jokinen E, Kanoni S, Kristiansson K, Kutalik Z, Lahti J, Luan J, Mägi R, Mahajan A, Mangino M, Medina-Gomez C, Monda KL, Nolte IM, Pérusse L, Prokopenko I, Qi L, Rose LM, Salvi E, Smith MT, Snieder H, Stančáková A, Ju Sung Y, Tachmazidou I, Teumer A, Thorleifsson G, van der Harst P, Walker RW, Wang SR, Wild SH, Willems SM, Wong A, Zhang W, Albrecht E, Couto Alves A, Bakker SJL, Barlassina C, Bartz TM, Beilby J, Bellis C, Bergman RN, Bergmann S, Blangero J, Blüher M, Boerwinkle E, Bonnycastle LL, Bornstein SR, Bruinenberg M, Campbell H, Chen YDI, Chiang CWK, Chines PS, Collins FS, Cucca F, Cupples LA, D'Avila F, de Geus EJ.C, Dedoussis G, Dimitriou M, Döring A, Eriksson JG, Farmaki AE, Farrall M, Ferreira T, Fischer K, Forouhi NG, Friedrich N, Gjesing AP, Glorioso N, Graff M, Grallert H, Grarup N, Gräßler J, Grewal J, Hamsten A, Harder MN, Hartman CA, Hassinen M, Hastie N, Hattersley AT, Havulinna AS, Heliövaara M, Hillege H, Hofman A, Holmen O, Homuth G, Hottenga JJ, Hui J, Husemoen LL, Hysi PG, Isaacs A, Ittermann T, Jalilzadeh S, James AL, Jørgensen T, Jousilahti P, Jula A, Marie Justesen J, Justice AE, Kähönen M, Karaleftheri M, Tee Khaw K, Keinanen-Kiukaanniemi SM, Kinnunen L, Knekt PB, Koistinen HA, Kolcic I, Kooner IK, Koskinen S, Kovacs P, Kyriakou T, Laitinen T, Langenberg C, Lewin AM, Lichtner P, Lindgren CM, Lindström J, Linneberg A, Lorbeer R, Lorentzon M, Luben R, Lyssenko V, Männistö S, Manunta P, Leach IM, McArdle WL, Mcknight B, Mohlke KL, Mihailov E, Milani L, Mills R, Montasser ME, Morris AP, Müller G, Musk AW, Narisu N, Ong KK, Oostra BA, Osmond C, Palotie A, Pankow JS, Paternoster L, Penninx BW, Pichler I, Pilia MG, Polašek O, Pramstaller PP, Raitakari OT, Rankinen T, Rao DC, Rayner NW, Ribel-Madsen R, Rice TK, Richards M, Ridker PM, Rivadeneira F, Ryan KA, Sanna S, Sarzynski MA, Scholtens S, Scott RA, Sebert S, Southam L, Sparsø TH, Steinthorsdottir V, Stirrups K, Stolk RP, Strauch K, Stringham HM, Swertz MA, Swift AJ, Tönjes A, Tsafantakis E, van der Most PJ, Van Vliet-Ostaptchouk JV, Vandenput L, Vartiainen E, Venturini C, Verweij N, Viikari JS, Vitart V, Vohl MC, Vonk JM, Waeber G, Widén E, Willemsen G, Wilsgaard T, Winkler TW, Wright AF, Yerges-Armstrong LM, Hua Zhao J, Carola Zillikens M, Boomsma DI, Bouchard C, Chambers JC, Chasman DI, Cusi D, Gansevoort RT, Gieger C, Hansen T, Hicks AA, Hu F, Hveem K, Jarvelin MR, Kajantie E, Kooner JS, Kuh D, Kuusisto J, Laakso M, Lakka TA, Lehtimäki T, Metspalu A, Njølstad I, Ohlsson C, Oldehinkel AJ, Palmer LJ, Pedersen O, Perola M, Peters A, Psaty BM, Puolijoki H, Rauramaa R, Rudan I, Salomaa V, Schwarz PEH, Shudiner AR, Smit JH, Sørensen TIA, Spector TD, Stefansson K, Stumvoll M, Tremblay A, Tuomilehto J, Uitterlinden AG, Uusitupa M, Völker U, Vollenweider P, Wareham NJ, Watkins H, Wilson JF, Zeggini E, Abecasis GR, Boehnke M, Borecki IB, Deloukas P, van Duijn CM, Fox C, Groop LC, Heid IM, Hunter DJ, Kaplan RC, McCarthy MI, North KE, O'Connell JR, Schlessinger D, Thorsteinsdottir U, Strachan DP, Frayling T, Hirschhorn JN, Müller-Nurasyid M, Loos RJF. A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape. Nat Commun 2016; 7:13357. [PMID: 27876822 PMCID: PMC5114527 DOI: 10.1038/ncomms13357] [Citation(s) in RCA: 52] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2016] [Accepted: 09/21/2016] [Indexed: 01/15/2023] Open
Abstract
Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.
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Affiliation(s)
- Janina S. Ried
- Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Janina Jeff M.
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Audrey Y. Chu
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02215, USA
| | - Jennifer L. Bragg-Gresham
- Kidney Epidemiology and Cost Center, Internal Medicine-Nephrology, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Jenny van Dongen
- Department of Biological Psychology, VU University, 1081BT Amsterdam, The Netherlands
| | - Jennifer E. Huffman
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH4 2XU Edinburgh, Scotland
| | - Tarunveer S. Ahluwalia
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, 2100 Copenhagen, Denmark
- Steno Diabetes Center A/S, DK-2820 Gentofte, Denmark
- COPSAC, Copenhagen Prospective Studies on Asthma in Childhood, Herlev and Gentofte Hospital, University of Copenhagen, Ledreborg Allé 34, DK-2820 Copenhagen, Denmark
| | - Gemma Cadby
- Centre for Genetic Origins of Health and Disease, University of Western Australia, Crawley, Western Australia 6009, Australia
| | - Niina Eklund
- Department of Health, National Institute for Health and Welfare (THL), FI-00271 Helsinki, Finland
| | - Joel Eriksson
- Department of Internal Medicine and Clinical Nutrition, Centre for Bone and Arthritis Research, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, 413 45 Gothenburg, Sweden
| | - Tõnu Esko
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts 2142, USA
- Divisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Massachusetts 02115, USA
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
| | - Mary F. Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Anuj Goel
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DU, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Mathias Gorski
- Department of Nephrology, University Hospital Regensburg, 93042 Regensburg, Germany
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, 93053 Regensburg, Germany
| | - Caroline Hayward
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH4 2XU Edinburgh, Scotland
| | - Nancy L. Heard-Costa
- National Heart, Lung, and Blood Institute, the Framingham Heart Study, Framingham, Massachusetts 01702, USA
- Department of Neurology, Boston University School of Medicine, Boston, Massachusetts 02118, USA
| | - Anne U. Jackson
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Eero Jokinen
- Hospital for Children and Adolescents, University of Helsinki, FI-00290 Helsinki, Finland
| | - Stavroula Kanoni
- Wellcome Trust Sanger Institute, Human Genetics, Hinxton, Cambridge CB10 1SA, UK
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
| | - Kati Kristiansson
- Department of Health, National Institute for Health and Welfare (THL), FI-00271 Helsinki, Finland
- Institute for Molecular Medicine Finland, University of Helsinki, FI-00290 Helsinki, Finland
| | - Zoltán Kutalik
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
- Department of Medical Genetics, University of Lausanne, Lausanne, 1005, Switzerland
- Institute of Social and Preventive Medicine, University Hospital Lausanne (CHUV), 1010 Lausanne, Switzerland
| | - Jari Lahti
- Folkhälsan Research Centre, FI-00290 Helsinki, Finland
- Institute of Behavioural Sciences, University of Helsinki, FI-00014 Helsinki, Finland
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Anubha Mahajan
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK
| | - Carolina Medina-Gomez
- Department of Epidemiology, Erasmus Medical Center, 3015GE Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, 3015GE Rotterdam, The Netherlands
| | - Keri L. Monda
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
- The Center for Observational Research, Amgen Inc., Thousand Oaks, California 91320-1799, USA
| | - Ilja M. Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands
| | - Louis Pérusse
- Department of Kinesiology, Laval University, Québec, Québec, Canada G1V 0A6
- Institute of Nutrition and Functional Foods, Laval University, Québec, Québec, Canada G1V 0A6
| | - Inga Prokopenko
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, London W12 0NN, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford OX3 7LJ, UK
| | - Lu Qi
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts 02115, USA
| | - Lynda M. Rose
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02215, USA
| | - Erika Salvi
- Department of Health Sciences, University of Milano at San Paolo Hospital, 20139 Milano, Italy
- Filarete Foundation, Genomic and Bioinformatics Unit, Milano 20139, Italy
| | - Megan T. Smith
- Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands
| | - Alena Stančáková
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, 70210 Kuopio, Finland
| | - Yun Ju Sung
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Ioanna Tachmazidou
- Wellcome Trust Sanger Institute, Human Genetics, Hinxton, Cambridge CB10 1SA, UK
| | - Alexander Teumer
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, 17475 Greifswald, Germany
| | | | - Pim van der Harst
- Durrer Center for Cardiogenetic Research, Interuniversity Cardiology Institute Netherlands-Netherlands Heart Institute, 3501 DG Utrecht, The Netherlands
- Department of Genetics, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands
- Department of Cardiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, Netherlands
| | - Ryan W. Walker
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
- The Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
| | - Sophie R. Wang
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA
- Division of Endocrinology, Boston Children's Hospital, Boston, Massachusetts 02115, USA
- Divisions of Genetics and Endocrinology and Program in Genomics, Boston's Children's Hospital, Boston, Massachusetts 02115, USA
| | - Sarah H. Wild
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, EH8 9AG Teviot Place, Edinburgh, Scotland
| | - Sara M. Willems
- Department of Epidemiology, Genetic Epidemiology Unit, Erasmus University Medical Center, 3015GE Rotterdam, The Netherlands
| | - Andrew Wong
- MRC Unit for Lifelong Health & Ageing at UCL, London WC1B 5JU, UK
| | - Weihua Zhang
- Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK
- Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK
| | - Eva Albrecht
- Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Alexessander Couto Alves
- Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London W12 0NN, UK
| | - Stephan J. L. Bakker
- Department of Medicine, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, Netherlands
| | - Cristina Barlassina
- Department of Health Sciences, University of Milano at San Paolo Hospital, 20139 Milano, Italy
- Filarete Foundation, Genomic and Bioinformatics Unit, Milano 20139, Italy
| | - Traci M. Bartz
- Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA
- Department of Medicine, University of Washington, Seattle, Washington 98101, USA
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington 98101, USA
| | - John Beilby
- Pathwest Laboratory Medicine of Western Australia, Nedlands, Western Australia 6009, Australia
- School of Pathology and Laboratory Medicine, University of Western Australia, Nedlands, Western Australia 6009, Australia
| | - Claire Bellis
- Genomics Research Centre, Institute of Health and Biomedical Innovation, Queensland University of Technology, Brisbane, Queensland 4001, Australia
- Human Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research of Singapore, Singapore 138672, Singapore
| | - Richard N. Bergman
- Diabetes and Obesity Research Institute, Cedars-Sinai Medical Center, Los Angeles, California 90048, USA
| | - Sven Bergmann
- Swiss Institute of Bioinformatics, 1015 Lausanne, Switzerland
- Department of Medical Genetics, University of Lausanne, Lausanne, 1005, Switzerland
| | - John Blangero
- South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville, Texas 78520, USA
| | - Matthias Blüher
- University of Leipzig, IFB Adiposity Diseases, 04103 Leipzig, Germany
- Department of Medicine, University of Leipzig, 04103 Leipzig, Germany
| | - Eric Boerwinkle
- Human Genetics Center and Institute of Molecular Medicine, University of Texas Health Science Center, Houston, Texas 77030, USA
| | - Lori L. Bonnycastle
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland 20892, USA
| | - Stefan R. Bornstein
- Medical Faculty Carl Gustav Carus, Department of Medicine III, University of Dresden, 01307 Dresden, Germany
| | - Marcel Bruinenberg
- University of Groningen, University Medical Center Groningen, The LifeLines Cohort Study, 9700 RB Groningen, The Netherlands
| | - Harry Campbell
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, EH8 9AG Teviot Place, Edinburgh, Scotland
| | - Yii-Der Ida Chen
- Los Angeles BioMedical Resesarch Institute at Harbor-UCLA Medical Center, Torrance, California 90502, USA
| | | | - Peter S. Chines
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland 20892, USA
| | - Francis S Collins
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland 20892, USA
| | | | - L Adrienne Cupples
- National Heart, Lung, and Blood Institute, the Framingham Heart Study, Framingham, Massachusetts 01702, USA
| | - Francesca D'Avila
- Department of Health Sciences, University of Milano at San Paolo Hospital, 20139 Milano, Italy
- Filarete Foundation, Genomic and Bioinformatics Unit, Milano 20139, Italy
| | - Eco J .C. de Geus
- Department of Biological Psychology, VU University, 1081BT Amsterdam, The Netherlands
- EMGO Institute for Health and Care Research, VU University Medical Center, 1081 BT Amsterdam, The Netherlands
| | - George Dedoussis
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 17671 Athens, Greece
| | - Maria Dimitriou
- Wellcome Trust Sanger Institute, Human Genetics, Hinxton, Cambridge CB10 1SA, UK
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 17671 Athens, Greece
| | - Angela Döring
- Institute of Epidemiology I, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Johan G. Eriksson
- Folkhälsan Research Centre, FI-00290 Helsinki, Finland
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, FI-00271 Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, FI-00014 Helsinki, Finland
| | - Aliki-Eleni Farmaki
- Department of Nutrition and Dietetics, School of Health Science and Education, Harokopio University, 17671 Athens, Greece
| | - Martin Farrall
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DU, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Teresa Ferreira
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Krista Fischer
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Nita G. Forouhi
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Nele Friedrich
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Anette Prior Gjesing
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Nicola Glorioso
- Hypertension and Related Disease Centre, AOU-University of Sassari, 7100 Sassari, Italy
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Harald Grallert
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany
- German Center for Diabetes Research (DZD), 85764 Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Niels Grarup
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Jürgen Gräßler
- Department of Medicine III, Pathobiochemistry, Technische Universitaet, 01307 Dresden, Germany
| | - Jagvir Grewal
- Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK
- Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK
| | - Anders Hamsten
- Department of Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Medicine Solna, Atherosclerosis Research Unit, Karolinska Institutet, 17176 Stockholm 17176, Sweden
- Center for Molecular Medicine, Karolinska University Hospital, 17176 Stockholm, Sweden
| | - Marie Neergaard Harder
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Catharina A. Hartman
- University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion Regulation, 9700 RB Groningen, The Netherlands
| | - Maija Hassinen
- Kuopio Research Institute of Exercise Medicine, 70100 Kuopio, Finland
| | - Nicholas Hastie
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH4 2XU Edinburgh, Scotland
| | - Andrew Tym Hattersley
- Institue of Biomedical & Clinical Science, University of Exeter, Barrack Road, Exeter EX2 5DW, UK
| | - Aki S. Havulinna
- Department of Health, National Institute for Health and Welfare (THL), FI-00271 Helsinki, Finland
| | - Markku Heliövaara
- Department of Health, National Institute for Health and Welfare (THL), FI-00271 Helsinki, Finland
| | - Hans Hillege
- Department of Cardiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, Netherlands
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, 3015GE Rotterdam, The Netherlands
| | - Oddgeir Holmen
- Department of Public Health and General Practice, Norwegian University of Science and Technology, 7489 Trondheim, Norway
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, VU University, 1081BT Amsterdam, The Netherlands
| | - Jennie Hui
- Pathwest Laboratory Medicine of Western Australia, Nedlands, Western Australia 6009, Australia
- School of Pathology and Laboratory Medicine, University of Western Australia, Nedlands, Western Australia 6009, Australia
- School of Population Health, University of Western Australia, Nedlands, Western Australia 6009, Australia
| | - Lise Lotte Husemoen
- Research Centre for Prevention and Health, Glostrup Hospital, 2600 Glostrup, Denmark
| | - Pirro G. Hysi
- Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK
| | - Aaron Isaacs
- Department of Epidemiology, Genetic Epidemiology Unit, Erasmus University Medical Center, 3015GE Rotterdam, The Netherlands
| | - Till Ittermann
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Shapour Jalilzadeh
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DU, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Alan L. James
- Department of Pulmonary Physiology and Sleep Medicine, Sir Charles Gairdner Hospital, Nedlands, Western Australia 6009, Australia
| | - Torben Jørgensen
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
- Faculty of Medicine, University of Aalborg, 9220 Aalborg, Denmark
- Research Centre for Prevention and Health, Capital Region of Denmark, DK2600 Glostrup, Denmark
| | - Pekka Jousilahti
- Department of Health, National Institute for Health and Welfare (THL), FI-00271 Helsinki, Finland
| | - Antti Jula
- Department of Health, National Institute for Health and Welfare (THL), FI-00271 Helsinki, Finland
| | - Johanne Marie Justesen
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Anne E. Justice
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599, USA
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, FI-33521 Tampere, Finland
- Department of Clinical Physiology, University of Tampere School of Medicine, FI-33014 Tampere, Finland
| | | | - Kay Tee Khaw
- Clinical Gerontology Unit, Box 251, Addenbrooke's Hospital, Hills Road, Cambridge CB2 2QQ, UK
| | - Sirkka M. Keinanen-Kiukaanniemi
- Faculty of Medicine, Institute of Health Sciences, University of Oulu, Oulu F1-90014, Finland
- Unit of General Practice, Oulu University Hospital, Oulu FI-90029, Finland
| | - Leena Kinnunen
- National Institute for Health and Welfare, FI-00271 Helsinki, Finland
| | - Paul B. Knekt
- Department of Health, National Institute for Health and Welfare (THL), FI-00271 Helsinki, Finland
| | - Heikki A. Koistinen
- National Institute for Health and Welfare, FI-00271 Helsinki, Finland
- Department of Medicine and Abdominal Center: Endocrinology, University of Helsinki and Helsinki University Central Hospital,, 00029 Helsinki, Finland
- Minerva Foundation Institute for Medical Research, 00290 Helsinki, Finland
| | - Ivana Kolcic
- Department of Public Health, Faculty of Medicine, University of Split, 21000 Split, Croatia
| | | | - Seppo Koskinen
- Department of Health, National Institute for Health and Welfare (THL), FI-00271 Helsinki, Finland
| | - Peter Kovacs
- University of Leipzig, IFB Adiposity Diseases, 04103 Leipzig, Germany
| | - Theodosios Kyriakou
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DU, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - Tomi Laitinen
- Kuopio University Hospital, 70029 Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, University of Eastern Finland, FI-70211 Kuopio, Finland
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
- Department of Epidemiology and Public Health, UCL, London WC1E 6BT, UK
| | - Alexandra M. Lewin
- Department of Epidemiology and Biostatistics, MRC Health Protection Agency (HPA) Centre for Environment and Health, School of Public Health, Imperial College, London W12 0NN, UK
| | - Peter Lichtner
- Institute of Human Genetics, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Cecilia M. Lindgren
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts 2142, USA
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- The Big Data Institute, University of Oxford, Oxford OX3 7LJ, UK
| | - Jaana Lindström
- Department of Health, National Institute for Health and Welfare (THL), FI-00271 Helsinki, Finland
| | - Allan Linneberg
- Research Centre for Prevention and Health, Glostrup Hospital, 2600 Glostrup, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, 2200 Copenhagen, Denmark
- Department of Clinical Experimental Research, Rigshospitalet, 2600 Glostrup, Denmark
| | - Roberto Lorbeer
- Institute for Community Medicine, University Medicine Greifswald, 17475 Greifswald, Germany
| | - Mattias Lorentzon
- Department of Internal Medicine and Clinical Nutrition, Centre for Bone and Arthritis Research, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, 413 45 Gothenburg, Sweden
| | - Robert Luben
- Strangeways Research Laboratory Wort's Causeway, Cambridge CB1 8RN, UK
| | - Valeriya Lyssenko
- Steno Diabetes Center A/S, DK-2820 Gentofte, Denmark
- Lund University Diabetes Centre and Department of Clinical Science, Diabetes & Endocrinology Unit, Lund University, 221 00 Malmö, Sweden
| | - Satu Männistö
- Department of Health, National Institute for Health and Welfare (THL), FI-00271 Helsinki, Finland
| | - Paolo Manunta
- Chair of Nephrology, Università Vita Salute San Raffaele and Genomics of Renal Diseases and Hypertension Unit, IRCCS San Raffaele Scientific Institute, Milan 20139, Italy
| | - Irene Mateo Leach
- Department of Cardiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, Netherlands
| | - Wendy L. McArdle
- School of Social and Community Medicine, University of Bristol, Bristol BS82BN, UK
| | - Barbara Mcknight
- Department of Biostatistics, University of Washington, Seattle, Washington 98195, USA
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington 98101, USA
- Divison of Public Health Sciences, Program in Biostatistics and Biomathematics, Fred Hutchinson Cancer Research Center, Seattle, Washington 98109, USA
| | - Karen L. Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599, USA
| | - Evelin Mihailov
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Lili Milani
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | | | - May E. Montasser
- Division of Endocrinology, Diabetes & Nutrition, Department of Medicine, Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
| | - Andrew P. Morris
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Department of Biostatistics, University of Liverpool, Liverpool L69 3GA, UK
| | - Gabriele Müller
- Center for Evidence Based Healthcare, University of Dresden, Medical Faculty Carl Gustav Carus, Dresden, 01307, Germany
| | - Arthur W. Musk
- Department of Respiratory Medicine, Sir Charles Gairdner Hospital, Nedlands, West Australia 6009, Australia
| | - Narisu Narisu
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland 20892, USA
| | - Ken K. Ong
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
- MRC Unit for Lifelong Health & Ageing at UCL, London WC1B 5JU, UK
- Department of Paediatrics, University of Cambridge, Cambridge CB2 0QQ, UK
| | - Ben A. Oostra
- Department of Epidemiology, Genetic Epidemiology Unit, Erasmus University Medical Center, 3015GE Rotterdam, The Netherlands
| | - Clive Osmond
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton SO16 6YD, UK
| | - Aarno Palotie
- Institute for Molecular Medicine Finland, University of Helsinki, FI-00290 Helsinki, Finland
- Massachusetts General Hospital, Center for Human Genetic Research, Psychiatric and Neurodevelopmental Genetics Unit, Boston, Massachusetts 02114, USA
| | - James S. Pankow
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota 55455-0381, USA
| | - Lavinia Paternoster
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol BS8 1TH, UK
| | - Brenda W. Penninx
- Department of Psychiatry and EMGO Institute for Health and Care Research, VU University Medical Center, AJ Ernstraat 1887, 1081 HL Amsterdam, The Netherlands
| | - Irene Pichler
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC), 39100 Bolzano, Italy
- Affiliated Institute of the University of Lübeck, 23562 Lübeck, Germany
| | - Maria G. Pilia
- Istituto di Ricerca Genetica e Biomedica, CNR, 9042 Monserrato, Italy
| | - Ozren Polašek
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, EH8 9AG Teviot Place, Edinburgh, Scotland
- Department of Public Health, Faculty of Medicine, University of Split, 21000 Split, Croatia
| | - Peter P. Pramstaller
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC), 39100 Bolzano, Italy
- Affiliated Institute of the University of Lübeck, 23562 Lübeck, Germany
- Department of Neurology, University of Lübeck, 23562 Lübeck, Germany
- Department of Neurology, General Central Hospital, 39100 Bolzano, Italy
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, FI-20521 Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, FI-20520 Turku, Finland
| | - Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana 70808, USA
| | - D. C. Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Nigel W. Rayner
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford OX3 7LJ, UK
- Wellcome Trust Sanger Institute, Human Genetics, Hinxton CB10 1HH, UK
| | - Rasmus Ribel-Madsen
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Treva K. Rice
- Division of Biostatistics, Washington University School of Medicine, St. Louis, Missouri 63110, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA
| | - Marcus Richards
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford OX3 7LJ, UK
- MRC Unit for Lifelong Health & Ageing at UCL, London WC1B 5JU, UK
| | - Paul M. Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02215, USA
- Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus Medical Center, 3015GE Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, 3015GE Rotterdam, The Netherlands
| | - Kathy A. Ryan
- Division of Endocrinology, Diabetes & Nutrition, Department of Medicine, Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
| | - Serena Sanna
- Istituto di Ricerca Genetica e Biomedica, CNR, 9042 Monserrato, Italy
| | - Mark A. Sarzynski
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana 70808, USA
| | - Salome Scholtens
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands
| | - Robert A. Scott
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Sylvain Sebert
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, London W12 0NN, UK
- Biocenter Oulu, University of Oulu, Oulu FI-90014, Finland
- Center For Life-Course Health Research, University of Oulu, FI-90014 Oulu, Finland
| | - Lorraine Southam
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Wellcome Trust Sanger Institute, Human Genetics, Hinxton, Cambridge CB10 1SA, UK
| | - Thomas Hempel Sparsø
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, 2100 Copenhagen, Denmark
| | | | - Kathleen Stirrups
- Wellcome Trust Sanger Institute, Human Genetics, Hinxton, Cambridge CB10 1SA, UK
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
| | - Ronald P. Stolk
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands
| | - Konstantin Strauch
- Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, 81377 Munich, Germany
| | - Heather M. Stringham
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Morris A. Swertz
- Department of Genetics, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands
| | - Amy J. Swift
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, NIH, Bethesda, Maryland 20892, USA
| | - Anke Tönjes
- Department of Medicine, University of Leipzig, 04103 Leipzig, Germany
| | | | - Peter J. van der Most
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands
| | - Jana V. Van Vliet-Ostaptchouk
- Department of Endocrinology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands
| | - Liesbeth Vandenput
- Department of Internal Medicine and Clinical Nutrition, Centre for Bone and Arthritis Research, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, 413 45 Gothenburg, Sweden
| | - Erkki Vartiainen
- Department of Health, National Institute for Health and Welfare (THL), FI-00271 Helsinki, Finland
| | - Cristina Venturini
- Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK
- Institute of Ophthalmology, University College London, London EC1V 9EL, UK
| | - Niek Verweij
- Department of Cardiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, Netherlands
| | - Jorma S. Viikari
- Department of Medicine, University of Turku, FI-20521 Turku, Finland
- Division of Medicine, Turku University Hospital, Turku, Finland
| | - Veronique Vitart
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH4 2XU Edinburgh, Scotland
| | - Marie-Claude Vohl
- Institute of Nutrition and Functional Foods, Laval University, Québec, Québec, Canada G1V 0A6
- School of Nutrition, Laval University, Québec, Québec, Canada G1V 0A6
| | - Judith M. Vonk
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, The Netherlands
| | - Gérard Waeber
- Department of Internal Medicine, University Hospital Lausanne (CHUV) and University of Lausanne, 1011 Lausanne, Switzerland
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland, University of Helsinki, FI-00290 Helsinki, Finland
| | - Gonneke Willemsen
- Department of Biological Psychology, VU University, 1081BT Amsterdam, The Netherlands
| | - Tom Wilsgaard
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, 9037 Tromsø, Norway
| | - Thomas W. Winkler
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, 93053 Regensburg, Germany
| | - Alan F. Wright
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH4 2XU Edinburgh, Scotland
| | - Laura M. Yerges-Armstrong
- Division of Endocrinology, Diabetes & Nutrition, Department of Medicine, Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
| | - Jing Hua Zhao
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - M. Carola Zillikens
- Department of Internal Medicine, Erasmus Medical Center, 3015GE Rotterdam, The Netherlands
| | - Dorret I. Boomsma
- Department of Biological Psychology, VU University, 1081BT Amsterdam, The Netherlands
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana 70808, USA
| | - John C. Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London W2 1PG, UK
- Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK
- Imperial College Healthcare NHS Trust, London W12 0HS, UK
| | - Daniel I. Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, Massachusetts 02215, USA
- Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Daniele Cusi
- Department of Health Sciences, University of Milano at San Paolo Hospital, 20139 Milano, Italy
- Filarete Foundation, Genomic and Bioinformatics Unit, Milano 20139, Italy
| | - Ron T. Gansevoort
- Department of Medicine, University of Groningen, University Medical Center Groningen, 9700 RB Groningen, Netherlands
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany
| | - Torben Hansen
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, 2100 Copenhagen, Denmark
- Faculty of Health Sciences, University of Southern Denmark, 5000 Odense, Denmark
| | - Andrew A. Hicks
- Center for Biomedicine, European Academy Bozen/Bolzano (EURAC), 39100 Bolzano, Italy
- Affiliated Institute of the University of Lübeck, 23562 Lübeck, Germany
| | - Frank Hu
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts 02115, USA
| | - Kristian Hveem
- Department of Public Health and General Practice, Norwegian University of Science and Technology, 7489 Trondheim, Norway
| | - Marjo-Riitta Jarvelin
- Biocenter Oulu, University of Oulu, Oulu FI-90014, Finland
- Unit of Primary Care, Oulu University Hospital, 90029 OYS Oulu, Finland
- Department of Epidemiology and Biostatistics, MRC–PHE Centre for Environment & Health, School of Public Health, Imperial College London W12 0NN, UK
- Faculty of Medicine, Center for Life Course Epidemiology, University of Oulu, P.O.Box 5000, FI-90014 Oulu, Finland
| | - Eero Kajantie
- Department of Health, National Institute for Health and Welfare (THL), FI-00271 Helsinki, Finland
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, FI-00271 Helsinki, Finland
- Children's Hospital, Helsinki University Hospital and University of Helsinki, FI-00029 Helsinki, Finland
- Department of Obstetrics and Gynecology, MRC Oulu, Oulu University Hospital and University of Oulu, FI-90029 Oulu, Finland
| | - Jaspal S. Kooner
- Ealing Hospital NHS Trust, Middlesex UB1 3HW, UK
- Imperial College Healthcare NHS Trust, London W12 0HS, UK
- National Heart and Lung Institute, Imperial College London, London W12 0NN, UK
| | - Diana Kuh
- MRC Unit for Lifelong Health & Ageing at UCL, London WC1B 5JU, UK
| | - Johanna Kuusisto
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, 70210 Kuopio, Finland
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, 70210 Kuopio, Finland
| | - Timo A. Lakka
- Kuopio Research Institute of Exercise Medicine, 70100 Kuopio, Finland
- Department of Physiology, Institute of Biomedicine, University of Eastern Finland, Kuopio Campus, 70210 Kuopio, Finland
| | - Terho Lehtimäki
- Department of Clinical Chemistry, University of Tampere School of Medicine, FI-33014 Tampere, Finland
- Department of Clinical Chemistry, Fimlab Laboratories and School of Medicine, University of Tampere, FI-33520 Tampere, Finland
| | - Andres Metspalu
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
| | - Inger Njølstad
- Department of Community Medicine, Faculty of Health Sciences, University of Tromsø, 9037 Tromsø, Norway
- Department of Clinical Medicine, Faculty of Health Sciences, University of Tromsø, 9037 Tromsø, Norway
| | - Claes Ohlsson
- Department of Internal Medicine and Clinical Nutrition, Centre for Bone and Arthritis Research, Institute of Medicine, Sahlgrenska Academy, University of Gothenburg, 413 45 Gothenburg, Sweden
| | - Albertine J. Oldehinkel
- University of Groningen, University Medical Center Groningen, Interdisciplinary Center Psychopathology and Emotion Regulation, 9700 RB Groningen, The Netherlands
| | - Lyle J. Palmer
- School of Public Health, University of Adelaide, Adelaide, South Australia 5005, Australia
- Robinson Research Institute, University of Adelaide, Adelaide, South Australia 5005, Australia
| | - Oluf Pedersen
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, 2100 Copenhagen, Denmark
| | - Markus Perola
- Department of Health, National Institute for Health and Welfare (THL), FI-00271 Helsinki, Finland
- Estonian Genome Center, University of Tartu, Tartu 51010, Estonia
- Institute for Molecular Medicine Finland, University of Helsinki, FI-00290 Helsinki, Finland
| | - Annette Peters
- Institute of Epidemiology II, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany
- DZHK (German Centre for Cardiovascular Research), partnersite Munich Heart Alliance, 80802 Munich, Germany
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, Washington 98101, USA
- Department of Medicine, University of Washington, Seattle, Washington 98101, USA
- Departments of Epidemiology and Health Services, University of Washington, Seattle, Washington 98101, USA
- Group Health Research Institute, Group Health Cooperative, Seatte, Washington 98101, USA
| | - Hannu Puolijoki
- South Ostrobothnia Central Hospital, Seinäjoki Fi-60220, Finland
| | - Rainer Rauramaa
- Kuopio Research Institute of Exercise Medicine, 70100 Kuopio, Finland
- Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, 70211 Kuopio, Finland
| | - Igor Rudan
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, EH8 9AG Teviot Place, Edinburgh, Scotland
| | - Veikko Salomaa
- Department of Health, National Institute for Health and Welfare (THL), FI-00271 Helsinki, Finland
| | - Peter E. H. Schwarz
- Medical Faculty Carl Gustav Carus, Department of Medicine III, University of Dresden, 01307 Dresden, Germany
- Paul Langerhans Institute Dresden, German Center for Diabetes Research (DZD), Dresden 01307, Germany
| | - Alan R. Shudiner
- Division of Endocrinology, Diabetes & Nutrition, Department of Medicine, Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
- Geriatric Research and Education Clinical Center, Vetrans Administration Medical Center, Baltimore, Maryland 21042, USA
| | - Jan H. Smit
- Department of Psychiatry and EMGO Institute for Health and Care Research, VU University Medical Center, AJ Ernstraat 1887, 1081 HL Amsterdam, The Netherlands
| | - Thorkild I. A. Sørensen
- Faculty of Health and Medical Sciences, Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, University of Copenhagen, 2100 Copenhagen, Denmark
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Bristol BS82BN, UK
- Institute of Preventive Medicine, Bispebjerg and Frederiksberg Hospital, The Capital Region, 2000 Frederiksberg, Denmark
| | - Timothy D. Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London SE1 7EH, UK
| | - Kari Stefansson
- deCODE Genetics, Amgen inc., 101 Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Michael Stumvoll
- University of Leipzig, IFB Adiposity Diseases, 04103 Leipzig, Germany
- Department of Medicine, University of Leipzig, 04103 Leipzig, Germany
| | - Angelo Tremblay
- Department of Kinesiology, Laval University, Québec, Québec, Canada G1V 0A6
| | - Jaakko Tuomilehto
- Diabetes Prevention Unit, National Institute for Health and Welfare, FI-00271 Helsinki, Finland
- Centre for Vascular Prevention, Danube-University Krems, 3500 Krems, Austria
- Diabetes Research Group, King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - André G. Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, 3015GE Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, 3015GE Rotterdam, The Netherlands
| | - Matti Uusitupa
- Department of Public Health and Clinical Nutrition, University of Eastern Finland, 70211 Kuopio, Finland
- Research Unit, Kuopio University Hospital, 70029 Kuopio, Finland
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, 17475 Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research), Partner Site Greifswald, 17475 Greifswald, Germany
| | - Peter Vollenweider
- Department of Internal Medicine, University Hospital Lausanne (CHUV) and University of Lausanne, 1011 Lausanne, Switzerland
| | - Nicholas J. Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
| | - Hugh Watkins
- Division of Cardiovascular Medicine, Radcliffe Department of Medicine, University of Oxford, Oxford OX3 9DU, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
| | - James F. Wilson
- MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, EH4 2XU Edinburgh, Scotland
- Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, EH8 9AG Teviot Place, Edinburgh, Scotland
| | - Eleftheria Zeggini
- Wellcome Trust Sanger Institute, Human Genetics, Hinxton, Cambridge CB10 1SA, UK
| | - Goncalo R. Abecasis
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Michael Boehnke
- Department of Biostatistics, Center for Statistical Genetics, University of Michigan, Ann Arbor, Michigan 48109, USA
| | - Ingrid B. Borecki
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, Missouri 63108, USA
| | - Panos Deloukas
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London EC1M 6BQ, UK
- Wellcome Trust Sanger Institute, Human Genetics, Hinxton CB10 1HH, UK
- Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorders (PACER-HD), King Abdulaziz University, Jeddah 21589, Saudi Arabia
| | - Cornelia M. van Duijn
- Department of Epidemiology, Genetic Epidemiology Unit, Erasmus University Medical Center, 3015GE Rotterdam, The Netherlands
- Center for Medical Systems Biology, 2300 Leiden, The Netherlands
| | - Caroline Fox
- National Heart, Lung, and Blood Institute, the Framingham Heart Study, Framingham, Massachusetts 01702, USA
- Harvard Medical School, Boston, Massachusetts, 02115, USA
| | - Leif C. Groop
- Lund University Diabetes Centre and Department of Clinical Science, Diabetes & Endocrinology Unit, Lund University, 221 00 Malmö, Sweden
- Finnish Institute for Molecular Medicine (FIMM), Helsinki University, 00014 Helsinki, Finland
| | - Iris M. Heid
- Department of Genetic Epidemiology, Institute of Epidemiology and Preventive Medicine, University of Regensburg, 93053 Regensburg, Germany
- Institute of Genetic Epidemiology, Helmholtz Zentrum München, Neuherberg 85764, Germany
| | - David J. Hunter
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts 2142, USA
- Department of Medicine, Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts 02115, USA
- Department of Nutrition, Harvard School of Public Health, Boston, Massachusetts 02115, USA
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts 02115, USA
| | - Robert C. Kaplan
- Department of Epidemiology and Popualtion Health, Albert Einstein College of Medicine, Bronx, New York 10461, USA
| | - Mark I. McCarthy
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford OX3 7BN, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Churchill Hospital, Oxford OX3 7LJ, UK
- Oxford NIHR Biomedical Research Centre, Oxford OX3 7LJ, UK
| | - Kari E. North
- Department of Epidemiology, Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina 27599-7400, USA
| | - Jeffrey R. O'Connell
- Division of Endocrinology, Diabetes & Nutrition, Department of Medicine, Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, Maryland 21201, USA
| | - David Schlessinger
- National Institute on Aging, National Institutes of Health, Bethesda, Maryland 20892, USA
| | - Unnur Thorsteinsdottir
- deCODE Genetics, Amgen inc., 101 Reykjavik, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - David P. Strachan
- Population Health Research Institute, St George's, University of London, London SW17 0RE, UK
| | - Timothy Frayling
- Genetics of Complex Traits, University of Exeter Medical School, University of Exeter, Exeter EX1 2LU, UK
| | - Joel N. Hirschhorn
- Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts 2142, USA
- Divisions of Endocrinology and Genetics and Center for Basic and Translational Obesity Research, Boston Children's Hospital, Boston, Massachusetts 02115, USA
- Department of Genetics, Harvard Medical School, Boston, Massachusetts 02115, USA
- Program in Medical and Population Genetics, Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, Massachusetts 02142, USA
- Division of Endocrinology, Boston Children's Hospital, Boston, Massachusetts 02115, USA
- Divisions of Genetics and Endocrinology and Program in Genomics, Boston's Children's Hospital, Boston, Massachusetts 02115, USA
- Metabolism Initiative, Broad Institute, Cambridge, Massachusetts 02142, USA
| | - Martina Müller-Nurasyid
- Institute of Genetic Epidemiology, Helmholtz Zentrum München-German Research Center for Environmental Health, 85764 Neuherberg, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, 81377 Munich, Germany
- DZHK (German Centre for Cardiovascular Research), partnersite Munich Heart Alliance, 80802 Munich, Germany
- Department of Medicine I, University Hospital Grosshadern, Ludwig-Maximilians-Universität, 81377 Munich, Germany
| | - Ruth J. F. Loos
- The Charles Bronfman Institute for Personalized Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Institute of Metabolic Science, University of Cambridge, Cambridge Biomedical Campus, Cambridge CB2 0QQ, UK
- The Department of Preventive Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
- The Genetics of Obesity and Related Metabolic Traits Program, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
- The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
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49
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Chang YC, Chiu YF, He CT, Sheu WHH, Lin MW, Seto TB, Assimes T, Jou YS, Su L, Lee WJ, Lee PC, Tsai SH, Chuang LM. Genome-wide linkage analysis and regional fine mapping identified variants in the RYR3 gene as a novel quantitative trait locus for circulating adiponectin in Chinese population. Medicine (Baltimore) 2016; 95:e5174. [PMID: 27858853 PMCID: PMC5591101 DOI: 10.1097/md.0000000000005174] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Abstract
Adiponectin is adipocyte-secreted cytokine with potent insulin-sensitizing action in peripheral tissues. The heritability of plasma adiponectin is high in Han Chinese population.To identify genetic loci influencing plasma adiponectin levels in Chinese population, we performed a genome-wide linkage scan in 1949 Chinese participants of the Stanford Asia-Pacific Program for Hypertension and Insulin Resistance family study and mapped a quantitative trail locus located on chromosome 15 at 31 cM (logarithm of odds = 3.04) with 1-logarithm of odds support interval at 24 to 34 cM. Within this mapped region, we further genotyped a total of 68 single-nucleotide polymorphisms in 12 genes. Association analysis revealed that haplotypes composed of single-nucleotide polymorphisms in the ryanodine receptor 3 (RYR3) gene had strongest association with plasma adiponectin. RYR3 haplotypes were also associated with systolic (P = 0.001) and diastolic (P = 7.1 × 10) blood pressure and high-density lipoprotein cholesterol (P = 1.4 × 10). Furthermore, an inverse relationship between expression of RYR3 and adiponectin was observed in human abdominal adipose tissue. In conclusion, a genome-wide linkage scan and regional association fine-mapping identified variants in the RYR3 gene as a quantitative trail locus for plasma adiponectin levels in Chinese population.
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Affiliation(s)
- Yi-Cheng Chang
- Graduate Institute of Medical Genomics and Proteomics, National Taiwan University
- Department of Internal Medicine, National Taiwan University Hospital
- Institute of Biomedical Science, Academia Sinica, Taipei
| | - Yen-Feng Chiu
- Division of Biostatistics and Bioinformatics, Institute of Population Health Sciences, National Health Research Institutes, Zhunan
| | - Chih-Tsueng He
- Department of Internal Medicine, Tri-Service General Hospital Songshan Branch, Taipei
| | - Wayne Huey-Herng Sheu
- Division of Endocrinology and Metabolism, Department of Internal Medicine, Taichung Veterans General Hospital, Taichung
| | - Ming-Wei Lin
- Institute of Public Health, National Yang-Ming University, Taipei, Taiwan
| | - Todd B. Seto
- Center for Outcomes Research and Evaluation, Non-Invasive Cardiology Laboratory, The Queen’s Medical Center, Honolulu, HI
| | | | - Yuh-Shan Jou
- Institute of Biomedical Science, Academia Sinica, Taipei
| | - Lynn Su
- Graduate Institute of Molecular Medicine, National Taiwan University, Taipei
| | - Wei-Jei Lee
- Department of Surgery, Ming-Sheng General Hospital, Taoyuan
| | - Po-Chu Lee
- Department of General Surgery, National Taiwan University Hospital
| | - Shu-Huei Tsai
- Department of Internal Medicine, National Taiwan University Hospital
| | - Lee-Ming Chuang
- Department of Internal Medicine, National Taiwan University Hospital
- Graduate Institute of Molecular Medicine, National Taiwan University, Taipei
- Institute of Preventive Medicine, College of Public Health, National Taiwan University, Taipei, Taiwan
- Correspondence: Lee-Ming Chuang, Department of Internal Medicine, National Taiwan University Hospital, 7 Chung-Shan South Road, Taipei, Taiwan (e-mail: )
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50
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Scheller EL, Burr AA, MacDougald OA, Cawthorn WP. Inside out: Bone marrow adipose tissue as a source of circulating adiponectin. Adipocyte 2016; 5:251-69. [PMID: 27617171 PMCID: PMC5014002 DOI: 10.1080/21623945.2016.1149269] [Citation(s) in RCA: 48] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/20/2015] [Revised: 01/25/2016] [Accepted: 01/27/2016] [Indexed: 02/09/2023] Open
Abstract
The adipocyte-derived hormone adiponectin mediates beneficial cardiometabolic effects, and hypoadiponectinemia is a biomarker for increased metabolic and cardiovascular risk. Indeed, circulating adiponectin decreases in obesity and insulin-resistance, likely because of impaired production from white adipose tissue (WAT). Conversely, lean states such as caloric restriction (CR) are characterized by hyperadiponectinemia, even without increased adiponectin production from WAT. The reasons underlying this paradox have remained elusive, but our recent research suggests that CR-associated hyperadiponectinemia derives from an unexpected source: bone marrow adipose tissue (MAT). Herein, we elaborate on this surprising discovery, including further discussion of potential mechanisms influencing adiponectin production from MAT; additional evidence both for and against our conclusions; and observations suggesting that the relationship between MAT and adiponectin might extend beyond CR. While many questions remain, the burgeoning study of MAT promises to reveal further key insights into MAT biology, both as a source of adiponectin and beyond.
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