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Gromovsky AD, Schugar RC, Brown AL, Helsley RN, Burrows AC, Ferguson D, Zhang R, Sansbury BE, Lee RG, Morton RE, Allende DS, Parks JS, Spite M, Brown JM. Δ-5 Fatty Acid Desaturase FADS1 Impacts Metabolic Disease by Balancing Proinflammatory and Proresolving Lipid Mediators. Arterioscler Thromb Vasc Biol 2018; 38:218-231. [PMID: 29074585 PMCID: PMC5746431 DOI: 10.1161/atvbaha.117.309660] [Citation(s) in RCA: 67] [Impact Index Per Article: 11.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Accepted: 10/08/2017] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Human genetic variants near the FADS (fatty acid desaturase) gene cluster (FADS1-2-3) are strongly associated with cardiometabolic traits including dyslipidemia, fatty liver, type 2 diabetes mellitus, and coronary artery disease. However, mechanisms underlying these genetic associations are unclear. APPROACH AND RESULTS Here, we specifically investigated the physiological role of the Δ-5 desaturase FADS1 in regulating diet-induced cardiometabolic phenotypes by treating hyperlipidemic LDLR (low-density lipoprotein receptor)-null mice with antisense oligonucleotides targeting the selective knockdown of Fads1. Fads1 knockdown resulted in striking reorganization of both ω-6 and ω-3 polyunsaturated fatty acid levels and their associated proinflammatory and proresolving lipid mediators in a highly diet-specific manner. Loss of Fads1 activity promoted hepatic inflammation and atherosclerosis, yet was associated with suppression of hepatic lipogenesis. Fads1 knockdown in isolated macrophages promoted classic M1 activation, whereas suppressing alternative M2 activation programs, and also altered systemic and tissue inflammatory responses in vivo. Finally, the ability of Fads1 to reciprocally regulate lipogenesis and inflammation may rely in part on its role as an effector of liver X receptor signaling. CONCLUSIONS These results position Fads1 as an underappreciated regulator of inflammation initiation and resolution, and suggest that endogenously synthesized arachidonic acid and eicosapentaenoic acid are key determinates of inflammatory disease progression and liver X receptor signaling.
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MESH Headings
- Animals
- Aorta/enzymology
- Aorta/pathology
- Aortic Diseases/enzymology
- Aortic Diseases/genetics
- Aortic Diseases/pathology
- Arachidonic Acid/metabolism
- Atherosclerosis/enzymology
- Atherosclerosis/genetics
- Atherosclerosis/pathology
- Cells, Cultured
- Delta-5 Fatty Acid Desaturase
- Disease Models, Animal
- Dyslipidemias/enzymology
- Dyslipidemias/genetics
- Dyslipidemias/pathology
- Eicosapentaenoic Acid/metabolism
- Fatty Acid Desaturases/genetics
- Fatty Acid Desaturases/metabolism
- Inflammation/enzymology
- Inflammation/genetics
- Inflammation/pathology
- Inflammation Mediators/metabolism
- Lipogenesis
- Liver/metabolism
- Liver X Receptors/metabolism
- Macrophage Activation
- Macrophages, Peritoneal/enzymology
- Macrophages, Peritoneal/pathology
- Mice, Inbred C57BL
- Mice, Knockout
- Oligonucleotides, Antisense/genetics
- Oligonucleotides, Antisense/metabolism
- Plaque, Atherosclerotic
- Receptors, LDL/deficiency
- Receptors, LDL/genetics
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Affiliation(s)
- Anthony D Gromovsky
- From the Department of Cellular and Molecular Medicine, Lerner Research Institute (A.D.G., R.C.S., A.L.B., R.N.H., A.C.B., D.F., R.Z., R.E.M., J.M.B.) and Department of Anatomical Pathology (D.S.A.), Cleveland Clinic, OH; Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (B.E.S., M.S.); Cardiovascular Group, Antisense Drug Discovery, Ionis Pharmaceuticals, Inc, Carlsbad, CA (R.G.L.); and Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC (J.S.P.)
| | - Rebecca C Schugar
- From the Department of Cellular and Molecular Medicine, Lerner Research Institute (A.D.G., R.C.S., A.L.B., R.N.H., A.C.B., D.F., R.Z., R.E.M., J.M.B.) and Department of Anatomical Pathology (D.S.A.), Cleveland Clinic, OH; Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (B.E.S., M.S.); Cardiovascular Group, Antisense Drug Discovery, Ionis Pharmaceuticals, Inc, Carlsbad, CA (R.G.L.); and Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC (J.S.P.)
| | - Amanda L Brown
- From the Department of Cellular and Molecular Medicine, Lerner Research Institute (A.D.G., R.C.S., A.L.B., R.N.H., A.C.B., D.F., R.Z., R.E.M., J.M.B.) and Department of Anatomical Pathology (D.S.A.), Cleveland Clinic, OH; Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (B.E.S., M.S.); Cardiovascular Group, Antisense Drug Discovery, Ionis Pharmaceuticals, Inc, Carlsbad, CA (R.G.L.); and Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC (J.S.P.)
| | - Robert N Helsley
- From the Department of Cellular and Molecular Medicine, Lerner Research Institute (A.D.G., R.C.S., A.L.B., R.N.H., A.C.B., D.F., R.Z., R.E.M., J.M.B.) and Department of Anatomical Pathology (D.S.A.), Cleveland Clinic, OH; Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (B.E.S., M.S.); Cardiovascular Group, Antisense Drug Discovery, Ionis Pharmaceuticals, Inc, Carlsbad, CA (R.G.L.); and Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC (J.S.P.)
| | - Amy C Burrows
- From the Department of Cellular and Molecular Medicine, Lerner Research Institute (A.D.G., R.C.S., A.L.B., R.N.H., A.C.B., D.F., R.Z., R.E.M., J.M.B.) and Department of Anatomical Pathology (D.S.A.), Cleveland Clinic, OH; Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (B.E.S., M.S.); Cardiovascular Group, Antisense Drug Discovery, Ionis Pharmaceuticals, Inc, Carlsbad, CA (R.G.L.); and Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC (J.S.P.)
| | - Daniel Ferguson
- From the Department of Cellular and Molecular Medicine, Lerner Research Institute (A.D.G., R.C.S., A.L.B., R.N.H., A.C.B., D.F., R.Z., R.E.M., J.M.B.) and Department of Anatomical Pathology (D.S.A.), Cleveland Clinic, OH; Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (B.E.S., M.S.); Cardiovascular Group, Antisense Drug Discovery, Ionis Pharmaceuticals, Inc, Carlsbad, CA (R.G.L.); and Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC (J.S.P.)
| | - Renliang Zhang
- From the Department of Cellular and Molecular Medicine, Lerner Research Institute (A.D.G., R.C.S., A.L.B., R.N.H., A.C.B., D.F., R.Z., R.E.M., J.M.B.) and Department of Anatomical Pathology (D.S.A.), Cleveland Clinic, OH; Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (B.E.S., M.S.); Cardiovascular Group, Antisense Drug Discovery, Ionis Pharmaceuticals, Inc, Carlsbad, CA (R.G.L.); and Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC (J.S.P.)
| | - Brian E Sansbury
- From the Department of Cellular and Molecular Medicine, Lerner Research Institute (A.D.G., R.C.S., A.L.B., R.N.H., A.C.B., D.F., R.Z., R.E.M., J.M.B.) and Department of Anatomical Pathology (D.S.A.), Cleveland Clinic, OH; Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (B.E.S., M.S.); Cardiovascular Group, Antisense Drug Discovery, Ionis Pharmaceuticals, Inc, Carlsbad, CA (R.G.L.); and Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC (J.S.P.)
| | - Richard G Lee
- From the Department of Cellular and Molecular Medicine, Lerner Research Institute (A.D.G., R.C.S., A.L.B., R.N.H., A.C.B., D.F., R.Z., R.E.M., J.M.B.) and Department of Anatomical Pathology (D.S.A.), Cleveland Clinic, OH; Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (B.E.S., M.S.); Cardiovascular Group, Antisense Drug Discovery, Ionis Pharmaceuticals, Inc, Carlsbad, CA (R.G.L.); and Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC (J.S.P.)
| | - Richard E Morton
- From the Department of Cellular and Molecular Medicine, Lerner Research Institute (A.D.G., R.C.S., A.L.B., R.N.H., A.C.B., D.F., R.Z., R.E.M., J.M.B.) and Department of Anatomical Pathology (D.S.A.), Cleveland Clinic, OH; Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (B.E.S., M.S.); Cardiovascular Group, Antisense Drug Discovery, Ionis Pharmaceuticals, Inc, Carlsbad, CA (R.G.L.); and Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC (J.S.P.)
| | - Daniela S Allende
- From the Department of Cellular and Molecular Medicine, Lerner Research Institute (A.D.G., R.C.S., A.L.B., R.N.H., A.C.B., D.F., R.Z., R.E.M., J.M.B.) and Department of Anatomical Pathology (D.S.A.), Cleveland Clinic, OH; Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (B.E.S., M.S.); Cardiovascular Group, Antisense Drug Discovery, Ionis Pharmaceuticals, Inc, Carlsbad, CA (R.G.L.); and Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC (J.S.P.)
| | - John S Parks
- From the Department of Cellular and Molecular Medicine, Lerner Research Institute (A.D.G., R.C.S., A.L.B., R.N.H., A.C.B., D.F., R.Z., R.E.M., J.M.B.) and Department of Anatomical Pathology (D.S.A.), Cleveland Clinic, OH; Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (B.E.S., M.S.); Cardiovascular Group, Antisense Drug Discovery, Ionis Pharmaceuticals, Inc, Carlsbad, CA (R.G.L.); and Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC (J.S.P.)
| | - Matthew Spite
- From the Department of Cellular and Molecular Medicine, Lerner Research Institute (A.D.G., R.C.S., A.L.B., R.N.H., A.C.B., D.F., R.Z., R.E.M., J.M.B.) and Department of Anatomical Pathology (D.S.A.), Cleveland Clinic, OH; Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (B.E.S., M.S.); Cardiovascular Group, Antisense Drug Discovery, Ionis Pharmaceuticals, Inc, Carlsbad, CA (R.G.L.); and Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC (J.S.P.)
| | - J Mark Brown
- From the Department of Cellular and Molecular Medicine, Lerner Research Institute (A.D.G., R.C.S., A.L.B., R.N.H., A.C.B., D.F., R.Z., R.E.M., J.M.B.) and Department of Anatomical Pathology (D.S.A.), Cleveland Clinic, OH; Center for Experimental Therapeutics and Reperfusion Injury, Department of Anesthesiology, Perioperative and Pain Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA (B.E.S., M.S.); Cardiovascular Group, Antisense Drug Discovery, Ionis Pharmaceuticals, Inc, Carlsbad, CA (R.G.L.); and Department of Internal Medicine-Section on Molecular Medicine, Wake Forest School of Medicine, Winston-Salem, NC (J.S.P.).
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Morrow NM, Huff MW. Knockdown of Δ-5 Fatty Acid Desaturase Is More Than Just a Fad. Arterioscler Thromb Vasc Biol 2017; 38:6-8. [PMID: 29282245 DOI: 10.1161/atvbaha.117.310382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Affiliation(s)
- Nadya M Morrow
- From the Robarts Research Institute, London, Ontario, Canada; and Department of Medicine and Department of Biochemistry, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, Canada
| | - Murray W Huff
- From the Robarts Research Institute, London, Ontario, Canada; and Department of Medicine and Department of Biochemistry, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, Canada.
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53
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Exposure to Night-Time Traffic Noise, Melatonin-Regulating Gene Variants and Change in Glycemia in Adults. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2017; 14:ijerph14121492. [PMID: 29194408 PMCID: PMC5750910 DOI: 10.3390/ijerph14121492] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/08/2017] [Revised: 11/24/2017] [Accepted: 11/29/2017] [Indexed: 11/16/2022]
Abstract
Traffic noise has been linked to diabetes, with limited understanding of its mechanisms. We hypothesize that night-time road traffic noise (RTN) may impair glucose homeostasis through circadian rhythm disturbances. We prospectively investigated the relationship between residential night-time RTN and subsequent eight-year change in glycosylated hemoglobin (ΔHbA1c) in 3350 participants of the Swiss Cohort Study on Air Pollution and Lung and Heart Diseases in Adults (SAPALDIA), adjusting for diabetes risk factors and air pollution levels. Annual average RTN (Lnight) was assigned to participants in 2001 using validated Swiss noise models. HbA1c was measured in 2002 and 2011 using liquid chromatography. We applied mixed linear models to explore RTN–ΔHbA1c association and its modification by a genetic risk score of six common circadian-related MTNR1B variants (MGRS). A 10 dB difference in RTN was associated with a 0.02% (0.003–0.04%) increase in mean ΔHbA1c in 2142 non-movers. RTN–ΔHbA1c association was modified by MGRS among diabetic participants (Pinteraction = 0.001). A similar trend in non-diabetic participants was non-significant. Among the single variants, we observed strongest interactions with rs10830963, an acknowledged diabetes risk variant also implicated in melatonin profile dysregulation. Night-time RTN may impair glycemic control, especially in diabetic individuals, through circadian rhythm disturbances. Experimental sleep studies are needed to test whether noise control may help individuals to attain optimal glycemic levels.
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54
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Evaluating the glucose raising effect of established loci via a genetic risk score. PLoS One 2017; 12:e0186669. [PMID: 29125842 PMCID: PMC5681259 DOI: 10.1371/journal.pone.0186669] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2016] [Accepted: 10/05/2017] [Indexed: 01/09/2023] Open
Abstract
Recent genome-wide association studies have identified several single nucleotide polymorphisms (SNPs) associated with glucose levels. We tested the hypothesis here whether the cumulative effect of glucose raising SNPs, assessed via a score, is associated with glucose levels. A total of 1,434 participants of Greek descent from the THISEAS study and 1,160 participants form the GOMAP study were included in this analysis. We developed a genetic risk score (GRS), based on the known glucose-raising loci, in order to investigate the cumulative effect of known glucose loci on glucose levels. In the THISEAS study, the GRS score was significantly associated with increased glucose levels (mmol/L) (β ± SE: 0.024 ± 0.004, P = 8.27e-07). The effect of the genetic risk score was also significant in the GOMAP study (β ± SE: 0.011 ± 0.005, P = 0.031). In the meta-analysis of the two studies both scores were significantly associated with higher glucose levels GRS: β ± SE: 0.019 ± 0.003, P = 1.41e-09. Also, variants at the SLC30A8, PROX1, MTNR1B, ADRA2A, G6PC2, LPIN3 loci indicated nominal evidence for association with glucose levels (p < 0.05). We replicate associations of the established glucose raising variants in the Greek population and confirm directional consistency of effects (binomial sign test p = 6.96e-05). We also demonstrate that the cumulative effect of the established glucose loci yielded a significant association with increasing glucose levels.
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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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Millette K, Georgia S. Gene Editing and Human Pluripotent Stem Cells: Tools for Advancing Diabetes Disease Modeling and Beta-Cell Development. Curr Diab Rep 2017; 17:116. [PMID: 28980194 DOI: 10.1007/s11892-017-0947-3] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
PURPOSE OF REVIEW This review will focus on the multiple approaches to gene editing and address the potential use of genetically modified human pluripotent stem cell-derived beta cells (SC-β) as a tool to study human beta-cell development and model their function in diabetes. We will explore how new variations of CRISPR/Cas9 gene editing may accelerate our understanding of beta-cell developmental biology, elucidate novel mechanisms that establish and regulate beta-cell function, and assist in pioneering new therapeutic modalities for treating diabetes. RECENT FINDINGS Improvements in CRISPR/Cas9 target specificity and homology-directed recombination continue to advance its use in engineering stem cells to model and potentially treat disease. We will review how CRISPR/Cas9 gene editing is informing our understanding of beta-cell development and expanding the therapeutic possibilities for treating diabetes and other diseases. Here we focus on the emerging use of gene editing technology, specifically CRISPR/Cas9, as a means of manipulating human gene expression to gain novel insights into the roles of key factors in beta-cell development and function. Taken together, the combined use of SC-β cells and CRISPR/Cas9 gene editing will shed new light on human beta-cell development and function and accelerate our progress towards developing new therapies for patients with diabetes.
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Affiliation(s)
- Katelyn Millette
- Center for Endocrinology, Diabetes and Metabolism, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA
| | - Senta Georgia
- Center for Endocrinology, Diabetes and Metabolism, Department of Pediatrics, Children's Hospital Los Angeles, Los Angeles, CA, USA.
- Departments of Pediatrics and Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
- Developmental Biology and Regenerative Medicine Program, Saban Research Institute of Children's Hospital Los Angeles, Los Angeles, CA, USA.
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Wheeler E, Marenne G, Barroso I. Genetic aetiology of glycaemic traits: approaches and insights. Hum Mol Genet 2017; 26:R172-R184. [PMID: 28977447 PMCID: PMC5886471 DOI: 10.1093/hmg/ddx293] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2017] [Revised: 07/18/2017] [Accepted: 07/21/2017] [Indexed: 12/17/2022] Open
Abstract
Glycaemic traits such as fasting and post-challenge glucose and insulin measures, as well as glycated haemoglobin (HbA1c), are used to diagnose and monitor diabetes. These traits are risk factors for cardiovascular disease even below the diabetic threshold, and their study can additionally yield insights into the pathophysiology of type 2 diabetes. To date, a diverse set of genetic approaches have led to the discovery of over 97 loci influencing glycaemic traits. In this review, we will focus on recent advances in the genetic aetiology of glycaemic traits, and the resulting biological insights. We will provide a brief overview of results ranging from common, to low- and rare-frequency variant-trait association studies, studies leveraging the diversity across populations, and studies harnessing the power of genetic and genomic approaches to gain insights into the biological underpinnings of these traits.
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Affiliation(s)
- Eleanor Wheeler
- Department of Human Genetics, Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Gaëlle Marenne
- Department of Human Genetics, Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge CB10 1SA, UK
| | - Inês Barroso
- Department of Human Genetics, Wellcome Trust Sanger Institute, Genome Campus, Hinxton, Cambridge CB10 1SA, UK
- Metabolic Research Laboratories, Wellcome Trust-MRC Institute of Metabolic Science, University of Cambridge, Cambridge CB2 0QQ, UK
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Marzuillo P, Di Sessa A, Umano GR, Nunziata L, Cirillo G, Perrone L, Miraglia Del Giudice E, Grandone A. Novel association between the nonsynonymous A803G polymorphism of the N-acetyltransferase 2 gene and impaired glucose homeostasis in obese children and adolescents. Pediatr Diabetes 2017; 18:478-484. [PMID: 27481583 DOI: 10.1111/pedi.12417] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/06/2016] [Accepted: 06/24/2016] [Indexed: 01/24/2023] Open
Abstract
BACKGROUND The N-acetyltransferase 2 ( NAT2 ) A803G polymorphism has been associated with decreased insulin sensitivity in a large adult population with the A allele associated with insulin-resistance-related traits. OBJECTIVE Evaluate the association of this polymorphism with anthropometric and metabolic parameters in obese children and adolescents. SUBJECTS A total of 748 obese children and adolescents were enrolled. METHODS Anthropometric and laboratory data were collected. During oral glucose tolerance test, the presence of a possible exaggerated plasma glucose excursion at 1 h (1HPG) or impaired glucose tolerance (IGT) was considered. Homeostasis model assessment, oral disposition index (oDI) and insulinogenic index (IDI) were calculated. Patients were genotyped for the NAT2 A803G polymorphism. RESULTS The prevalence of both IGT and elevated-1HPG was higher in children carrying the A803 allele (P = .02 and P = .03). Moreover, this allele was associated with both oDI and IGI reduction (P = .01). No differences among the NAT2 A803G genotypes for the other parameters were shown. Children homozygous for the A allele presented an odds ratio (OR), to show IGT of 4.9 (P = .01). Children both homozygous and heterozygous for the A allele had higher risk to show elevated-1HPG (OR of 2.7, P = .005; and OR = 2.3, P = .005) compared with patients homozygous for the NAT2 803G allele. CONCLUSIONS NAT2 A803 allele seems to play a role in worsening the destiny of obese children carrying it, predisposing them to elevated-1HPG and IGT and then to a possible future type 2 diabetes mellitus throughout an impairment of pancreatic β-cellular insulin secretion as suggested by oDI and IGI reduction.
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Affiliation(s)
- Pierluigi Marzuillo
- Department of Woman, Child and General and Specialized Surgery, Seconda Università degli Studi di Napoli, Napoli, Italy
| | - Anna Di Sessa
- Department of Woman, Child and General and Specialized Surgery, Seconda Università degli Studi di Napoli, Napoli, Italy
| | - Giuseppina Rosaria Umano
- Department of Woman, Child and General and Specialized Surgery, Seconda Università degli Studi di Napoli, Napoli, Italy
| | - Luigia Nunziata
- Department of Woman, Child and General and Specialized Surgery, Seconda Università degli Studi di Napoli, Napoli, Italy
| | - Grazia Cirillo
- Department of Woman, Child and General and Specialized Surgery, Seconda Università degli Studi di Napoli, Napoli, Italy
| | - Laura Perrone
- Department of Woman, Child and General and Specialized Surgery, Seconda Università degli Studi di Napoli, Napoli, Italy
| | - Emanuele Miraglia Del Giudice
- Department of Woman, Child and General and Specialized Surgery, Seconda Università degli Studi di Napoli, Napoli, Italy
| | - Anna Grandone
- Department of Woman, Child and General and Specialized Surgery, Seconda Università degli Studi di Napoli, Napoli, Italy
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Interaction of insulin-like growth factor-I and insulin resistance-related genetic variants with lifestyle factors on postmenopausal breast cancer risk. Breast Cancer Res Treat 2017; 164:475-495. [PMID: 28478612 DOI: 10.1007/s10549-017-4272-y] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2017] [Accepted: 04/29/2017] [Indexed: 12/31/2022]
Abstract
PURPOSE Genetic variants and traits in metabolic signaling pathways may interact with obesity, physical activity, and exogenous estrogen (E), influencing postmenopausal breast cancer risk, but these inter-related pathways are incompletely understood. METHODS We used 75 single-nucleotide polymorphisms (SNPs) in genes related to insulin-like growth factor-I (IGF-I)/insulin resistance (IR) traits and signaling pathways, and data from 1003 postmenopausal women in Women's Health Initiative Observation ancillary studies. Stratifying via obesity and lifestyle modifiers, we assessed the role of IGF-I/IR traits (fasting IGF-I, IGF-binding protein 3, insulin, glucose, and homeostatic model assessment-insulin resistance) in breast cancer risk as a mediator or influencing factor. RESULTS Seven SNPs in IGF-I and INS genes were associated with breast cancer risk. These associations differed between non-obese/active and obese/inactive women and between exogenous E non-users and users. The mediation effects of IGF-I/IR traits on the relationship between these SNPs and cancer differed between strata, but only roughly 35% of the cancer risk due to the SNPs was mediated by traits. Similarly, carriers of 20 SNPs in PIK3R1, AKT1/2, and MAPK1 genes (signaling pathways-genetic variants) had different associations with breast cancer between strata, and the proportion of the SNP-cancer relationship explained by traits varied 45-50% between the strata. CONCLUSIONS Our findings suggest that IGF-I/IR genetic variants interact with obesity and lifestyle factors, altering cancer risk partially through pathways other than IGF-I/IR traits. Unraveling gene-phenotype-lifestyle interactions will provide data on potential genetic targets in clinical trials for cancer prevention and intervention strategies to reduce breast cancer risk.
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Jung SY, Sobel EM, Papp JC, Zhang ZF. Effect of genetic variants and traits related to glucose metabolism and their interaction with obesity on breast and colorectal cancer risk among postmenopausal women. BMC Cancer 2017; 17:290. [PMID: 28446149 PMCID: PMC5405540 DOI: 10.1186/s12885-017-3284-7] [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] [Received: 05/26/2016] [Accepted: 04/19/2017] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Impaired glucose metabolism-related genetic variants and traits likely interact with obesity and related lifestyle factors, influencing postmenopausal breast and colorectal cancer (CRC), but their interconnected pathways are not fully understood. By stratifying via obesity and lifestyles, we partitioned the total effect of glucose metabolism genetic variants on cancer risk into two putative mechanisms: 1) indirect (risk-associated glucose metabolism genetic variants mediated by glucose metabolism traits) and 2) direct (risk-associated glucose metabolism genetic variants through pathways other than glucose metabolism traits) effects. METHOD Using 16 single-nucleotide polymorphisms (SNPs) associated with glucose metabolism and data from 5379 postmenopausal women in the Women's Health Initiative Harmonized and Imputed Genome-Wide Association Studies, we retrospectively assessed the indirect and direct effects of glucose metabolism-traits (fasting glucose, insulin, and homeostatic model assessment-insulin resistance [HOMA-IR]) using two quantitative tests. RESULTS Several SNPs were associated with breast cancer and CRC risk, and these SNP-cancer associations differed between non-obese and obese women. In both strata, the direct effect of cancer risk associated with the SNP accounted for the majority of the total effect for most SNPs, with roughly 10% of cancer risk due to the SNP that was from an indirect effect mediated by glucose metabolism traits. No apparent differences in the indirect (glucose metabolism-mediated) effects were seen between non-obese and obese women. It is notable that among obese women, 50% of cancer risk was mediated via glucose metabolism trait, owing to two SNPs: in breast cancer, in relation to GCKR through glucose, and in CRC, in relation to DGKB/TMEM195 through HOMA-IR. CONCLUSIONS Our findings suggest that glucose metabolism genetic variants interact with obesity, resulting in altered cancer risk through pathways other than those mediated by glucose metabolism traits.
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Affiliation(s)
- Su Yon Jung
- Translational Sciences Section, Jonsson Comprehensive Cancer Center, School of Nursing, University of California Los Angeles, 700 Tiverton Ave, 3-264 Factor Building, Los Angeles, CA, 90095, USA.
| | - Eric M Sobel
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Jeanette C Papp
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
| | - Zuo-Feng Zhang
- Department of Epidemiology, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
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61
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Boortz KA, Syring KE, Pound LD, Mo H, Bastarache L, Oeser JK, McGuinness OP, Denny JC, O’Brien RM. Effects of G6pc2 deletion on body weight and cholesterol in mice. J Mol Endocrinol 2017; 58:127-139. [PMID: 28122818 PMCID: PMC5380368 DOI: 10.1530/jme-16-0202] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2017] [Accepted: 01/24/2017] [Indexed: 11/08/2022]
Abstract
Genome-wide association study (GWAS) data have linked the G6PC2 gene to variations in fasting blood glucose (FBG). G6PC2 encodes an islet-specific glucose-6-phosphatase catalytic subunit that forms a substrate cycle with the beta cell glucose sensor glucokinase. This cycle modulates the glucose sensitivity of insulin secretion and hence FBG. GWAS data have not linked G6PC2 to variations in body weight but we previously reported that female C57BL/6J G6pc2-knockout (KO) mice were lighter than wild-type littermates on both a chow and high-fat diet. The purpose of this study was to compare the effects of G6pc2 deletion on FBG and body weight in both chow-fed and high-fat-fed mice on two other genetic backgrounds. FBG was reduced in G6pc2 KO mice largely independent of gender, genetic background or diet. In contrast, the effect of G6pc2 deletion on body weight was markedly influenced by these variables. Deletion of G6pc2 conferred a marked protection against diet-induced obesity in male mixed genetic background mice, whereas in 129SvEv mice deletion of G6pc2 had no effect on body weight. G6pc2 deletion also reduced plasma cholesterol levels in a manner dependent on gender, genetic background and diet. An association between G6PC2 and plasma cholesterol was also observed in humans through electronic health record-derived phenotype analyses. These observations suggest that the action of G6PC2 on FBG is largely independent of the influences of environment, modifier genes or epigenetic events, whereas the action of G6PC2 on body weight and cholesterol are influenced by unknown variables.
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Affiliation(s)
- Kayla A. Boortz
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Kristen E. Syring
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Lynley D. Pound
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Huan Mo
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Lisa Bastarache
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - James K. Oeser
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Owen P. McGuinness
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Joshua C. Denny
- Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232
- Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN 37232
| | - Richard M. O’Brien
- Department of Molecular Physiology and Biophysics, Vanderbilt University School of Medicine, Nashville, TN 37232
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62
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Laakso M, Kuusisto J, Stančáková A, Kuulasmaa T, Pajukanta P, Lusis AJ, Collins FS, Mohlke KL, Boehnke M. The Metabolic Syndrome in Men study: a resource for studies of metabolic and cardiovascular diseases. J Lipid Res 2017; 58:481-493. [PMID: 28119442 DOI: 10.1194/jlr.o072629] [Citation(s) in RCA: 119] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2016] [Revised: 01/15/2017] [Indexed: 12/30/2022] Open
Abstract
The Metabolic Syndrome in Men (METSIM) study is a population-based study including 10,197 Finnish men examined in 2005-2010. The aim of the study is to investigate nongenetic and genetic factors associated with the risk of T2D and CVD, and with cardiovascular risk factors. The protocol includes a detailed phenotyping of the participants, an oral glucose tolerance test, fasting laboratory measurements including proton NMR measurements, mass spectometry metabolomics, adipose tissue biopsies from 1,400 participants, and a stool sample. In our ongoing follow-up study, we have, to date, reexamined 6,496 participants. Extensive genotyping and exome sequencing have been performed for essentially all METSIM participants, and >2,000 METSIM participants have been whole-genome sequenced. We have identified several nongenetic markers associated with the development of diabetes and cardiovascular events, and participated in several genetic association studies to identify gene variants associated with diabetes, hyperglycemia, and cardiovascular risk factors. The generation of a phenotype and genotype resource in the METSIM study allows us to proceed toward a "systems genetics" approach, which includes statistical methods to quantitate and integrate intermediate phenotypes, such as transcript, protein, or metabolite levels, to provide a global view of the molecular architecture of complex traits.
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Affiliation(s)
- Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland .,Department of Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland.,Department of Medicine, Kuopio University Hospital, Kuopio, Finland
| | - Alena Stančáková
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Teemu Kuulasmaa
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Päivi Pajukanta
- Departments of Human Genetics David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, CA.,Molecular Biology Institute, University of California, Los Angeles, Los Angeles, CA
| | - Aldons J Lusis
- Departments of Human Genetics David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, CA.,Medicine, David Geffen School of Medicine at University of California, Los Angeles, Los Angeles, CA
| | - Francis S Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, MD
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI
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63
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Gosadi IM. Assessment of the environmental and genetic factors influencing prevalence of metabolic syndrome in Saudi Arabia. Saudi Med J 2017; 37:12-20. [PMID: 26739969 PMCID: PMC4724673 DOI: 10.15537/smj.2016.1.12675] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Abstract
Metabolic syndrome (MS) is a combination of factors that increases the risk of cardiovascular atherosclerotic diseases including diabetes, obesity, dyslipidemia, and high blood pressure. Cardiovascular diseases are one of the leading causes of death in the adult Saudi population where the increase in cardiovascular-related mortality is augmented by the rise in the prevalence of MS. Metabolic syndrome is a multi-factorial disorder influenced by interactions between genetic and environmental components. This review aims to provide a comprehensive assessment of studied environmental and genetic factors explaining the prevalence of MS in the Kingdom of Saudi Arabia. Additionally, this review aims to illustrate factors related to the population genetics of Saudi Arabia, which might explain a proportion of the prevalence of MS.
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Affiliation(s)
- Ibrahim M Gosadi
- Prince Sattam Chair for Epidemiology and Public Health Research, Department of Family and Community Medicine, College of Medicine, King Saud University, Riyadh, Kingdom of Saudi Arabia. E-mail.
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64
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Tarnowski M, Malinowski D, Safranow K, Dziedziejko V, Czerewaty M, Pawlik A. Hematopoietically expressed homeobox (HHEX) gene polymorphism (rs5015480) is associated with increased risk of gestational diabetes mellitus. Clin Genet 2016; 91:843-848. [PMID: 27684496 DOI: 10.1111/cge.12875] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2016] [Revised: 09/21/2016] [Accepted: 09/25/2016] [Indexed: 01/01/2023]
Abstract
Gestational diabetes mellitus (GDM) is a metabolic disorder that occurs during pregnancy. HHEX and PROX1 are genetic loci associated with diabetes mellitus type 2. HHEX and PROX1 play significant roles in carbohydrate intolerance and diabetes because these transcription factors may be involved in the regulation of insulin secretion and in glucose and lipid metabolism. The aim of this study was to examine the association between HHEX (rs5015480) and PROX1 (rs340874) gene polymorphisms and GDM. This study included 204 pregnant women with GDM and 207 pregnant women with the normal glucose tolerance (NGT). The diagnosis of GDM was based on a 75-g oral glucose tolerance test at 24-28 weeks' gestation. There was a statistically significant prevalence of the HHEX rs5015480 CC genotype and C allele among women with GDM (C vs T allele, p = 0.021, odds ratio OR = 1.40, 95% CI: 1.05-1.87). Statistically significant higher increase of body mass and BMI during pregnancy was found in women with the HHEX rs5015480 CC genotype. The results of our study suggest an association between the HHEX gene rs5015480 polymorphism and risk of GDM. The HHEX gene rs5015480 C allele may be a risk allele of GDM that is associated with increased BMI during pregnancy.
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Affiliation(s)
- M Tarnowski
- Department of Physiology, Pomeranian Medical University, Szczecin, Poland
| | - D Malinowski
- Department of Physiology, Pomeranian Medical University, Szczecin, Poland
| | - K Safranow
- Department of Biochemistry and Medical Chemistry, Pomeranian Medical University, Szczecin, Poland
| | - V Dziedziejko
- Department of Biochemistry and Medical Chemistry, Pomeranian Medical University, Szczecin, Poland
| | - M Czerewaty
- Department of Physiology, Pomeranian Medical University, Szczecin, Poland
| | - A Pawlik
- Department of Physiology, Pomeranian Medical University, Szczecin, Poland
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65
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Boortz KA, Syring KE, Lee RA, Dai C, Oeser JK, McGuinness OP, Wang JC, O'Brien RM. G6PC2 Modulates the Effects of Dexamethasone on Fasting Blood Glucose and Glucose Tolerance. Endocrinology 2016; 157:4133-4145. [PMID: 27653037 PMCID: PMC5086534 DOI: 10.1210/en.2016-1678] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
The glucose-6-phosphatase catalytic subunit 2 (G6PC2) gene encodes an islet-specific glucose-6-phosphatase catalytic subunit. G6PC2 forms a substrate cycle with glucokinase that determines the glucose sensitivity of insulin secretion. Consequently, deletion of G6pc2 lowers fasting blood glucose (FBG) without affecting fasting plasma insulin. Although chronic elevation of FBG is detrimental to health, glucocorticoids induce G6PC2 expression, suggesting that G6PC2 evolved to transiently modulate FBG under conditions of glucocorticoid-related stress. We show, using competition and mutagenesis experiments, that the synthetic glucocorticoid dexamethasone (Dex) induces G6PC2 promoter activity through a mechanism involving displacement of the islet-enriched transcription factor MafA by the glucocorticoid receptor. The induction of G6PC2 promoter activity by Dex is modulated by a single nucleotide polymorphism, previously linked to altered FBG in humans, that affects FOXA2 binding. A 5-day repeated injection paradigm was used to examine the chronic effect of Dex on FBG and glucose tolerance in wild-type (WT) and G6pc2 knockout mice. Acute Dex treatment only induces G6pc2 expression in 129SvEv but not C57BL/6J mice, but this chronic treatment induced G6pc2 expression in both. In 6-hour fasted C57BL/6J WT mice, Dex treatment lowered FBG and improved glucose tolerance, with G6pc2 deletion exacerbating the decrease in FBG and enhancing the improvement in glucose tolerance. In contrast, in 24-hour fasted C57BL/6J WT mice, Dex treatment raised FBG but still improved glucose tolerance, with G6pc2 deletion limiting the increase in FBG and enhancing the improvement in glucose tolerance. These observations demonstrate that G6pc2 modulates the complex effects of Dex on both FBG and glucose tolerance.
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Affiliation(s)
- Kayla A Boortz
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
| | - Kristen E Syring
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
| | - Rebecca A Lee
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
| | - Chunhua Dai
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
| | - James K Oeser
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
| | - Owen P McGuinness
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
| | - Jen-Chywan Wang
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
| | - Richard M O'Brien
- Departments of Molecular Physiology and Biophysics (K.A.B., K.E.S., J.K.O., O.P.M., R.M.O.) and Medicine (C.D.), Vanderbilt University School of Medicine, Nashville, Tennessee 37232; and Department of Nutritional Sciences and Toxicology (R.A.L., J.-C.W.), University of California at Berkeley, Berkeley, California 94720
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66
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Walford GA, Gustafsson S, Rybin D, Stančáková A, Chen H, Liu CT, Hong J, Jensen RA, Rice K, Morris AP, Mägi R, Tönjes A, Prokopenko I, Kleber ME, Delgado G, Silbernagel G, Jackson AU, Appel EV, Grarup N, Lewis JP, Montasser ME, Landenvall C, Staiger H, Luan J, Frayling TM, Weedon MN, Xie W, Morcillo S, Martínez-Larrad MT, Biggs ML, Chen YDI, Corbaton-Anchuelo A, Færch K, Gómez-Zumaquero JM, Goodarzi MO, Kizer JR, Koistinen HA, Leong A, Lind L, Lindgren C, Machicao F, Manning AK, Martín-Núñez GM, Rojo-Martínez G, Rotter JI, Siscovick DS, Zmuda JM, Zhang Z, Serrano-Rios M, Smith U, Soriguer F, Hansen T, Jørgensen TJ, Linnenberg A, Pedersen O, Walker M, Langenberg C, Scott RA, Wareham NJ, Fritsche A, Häring HU, Stefan N, Groop L, O'Connell JR, Boehnke M, Bergman RN, Collins FS, Mohlke KL, Tuomilehto J, März W, Kovacs P, Stumvoll M, Psaty BM, Kuusisto J, Laakso M, Meigs JB, Dupuis J, Ingelsson E, Florez JC. Genome-Wide Association Study of the Modified Stumvoll Insulin Sensitivity Index Identifies BCL2 and FAM19A2 as Novel Insulin Sensitivity Loci. Diabetes 2016; 65:3200-11. [PMID: 27416945 PMCID: PMC5033262 DOI: 10.2337/db16-0199] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/08/2016] [Accepted: 07/05/2016] [Indexed: 01/19/2023]
Abstract
Genome-wide association studies (GWAS) have found few common variants that influence fasting measures of insulin sensitivity. We hypothesized that a GWAS of an integrated assessment of fasting and dynamic measures of insulin sensitivity would detect novel common variants. We performed a GWAS of the modified Stumvoll Insulin Sensitivity Index (ISI) within the Meta-Analyses of Glucose and Insulin-Related Traits Consortium. Discovery for genetic association was performed in 16,753 individuals, and replication was attempted for the 23 most significant novel loci in 13,354 independent individuals. Association with ISI was tested in models adjusted for age, sex, and BMI and in a model analyzing the combined influence of the genotype effect adjusted for BMI and the interaction effect between the genotype and BMI on ISI (model 3). In model 3, three variants reached genome-wide significance: rs13422522 (NYAP2; P = 8.87 × 10(-11)), rs12454712 (BCL2; P = 2.7 × 10(-8)), and rs10506418 (FAM19A2; P = 1.9 × 10(-8)). The association at NYAP2 was eliminated by conditioning on the known IRS1 insulin sensitivity locus; the BCL2 and FAM19A2 associations were independent of known cardiometabolic loci. In conclusion, we identified two novel loci and replicated known variants associated with insulin sensitivity. Further studies are needed to clarify the causal variant and function at the BCL2 and FAM19A2 loci.
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Affiliation(s)
- Geoffrey A Walford
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA Department of Medicine, Harvard Medical School, Boston, MA
| | | | - Denis Rybin
- Data Coordinating Center, Boston University School of Public Health, Boston, MA
| | - Alena Stančáková
- University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Han Chen
- Department of Biostatistics, Boston University School of Public Health, Boston, MA Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Jaeyoung Hong
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Richard A Jensen
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA Department of Medicine, University of Washington, Seattle, WA
| | - Ken Rice
- Department of Biostatistics, University of Washington, Seattle, WA
| | - Andrew P Morris
- Department of Biostatistics, University of Liverpool, Liverpool, U.K. Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K
| | - Reedik Mägi
- Estonian Genome Center, University of Tartu, Tartu, Estonia
| | - Anke Tönjes
- Department of Medicine, University of Leipzig, Leipzig, Germany
| | - Inga Prokopenko
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K. Department of Genomics of Common Disease, Imperial College London, London, U.K. Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, U.K
| | - Marcus E Kleber
- Fifth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Graciela Delgado
- Fifth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany
| | - Günther Silbernagel
- Division of Angiology, Department of Internal Medicine, Medical University of Graz, Graz, Austria
| | - Anne U Jackson
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI
| | - Emil V Appel
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Joshua P Lewis
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - May E Montasser
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Claes Landenvall
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Malmö, Sweden Department of Immunology, Genetics and Pathology, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Harald Staiger
- Department of Internal Medicine, Division of Endocrinology and Diabetology, Angiology, Nephrology, and Clinical Chemistry, University Hospital Tübingen, Tübingen, Germany German Center for Diabetes Research (DZD), Tübingen, Germany Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich, University of Tübingen, Tübingen, Germany
| | - Jian'an Luan
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, U.K
| | | | | | - Weijia Xie
- University of Exeter Medical School, Exeter, U.K
| | - Sonsoles Morcillo
- CIBER Pathophysiology of Obesity and Nutrition, Madrid, Spain Department of Endocrinology and Nutrition, Hospital Regional Universitario de Málaga, Málaga, Spain
| | - María Teresa Martínez-Larrad
- Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | - Mary L Biggs
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA Department of Biostatistics, University of Washington, Seattle, WA
| | - Yii-Der Ida Chen
- Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, CA
| | - Arturo Corbaton-Anchuelo
- Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | | | - Juan Miguel Gómez-Zumaquero
- Instituto de Investigación Biomédica de Málaga (IBIMA), Málaga, Spain Sequencing and Genotyping Platform, Hospital Carlos Haya de Málaga, Málaga, Spain
| | - Mark O Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Jorge R Kizer
- Department of Medicine, Albert Einstein College of Medicine and Montefiore Medical Center, Bronx, NY Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY
| | - Heikki A Koistinen
- Department of Health, National Institute for Health and Welfare, Helsinki, Finland Minerva Foundation Institute for Medical Research, Biomedicum 2U, Helsinki, Finland Department of Medicine and Abdominal Center: Endocrinology, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Aaron Leong
- Department of Medicine, Harvard Medical School, Boston, MA Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA
| | - Lars Lind
- Department of Medical Sciences, Uppsala University, Uppsala, Sweden
| | - Cecilia Lindgren
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K. Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA
| | - Fausto Machicao
- German Center for Diabetes Research (DZD), Tübingen, Germany Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich, University of Tübingen, Tübingen, Germany
| | - Alisa K Manning
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA Department of Medicine, Harvard Medical School, Boston, MA Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA
| | - Gracia María Martín-Núñez
- Department of Endocrinology and Nutrition, Hospitales Regional Universitario y Virgen de la Victoria de Málaga, Málaga, Spain
| | - Gemma Rojo-Martínez
- Department of Endocrinology and Nutrition, Hospital Regional Universitario de Málaga, Málaga, Spain Instituto de Investigación Biomédica de Málaga (IBIMA), Málaga, Spain CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, Spain
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Departments of Pediatrics and Medicine, LABioMed at Harbor-UCLA Medical Center, Torrance, CA
| | - David S Siscovick
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA Department of Medicine, University of Washington, Seattle, WA Department of Epidemiology, University of Washington, Seattle, WA The New York Academy of Medicine, New York, NY
| | - Joseph M Zmuda
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA
| | - Zhongyang Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY Icahn Institute for Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, NY
| | - Manuel Serrano-Rios
- Spanish Biomedical Research Centre in Diabetes and Associated Metabolic Disorders (CIBERDEM), Instituto de Investigación Sanitaria del Hospital Clínico San Carlos (IdISSC), Madrid, Spain
| | - Ulf Smith
- The Lundberg Laboratory for Diabetes Research, Department of Molecular and Clinical Medicine, Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Federico Soriguer
- Department of Endocrinology and Nutrition, Hospital Regional Universitario de Málaga, Málaga, Spain Instituto de Investigación Biomédica de Málaga (IBIMA), Málaga, Spain CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, Spain
| | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben J Jørgensen
- Department of Public Health, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark Faculty of Medicine, Aalborg University, Aalborg, Denmark Research Center for Prevention and Health, The Capital Region of Denmark, Copenhagen, Denmark
| | - Allan Linnenberg
- Research Center for Prevention and Health, The Capital Region of Denmark, Copenhagen, Denmark Department of Clinical Experimental Research, Rigshospitalet, Glostrup, Denmark Department of Clinical Medicine, Faculty of Health and Medical Science, University of Copenhagen, Copenhagen, Denmark
| | - Oluf Pedersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Mark Walker
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, U.K
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, U.K
| | - Robert A Scott
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, U.K
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge School of Clinical Medicine, Cambridge, U.K
| | - Andreas Fritsche
- Department of Internal Medicine, Division of Endocrinology and Diabetology, Angiology, Nephrology, and Clinical Chemistry, University Hospital Tübingen, Tübingen, Germany German Center for Diabetes Research (DZD), Tübingen, Germany Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich, University of Tübingen, Tübingen, Germany
| | - Hans-Ulrich Häring
- Department of Internal Medicine, Division of Endocrinology and Diabetology, Angiology, Nephrology, and Clinical Chemistry, University Hospital Tübingen, Tübingen, Germany German Center for Diabetes Research (DZD), Tübingen, Germany Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich, University of Tübingen, Tübingen, Germany
| | - Norbert Stefan
- Department of Internal Medicine, Division of Endocrinology and Diabetology, Angiology, Nephrology, and Clinical Chemistry, University Hospital Tübingen, Tübingen, Germany German Center for Diabetes Research (DZD), Tübingen, Germany Institute for Diabetes Research and Metabolic Diseases, Helmholtz Center Munich, University of Tübingen, Tübingen, Germany
| | - Leif Groop
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Malmö, Sweden Finnish Institute for Molecular Medicine, University of Helsinki, Helsinki, Finland
| | - Jeff R O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, University of Maryland School of Medicine, Baltimore, MD Program for Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Michael Boehnke
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, Ann Arbor, MI
| | - Richard N Bergman
- Diabetes and Obesity Research Institute, Cedars-Sinai Medical Center, Los Angeles, CA
| | - Francis S Collins
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD
| | - Karen L Mohlke
- Department of Genetics, University of North Carolina, Chapel Hill, NC
| | - Jaakko Tuomilehto
- Chronic Disease Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland Centre for Vascular Prevention, Danube-University Krems, Krems, Austria Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia Dasman Diabetes Institute, Dasman, Kuwait
| | - Winfried März
- Fifth Department of Medicine, Medical Faculty Mannheim, Heidelberg University, Heidelberg, Germany Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Graz, Austria Synlab Academy, Synlab Services GmbH, Mannheim and Augsburg, Germany
| | - Peter Kovacs
- Integrated Research and Treatment (IFB) Center AdiposityDiseases, University of Leipzig, Leipzig, Germany
| | | | - Bruce M Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA Department of Medicine, University of Washington, Seattle, WA Epidemiology and Health Services, University of Washington, Seattle, WA Group Health Research Institute, Seattle, WA Group Health Cooperation, Seattle, WA
| | - Johanna Kuusisto
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - James B Meigs
- Department of Medicine, Harvard Medical School, Boston, MA Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA Broad Institute of the Massachusetts Institute of Technology and Harvard University, Cambridge, MA
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA Framingham Heart Study, National Heart, Lung, and Blood Institute, Framingham, MA
| | - Erik Ingelsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden Department of Medicine, Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA
| | - Jose C Florez
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA Department of Medicine, Harvard Medical School, Boston, MA
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Stefan N, Fritsche A, Schick F, Häring HU. Phenotypes of prediabetes and stratification of cardiometabolic risk. Lancet Diabetes Endocrinol 2016; 4:789-798. [PMID: 27185609 DOI: 10.1016/s2213-8587(16)00082-6] [Citation(s) in RCA: 143] [Impact Index Per Article: 17.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/06/2016] [Revised: 02/17/2016] [Accepted: 02/26/2016] [Indexed: 02/07/2023]
Abstract
Prediabetes is associated with increased risks of type 2 diabetes, cardiovascular disease, dementia, and cancer, and its prevalence is increasing worldwide. Lifestyle and pharmacological interventions in people with prediabetes can prevent the development of diabetes and possibly cardiovascular disease. However, prediabetes is a highly heterogeneous metabolic state, both with respect to its pathogenesis and prediction of disease. Improved understanding of these features and precise phenotyping of prediabetes could help to improve stratification of disease risk. In this Personal View, we focus on the extreme metabolic phenotypes of metabolically healthy obesity and metabolically unhealthy normal weight, insulin secretion failure, insulin resistance, visceral obesity, and non-alcoholic fatty liver disease. We present new analyses aimed at improving characterisation of phenotypes in lean, overweight, and obese people with prediabetes. We discuss evidence from lifestyle intervention studies to explore whether these phenotypes can also be used for individualised prediction and prevention of cardiometabolic diseases.
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Affiliation(s)
- Norbert Stefan
- Department of Internal Medicine IV, University Hospital Tübingen, Tübingen, Germany; Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Centre Munich at the University of Tübingen, Tübingen, Germany; German Centre for Diabetes Research (DZD), Tübingen, Germany.
| | - Andreas Fritsche
- Department of Internal Medicine IV, University Hospital Tübingen, Tübingen, Germany; Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Centre Munich at the University of Tübingen, Tübingen, Germany; German Centre for Diabetes Research (DZD), Tübingen, Germany
| | - Fritz Schick
- Section of Experimental Radiology, University Hospital Tübingen, Tübingen, Germany; Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Centre Munich at the University of Tübingen, Tübingen, Germany; German Centre for Diabetes Research (DZD), Tübingen, Germany
| | - Hans-Ulrich Häring
- Department of Internal Medicine IV, University Hospital Tübingen, Tübingen, Germany; Institute of Diabetes Research and Metabolic Diseases (IDM) of the Helmholtz Centre Munich at the University of Tübingen, Tübingen, Germany; German Centre for Diabetes Research (DZD), Tübingen, Germany
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68
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Mehta ZB, Fine N, Pullen TJ, Cane MC, Hu M, Chabosseau P, Meur G, Velayos-Baeza A, Monaco AP, Marselli L, Marchetti P, Rutter GA. Changes in the expression of the type 2 diabetes-associated gene VPS13C in the β-cell are associated with glucose intolerance in humans and mice. Am J Physiol Endocrinol Metab 2016; 311:E488-507. [PMID: 27329800 PMCID: PMC5005967 DOI: 10.1152/ajpendo.00074.2016] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/26/2016] [Accepted: 06/20/2016] [Indexed: 12/31/2022]
Abstract
Single nucleotide polymorphisms (SNPs) close to the VPS13C, C2CD4A and C2CD4B genes on chromosome 15q are associated with impaired fasting glucose and increased risk of type 2 diabetes. eQTL analysis revealed an association between possession of risk (C) alleles at a previously implicated causal SNP, rs7163757, and lowered VPS13C and C2CD4A levels in islets from female (n = 40, P < 0.041) but not from male subjects. Explored using promoter-reporter assays in β-cells and other cell lines, the risk variant at rs7163757 lowered enhancer activity. Mice deleted for Vps13c selectively in the β-cell were generated by crossing animals bearing a floxed allele at exon 1 to mice expressing Cre recombinase under Ins1 promoter control (Ins1Cre). Whereas Vps13c(fl/fl):Ins1Cre (βVps13cKO) mice displayed normal weight gain compared with control littermates, deletion of Vps13c had little effect on glucose tolerance. Pancreatic histology revealed no significant change in β-cell mass in KO mice vs. controls, and glucose-stimulated insulin secretion from isolated islets was not altered in vitro between control and βVps13cKO mice. However, a tendency was observed in female null mice for lower insulin levels and β-cell function (HOMA-B) in vivo. Furthermore, glucose-stimulated increases in intracellular free Ca(2+) were significantly increased in islets from female KO mice, suggesting impaired Ca(2+) sensitivity of the secretory machinery. The present data thus provide evidence for a limited role for changes in VPS13C expression in conferring altered disease risk at this locus, particularly in females, and suggest that C2CD4A may also be involved.
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Affiliation(s)
- Zenobia B Mehta
- Section of Cell Biology and Functional Genomics, Imperial College London, London, United Kingdom
| | - Nicholas Fine
- Section of Cell Biology and Functional Genomics, Imperial College London, London, United Kingdom
| | - Timothy J Pullen
- Section of Cell Biology and Functional Genomics, Imperial College London, London, United Kingdom
| | - Matthew C Cane
- Section of Cell Biology and Functional Genomics, Imperial College London, London, United Kingdom
| | - Ming Hu
- Section of Cell Biology and Functional Genomics, Imperial College London, London, United Kingdom
| | - Pauline Chabosseau
- Section of Cell Biology and Functional Genomics, Imperial College London, London, United Kingdom
| | - Gargi Meur
- Section of Cell Biology and Functional Genomics, Imperial College London, London, United Kingdom
| | | | - Anthony P Monaco
- Wellcome Trust Centre for Human Genetics, Oxford, United Kingdom; and
| | - Lorella Marselli
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Piero Marchetti
- Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
| | - Guy A Rutter
- Section of Cell Biology and Functional Genomics, Imperial College London, London, United Kingdom;
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Beer NL, Gloyn AL. Genome-edited human stem cell-derived beta cells: a powerful tool for drilling down on type 2 diabetes GWAS biology. F1000Res 2016; 5:F1000 Faculty Rev-1711. [PMID: 27508066 PMCID: PMC4955023 DOI: 10.12688/f1000research.8682.1] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 07/11/2016] [Indexed: 12/30/2022] Open
Abstract
Type 2 diabetes (T2D) is a disease of pandemic proportions, one defined by a complex aetiological mix of genetic, epigenetic, environmental, and lifestyle risk factors. Whilst the last decade of T2D genetic research has identified more than 100 loci showing strong statistical association with disease susceptibility, our inability to capitalise upon these signals reflects, in part, a lack of appropriate human cell models for study. This review discusses the impact of two complementary, state-of-the-art technologies on T2D genetic research: the generation of stem cell-derived, endocrine pancreas-lineage cells and the editing of their genomes. Such models facilitate investigation of diabetes-associated genomic perturbations in a physiologically representative cell context and allow the role of both developmental and adult islet dysfunction in T2D pathogenesis to be investigated. Accordingly, we interrogate the role that patient-derived induced pluripotent stem cell models are playing in understanding cellular dysfunction in monogenic diabetes, and how site-specific nucleases such as the clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 system are helping to confirm genes crucial to human endocrine pancreas development. We also highlight the novel biology gleaned in the absence of patient lines, including an ability to model the whole phenotypic spectrum of diabetes phenotypes occurring both in utero and in adult cells, interrogating the non-coding 'islet regulome' for disease-causing perturbations, and understanding the role of other islet cell types in aberrant glycaemia. This article aims to reinforce the importance of investigating T2D signals in cell models reflecting appropriate species, genomic context, developmental time point, and tissue type.
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Affiliation(s)
- Nicola L. Beer
- Oxford Centre for Diabetes Endocrinology and Metabolism, Churchill Hospital, Oxford, UK,
| | - Anna L. Gloyn
- Oxford Centre for Diabetes Endocrinology and Metabolism, Churchill Hospital, Oxford, UK,Wellcome Trust Centre for Human Genetics, Oxford, UK,Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, UK
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Abstract
As with other complex diseases, unbiased association studies followed by physiological and experimental characterization have for years formed a paradigm for identifying genes or processes of relevance to type 2 diabetes mellitus (T2D). Recent large-scale common and rare variant genome-wide association studies (GWAS) suggest that substantially larger association studies are needed to identify most T2D loci in the population. To hasten clinical translation of genetic discoveries, new paradigms are also required to aid specialized investigation of nascent hypotheses. We argue for an integrated T2D knowledgebase, designed for a worldwide community to access aggregated large-scale genetic data sets, as one paradigm to catalyse convergence of these efforts.
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71
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Jung SY, Sobel EM, Papp JC, Crandall CJ, Fu AN, Zhang ZF. Obesity and associated lifestyles modify the effect of glucose metabolism-related genetic variants on impaired glucose homeostasis among postmenopausal women. Genet Epidemiol 2016; 40:520-30. [PMID: 27377425 DOI: 10.1002/gepi.21991] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2015] [Revised: 05/24/2016] [Accepted: 06/05/2016] [Indexed: 01/19/2023]
Abstract
PURPOSE Impaired glucose metabolism-related genetic variants likely interact with obesity-modifiable factors in response to glucose intolerance, yet their interconnected pathways have not been fully characterized. METHODS With data from 1,027 postmenopausal participants of the Genomics and Randomized Trials Network study and 15 single-nucleotide polymorphisms (SNPs) associated with glucose homeostasis, we assessed whether obesity, physical activity, and high dietary fat intake interact with the SNP-glucose variations. We used regression analysis plus stratification and graphic approaches. RESULTS Across carriers of the 15 SNPs, fasting levels of glucose, insulin, and homeostatic model assessment-insulin resistance (HOMA-IR) were higher in obese, inactive, and high fat-diet women than in their respective counterparts. Carriers within subgroups differently demonstrated the direction and/or magnitude of the variants' effect on glucose-relevant traits. Variants in GCKR, GCK, DGKB/TMEM195 (P for interactions = 0.02, 0.02, and 0.01), especially, showed interactions with obesity: obese, inactive, and high fat-diet women had greater increases in fasting glucose, insulin, and HOMA-IR levels. Obese carriers at TCF7L2 variant had greater increases in fasting glucose levels than nonobese carriers (P for interaction = 0.04), whereas active women had greater decreases in insulin and HOMA-IR levels than inactive women (P for interaction = 0.02 in both levels). CONCLUSIONS Our data support the important role of obesity in modifying glucose homeostasis in response to glucose metabolism-relevant variants. These findings may inform research on the role of glucose homeostasis in the etiology of chronic disease and the development of intervention strategies to reduce risk in postmenopausal women.
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Affiliation(s)
- Su Yon Jung
- Translational Sciences Section, Jonsson Comprehensive Cancer Center, School of Nursing, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Eric M Sobel
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Jeanette C Papp
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Carolyn J Crandall
- Division of General Internal Medicine, Department of Internal Medicine, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Alan N Fu
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, United States of America
| | - Zuo-Feng Zhang
- Department of Epidemiology, Fielding School of Public Health, University of California, Los Angeles, Los Angeles, California, United States of America
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72
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Deelen J, van den Akker EB, Trompet S, van Heemst D, Mooijaart SP, Slagboom PE, Beekman M. Employing biomarkers of healthy ageing for leveraging genetic studies into human longevity. Exp Gerontol 2016; 82:166-74. [PMID: 27374409 DOI: 10.1016/j.exger.2016.06.013] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2016] [Revised: 05/27/2016] [Accepted: 06/27/2016] [Indexed: 01/03/2023]
Abstract
Genetic studies have thus far identified a limited number of loci associated with human longevity by applying age at death or survival up to advanced ages as phenotype. As an alternative approach, one could first try to identify biomarkers of healthy ageing and the genetic variants associated with these traits and subsequently determine the association of these variants with human longevity. In the present study, we used this approach by testing whether the 35 baseline serum parameters measured in the Leiden Longevity Study (LLS) meet the proposed criteria for a biomarker of healthy ageing. The LLS consists of 421 families with long-lived siblings of European descent, who were recruited together with their offspring and the spouses of the offspring (controls). To test the four criteria for a biomarker of healthy ageing in the LLS, we determined the association of the serum parameters with chronological age, familial longevity, general practitioner-reported general health, and mortality. Out of the 35 serum parameters, we identified glucose, insulin, and triglycerides as biomarkers of healthy ageing, meeting all four criteria in the LLS. We subsequently showed that the genetic variants previously associated with these parameters are significantly enriched in the largest genome-wide association study for human longevity. In conclusion, we showed that biomarkers of healthy ageing can be used to leverage genetic studies into human longevity. We identified several genetic variants influencing the variation in glucose, insulin and triglycerides that contribute to human longevity.
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Affiliation(s)
- Joris Deelen
- Department of Molecular Epidemiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; Max Planck Institute for Biology of Ageing, P.O. Box 41 06 23, 50866 Cologne, Germany.
| | - Erik B van den Akker
- Department of Molecular Epidemiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; Delft Bioinformatics Lab, Delft University of Technology, P.O. Box 5031, 2600 GA Delft, The Netherlands.
| | - Stella Trompet
- Department of Gerontology and Geriatrics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands; Department of Cardiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands.
| | - Diana van Heemst
- Department of Gerontology and Geriatrics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands.
| | - Simon P Mooijaart
- Department of Gerontology and Geriatrics, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands.
| | - P Eline Slagboom
- Department of Molecular Epidemiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands.
| | - Marian Beekman
- Department of Molecular Epidemiology, Leiden University Medical Center, P.O. Box 9600, 2300 RC Leiden, The Netherlands.
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Samson SL, Garber AJ. Prevention of type 2 Diabetes Mellitus: Potential of pharmacological agents. Best Pract Res Clin Endocrinol Metab 2016; 30:357-71. [PMID: 27432071 DOI: 10.1016/j.beem.2016.06.005] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
People with impaired glucose tolerance or impaired fasting glucose, or "pre-diabetes", are at high risk for progression to type 2 diabetes, as are those with metabolic syndrome or a history of gestational diabetes. Both glucose-lowering and anti-obesity pharmacotherapies have been studied to determine if the onset of type 2 diabetes can be delayed or prevented. Here we review the available data in the field. The most common theme is the reduction in insulin resistance, such as with weight loss, decreasing demands on the beta cell to improve insulin secretion and prolong its function. Overall, therapies which decrease diabetes incidence in high-risk populations delay the onset of diabetes but do not correct the underlying beta cell defect.
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Affiliation(s)
- Susan L Samson
- Department of Medicine, Baylor College of Medicine, One Baylor Plaza, ABBR R615, Houston, TX 77030, USA.
| | - Alan J Garber
- Department of Medicine, Baylor College of Medicine, One Baylor Plaza- BCM 620, Houston, TX 77030, USA; Department of Molecular and Cellular Biology, Baylor College of Medicine, One Baylor Plaza- BCM 620, Houston, TX 77030, USA; Department of Biochemistry and Molecular Biology, Baylor College of Medicine, One Baylor Plaza- BCM 620, Houston, TX 77030, USA
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74
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Yang Y, Chan L. Monogenic Diabetes: What It Teaches Us on the Common Forms of Type 1 and Type 2 Diabetes. Endocr Rev 2016; 37:190-222. [PMID: 27035557 PMCID: PMC4890265 DOI: 10.1210/er.2015-1116] [Citation(s) in RCA: 84] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
To date, more than 30 genes have been linked to monogenic diabetes. Candidate gene and genome-wide association studies have identified > 50 susceptibility loci for common type 1 diabetes (T1D) and approximately 100 susceptibility loci for type 2 diabetes (T2D). About 1-5% of all cases of diabetes result from single-gene mutations and are called monogenic diabetes. Here, we review the pathophysiological basis of the role of monogenic diabetes genes that have also been found to be associated with common T1D and/or T2D. Variants of approximately one-third of monogenic diabetes genes are associated with T2D, but not T1D. Two of the T2D-associated monogenic diabetes genes-potassium inward-rectifying channel, subfamily J, member 11 (KCNJ11), which controls glucose-stimulated insulin secretion in the β-cell; and peroxisome proliferator-activated receptor γ (PPARG), which impacts multiple tissue targets in relation to inflammation and insulin sensitivity-have been developed as major antidiabetic drug targets. Another monogenic diabetes gene, the preproinsulin gene (INS), is unique in that INS mutations can cause hyperinsulinemia, hyperproinsulinemia, neonatal diabetes mellitus, one type of maturity-onset diabetes of the young (MODY10), and autoantibody-negative T1D. Dominant heterozygous INS mutations are the second most common cause of permanent neonatal diabetes. Moreover, INS gene variants are strongly associated with common T1D (type 1a), but inconsistently with T2D. Variants of the monogenic diabetes gene Gli-similar 3 (GLIS3) are associated with both T1D and T2D. GLIS3 is a key transcription factor in insulin production and β-cell differentiation during embryonic development, which perturbation forms the basis of monogenic diabetes as well as its association with T1D. GLIS3 is also required for compensatory β-cell proliferation in adults; impairment of this function predisposes to T2D. Thus, monogenic forms of diabetes are invaluable "human models" that have contributed to our understanding of the pathophysiological basis of common T1D and T2D.
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Affiliation(s)
- Yisheng Yang
- Division of Endocrinology (Y.Y.), Department of Medicine, MetroHealth Medical Center, Case Western Reserve University, Cleveland, Ohio 44109; and Diabetes and Endocrinology Research Center (L.C.), Division of Diabetes, Endocrinology and Metabolism, Departments of Medicine, Molecular and Cellular Biology, Biochemistry and Molecular Biology, and Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030
| | - Lawrence Chan
- Division of Endocrinology (Y.Y.), Department of Medicine, MetroHealth Medical Center, Case Western Reserve University, Cleveland, Ohio 44109; and Diabetes and Endocrinology Research Center (L.C.), Division of Diabetes, Endocrinology and Metabolism, Departments of Medicine, Molecular and Cellular Biology, Biochemistry and Molecular Biology, and Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas 77030
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75
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Kohane IS. Deeper, longer phenotyping to accelerate the discovery of the genetic architectures of diseases. Genome Biol 2016; 15:115. [PMID: 25165795 PMCID: PMC4054856 DOI: 10.1186/gb4175] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023] Open
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76
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Paul L, Walker EM, Drosos Y, Cyphert HA, Neale G, Stein R, South J, Grosveld G, Herrera PL, Sosa-Pineda B. Lack of Prox1 Downregulation Disrupts the Expansion and Maturation of Postnatal Murine β-Cells. Diabetes 2016; 65:687-98. [PMID: 26631740 PMCID: PMC4764148 DOI: 10.2337/db15-0713] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/27/2015] [Accepted: 11/20/2015] [Indexed: 12/18/2022]
Abstract
Transcription factor expression fluctuates during β-cell ontogeny, and disruptions in this pattern can affect the development or function of those cells. Here we uncovered that murine endocrine pancreatic progenitors express high levels of the homeodomain transcription factor Prox1, whereas both immature and mature β-cells scarcely express this protein. We also investigated if sustained Prox1 expression is incompatible with β-cell development or maintenance using transgenic mouse approaches. We discovered that Prox1 upregulation in mature β-cells has no functional consequences; in contrast, Prox1 overexpression in immature β-cells promotes acute fasting hyperglycemia. Using a combination of immunostaining and quantitative and comparative gene expression analyses, we determined that Prox1 upregulation reduces proliferation, impairs maturation, and enables apoptosis in postnatal β-cells. Also, we uncovered substantial deficiency in β-cells that overexpress Prox1 of the key regulator of β-cell maturation MafA, several MafA downstream targets required for glucose-stimulated insulin secretion, and genes encoding important components of FGF signaling. Moreover, knocking down PROX1 in human EndoC-βH1 β-cells caused increased expression of many of these same gene products. These and other results in our study indicate that reducing the expression of Prox1 is beneficial for the expansion and maturation of postnatal β-cells.
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Affiliation(s)
- Leena Paul
- Department of Genetics, St. Jude Children's Research Hospital, Memphis, TN
| | - Emily M Walker
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN
| | - Yiannis Drosos
- Department of Genetics, St. Jude Children's Research Hospital, Memphis, TN
| | - Holly A Cyphert
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN
| | - Geoffrey Neale
- Hartwell Center for Bioinformatics & Biotechnology, St. Jude Children's Research Hospital, Memphis, TN
| | - Roland Stein
- Department of Molecular Physiology and Biophysics, Vanderbilt University Medical School, Nashville, TN
| | - Jack South
- Department of Genetics, St. Jude Children's Research Hospital, Memphis, TN
| | - Gerard Grosveld
- Department of Genetics, St. Jude Children's Research Hospital, Memphis, TN
| | - Pedro L Herrera
- Department of Genetic Medicine and Development, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Beatriz Sosa-Pineda
- Department of Genetics, St. Jude Children's Research Hospital, Memphis, TN Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL
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Tian Y, Zhang W, Zhao S, Sun Y, Bian Y, Chen T, Du Y, Zhang J, Wang Z, Huang T, Peng Y, Yang P, Zhao H, Chen ZJ. FADS1-FADS2 gene cluster confers risk to polycystic ovary syndrome. Sci Rep 2016; 6:21195. [PMID: 26879377 PMCID: PMC4754766 DOI: 10.1038/srep21195] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2015] [Accepted: 01/19/2016] [Indexed: 01/22/2023] Open
Abstract
Dyslipidemia is common in polycystic ovary syndrome (PCOS). This study was aimed to investigate whether fatty acid desaturase genes (FADS), a dyslipidemia-related gene cluster, are associated with PCOS. We scanned variations of FADS genes using our previous data of genome-wide association study (GWAS) for PCOS and selected rs174570 for further study. The case-control study was conducted in an independent cohort of 1918 PCOS cases and 1889 age-matched controls and family-based study was conducted in a set of 243 core family trios with PCOS probands. Minor allele frequency (allele T) of rs174570 was significantly lower in PCOS cases than that in age-matched controls (P = 2.17E-03, OR = 0.85), even after adjustment of BMI and age. PCOS subjects carrying CC genotype had higher testosterone level and similar lipid/glucose level compared with those carrying TT or TC genotype. In trios, transmission disequilibrium test (TDT) analysis revealed risk allele C of rs174570 was significantly over-transmitted (P = 2.00E-04). Decreased expression of FADS2 was detected in PCOS cases and expression quantitative trait loci (eQTL) analysis revealed the risk allele C dosage was correlated with the decline of FADS2 expression (P = 0.002). Our results demonstrate that FADS1-FADS2 are susceptibility genes for PCOS.
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Affiliation(s)
- Ye Tian
- Center for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.,Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics, Shanghai, China.,Center for Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; National Research Center for Assisted Reproductive Technology and Reproductive Genetics, China; The Key laboratory for Reproductive Endocrinology of Ministry of Education, China; Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, China
| | - Wei Zhang
- Department of joint and bone oncology, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China
| | - Shigang Zhao
- Center for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.,Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics, Shanghai, China
| | - Yinhua Sun
- Center for Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; National Research Center for Assisted Reproductive Technology and Reproductive Genetics, China; The Key laboratory for Reproductive Endocrinology of Ministry of Education, China; Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, China
| | - Yuehong Bian
- Center for Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; National Research Center for Assisted Reproductive Technology and Reproductive Genetics, China; The Key laboratory for Reproductive Endocrinology of Ministry of Education, China; Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, China
| | - Tailai Chen
- Center for Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; National Research Center for Assisted Reproductive Technology and Reproductive Genetics, China; The Key laboratory for Reproductive Endocrinology of Ministry of Education, China; Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, China
| | - Yanzhi Du
- Center for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.,Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics, Shanghai, China
| | - Jiangtao Zhang
- Center for Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; National Research Center for Assisted Reproductive Technology and Reproductive Genetics, China; The Key laboratory for Reproductive Endocrinology of Ministry of Education, China; Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, China
| | - Zhao Wang
- Center for Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; National Research Center for Assisted Reproductive Technology and Reproductive Genetics, China; The Key laboratory for Reproductive Endocrinology of Ministry of Education, China; Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, China
| | - Tao Huang
- Center for Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; National Research Center for Assisted Reproductive Technology and Reproductive Genetics, China; The Key laboratory for Reproductive Endocrinology of Ministry of Education, China; Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, China
| | - Yingqian Peng
- Center for Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; National Research Center for Assisted Reproductive Technology and Reproductive Genetics, China; The Key laboratory for Reproductive Endocrinology of Ministry of Education, China; Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, China
| | - Ping Yang
- Center for Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; National Research Center for Assisted Reproductive Technology and Reproductive Genetics, China; The Key laboratory for Reproductive Endocrinology of Ministry of Education, China; Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, China
| | - Han Zhao
- Center for Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; National Research Center for Assisted Reproductive Technology and Reproductive Genetics, China; The Key laboratory for Reproductive Endocrinology of Ministry of Education, China; Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, China
| | - Zi-Jiang Chen
- Center for Reproductive Medicine, Ren Ji Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China.,Shanghai Key Laboratory for Assisted Reproduction and Reproductive Genetics, Shanghai, China.,Center for Reproductive Medicine, Shandong Provincial Hospital Affiliated to Shandong University, Jinan, China; National Research Center for Assisted Reproductive Technology and Reproductive Genetics, China; The Key laboratory for Reproductive Endocrinology of Ministry of Education, China; Shandong Provincial Key Laboratory of Reproductive Medicine, Jinan, China
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Hivert MF, Christophi CA, Franks PW, Jablonski KA, Ehrmann DA, Kahn SE, Horton ES, Pollin TI, Mather KJ, Perreault L, Barrett-Connor E, Knowler WC, Florez JC. Lifestyle and Metformin Ameliorate Insulin Sensitivity Independently of the Genetic Burden of Established Insulin Resistance Variants in Diabetes Prevention Program Participants. Diabetes 2016; 65:520-6. [PMID: 26525880 PMCID: PMC4747453 DOI: 10.2337/db15-0950] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/10/2015] [Accepted: 10/27/2015] [Indexed: 12/15/2022]
Abstract
Large genome-wide association studies of glycemic traits have identified genetics variants that are associated with insulin resistance (IR) in the general population. It is unknown whether people with genetic enrichment for these IR variants respond differently to interventions that aim to improve insulin sensitivity. We built a genetic risk score (GRS) based on 17 established IR variants and effect sizes (weighted IR-GRS) in 2,713 participants of the Diabetes Prevention Program (DPP) with genetic consent. We tested associations between the weighted IR-GRS and insulin sensitivity index (ISI) at baseline in all participants, and with change in ISI over 1 year of follow-up in the DPP intervention (metformin and lifestyle) and control (placebo) arms. All models were adjusted for age, sex, ethnicity, and waist circumference at baseline (plus baseline ISI for 1-year ISI change models). A higher IR-GRS was associated with lower baseline ISI (β = -0.754 [SE = 0.229] log-ISI per unit, P = 0.001 in fully adjusted models). There was no differential effect of treatment for the association between the IR-GRS on the change in ISI; higher IR-GRS was associated with an attenuation in ISI improvement over 1 year (β = -0.520 [SE = 0.233], P = 0.03 in fully adjusted models; all treatment arms). Lifestyle intervention and metformin treatment improved the ISI, regardless of the genetic burden of IR variants.
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Affiliation(s)
- Marie-France Hivert
- Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, MA Department of Medicine, Université de Sherbrooke, Sherbrooke, Québec, Canada
| | | | - Paul W Franks
- Genetic & Molecular Epidemiology Unit, Lund University Diabetes Center, Department of Clinical Sciences, Lund University, Malmö, Sweden Department of Nutrition, Harvard School of Public Health, Boston, MA Department of Public Health and Clinical Medicine, Division of Medicine, Umeå University, Umeå, Sweden
| | | | - David A Ehrmann
- Department of Medicine, The University of Chicago School of Medicine, Chicago, IL
| | - Steven E Kahn
- Division of Metabolism, Endocrinology & Nutrition, VA Puget Sound Health Care System and University of Washington, Seattle, WA
| | - Edward S Horton
- Section on Clinical, Behavioral & Outcomes Research, Joslin Diabetes Center, Boston, MA Department of Medicine, Harvard Medical School, Boston, MA
| | - Toni I Pollin
- Departments of Medicine and Epidemiology & Public Health, University of Maryland School of Medicine, Baltimore, MD Program in Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD
| | - Kieren J Mather
- Division of Endocrinology, Department of Medicine, Indiana University School of Medicine, Indianapolis, IN
| | - Leigh Perreault
- Department of Medicine, Division of Endocrinology, Metabolism and Diabetes, University of Colorado Anschutz Medical Campus, Aurora, CO
| | - Elizabeth Barrett-Connor
- Division of Epidemiology, Department of Family Medicine and Public Health, University of California, San Diego, La Jolla, CA
| | - William C Knowler
- Diabetes Epidemiology and Clinical Research Section, National Institute of Diabetes and Digestive and Kidney Diseases, Phoenix, AZ
| | - Jose C Florez
- Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, MA Department of Medicine, Harvard Medical School, Boston, MA Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA Program in Medical and Population Genetics, Broad Institute, Cambridge, MA
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79
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Shah M, Varghese RT, Miles JM, Piccinini F, Dalla Man C, Cobelli C, Bailey KR, Rizza RA, Vella A. TCF7L2 Genotype and α-Cell Function in Humans Without Diabetes. Diabetes 2016; 65:371-80. [PMID: 26525881 PMCID: PMC4747457 DOI: 10.2337/db15-1233] [Citation(s) in RCA: 38] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/02/2015] [Accepted: 10/26/2015] [Indexed: 12/20/2022]
Abstract
The diabetes-associated allele in TCF7L2 increases the rate of conversion to diabetes; however, the mechanism by which this occurs remains elusive. We hypothesized that the diabetes-associated allele in this locus (rs7903146) impairs insulin secretion and that this defect would be exacerbated by acute free fatty acid (FFA)-induced insulin resistance. We studied 120 individuals of whom one-half were homozygous for the diabetes-associated allele TT at rs7903146 and one-half were homozygous for the protective allele CC. After a screening examination during which glucose tolerance status was determined, subjects were studied on two occasions in random order while undergoing an oral challenge. During one study day, FFA was elevated by infusion of Intralipid plus heparin. On the other study day, subjects received the same amount of glycerol as present in the Intralipid infusion. β-Cell responsivity indices were estimated with the oral C-peptide minimal model. We report that β-cell responsivity was slightly impaired in the TT genotype group. Moreover, the hyperbolic relationship between insulin secretion and β-cell responsivity differed significantly between genotypes. Subjects also exhibited impaired suppression of glucagon after an oral challenge. These data imply that a genetic variant harbored within the TCF7L2 locus impairs glucose tolerance through effects on glucagon as well as on insulin secretion.
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Affiliation(s)
- Meera Shah
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition Research, Mayo Clinic, Rochester, MN
| | - Ron T Varghese
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition Research, Mayo Clinic, Rochester, MN
| | - John M Miles
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition Research, Mayo Clinic, Rochester, MN
| | - Francesca Piccinini
- Department of Information Engineering, Università degli Studi di Padova, Padova, Italy
| | - Chiara Dalla Man
- Department of Information Engineering, Università degli Studi di Padova, Padova, Italy
| | - Claudio Cobelli
- Department of Information Engineering, Università degli Studi di Padova, Padova, Italy
| | - Kent R Bailey
- Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN
| | - Robert A Rizza
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition Research, Mayo Clinic, Rochester, MN
| | - Adrian Vella
- Division of Endocrinology, Diabetes, Metabolism, and Nutrition Research, Mayo Clinic, Rochester, MN
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80
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Ohn JH, Kwak SH, Cho YM, Lim S, Jang HC, Park KS, Cho NH. 10-year trajectory of β-cell function and insulin sensitivity in the development of type 2 diabetes: a community-based prospective cohort study. Lancet Diabetes Endocrinol 2016; 4:27-34. [PMID: 26577716 DOI: 10.1016/s2213-8587(15)00336-8] [Citation(s) in RCA: 138] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/30/2015] [Revised: 09/01/2015] [Accepted: 09/02/2015] [Indexed: 12/21/2022]
Abstract
BACKGROUND The relative contributions of β-cell function and insulin sensitivity in the pathogenesis of type 2 diabetes are not fully understood. We investigated the longitudinal change in β-cell function and insulin sensitivity in the development of diabetes and the role of genetic variants in deterioration of glucose tolerance. METHODS We followed up 4106 participants with normal glucose tolerance (NGT) from the Korean Genome and Epidemiology Study with oral glucose tolerance tests every 2 years for 10 years. We estimated pancreatic β-cell function with the 60 min insulinogenic index (IGI60) and insulin sensitivity with the composite (Matsuda) insulin sensitivity index (ISI). We investigated the association of 66 known type 2 diabetes genetic variants with risk of prediabetes or diabetes and impaired β-cell function and insulin sensitivity. FINDINGS During 10 years of follow-up, 1093 (27%) of 4106 participants developed prediabetes and 498 (12%) participants developed diabetes. Compared with participants who remained NGT, those who progressed to diabetes had a lower IGI60 (unadjusted data 5·1 μU/mmol [95% CI 0·5-56·1] vs 7·9 μU/mmol [0·5-113·8]; p<0·0001) and lower ISI (unadjusted data 8·2 [2·6-26·0] vs 10·0 [3·2-31·6]; p<0·0001) at baseline. Participants who had NGT at 10 years showed a decrease in ISI (adjusted data 10·1 [9·9-10·3] vs 7·4 [7·3-7·6]; p<0·0001) but a compensatory increase in IGI60 (adjusted data 6·9 μU/mmol [6·5-7·2] vs 11·7 μU/mmol [11·2-12·1]; p<0·0001) compared with baseline. By contrast, participants who developed diabetes showed a decrease in ISI (adjusted data 8·4 [8·0-8·7] vs 3·0 [2·8-3·2]; p<0·0001) but no significant compensatory increase (p=0·95) in IGI60. A genetic variant near the glucokinase gene (rs4607517) was significantly associated with progression to prediabetes or diabetes (hazard ratio 1·27, 1·16-1·38; p=1·70 × 10(-7)). INTERPRETATION Decreased β-cell function, which might be determined partly by genetic factors, and impaired β-cell compensation for progressive decline in insulin sensitivity are crucial factors in the deterioration of glucose tolerance. FUNDING South Korean Ministry of Health & Welfare.
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Affiliation(s)
- Jung Hun Ohn
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea; Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Soo Heon Kwak
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
| | - Young Min Cho
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
| | - Soo Lim
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea; Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Hak Chul Jang
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea; Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam, South Korea
| | - Kyong Soo Park
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea; Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea.
| | - Nam H Cho
- Department of Preventive Medicine, Ajou University School of Medicine, Suwon, South Korea.
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Powell DR, Gay JP, Smith M, Wilganowski N, Harris A, Holland A, Reyes M, Kirkham L, Kirkpatrick LL, Zambrowicz B, Hansen G, Platt KA, van Sligtenhorst I, Ding ZM, Desai U. Fatty acid desaturase 1 knockout mice are lean with improved glycemic control and decreased development of atheromatous plaque. Diabetes Metab Syndr Obes 2016; 9:185-99. [PMID: 27382320 PMCID: PMC4922822 DOI: 10.2147/dmso.s106653] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Delta-5 desaturase (D5D) and delta-6 desaturase (D6D), encoded by fatty acid desaturase 1 (FADS1) and FADS2 genes, respectively, are enzymes in the synthetic pathways for ω3, ω6, and ω9 polyunsaturated fatty acids (PUFAs). Although PUFAs appear to be involved in mammalian metabolic pathways, the physiologic effect of isolated D5D deficiency on these pathways is unclear. After generating >4,650 knockouts (KOs) of independent mouse genes and analyzing them in our high-throughput phenotypic screen, we found that Fads1 KO mice were among the leanest of 3,651 chow-fed KO lines analyzed for body composition and were among the most glucose tolerant of 2,489 high-fat-diet-fed KO lines analyzed by oral glucose tolerance test. In confirmatory studies, chow- or high-fat-diet-fed Fads1 KO mice were leaner than wild-type (WT) littermates; when data from multiple cohorts of adult mice were combined, body fat was 38% and 31% lower in Fads1 male and female KO mice, respectively. Fads1 KO mice also had lower glucose and insulin excursions during oral glucose tolerance tests along with lower fasting glucose, insulin, triglyceride, and total cholesterol levels. In additional studies using a vascular injury model, Fads1 KO mice had significantly decreased femoral artery intima/media ratios consistent with a decreased inflammatory response in their arterial wall. Based on this result, we bred Fads1 KO and WT mice onto an ApoE KO background and fed them a Western diet for 14 weeks; in this atherogenic environment, aortic trees of Fads1 KO mice had 40% less atheromatous plaque compared to WT littermates. Importantly, PUFA levels measured in brain and liver phospholipid fractions of Fads1 KO mice were consistent with decreased D5D activity and normal D6D activity. The beneficial metabolic phenotype demonstrated in Fads1 KO mice suggests that selective D5D inhibitors may be useful in the treatment of human obesity, diabetes, and atherosclerotic cardiovascular disease.
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Affiliation(s)
- David R Powell
- Metabolism Research, Lexicon Pharmaceuticals, Inc., The Woodlands, TX, USA
- Correspondence: David R Powell, Lexicon Pharmaceuticals, Inc., 8800 Technology Forest Place, The Woodlands, TX 77381, USA, Tel +1 281 863 3060, Fax +1 281 863 8115, Email
| | - Jason P Gay
- Metabolism Research, Lexicon Pharmaceuticals, Inc., The Woodlands, TX, USA
| | - Melinda Smith
- Metabolism Research, Lexicon Pharmaceuticals, Inc., The Woodlands, TX, USA
| | | | - Angela Harris
- Metabolism Research, Lexicon Pharmaceuticals, Inc., The Woodlands, TX, USA
| | - Autumn Holland
- Metabolism Research, Lexicon Pharmaceuticals, Inc., The Woodlands, TX, USA
| | - Maricela Reyes
- Metabolism Research, Lexicon Pharmaceuticals, Inc., The Woodlands, TX, USA
| | - Laura Kirkham
- Metabolism Research, Lexicon Pharmaceuticals, Inc., The Woodlands, TX, USA
| | | | - Brian Zambrowicz
- Metabolism Research, Lexicon Pharmaceuticals, Inc., The Woodlands, TX, USA
| | - Gwenn Hansen
- Metabolism Research, Lexicon Pharmaceuticals, Inc., The Woodlands, TX, USA
| | - Kenneth A Platt
- Metabolism Research, Lexicon Pharmaceuticals, Inc., The Woodlands, TX, USA
| | | | - Zhi-Ming Ding
- Metabolism Research, Lexicon Pharmaceuticals, Inc., The Woodlands, TX, USA
| | - Urvi Desai
- Metabolism Research, Lexicon Pharmaceuticals, Inc., The Woodlands, TX, USA
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Transcript Expression Data from Human Islets Links Regulatory Signals from Genome-Wide Association Studies for Type 2 Diabetes and Glycemic Traits to Their Downstream Effectors. PLoS Genet 2015; 11:e1005694. [PMID: 26624892 PMCID: PMC4666611 DOI: 10.1371/journal.pgen.1005694] [Citation(s) in RCA: 127] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2015] [Accepted: 10/30/2015] [Indexed: 01/01/2023] Open
Abstract
The intersection of genome-wide association analyses with physiological and functional data indicates that variants regulating islet gene transcription influence type 2 diabetes (T2D) predisposition and glucose homeostasis. However, the specific genes through which these regulatory variants act remain poorly characterized. We generated expression quantitative trait locus (eQTL) data in 118 human islet samples using RNA-sequencing and high-density genotyping. We identified fourteen loci at which cis-exon-eQTL signals overlapped active islet chromatin signatures and were coincident with established T2D and/or glycemic trait associations. At some, these data provide an experimental link between GWAS signals and biological candidates, such as DGKB and ADCY5. At others, the cis-signals implicate genes with no prior connection to islet biology, including WARS and ZMIZ1. At the ZMIZ1 locus, we show that perturbation of ZMIZ1 expression in human islets and beta-cells influences exocytosis and insulin secretion, highlighting a novel role for ZMIZ1 in the maintenance of glucose homeostasis. Together, these findings provide a significant advance in the mechanistic insights of T2D and glycemic trait association loci.
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83
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Rubtsov PM, Igudin EL, Tiulpakov AN. Glucokinase and glucokinase regulatory proteins as molecular targets for novel antidiabetic drugs. Mol Biol 2015. [DOI: 10.1134/s0026893315040147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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84
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Siddiqui K, Tyagi S. Genetics, genomics and personalized medicine in Type 2 diabetes: a perspective on the Arab region. Per Med 2015; 12:417-431. [DOI: 10.2217/pme.15.11] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Type 2 diabetes (T2D) is a wide-spread, chronic metabolic disorder, affecting millions of people worldwide. The epidemic of diabetes has placed a huge strain on public health, longevity and economy. T2D occurs as a result of both genetic and environmental factors and is heterogeneous in its presentation across individuals. This review gives an overview of the genetic variations identified by genome-wide association studies which predispose individuals to T2D and those which are responsible for variable drug response across patients, and the necessity to adopt a personalized approach to diabetes management. We also include a perspective on diabetes in Arabs, given the high incidence of T2D and consanguineous marriages, and the need to understand associated genetic components in this vulnerable population.
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Affiliation(s)
- Khalid Siddiqui
- Strategic Center for Diabetes Research, College of Medicine, King Saud University, P.O. Box 245, Riyadh 11411, Kingdom of Saudi Arabia
| | - Shivani Tyagi
- Freelance writer, Al Rajhi Street, Sulaimaniyah District, Riyadh, Kingdom of Saudi Arabia
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Kochetova OV, Viktorova TV, Mustafina OE, Karpov AA, Khusnutdinova EK. Genetic association of ADRA2A and ADRB3 genes with metabolic syndrome among the Tatars. RUSS J GENET+ 2015. [DOI: 10.1134/s1022795415070066] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
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Rousseaux J, Duhamel A, Dumont J, Dallongeville J, Molnar D, Widhalm K, Manios Y, Sjöström M, Kafatos A, Breidenassel C, Gonzales-Gross M, Cuenca-Garcia M, Censi L, Ascensión M, De Henauw S, Moreno LA, Meirhaeghe A, Gottrand F. The n-3 long-chain PUFAs modulate the impact of the GCKR Pro446Leu polymorphism on triglycerides in adolescents. J Lipid Res 2015; 56:1774-80. [PMID: 26136510 DOI: 10.1194/jlr.m057570] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2015] [Indexed: 01/19/2023] Open
Abstract
Dietary n-3 long-chain PUFAs (LC-PUFAs) are associated with improvement in the parameters of the metabolic syndrome (MetS). Glucokinase regulatory protein (GCKR) is a key protein regulating intracellular glucose disposal. Our aim was to investigate: i) the relationship between the GCKR rs1260326 (Pro446Leu) polymorphism and parameters of the MetS; and ii) a potential influence of n-3 and n-6 LC-PUFA levels on this relationship in the HELENA study (1,155 European adolescents). Linear regression analyses were performed to study the association between rs1260326 and the outcomes of interest. Interactions between rs1260326 and LC-PUFA levels on outcomes were explored. The T allele of rs1260326 was associated with higher serum TG concentrations compared with the C allele. In contrast to n-6 LC-PUFA levels, a significant interaction (P = 0.01) between rs1260326 and total n-3 LC-PUFA levels on serum TG concentrations was observed. After stratification on the n-3 LC-PUFA median values, the association between rs1260326 and TG concentration was significant only in the group with high n-3 LC-PUFA levels. In conclusion, this is the first evidence that n-3 LC-PUFAs may modulate the impact of the GCKR rs1260326 polymorphism on TG concentrations in adolescents. Several molecular mechanisms, in link with glucose uptake, could explain these findings.
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Affiliation(s)
- Julien Rousseaux
- Inserm U995, LIRIC, CHU Lille, University Lille, Lille, France Unité de Biostatistiques, CERIM, EA2694, CHU Lille, University Lille, Lille, France
| | - Alain Duhamel
- Unité de Biostatistiques, CERIM, EA2694, CHU Lille, University Lille, Lille, France
| | - Julie Dumont
- Inserm UMR1167, Institut Pasteur de Lille, University Lille, Lille, France
| | - Jean Dallongeville
- Inserm UMR1167, Institut Pasteur de Lille, University Lille, Lille, France
| | - Denes Molnar
- Department of Pediatrics, University of Pécs, Pécs, Hungary
| | - Kurt Widhalm
- Academic Institute for Clinical Nutrition, Vienna, Austria and Private Medical University Salzburg, Salzburg, Austria
| | - Yannis Manios
- Department of Nutrition and Dietetics, Harokopio University, Athens, Greece
| | - Michael Sjöström
- Unit for Preventive Nutrition, Department of Biosciences and Nutrition, Karolinska Institute, Huddinge, Sweden
| | - Anthony Kafatos
- Preventive Medicine and Nutrition Unit, School of Medicine, University of Crete, Heraklion, Greece
| | - Christina Breidenassel
- Institut für Ernährungs-und Lebensmittelwissenschaften, Humanernährung, Rheinische Friedrich-Wilhelms, Universität Bonn, Bonn, Germany
| | - Marcela Gonzales-Gross
- Facultad de la Actividad Física y del Deporte-INEF, Universidad Politécnica de Madrid, Madrid, Spain
| | | | - Laura Censi
- National Research Institute on Food and Nutrition, Rome, Italy
| | - Marcos Ascensión
- Immunonutrition Research Group, Department of Metabolism and Nutrition, Institute of Food Science and Technology and Nutrition (ICTAN-CSIC), Madrid, Spain
| | - Stefaan De Henauw
- Department of Public Health, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
| | - Luis A Moreno
- GENUD (Growth, Exercise, Nutrition and Development) Research Group, Escuela Universitaria de Ciencias de la Salud, Universidad de Zaragoza, Zaragoza, Spain
| | - Aline Meirhaeghe
- Inserm UMR1167, Institut Pasteur de Lille, University Lille, Lille, France
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Zheng C, Dalla Man C, Cobelli C, Groop L, Zhao H, Bale AE, Shaw M, Duran E, Pierpont B, Caprio S, Santoro N. A common variant in the MTNR1b gene is associated with increased risk of impaired fasting glucose (IFG) in youth with obesity. Obesity (Silver Spring) 2015; 23:1022-9. [PMID: 25919927 PMCID: PMC4414047 DOI: 10.1002/oby.21030] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/06/2014] [Accepted: 12/21/2014] [Indexed: 11/17/2022]
Abstract
OBJECTIVE To explore the role of MTNR1B rs10830963 and G6PC2 rs560887 variants in the pathogenesis of impaired fasting glucose (IFG) in obese adolescents. METHODS A total of 346 Caucasians, 218 African-Americans, and 217 Hispanics obese children and adolescents underwent an oral glucose tolerance test (OGTT) and 518 underwent the evaluation of insulin secretion by the oral minimal model (OMM). Also, 274 subjects underwent a second OGTT after 3.0 ± 2.1 years. RESULTS The MTNR1B rs10830963 variant was associated with higher fasting glucose levels and lower dynamic beta-cell response in Caucasians and Hispanics (P < 0.05) and conferred an increased risk of showing IFG to Caucasians (P = 0.05), African-Americans (P = 0.0066), and Hispanics (P = 0.024). Despite the association between the G6PC2 rs560887 and higher fasting glucose levels (P < 0.05), there was no association between this variant and IFG at baseline or at follow-up (all P > 0.10). CONCLUSIONS It has been shown for the first time in obese youth that the MTNR1B variant is associated with an increased risk of IFG.
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Affiliation(s)
- Chao Zheng
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT
- Department of Endocrinology, The 2 Affiliated Hospital & Yuying Children's Hospital of Wenzhou Medical University
| | - Chiara Dalla Man
- Department of Information Engineering, University of Padua, Padua, Italy
| | - Claudio Cobelli
- Department of Information Engineering, University of Padua, Padua, Italy
| | - Leif Groop
- Department of Clinical Sciences/Diabetes & Endocrinology and Lund University Diabetes Centre, Lund University, University Hospital, Malmoe, Malmoe, Sweden
| | - Hongyu Zhao
- Department of Biostatistics, Yale School of Public Health, New Haven, CT
| | - Allen E Bale
- Department of Genetics, Yale University School of Medicine, New Haven, CT
| | - Melissa Shaw
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT
| | - Elvira Duran
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT
| | - Bridget Pierpont
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT
| | - Sonia Caprio
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT
| | - Nicola Santoro
- Department of Pediatrics, Yale University School of Medicine, New Haven, CT
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88
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Salman M, Dasgupta S, Cholendra A, Venugopal PN, Lakshmi GL, Xaviour D, Rao J, D'Souza CJM. MTNR1B gene polymorphisms and susceptibility to Type 2 Diabetes: A pilot study in South Indians. Gene 2015; 566:189-93. [PMID: 25922310 DOI: 10.1016/j.gene.2015.04.064] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2015] [Revised: 03/26/2015] [Accepted: 04/17/2015] [Indexed: 01/23/2023]
Abstract
Type 2 Diabetes (T2D) is the major health concern in the Indian subcontinent. A genome-wide association study carried out with non-diabetic Indians showed association of MTNR1B variants with fasting glucose. MTNR1B mediates the effect of melatonin on insulin secretion. In light of the growing importance of MTNR1B in the etiology of T2D, we sought to test its association with the disease in the south Indian type 2 diabetics. Five single nucleotide polymorphisms of MTNR1B (rs10830962, rs10830963, rs3847554, rs1387153 and rs2166706) were genotyped in 346 T2D patients and 341 non-diabetic controls. None of the SNPs differed significantly between patients and controls with respect to allele and genotype frequencies. Linear regression analysis after adjustment for age, sex and BMI showed a significant positive association of rs3847554 with fasting glucose under recessive model (β=14.98, p=0.012). Haplotypes constituted by minor alleles of rs3847554, rs1387153, rs2166706, rs10830963 and major allele of rs10830962 showed significant positive correlation with fasting glucose (p<0.05). Though the results obtained are suggestive of MTNR1B role in T2D etiology, they need to be confirmed with much larger sample sizes.
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Affiliation(s)
- Mohammed Salman
- Anthropological Survey of India, Southern Regional Centre, Mysore 570026, Karnataka, India; Department of Studies in Biochemistry, University of Mysore, Mysore 570006, Karnataka, India.
| | - Shruti Dasgupta
- Department of Studies in Biotechnology, University of Mysore, Mysore 570006, Karnataka, India.
| | - A Cholendra
- Department of Anthropology, Division of Human Genetics, Sri Venkateswara University, Tirupati 517502, Andhra Pradesh, India.
| | - P N Venugopal
- Anthropological Survey of India, North-West Regional Center, Dehradun 248 195, India.
| | - G L Lakshmi
- Anthropological Survey of India, Southern Regional Centre, Mysore 570026, Karnataka, India.
| | - D Xaviour
- Anthropological Survey of India, Southern Regional Centre, Mysore 570026, Karnataka, India.
| | - Jayashankar Rao
- Anthropological Survey of India, Southern Regional Centre, Mysore 570026, Karnataka, India.
| | - Cletus J M D'Souza
- Department of Studies in Biochemistry, University of Mysore, Mysore 570006, Karnataka, India.
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89
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Hansell NK, Halford GS, Andrews G, Shum DHK, Harris SE, Davies G, Franic S, Christoforou A, Zietsch B, Painter J, Medland SE, Ehli EA, Davies GE, Steen VM, Lundervold AJ, Reinvang I, Montgomery GW, Espeseth T, Hulshoff Pol HE, Starr JM, Martin NG, Le Hellard S, Boomsma DI, Deary IJ, Wright MJ. Genetic basis of a cognitive complexity metric. PLoS One 2015; 10:e0123886. [PMID: 25860228 PMCID: PMC4393228 DOI: 10.1371/journal.pone.0123886] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2014] [Accepted: 02/23/2015] [Indexed: 01/15/2023] Open
Abstract
Relational complexity (RC) is a metric reflecting capacity limitation in relational processing. It plays a crucial role in higher cognitive processes and is an endophenotype for several disorders. However, the genetic underpinnings of complex relational processing have not been investigated. Using the classical twin model, we estimated the heritability of RC and genetic overlap with intelligence (IQ), reasoning, and working memory in a twin and sibling sample aged 15-29 years (N = 787). Further, in an exploratory search for genetic loci contributing to RC, we examined associated genetic markers and genes in our Discovery sample and selected loci for replication in four independent samples (ALSPAC, LBC1936, NTR, NCNG), followed by meta-analysis (N>6500) at the single marker level. Twin modelling showed RC is highly heritable (67%), has considerable genetic overlap with IQ (59%), and is a major component of genetic covariation between reasoning and working memory (72%). At the molecular level, we found preliminary support for four single-marker loci (one in the gene DGKB), and at a gene-based level for the NPS gene, having influence on cognition. These results indicate that genetic sources influencing relational processing are a key component of the genetic architecture of broader cognitive abilities. Further, they suggest a genetic cascade, whereby genetic factors influencing capacity limitation in relational processing have a flow-on effect to more complex cognitive traits, including reasoning and working memory, and ultimately, IQ.
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Affiliation(s)
- Narelle K. Hansell
- Neuroimaging Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- * E-mail:
| | - Graeme S. Halford
- School of Applied Psychology, Griffith University, Mt Gravatt Campus, Brisbane, Australia
- Behavioural Basis of Health Program, Griffith Health Institute and School of Applied Psychology, Griffith University, Brisbane, Australia
| | - Glenda Andrews
- Behavioural Basis of Health Program, Griffith Health Institute and School of Applied Psychology, Griffith University, Brisbane, Australia
- School of Applied Psychology, Griffith University, Gold Coast Campus, Southport, Australia
| | - David H. K. Shum
- Behavioural Basis of Health Program, Griffith Health Institute and School of Applied Psychology, Griffith University, Brisbane, Australia
| | - Sarah E. Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Gail Davies
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
| | - Sanja Franic
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Andrea Christoforou
- K.G. Jebsen Centre for Psychosis Research and the Norwegian Center for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Brendan Zietsch
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
- School of Psychology, University of Queensland, St Lucia, Brisbane, Australia
| | - Jodie Painter
- Molecular Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Sarah E. Medland
- Quantitative Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Erik A. Ehli
- Avera Institute for Human Genetics, Avera McKennan Hospital & University Health Center, Sioux Falls, South Dakota, United States of America
| | - Gareth E. Davies
- Avera Institute for Human Genetics, Avera McKennan Hospital & University Health Center, Sioux Falls, South Dakota, United States of America
| | - Vidar M. Steen
- K.G. Jebsen Centre for Psychosis Research and the Norwegian Center for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Astri J. Lundervold
- K.G. Jebsen Center for Research on Neuropsychiatric Disorders, University of Bergen, Bergen, Norway
- Department of Biological and Medical Psychology, University of Bergen, Bergen, Norway
- Center for Research on Aging and Dementia, Haraldsplass Deaconess Hospital, Bergen, Norway
| | - Ivar Reinvang
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Grant W. Montgomery
- Molecular Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Thomas Espeseth
- Department of Psychology, University of Oslo, Oslo, Norway
- Norwegian Center for Mental Disorders Research (NORMENT) and the K.G. Jebsen Center for Psychosis Research, Division of Mental Health and Addiction, Oslo University Hospital, Oslo, Norway
| | - Hilleke E. Hulshoff Pol
- Brain Center Rudolf Magnus, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands
| | - John M. Starr
- Department of Psychology, University of Edinburgh, Edinburgh, United Kingdom
- Alzheimer Scotland Dementia Research Centre, University of Edinburgh, Edinburgh, United Kingdom
| | - Nicholas G. Martin
- Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Stephanie Le Hellard
- K.G. Jebsen Centre for Psychosis Research and the Norwegian Center for Mental Disorders Research (NORMENT), Department of Clinical Science, University of Bergen, Bergen, Norway
- Dr Einar Martens Research Group for Biological Psychiatry, Center for Medical Genetics and Molecular Medicine, Haukeland University Hospital, Bergen, Norway
| | - Dorret I. Boomsma
- Department of Biological Psychology, Vrije Universiteit, Amsterdam, The Netherlands
| | - Ian J. Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Genomic and Experimental Medicine, University of Edinburgh, Edinburgh, United Kingdom
| | - Margaret J. Wright
- Neuroimaging Genetics, QIMR Berghofer Medical Research Institute, Brisbane, Australia
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90
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Knowles JW, Xie W, Zhang Z, Chennamsetty I, Assimes TL, Paananen J, Hansson O, Pankow J, Goodarzi MO, Carcamo-Orive I, Morris AP, Chen YDI, Mäkinen VP, Ganna A, Mahajan A, Guo X, Abbasi F, Greenawalt DM, Lum P, Molony C, Lind L, Lindgren C, Raffel LJ, Tsao PS, Schadt EE, Rotter JI, Sinaiko A, Reaven G, Yang X, Hsiung CA, Groop L, Cordell HJ, Laakso M, Hao K, Ingelsson E, Frayling TM, Weedon MN, Walker M, Quertermous T. Identification and validation of N-acetyltransferase 2 as an insulin sensitivity gene. J Clin Invest 2015; 125:1739-51. [PMID: 25798622 DOI: 10.1172/jci74692] [Citation(s) in RCA: 77] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2013] [Accepted: 02/05/2015] [Indexed: 11/17/2022] Open
Abstract
Decreased insulin sensitivity, also referred to as insulin resistance (IR), is a fundamental abnormality in patients with type 2 diabetes and a risk factor for cardiovascular disease. While IR predisposition is heritable, the genetic basis remains largely unknown. The GENEticS of Insulin Sensitivity consortium conducted a genome-wide association study (GWAS) for direct measures of insulin sensitivity, such as euglycemic clamp or insulin suppression test, in 2,764 European individuals, with replication in an additional 2,860 individuals. The presence of a nonsynonymous variant of N-acetyltransferase 2 (NAT2) [rs1208 (803A>G, K268R)] was strongly associated with decreased insulin sensitivity that was independent of BMI. The rs1208 "A" allele was nominally associated with IR-related traits, including increased fasting glucose, hemoglobin A1C, total and LDL cholesterol, triglycerides, and coronary artery disease. NAT2 acetylates arylamine and hydrazine drugs and carcinogens, but predicted acetylator NAT2 phenotypes were not associated with insulin sensitivity. In a murine adipocyte cell line, silencing of NAT2 ortholog Nat1 decreased insulin-mediated glucose uptake, increased basal and isoproterenol-stimulated lipolysis, and decreased adipocyte differentiation, while Nat1 overexpression produced opposite effects. Nat1-deficient mice had elevations in fasting blood glucose, insulin, and triglycerides and decreased insulin sensitivity, as measured by glucose and insulin tolerance tests, with intermediate effects in Nat1 heterozygote mice. Our results support a role for NAT2 in insulin sensitivity.
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91
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Prasad RB, Groop L. Genetics of type 2 diabetes-pitfalls and possibilities. Genes (Basel) 2015; 6:87-123. [PMID: 25774817 PMCID: PMC4377835 DOI: 10.3390/genes6010087] [Citation(s) in RCA: 275] [Impact Index Per Article: 30.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2014] [Revised: 01/28/2015] [Accepted: 02/27/2015] [Indexed: 12/11/2022] Open
Abstract
Type 2 diabetes (T2D) is a complex disease that is caused by a complex interplay between genetic, epigenetic and environmental factors. While the major environmental factors, diet and activity level, are well known, identification of the genetic factors has been a challenge. However, recent years have seen an explosion of genetic variants in risk and protection of T2D due to the technical development that has allowed genome-wide association studies and next-generation sequencing. Today, more than 120 variants have been convincingly replicated for association with T2D and many more with diabetes-related traits. Still, these variants only explain a small proportion of the total heritability of T2D. In this review, we address the possibilities to elucidate the genetic landscape of T2D as well as discuss pitfalls with current strategies to identify the elusive unknown heritability including the possibility that our definition of diabetes and its subgroups is imprecise and thereby makes the identification of genetic causes difficult.
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Affiliation(s)
- Rashmi B Prasad
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Lund University, CRC, Skåne University Hospital SUS, SE-205 02 Malmö, Sweden.
| | - Leif Groop
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Lund University, CRC, Skåne University Hospital SUS, SE-205 02 Malmö, Sweden.
- Finnish Institute of Molecular Medicine (FIMM), Helsinki University, Helsinki 00014, Finland.
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92
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Kretowski A, Adamska E, Maliszewska K, Wawrusiewicz-Kurylonek N, Citko A, Goscik J, Bauer W, Wilk J, Golonko A, Waszczeniuk M, Lipinska D, Hryniewicka J, Niemira M, Paczkowska M, Ciborowski M, Gorska M. The rs340874 PROX1 type 2 diabetes mellitus risk variant is associated with visceral fat accumulation and alterations in postprandial glucose and lipid metabolism. GENES AND NUTRITION 2015; 10:4. [PMID: 25601634 PMCID: PMC4298567 DOI: 10.1007/s12263-015-0454-6] [Citation(s) in RCA: 31] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/01/2014] [Accepted: 01/05/2015] [Indexed: 01/08/2023]
Abstract
Large-scale meta-analyses of genome-wide association studies have recently confirmed that the rs340874 single-nucleotide polymorphism in PROX1 gene is associated with fasting glycemia and type 2 diabetes mellitus; however, the mechanism of this link was not well established. The aim of our study was to evaluate the functional/phenotypic differences related to rs340874 PROX1 variants. The study group comprised 945 subjects of Polish origin (including 634 with BMI > 25) without previously known dysglycemia. We analyzed behavioral patterns (diet, physical activity), body fat distribution and glucose/fat metabolism after standardized meals and during the oral glucose tolerance test. We found that the carriers of the rs340874 PROX1 CC genotype had higher nonesterified fatty acids levels after high-fat meal (p = 0.035) and lower glucose oxidation (p = 0.014) after high-carbohydrate meal in comparison with subjects with other PROX1 genotypes. Moreover, in subjects with CC variant, we found higher accumulation of visceral fat (p < 0.02), but surprisingly lower daily food consumption (p < 0.001). We hypothesize that lipid metabolism alterations in subjects with the PROX1 CC genotype may be a primary cause of higher glucose levels after glucose load, since the fatty acids can inhibit insulin-stimulated glucose uptake by decreasing carbohydrate oxidation. Our observations suggest that the PROX1 variants have pleiotropic effect on disease pathways and it seem to be a very interesting goal of research on prevention of obesity and type 2 diabetes mellitus. The study may help to understand the mechanisms of visceral obesity and type 2 diabetes mellitus risk development.
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Affiliation(s)
- Adam Kretowski
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, M.C. Sklodowskiej-Curie 24A, 15-276 Bialystok, Poland.,Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Edyta Adamska
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Katarzyna Maliszewska
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, M.C. Sklodowskiej-Curie 24A, 15-276 Bialystok, Poland
| | - Natalia Wawrusiewicz-Kurylonek
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, M.C. Sklodowskiej-Curie 24A, 15-276 Bialystok, Poland
| | - Anna Citko
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, M.C. Sklodowskiej-Curie 24A, 15-276 Bialystok, Poland.,Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Joanna Goscik
- Centre for Experimental Medicine, Medical University of Bialystok, Bialystok, Poland
| | - Witold Bauer
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, M.C. Sklodowskiej-Curie 24A, 15-276 Bialystok, Poland.,Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Juliusz Wilk
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, M.C. Sklodowskiej-Curie 24A, 15-276 Bialystok, Poland
| | - Anna Golonko
- Department of Dietetics and Nutrition, Medical University of Bialystok, Bialystok, Poland
| | - Magdalena Waszczeniuk
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, M.C. Sklodowskiej-Curie 24A, 15-276 Bialystok, Poland.,Department of Dietetics and Nutrition, Medical University of Bialystok, Bialystok, Poland
| | - Danuta Lipinska
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, M.C. Sklodowskiej-Curie 24A, 15-276 Bialystok, Poland
| | - Justyna Hryniewicka
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, M.C. Sklodowskiej-Curie 24A, 15-276 Bialystok, Poland
| | - Magdalena Niemira
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | | | - Michal Ciborowski
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Maria Gorska
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, M.C. Sklodowskiej-Curie 24A, 15-276 Bialystok, Poland
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93
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Burns SM, Vetere A, Walpita D, Dančík V, Khodier C, Perez J, Clemons PA, Wagner BK, Altshuler D. High-throughput luminescent reporter of insulin secretion for discovering regulators of pancreatic Beta-cell function. Cell Metab 2015; 21:126-37. [PMID: 25565210 DOI: 10.1016/j.cmet.2014.12.010] [Citation(s) in RCA: 77] [Impact Index Per Article: 8.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/28/2014] [Revised: 10/14/2014] [Accepted: 12/13/2014] [Indexed: 12/16/2022]
Abstract
Defects in insulin secretion play a central role in the pathogenesis of type 2 diabetes, yet the mechanisms driving beta-cell dysfunction remain poorly understood, and therapies to preserve glucose-dependent insulin release are inadequate. We report a luminescent insulin secretion assay that enables large-scale investigations of beta-cell function, created by inserting Gaussia luciferase into the C-peptide portion of proinsulin. Beta-cell lines expressing this construct cosecrete luciferase and insulin in close correlation, under both standard conditions or when stressed by cytokines, fatty acids, or ER toxins. We adapted the reporter for high-throughput assays and performed a 1,600-compound pilot screen, which identified several classes of drugs inhibiting secretion, as well as glucose-potentiated secretagogues that were confirmed to have activity in primary human islets. Requiring 40-fold less time and expense than the traditional ELISA, this assay may accelerate the identification of pathways governing insulin secretion and compounds that safely augment beta-cell function in diabetes.
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Affiliation(s)
- Sean M Burns
- Diabetes Unit of the Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Molecular Biology, Massachusetts General Hospital, Boston, MA 02114, USA; Medical and Population Genetics Program, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA.
| | - Amedeo Vetere
- Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Deepika Walpita
- Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Vlado Dančík
- Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Carol Khodier
- Center for the Development of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Jose Perez
- Center for the Development of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Paul A Clemons
- Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - Bridget K Wagner
- Center for the Science of Therapeutics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
| | - David Altshuler
- Diabetes Unit of the Department of Medicine, Massachusetts General Hospital, Boston, MA 02114, USA; Center for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Molecular Biology, Massachusetts General Hospital, Boston, MA 02114, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA; Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02142, USA; Medical and Population Genetics Program, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
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94
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Scott RA, Fall T, Pasko D, Barker A, Sharp SJ, Arriola L, Balkau B, Barricarte A, Barroso I, Boeing H, Clavel-Chapelon F, Crowe FL, Dekker JM, Fagherazzi G, Ferrannini E, Forouhi NG, Franks PW, Gavrila D, Giedraitis V, Grioni S, Groop LC, Kaaks R, Key TJ, Kühn T, Lotta LA, Nilsson PM, Overvad K, Palli D, Panico S, Quirós JR, Rolandsson O, Roswall N, Sacerdote C, Sala N, Sánchez MJ, Schulze MB, Siddiq A, Slimani N, Sluijs I, Spijkerman AM, Tjonneland A, Tumino R, van der A DL, Yaghootkar H, McCarthy MI, Semple RK, Riboli E, Walker M, Ingelsson E, Frayling TM, Savage DB, Langenberg C, Wareham NJ. Common genetic variants highlight the role of insulin resistance and body fat distribution in type 2 diabetes, independent of obesity. Diabetes 2014; 63:4378-4387. [PMID: 24947364 PMCID: PMC4241116 DOI: 10.2337/db14-0319] [Citation(s) in RCA: 141] [Impact Index Per Article: 14.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2023]
Abstract
We aimed to validate genetic variants as instruments for insulin resistance and secretion, to characterize their association with intermediate phenotypes, and to investigate their role in type 2 diabetes (T2D) risk among normal-weight, overweight, and obese individuals. We investigated the association of genetic scores with euglycemic-hyperinsulinemic clamp- and oral glucose tolerance test-based measures of insulin resistance and secretion and a range of metabolic measures in up to 18,565 individuals. We also studied their association with T2D risk among normal-weight, overweight, and obese individuals in up to 8,124 incident T2D cases. The insulin resistance score was associated with lower insulin sensitivity measured by M/I value (β in SDs per allele [95% CI], -0.03 [-0.04, -0.01]; P = 0.004). This score was associated with lower BMI (-0.01 [-0.01, -0.0]; P = 0.02) and gluteofemoral fat mass (-0.03 [-0.05, -0.02; P = 1.4 × 10(-6)) and with higher alanine transaminase (0.02 [0.01, 0.03]; P = 0.002) and γ-glutamyl transferase (0.02 [0.01, 0.03]; P = 0.001). While the secretion score had a stronger association with T2D in leaner individuals (Pinteraction = 0.001), we saw no difference in the association of the insulin resistance score with T2D among BMI or waist strata (Pinteraction > 0.31). While insulin resistance is often considered secondary to obesity, the association of the insulin resistance score with lower BMI and adiposity and with incident T2D even among individuals of normal weight highlights the role of insulin resistance and ectopic fat distribution in T2D, independently of body size.
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Affiliation(s)
- Robert A Scott
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Tove Fall
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Dorota Pasko
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | - Adam Barker
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Stephen J Sharp
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Larraitz Arriola
- Public Health Division of Gipuzkoa, San Sebastian, Spain
- Instituto BIO-Donostia, Basque Government, San Sebastian, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | - Beverley Balkau
- Inserm, CESP, U1018, Villejuif, France
- Univ Paris-Sud, UMRS 1018, Villejuif, France
| | - Aurelio Barricarte
- Navarre Public Health Institute (ISPN), Pamplona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | - Inês Barroso
- The Wellcome Trust Sanger Institute, Cambridge, United Kingdom
- University of Cambridge Metabolic Research Laboratories, Cambridge, UK
| | - Heiner Boeing
- German Institute of Human Nutrition Potsdam-Rehbruecke, Germany
| | | | | | - Jacqueline M Dekker
- Department of Epidemiology and Biostatistics, VrijeUniversiteit Medical Center, Amsterdam, The Netherlands
| | - Guy Fagherazzi
- Inserm, CESP, U1018, Villejuif, France
- Univ Paris-Sud, UMRS 1018, Villejuif, France
| | - Ele Ferrannini
- Department of Internal Medicine, University of Pisa, Pisa, Italy
| | - Nita G Forouhi
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Paul W Franks
- Lund University, Malmö, Sweden
- Umeå University, Umeå, Sweden
| | - Diana Gavrila
- Department of Epidemiology, Murcia Regional Health Council, Murcia, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain
| | - Vilmantas Giedraitis
- Department of Public Health and Caring Sciences, Geriatrics, Uppsala University Sweden
| | - Sara Grioni
- Epidemiology and Prevention Unit, Milan, Italy
| | - Leif C Groop
- University Hospital Scania, Malmö, Sweden
- Institute for Molecular Medicine Finland FIMM, University of Helsinki, Helsinki, Finland
| | - Rudolf Kaaks
- German Cancer Research Centre (DKFZ), Heidelberg, Germany
| | | | - Tilman Kühn
- German Cancer Research Centre (DKFZ), Heidelberg, Germany
| | - Luca A Lotta
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | | | - Kim Overvad
- Department of Public Health, Section for Epidemiology, Aarhus University, Aarhus, Denmark
- Aalborg University Hospital, Aalborg, Denmark
| | - Domenico Palli
- Cancer Research and Prevention Institute (ISPO), Florence, Italy
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia, Federico II University, Naples, Italy
| | | | | | - Nina Roswall
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Citta' della Salute e della Scienza Hospital-University of Turin and Center for Cancer Prevention (CPO), Torino, Italy
- Human Genetics Foundation (HuGeF), Torino, Italy
| | - Núria Sala
- Unit of Nutrition, Environment and Cancer, Cancer Epidemiology Research Program, and Translational Research Laboratory, Catalan Institute of Oncology (IDIBELL), Barcelona, Spain
| | - María-José Sánchez
- Andalusian School of Public Health, Granada, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Spain
- Instituto de Investigación Biosanitaria de Granada (Granada.ibs), Granada (Spain)
| | | | - Afshan Siddiq
- School of Public Health, Imperial College London, UK
| | - Nadia Slimani
- International Agency for Research on Cancer, Lyon, France
| | - Ivonne Sluijs
- University Medical Center Utrecht, Utrecht, the Netherlands
| | | | | | | | - Daphne L van der A
- National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Hanieh Yaghootkar
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | - Mark I McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism (OCDEM), University of Oxford, UK
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford, UK
| | - Robert K Semple
- University of Cambridge Metabolic Research Laboratories, Cambridge, UK
| | - Elio Riboli
- School of Public Health, Imperial College London, UK
| | - Mark Walker
- Institute of Cellular Medicine, Newcastle University, Newcastle upon Tyne, UK
| | - Erik Ingelsson
- Department of Medical Sciences, Molecular Epidemiology and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Tim M Frayling
- Genetics of Complex Traits, University of Exeter Medical School, Exeter, UK
| | - David B Savage
- University of Cambridge Metabolic Research Laboratories, Cambridge, UK
| | - Claudia Langenberg
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Nicholas J Wareham
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
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95
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Novel loci affecting iron homeostasis and their effects in individuals at risk for hemochromatosis. Nat Commun 2014; 5:4926. [PMID: 25352340 PMCID: PMC4215164 DOI: 10.1038/ncomms5926] [Citation(s) in RCA: 185] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2014] [Accepted: 08/06/2014] [Indexed: 12/13/2022] Open
Abstract
Variation in body iron is associated with or causes diseases, including anaemia and iron overload. Here, we analyse genetic association data on biochemical markers of iron status from 11 European-population studies, with replication in eight additional cohorts (total up to 48,972 subjects). We find 11 genome-wide-significant (P<5 × 10(-8)) loci, some including known iron-related genes (HFE, SLC40A1, TF, TFR2, TFRC, TMPRSS6) and others novel (ABO, ARNTL, FADS2, NAT2, TEX14). SNPs at ARNTL, TF, and TFR2 affect iron markers in HFE C282Y homozygotes at risk for hemochromatosis. There is substantial overlap between our iron loci and loci affecting erythrocyte and lipid phenotypes. These results will facilitate investigation of the roles of iron in disease.
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96
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Meigs JB, Grant RW, Piccolo R, López L, Florez JC, Porneala B, Marceau L, McKinlay JB. Association of African genetic ancestry with fasting glucose and HbA1c levels in non-diabetic individuals: the Boston Area Community Health (BACH) Prediabetes Study. Diabetologia 2014; 57:1850-8. [PMID: 24942103 PMCID: PMC5424892 DOI: 10.1007/s00125-014-3301-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2014] [Accepted: 05/20/2014] [Indexed: 12/16/2022]
Abstract
AIMS/HYPOTHESIS To test among diabetes-free urban community-dwelling adults the hypothesis that the proportion of African genetic ancestry is positively associated with glycaemia, after accounting for other continental ancestry proportions, BMI and socioeconomic status (SES). METHODS The Boston Area Community Health cohort is a multi-stage 1:1:1 stratified random sample of self-identified African-American, Hispanic and white adults from three Boston inner city areas. We measured 62 ancestry informative markers, fasting glucose (FG), HbA1c, BMI and SES (income, education, occupation and insurance status) and analysed 1,387 eligible individuals (379 African-American, 411 Hispanic, 597 white) without clinical or biochemical evidence of diabetes. We used three-heritage multinomial linear regression models to test the association of FG or HbA1c with genetic ancestry proportion adjusted for: (1) age and sex; (2) age, sex and BMI; and (3) age, sex, BMI and SES. RESULTS Mean age- and sex-adjusted FG levels were 5.73 and 5.54 mmol/l among those with 100% African or European ancestry, respectively. Using per cent European ancestry as the referent, each 1% increase in African ancestry proportion was associated with an age- and sex-adjusted FG increase of 0.0019 mmol/l (p = 0.01). In the BMI- and SES-adjusted model the slope was 0.0019 (p = 0.02). Analysis of HbA1c gave similar results. CONCLUSIONS/INTERPRETATION A greater proportion of African genetic ancestry is independently associated with higher FG levels in a non-diabetic community-based cohort, even accounting for other ancestry proportions, obesity and SES. The results suggest that differences between African-Americans and whites in type 2 diabetes risk may include genetically mediated differences in glucose homeostasis.
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Affiliation(s)
- James B Meigs
- Division of General Internal Medicine, Department of Medicine, Massachusetts General Hospital, 50 Staniford St, 9th Floor, Boston, MA, 02114, USA,
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97
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Genetic variation at glucose and insulin trait loci and response to glucose-insulin-potassium (GIK) therapy: the IMMEDIATE trial. THE PHARMACOGENOMICS JOURNAL 2014; 15:55-62. [PMID: 25135348 DOI: 10.1038/tpj.2014.41] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/13/2014] [Revised: 04/29/2014] [Accepted: 06/04/2014] [Indexed: 11/09/2022]
Abstract
The mechanistic effects of intravenous glucose, insulin and potassium (GIK) in cardiac ischemia are not well understood. We conducted a genetic sub-study of the Immediate Myocardial Metabolic Enhancement During Initial Assessment and Treatment in Emergency care (IMMEDIATE) Trial to explore effects of common and rare glucose and insulin-related genetic loci on initial to 6-h and 6- to 12-h change in plasma glucose and potassium. We identified 27 NOTCH2/ADAM30 and 8 C2CD4B variants conferring a 40-57% increase in glucose during the first 6 h of infusion (P<5.96 × 10(-6)). Significant associations were also found for ABCB11 and SLC30A8 single-nucleotide polymorphisms (SNPs) and glucose responses, and an SEC61A2 SNP with a potassium response to GIK. These studies identify genetic factors that may impact the metabolic response to GIK, which could influence treatment benefits in the setting of acute coronary syndromes (ACS).
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98
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Thomsen SK, Gloyn AL. The pancreatic β cell: recent insights from human genetics. Trends Endocrinol Metab 2014; 25:425-34. [PMID: 24986330 PMCID: PMC4229643 DOI: 10.1016/j.tem.2014.05.001] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2014] [Revised: 05/02/2014] [Accepted: 05/07/2014] [Indexed: 12/14/2022]
Abstract
Diabetes mellitus is a metabolic disease characterised by relative or absolute pancreatic β cell dysfunction. Genetic variants implicated in disease risk can be identified by studying affected individuals. To understand the mechanisms driving genetic associations, variants must be translated through causative transcripts to biological insights. Studies into the genetic basis of Mendelian forms of diabetes have successfully identified genes involved in both β cell function and pancreatic development. For type 2 diabetes (T2D), genome-wide association studies (GWASs) are uncovering an ever-increasing number of susceptibility variants that exert their effect through β cell dysfunction, but translation to mechanistic understanding has in most cases been slow. Improved annotations of the islet genome and advances in whole-genome and -exome sequencing (WHS and WES) have facilitated recent progress.
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Affiliation(s)
- Soren K Thomsen
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Headington, OX3 7LE, UK
| | - Anna L Gloyn
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Headington, OX3 7LE, UK; Oxford National Institute for Health Research (NIHR) Biomedical Research Centre, Churchill Hospital, Headington, OX3 7LE, UK.
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99
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Grarup N, Sandholt CH, Hansen T, Pedersen O. Genetic susceptibility to type 2 diabetes and obesity: from genome-wide association studies to rare variants and beyond. Diabetologia 2014; 57:1528-41. [PMID: 24859358 DOI: 10.1007/s00125-014-3270-4] [Citation(s) in RCA: 127] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/13/2013] [Accepted: 04/22/2014] [Indexed: 12/29/2022]
Abstract
During the past 7 years, genome-wide association studies have shed light on the contribution of common genomic variants to the genetic architecture of type 2 diabetes, obesity and related intermediate phenotypes. The discoveries have firmly established more than 175 genomic loci associated with these phenotypes. Despite the tight correlation between type 2 diabetes and obesity, these conditions do not appear to share a common genetic background, since they have few genetic risk loci in common. The recent genetic discoveries do however highlight specific details of the interplay between the pathogenesis of type 2 diabetes, insulin resistance and obesity. The focus is currently shifting towards investigations of data from targeted array-based genotyping and exome and genome sequencing to study the individual and combined effect of low-frequency and rare variants in metabolic disease. Here we review recent progress as regards the concepts, methodologies and derived outcomes of studies of the genetics of type 2 diabetes and obesity, and discuss avenues to be investigated in the future within this research field.
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Affiliation(s)
- Niels Grarup
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, DIKU Building, Universitetsparken 1, 2100, Copenhagen Ø, Denmark,
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100
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Kraja AT, Chasman DI, North KE, Reiner AP, Yanek LR, Kilpeläinen TO, Smith JA, Dehghan A, Dupuis J, Johnson AD, Feitosa MF, Tekola-Ayele F, Chu AY, Nolte IM, Dastani Z, Morris A, Pendergrass SA, Sun YV, Ritchie MD, Vaez A, Lin H, Ligthart S, Marullo L, Rohde R, Shao Y, Ziegler MA, Im HK, Schnabel RB, Jørgensen T, Jørgensen ME, Hansen T, Pedersen O, Stolk RP, Snieder H, Hofman A, Uitterlinden AG, Franco OH, Ikram MA, Richards JB, Rotimi C, Wilson JG, Lange L, Ganesh SK, Nalls M, Rasmussen-Torvik LJ, Pankow JS, Coresh J, Tang W, Linda Kao WH, Boerwinkle E, Morrison AC, Ridker PM, Becker DM, Rotter JI, Kardia SLR, Loos RJF, Larson MG, Hsu YH, Province MA, Tracy R, Voight BF, Vaidya D, O'Donnell CJ, Benjamin EJ, Alizadeh BZ, Prokopenko I, Meigs JB, Borecki IB. Pleiotropic genes for metabolic syndrome and inflammation. Mol Genet Metab 2014; 112:317-38. [PMID: 24981077 PMCID: PMC4122618 DOI: 10.1016/j.ymgme.2014.04.007] [Citation(s) in RCA: 88] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/25/2014] [Revised: 04/26/2014] [Accepted: 04/26/2014] [Indexed: 01/11/2023]
Abstract
Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation.
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Affiliation(s)
- Aldi T Kraja
- Division of Statistical Genomics, Department of Genetics and Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA.
| | - Daniel I Chasman
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Kari E North
- Department of Epidemiology and Carolina Center for Genome Sciences, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, NC, USA.
| | | | - Lisa R Yanek
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Tuomas O Kilpeläinen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Jennifer A Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA.
| | - Abbas Dehghan
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA; National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA.
| | - Andrew D Johnson
- National Heart, Lung and Blood Institute (NHLBI) Division of Intramural Research and NHLBI's Framingham Heart Study, Framingham, MA, USA.
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics and Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA.
| | - Fasil Tekola-Ayele
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
| | - Audrey Y Chu
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Ilja M Nolte
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
| | - Zari Dastani
- Department of Epidemiology, Biostatistics and Occupational Health, Jewish General Hospital, Lady Davis Institute, McGill University Montreal, Quebec, Canada.
| | - Andrew Morris
- The Welcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK.
| | - Sarah A Pendergrass
- Department of Biochemistry and Molecular Biology, Eberly College of Science and The Huck Institutes of the Life Sciences, The Pennsylvania State University, PA, USA.
| | - Yan V Sun
- Department of Epidemiology, Rollins School of Public Health, and Department of Biomedical Informatics, School of Medicine, Emory University, Atlanta, GA, USA.
| | - Marylyn D Ritchie
- Department of Biochemistry and Molecular Biology, Pennsylvania State University, University Park, PA, USA.
| | - Ahmad Vaez
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
| | - Honghuang Lin
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
| | - Symen Ligthart
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.
| | - Letizia Marullo
- The Welcome Trust Centre for Human Genetics, University of Oxford, Oxford, UK; Department of Life Sciences and Biotechnology, University of Ferrara, Ferrara, Italy.
| | - Rebecca Rohde
- Department of Epidemiology and Carolina Center for Genome Sciences, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, NC, USA.
| | - Yaming Shao
- Department of Epidemiology and Carolina Center for Genome Sciences, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, NC, USA.
| | - Mark A Ziegler
- Division of Biostatistics, MSIBS Program, Washington University School of Medicine, St. Louis, MO, USA.
| | - Hae Kyung Im
- Department of Health Studies, University of Chicago, IL, USA.
| | - Renate B Schnabel
- Department of General and Interventional Cardiology University Heart Center Hamburg-Eppendorf, Hamburg, Germany.
| | - Torben Jørgensen
- Research Centre for Prevention and Health, Glostrup Hospital, Glostrup, Denmark; Faculty of Health Science, University of Copenhagen, Copenhagen, Denmark.
| | | | - Torben Hansen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Oluf Pedersen
- The Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Ronald P Stolk
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
| | - Harold Snieder
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
| | - Albert Hofman
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.
| | - Andre G Uitterlinden
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands.
| | - Oscar H Franco
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands.
| | - J Brent Richards
- Department of Epidemiology, Biostatistics and Occupational Health, Jewish General Hospital, Lady Davis Institute, McGill University Montreal, Quebec, Canada; Department of Medicine, Human Genetics, Epidemiology and Biostatistics, McGill University, Canada; Department of Twin Research, King's College, London, UK.
| | - Charles Rotimi
- Center for Research on Genomics and Global Health, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA.
| | | | - Leslie Lange
- Department of Genetics, University of North Carolina, NC, USA.
| | - Santhi K Ganesh
- Department of Internal Medicine, University of Michigan, MI, USA.
| | - Mike Nalls
- Molecular Genetics Section, Laboratory of Neurogenetics, National Institute on Aging, NIH, Bethesda, MD, USA.
| | | | - James S Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA.
| | - Josef Coresh
- Department of Medicine, Epidemiology, Biostatistics, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Weihong Tang
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA.
| | - W H Linda Kao
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas - Houston Health Science Center at Houston, Houston, TX, USA.
| | - Alanna C Morrison
- Human Genetics Center, University of Texas - Houston Health Science Center at Houston, Houston, TX, USA.
| | - Paul M Ridker
- Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Diane M Becker
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute (LA BioMed), Harbor-UCLA Medical Center, Torrance, CA, USA.
| | - Sharon L R Kardia
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA.
| | - Ruth J F Loos
- The Genetics of Obesity and Related Metabolic Traits Program, The Charles Bronfman Institute for Personalized Medicine, The Mindich Child Health and Development Institute, The Icahn School of Medicine at Mount Sinai, New York, NY, USA.
| | - Martin G Larson
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA; National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA; Department of Mathematics and Statistics, Boston University, Boston, MA, USA.
| | - Yi-Hsiang Hsu
- Hebrew Senior Life Institute for Aging Research, Harvard Medical School and Molecular and Integrative Physiological Sciences, Harvard School of Public Health, Boston, MA, USA.
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics and Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA.
| | - Russell Tracy
- University of Vermont College of Medicine, Burlington, VT, USA.
| | - Benjamin F Voight
- Department of Pharmacology, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, USA; Department of Genetics, University of Pennsylvania - Perelman School of Medicine, Philadelphia, PA, USA.
| | - Dhananjay Vaidya
- Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
| | - Christopher J O'Donnell
- National Heart, Lung and Blood Institute (NHLBI) Division of Intramural Research and NHLBI's Framingham Heart Study, Framingham, MA, USA.
| | - Emelia J Benjamin
- National Heart, Lung, and Blood Institute's and Boston University's Framingham Heart Study, Framingham, MA, USA; Cardiology and Preventive Medicine Sections, Department of Medicine, Boston University School of Medicine, Boston, MA, USA.
| | - Behrooz Z Alizadeh
- Department of Epidemiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
| | - Inga Prokopenko
- Department of Genomics of Common Diseases, School of Public Health, Imperial College London, London W12 0NN, UK.
| | - James B Meigs
- General Medicine Division, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA.
| | - Ingrid B Borecki
- Division of Statistical Genomics, Department of Genetics and Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA.
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