151
|
Abstract
PURPOSE OF REVIEW Smaller size at birth is associated with a higher risk of type 2 diabetes in later life, but the mechanisms behind this association are poorly understood. Genetic variants which influence susceptibility to type 2 diabetes via effects on insulin secretion or action are good candidates for association with birth weight because foetal insulin is a key foetal growth factor. This review will focus on recent progress in identifying associations between common genetic variants and birth weight. RECENT FINDINGS Foetal genetic variants at two loci (near CCNL1 and in ADCY5) were robustly associated with birth weight via the foetal genotype in the first genome-wide association study of birth weight. The birth weight-lowering allele at ADCY5 also predisposes to type 2 diabetes. In addition, evidence from studies of other type 2 diabetes loci is accumulating for association between the foetal risk alleles at CDKAL1 and HHEX-IDE and lower birth weight, and the maternal risk alleles at GCK and TCF7L2 and higher birth weight. SUMMARY The associations with birth weight at ADCY5, CDKAL1 and HHEX-IDE support the foetal insulin hypothesis, which proposed that type 2 diabetes and lower birth weight could be two phenotypes of the same genotype. The associations at GCK and TCF7L2 illustrate that maternal genes are also important determinants of birth weight.
Collapse
Affiliation(s)
- Hanieh Yaghootkar
- Genetics of Complex Traits, Peninsula College of Medicine and Dentistry, University of Exeter, Exeter, UK
| | | |
Collapse
|
152
|
Bo S, Cassader M, Cavallo-Perin P, Durazzo M, Rosato R, Gambino R. The rs553668 polymorphism of the ADRA2A gene predicts the worsening of fasting glucose values in a cohort of subjects without diabetes. A population-based study. Diabet Med 2012; 29:549-52. [PMID: 22061269 DOI: 10.1111/j.1464-5491.2011.03522.x] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
AIMS Single-nucleotide polymorphisms in the human ADRA2A gene have been associated with increased risk of Type 2 diabetes. The associations between the rs553668 polymorphism and fasting glucose concentrations both cross-sectionally and longitudinally after 6-year follow-up were evaluated in an adult Caucasian population-based cohort. METHODS From a cohort of 1658 individuals, after excluding patients with diabetes, those who died and those whose blood samples were not available for genotyping, data of 1345 individuals were analysed. RESULTS Subjects homozygous for the A allele showed significantly increased baseline fasting glucose values and a significant worsening of fasting glucose (β = 0.48; 95% CI 0.10-0.86) and insulin secretion (β =-20.75; -32.67 to -8.82 for homeostasis model assessment for β-cell function) at follow-up by using generalized estimating equations. Incidence of impaired fasting glucose and diabetes was almost twofold higher in subjects homozygous for the A allele (respectively: incident impaired fasting glucose 7.6-8.2, 16.1%, incident diabetes 1.7-2.3, 3.2% in GG, AG, AA carriers). CONCLUSIONS Our results suggested that the rs553668 polymorphism is associated with glucose worsening in subjects without diabetes at baseline.
Collapse
Affiliation(s)
- S Bo
- Department of Internal Medicine, University of Torino, Turin, Italy
| | | | | | | | | | | |
Collapse
|
153
|
Blüher S, Markert J, Herget S, Yates T, Davis M, Müller G, Waldow T, Schwarz PEH. Who should we target for diabetes prevention and diabetes risk reduction? Curr Diab Rep 2012; 12:147-156. [PMID: 22298028 DOI: 10.1007/s11892-012-0255-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
|
154
|
Vaxillaire M, Bonnefond A, Froguel P. The lessons of early-onset monogenic diabetes for the understanding of diabetes pathogenesis. Best Pract Res Clin Endocrinol Metab 2012; 26:171-87. [PMID: 22498247 DOI: 10.1016/j.beem.2011.12.001] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Monogenic diabetes consists of different subtypes of single gene disorders comprising a large spectrum of phenotypes, namely neonatal diabetes mellitus or monogenic diabetes of infancy, dominantly inherited familial forms of early-onset diabetes (called Maturity-Onset Diabetes of the Young) and rarer diabetes-associated syndromic diseases. All these forms diagnosed at a very-young age are unrelated to auto-immunity. Their genetic dissection has revealed major genes in developmental and/or functional processes of the pancreatic β-cell physiology, and various molecular mechanisms underlying the primary pancreatic defects. Most of these discoveries have had remarkable consequences on the patients care and patient's long-term condition with outstanding examples of successful genomic medicine, which are highlighted in this chapter. Increasing evidence also shows that frequent polymorphisms in or near monogenic diabetes genes may contribute to adult polygenic type 2 diabetes. In this regard, unelucidated forms of monogenic diabetes represent invaluable models for identifying new targets of β-cell dysfunction.
Collapse
Affiliation(s)
- Martine Vaxillaire
- Centre National de la Recherche Scientifique UMR, Genomics and Metabolic Diseases, Lille Pasteur Institute, Lille Nord de France University, France.
| | | | | |
Collapse
|
155
|
Abstract
Type 2 diabetes is a complex metabolic disorder characterised by varying degrees of impairment in insulin secretion and resistance to the action of insulin. Considerable progress has been made recently in understanding the genetic determinants of diabetes. A logical next step is to describe how these variants relate to the underlying pathophysiological processes that lead to diabetes as this may provide insights into pathways to disease. These quantitative traits are, of course, of direct interest in themselves and a growing literature is now emerging on the genetic determinants of insulin secretion and insulin resistance. This review article focuses on describing the complex associations between type 2 diabetes risk variants and quantitative glycaemic traits and the relationship between variants initially discovered in association studies of these traits and risk of type 2 diabetes.
Collapse
Affiliation(s)
- Adam Barker
- Medical Research Council Epidemiology Unit, Addenbrooke's Hospital, Institute of Metabolic Science, Cambridge, UK
| | | | | |
Collapse
|
156
|
Hellstrand S, Sonestedt E, Ericson U, Gullberg B, Wirfält E, Hedblad B, Orho-Melander M. Intake levels of dietary long-chain PUFAs modify the association between genetic variation in FADS and LDL-C. J Lipid Res 2012; 53:1183-9. [PMID: 22451038 PMCID: PMC3351825 DOI: 10.1194/jlr.p023721] [Citation(s) in RCA: 56] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Polymorphisms of the FA desaturase (FADS) gene cluster have been
associated with LDL, HDL, and triglyceride concentrations. Because FADS converts
α-linolenic acid (ALA) and linoleic acid into PUFAs, we investigated the
interaction between different PUFA intakes and the FADS polymorphism
rs174547 (T>C) on fasting blood lipid and lipoprotein concentrations. We included
4,635 individuals (60% females, 45–68 years) from the Swedish population-based
Malmö Diet and Cancer cohort. Dietary intakes were assessed by a modified diet
history method including 7-day registration of cooked meals. The C-allele of rs174547
was associated with lower LDL concentration (P = 0.03). We
observed significant interaction between rs174547 and long-chain ω-3 PUFA
intakes on LDL (P = 0.01); the C-allele was only associated
with lower LDL among individuals in the lowest tertile of long-chain ω-3 PUFA
intakes (P < 0.001). In addition, significant interaction was
observed between rs174547 and the ratio of ALA and linoleic FA intakes on HDL
(P = 0.03). However, no significant associations between
the C-allele and HDL were detected within the intake tertiles of the ratio. Our
findings suggest that dietary intake levels of different PUFAs modify the associated
effect of genetic variation in FADS on LDL and HDL
Collapse
Affiliation(s)
- S Hellstrand
- Diabetes and Cardiovascular Disease, Genetic Epidemiology, Department of Clinical Sciences in Malmö, Lund University, Sweden.
| | | | | | | | | | | | | |
Collapse
|
157
|
van Vliet-Ostaptchouk JV, van Haeften TW, Landman GWD, Reiling E, Kleefstra N, Bilo HJG, Klungel OH, de Boer A, van Diemen CC, Wijmenga C, Boezen HM, Dekker JM, van 't Riet E, Nijpels G, Welschen LMC, Zavrelova H, Bruin EJ, Elbers CC, Bauer F, Onland-Moret NC, van der Schouw YT, Grobbee DE, Spijkerman AMW, van der A DL, Simonis-Bik AM, Eekhoff EMW, Diamant M, Kramer MHH, Boomsma DI, de Geus EJ, Willemsen G, Slagboom PE, Hofker MH, 't Hart LM. Common variants in the type 2 diabetes KCNQ1 gene are associated with impairments in insulin secretion during hyperglycaemic glucose clamp. PLoS One 2012; 7:e32148. [PMID: 22403629 PMCID: PMC3293880 DOI: 10.1371/journal.pone.0032148] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2011] [Accepted: 01/24/2012] [Indexed: 12/30/2022] Open
Abstract
BACKGROUND Genome-wide association studies in Japanese populations recently identified common variants in the KCNQ1 gene to be associated with type 2 diabetes. We examined the association of these variants within KCNQ1 with type 2 diabetes in a Dutch population, investigated their effects on insulin secretion and metabolic traits and on the risk of developing complications in type 2 diabetes patients. METHODOLOGY The KCNQ1 variants rs151290, rs2237892, and rs2237895 were genotyped in a total of 4620 type 2 diabetes patients and 5285 healthy controls from the Netherlands. Data on macrovascular complications, nephropathy and retinopathy were available in a subset of diabetic patients. Association between genotype and insulin secretion/action was assessed in the additional sample of 335 individuals who underwent a hyperglycaemic clamp. PRINCIPAL FINDINGS We found that all the genotyped KCNQ1 variants were significantly associated with type 2 diabetes in our Dutch population, and the association of rs151290 was the strongest (OR 1.20, 95% CI 1.07-1.35, p = 0.002). The risk C-allele of rs151290 was nominally associated with reduced first-phase glucose-stimulated insulin secretion, while the non-risk T-allele of rs2237892 was significantly correlated with increased second-phase glucose-stimulated insulin secretion (p = 0.025 and 0.0016, respectively). In addition, the risk C-allele of rs2237892 was associated with higher LDL and total cholesterol levels (p = 0.015 and 0.003, respectively). We found no evidence for an association of KCNQ1 with diabetic complications. CONCLUSIONS Common variants in the KCNQ1 gene are associated with type 2 diabetes in a Dutch population, which can be explained at least in part by an effect on insulin secretion. Furthermore, our data suggest that KCNQ1 is also associated with lipid metabolism.
Collapse
Affiliation(s)
- Jana V van Vliet-Ostaptchouk
- Molecular Genetics, Department of Pathology and Medical Biology, University Medical Center Groningen, University of Groningen, Groningen, the Netherlands.
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
158
|
Hardeland R, Madrid JA, Tan DX, Reiter RJ. Melatonin, the circadian multioscillator system and health: the need for detailed analyses of peripheral melatonin signaling. J Pineal Res 2012; 52:139-66. [PMID: 22034907 DOI: 10.1111/j.1600-079x.2011.00934.x] [Citation(s) in RCA: 299] [Impact Index Per Article: 24.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Evidence is accumulating regarding the importance of circadian core oscillators, several associated factors, and melatonin signaling in the maintenance of health. Dysfunction of endogenous clocks, melatonin receptor polymorphisms, age- and disease-associated declines of melatonin likely contribute to numerous diseases including cancer, metabolic syndrome, diabetes type 2, hypertension, and several mood and cognitive disorders. Consequences of gene silencing, overexpression, gene polymorphisms, and deviant expression levels in diseases are summarized. The circadian system is a complex network of central and peripheral oscillators, some of them being relatively independent of the pacemaker, the suprachiasmatic nucleus. Actions of melatonin on peripheral oscillators are poorly understood. Various lines of evidence indicate that these clocks are also influenced or phase-reset by melatonin. This includes phase differences of core oscillator gene expression under impaired melatonin signaling, effects of melatonin and melatonin receptor knockouts on oscillator mRNAs or proteins. Cross-connections between melatonin signaling pathways and oscillator proteins, including associated factors, are discussed in this review. The high complexity of the multioscillator system comprises alternate or parallel oscillators based on orthologs and paralogs of the core components and a high number of associated factors with varying tissue-specific importance, which offers numerous possibilities for interactions with melatonin. It is an aim of this review to stimulate research on melatonin signaling in peripheral tissues. This should not be restricted to primary signal molecules but rather include various secondarily connected pathways and discriminate between direct effects of the pineal indoleamine at the target organ and others mediated by modulation of oscillators.
Collapse
Affiliation(s)
- Rüdiger Hardeland
- Johann Friedrich Blumenbach Institute of Zoology and Anthropology, University of Göttingen, Germany.
| | | | | | | |
Collapse
|
159
|
Kröger J, Schulze MB. Recent insights into the relation of Δ5 desaturase and Δ6 desaturase activity to the development of type 2 diabetes. Curr Opin Lipidol 2012; 23:4-10. [PMID: 22123669 DOI: 10.1097/mol.0b013e32834d2dc5] [Citation(s) in RCA: 108] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
PURPOSE OF REVIEW The Δ5 desaturase (D5D) and Δ6 desaturase (D6D) are key enzymes in the metabolism of polyunsaturated fatty acids. This review aims to summarize recent advances towards understanding the relation of the activities of D5D and D6D to the development of type 2 diabetes. RECENT FINDINGS Prospective studies that investigated fatty acid product-to-precursor ratios in blood as estimates of desaturase activity reported a clear inverse relation of D5D activity and a strong direct relation of D6D activity to diabetes incidence. Due to the prospective design and comprehensive confounder adjustment in these studies, confounding and reverse causation are unlikely explanations for these findings. Furthermore, studies on genetic variation in the FADS1 and FADS2 genes, which encode D5D and D6D, also point to an influence of D5D and D6D activity on glucose metabolism. The inverse relation of D5D activity and the direct relation of D6D activity to diabetes risk have been corroborated by a Mendelian randomization approach recently. SUMMARY These recent studies suggest an important role of D5D and D6D activities for the development of type 2 diabetes. Factors which influence the activities of these desaturases are likely to be of public health relevance.
Collapse
Affiliation(s)
- Janine Kröger
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany.
| | | |
Collapse
|
160
|
Walford G, Green T, Neale B, Isakova T, Rotter J, Grant S, Fox C, Pankow J, Wilson J, Meigs J, Siscovick D, Bowden D, Daly M, Florez J. Common genetic variants differentially influence the transition from clinically defined states of fasting glucose metabolism. Diabetologia 2012; 55:331-9. [PMID: 22038522 PMCID: PMC3589986 DOI: 10.1007/s00125-011-2353-8] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/13/2011] [Accepted: 10/06/2011] [Indexed: 02/07/2023]
Abstract
AIMS/HYPOTHESIS Common genetic variants have been associated with type 2 diabetes. We hypothesised that a subset of these variants may have different effects on the transition from normal fasting glucose (NFG) to impaired fasting glucose (IFG) than on that from IFG to diabetes. METHODS We identified 16 type 2 diabetes risk variants from the Illumina Broad Candidate-gene Association Resource (CARe) array genotyped in 26,576 CARe participants. Participants were categorised at baseline as NFG, IFG or type 2 diabetic (n = 16,465, 8,017 or 2,291, respectively). Using Cox proportional hazards and likelihood ratio tests (LRTs), we compared rates of progression by genotype for 4,909 (NFG to IFG) and 1,518 (IFG to type 2 diabetes) individuals, respectively. We then performed multinomial regression analyses at baseline, comparing the risk of assignment to the NFG, IFG or diabetes groups by genotype. RESULTS The rate of progression from NFG to IFG was significantly greater in participants carrying the risk allele at MTNR1B (p = 1 × 10(-4)), nominally greater at GCK and SLC30A8 (p < 0.05) and nominally smaller at IGF2BP2 (p = 0.01) than the rate of progression from IFG to diabetes by the LRT. Results of the baseline, multinomial regression model were consistent with these findings. CONCLUSIONS/INTERPRETATION Common genetic risk variants at GCK, SLC30A8, IGF2BP2 and MTNR1B influence to different extents the development of IFG and the transition from IFG to type 2 diabetes. Our findings may have implications for understanding the genetic contribution of these variants to the development of IFG and type 2 diabetes.
Collapse
Affiliation(s)
- G.A. Walford
- Center for Human Genetic Research, Simches Research Building - CPZN 5.250, Massachusetts General Hospital, 185 Cambridge Street, Boston, MA 02114, USA
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - T. Green
- Center for Human Genetic Research, Simches Research Building - CPZN 5.250, Massachusetts General Hospital, 185 Cambridge Street, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - B. Neale
- Center for Human Genetic Research, Simches Research Building - CPZN 5.250, Massachusetts General Hospital, 185 Cambridge Street, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - T. Isakova
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Renal Unit, Massachusetts General Hospital, Boston, MA, USA
| | - J.I. Rotter
- Medical Genetics Institute, Cedars Sinai Medical Center, Los Angeles, CA, USA
| | - S.F.A. Grant
- Center for Applied Genomics, Division of Human Genetics, Children's Hospital of Philadelphia Research Institute, Philadelphia, PA, USA
- Department of Pediatrics, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - C.S. Fox
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, MA, USA
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - J.S. Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - J.G. Wilson
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Medicine, V.A. Medical Center, Jackson, MS, USA
| | - J.B. Meigs
- General Medicine Division, Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - D.S. Siscovick
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - D.W. Bowden
- Department of Biochemistry, Centers for Human Genomics and Diabetes Research, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - M.J. Daly
- Center for Human Genetic Research, Simches Research Building - CPZN 5.250, Massachusetts General Hospital, 185 Cambridge Street, Boston, MA 02114, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - J.C. Florez
- Center for Human Genetic Research, Simches Research Building - CPZN 5.250, Massachusetts General Hospital, 185 Cambridge Street, Boston, MA 02114, USA
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| |
Collapse
|
161
|
Rees MG, Ng D, Ruppert S, Turner C, Beer NL, Swift AJ, Morken MA, Below JE, Blech I, Mullikin JC, McCarthy MI, Biesecker LG, Gloyn AL, Collins FS. Correlation of rare coding variants in the gene encoding human glucokinase regulatory protein with phenotypic, cellular, and kinetic outcomes. J Clin Invest 2011; 122:205-17. [PMID: 22182842 DOI: 10.1172/jci46425] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2011] [Accepted: 11/09/2011] [Indexed: 01/24/2023] Open
Abstract
Defining the genetic contribution of rare variants to common diseases is a major basic and clinical science challenge that could offer new insights into disease etiology and provide potential for directed gene- and pathway-based prevention and treatment. Common and rare nonsynonymous variants in the GCKR gene are associated with alterations in metabolic traits, most notably serum triglyceride levels. GCKR encodes glucokinase regulatory protein (GKRP), a predominantly nuclear protein that inhibits hepatic glucokinase (GCK) and plays a critical role in glucose homeostasis. The mode of action of rare GCKR variants remains unexplored. We identified 19 nonsynonymous GCKR variants among 800 individuals from the ClinSeq medical sequencing project. Excluding the previously described common missense variant p.Pro446Leu, all variants were rare in the cohort. Accordingly, we functionally characterized all variants to evaluate their potential phenotypic effects. Defects were observed for the majority of the rare variants after assessment of cellular localization, ability to interact with GCK, and kinetic activity of the encoded proteins. Comparing the individuals with functional rare variants to those without such variants showed associations with lipid phenotypes. Our findings suggest that, while nonsynonymous GCKR variants, excluding p.Pro446Leu, are rare in individuals of mixed European descent, the majority do affect protein function. In sum, this study utilizes computational, cell biological, and biochemical methods to present a model for interpreting the clinical significance of rare genetic variants in common disease.
Collapse
Affiliation(s)
- Matthew G Rees
- National Human Genome Research Institute, NIH, Bethesda, Maryland 20892, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
162
|
McCulloch LJ, van de Bunt M, Braun M, Frayn KN, Clark A, Gloyn AL. GLUT2 (SLC2A2) is not the principal glucose transporter in human pancreatic beta cells: implications for understanding genetic association signals at this locus. Mol Genet Metab 2011; 104:648-53. [PMID: 21920790 DOI: 10.1016/j.ymgme.2011.08.026] [Citation(s) in RCA: 125] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/11/2011] [Revised: 08/23/2011] [Accepted: 08/23/2011] [Indexed: 11/30/2022]
Abstract
SLC2A2 encoding glucose transporter -2 (GLUT2) acts as the primary glucose transporter and sensor in rodent pancreatic islets and is widely assumed to play a similar role in humans. In healthy adults SLC2A2 variants are associated with elevated fasting plasma glucose (fpg) concentrations but physiological characterisation does not support a defect in pancreatic beta-cell function. Interspecies differences can create barriers for the follow up of disease association signals. We hypothesised that GLUT2 is not the principal glucose transporter in human beta-cells and that SLC2A2 variants exert their effect on fpg levels through defects in other tissues. SLC2A1-4 (GLUT 1-4) mRNA expression levels were determined in human and mouse islets, beta-cells, liver, muscle and adipose tissue by qRT-PCR whilst GLUT1-3 protein levels were examined by immunohistochemistry. The presence of all three glucose transporters was demonstrated in human and mouse islets and purified beta-cells. Quantitative expression profiling demonstrated that Slc2a2 is the predominant glucose transporter (expression >10 fold higher that Slc2a1) in mouse islets whilst SLC2A1 and SLC2A3 predominate in both human islets and beta-cells (expression 2.8 and 2.7 fold higher than SLC2A2 respectively). Our data therefore suggest that GLUT2 is unlikely to be the principal glucose transporter in human beta-cells and that SLC2A2 defects in other metabolic tissues drive the observed differences in glucose levels between carriers of SLC2A2 variants. Direct extrapolation from rodent to human islet glucose transporter activity is unlikely to be appropriate.
Collapse
Affiliation(s)
- Laura J McCulloch
- Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford, UK
| | | | | | | | | | | |
Collapse
|
163
|
Abstract
A growing need exists to deliver effective and affordable prevention programs and to take urgent action to address the major public health challenge that diabetes represents. Achieving prevention of type 2 diabetes requires moving through a series of steps from basic science discovery to widespread distribution of effective interventions. Understanding the cellular level influences on diabetes prevention will help target particular interventions to those who may be most responsive. Several randomized controlled trials conducted throughout the world have demonstrated that type 2 diabetes can be prevented or delayed. Subsequent real-world translation studies have provided important information necessary to reduce cost and increase access. Ultimately achieving a population impact in diabetes prevention requires widespread distribution of effective interventions, which is supported by policies that help achieve sustainability and reach. The use of a global stakeholder network can help to share experiences and build on partner knowledge gained.
Collapse
Affiliation(s)
- P E H Schwarz
- Division for Prevention and Care of Diabetes Mellitus, Technische Universität Dresden, Germany.
| | | |
Collapse
|
164
|
|
165
|
Wheeler E, Barroso I. Genome-wide association studies and type 2 diabetes. Brief Funct Genomics 2011; 10:52-60. [PMID: 21436302 DOI: 10.1093/bfgp/elr008] [Citation(s) in RCA: 79] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
In recent years, the search for genetic determinants of type 2 diabetes (T2D) has changed dramatically. Although linkage and small-scale candidate gene studies were highly successful in the identification of genes, which, when mutated, caused monogenic forms of T2D, they were largely unsuccessful when applied to the more common forms of the disease. To date, these approaches have only identified two loci (PPARG, KCNJ11) robustly implicated in T2D susceptibility. The ability to perform large-scale association analysis, including genome-wide association studies (GWAS) in many thousands of samples from different populations, and subsequently, the shift to form large international collaborations to perform meta-analyses across many studies has taken the number of independent loci showing genome-wide significant associations with T2D to 44. This number includes six loci identified initially through the analysis of quantitative glycaemic phenotypes, illustrating the usefulness of this approach both to identify new disease genes and gain insight into the mechanisms leading to disease. Combined, these loci still only account for ∼10% of the observed familial clustering in Europeans, leaving much of the variance unexplained. In this review, we will describe what GWAS have taught us about the genetic basis of T2D and discuss possible next steps to uncover the remaining heritability.
Collapse
|
166
|
Strawbridge RJ, Dupuis J, Prokopenko I, Barker A, Ahlqvist E, Rybin D, Petrie JR, Travers ME, Bouatia-Naji N, Dimas AS, Nica A, Wheeler E, Chen H, Voight BF, Taneera J, Kanoni S, Peden JF, Turrini F, Gustafsson S, Zabena C, Almgren P, Barker DJ, Barnes D, Dennison EM, Eriksson JG, Eriksson P, Eury E, Folkersen L, Fox CS, Frayling TM, Goel A, Gu HF, Horikoshi M, Isomaa B, Jackson AU, Jameson KA, Kajantie E, Kerr-Conte J, Kuulasmaa T, Kuusisto J, Loos RJ, Luan J, Makrilakis K, Manning AK, Martínez-Larrad MT, Narisu N, Nastase Mannila M, Öhrvik J, Osmond C, Pascoe L, Payne F, Sayer AA, Sennblad B, Silveira A, Stančáková A, Stirrups K, Swift AJ, Syvänen AC, Tuomi T, van 't Hooft FM, Walker M, Weedon MN, Xie W, Zethelius B, Ongen H, Mälarstig A, Hopewell JC, Saleheen D, Chambers J, Parish S, Danesh J, Kooner J, Östenson CG, Lind L, Cooper CC, Serrano-Ríos M, Ferrannini E, Forsen TJ, Clarke R, Franzosi MG, Seedorf U, Watkins H, Froguel P, Johnson P, Deloukas P, Collins FS, Laakso M, Dermitzakis ET, Boehnke M, McCarthy MI, Wareham NJ, Groop L, Pattou F, Gloyn AL, Dedoussis GV, Lyssenko V, Meigs JB, Barroso I, Watanabe RM, Ingelsson E, Langenberg C, Hamsten A, Florez JC. Genome-wide association identifies nine common variants associated with fasting proinsulin levels and provides new insights into the pathophysiology of type 2 diabetes. Diabetes 2011; 60:2624-34. [PMID: 21873549 PMCID: PMC3178302 DOI: 10.2337/db11-0415] [Citation(s) in RCA: 257] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/23/2011] [Accepted: 06/29/2011] [Indexed: 12/17/2022]
Abstract
OBJECTIVE Proinsulin is a precursor of mature insulin and C-peptide. Higher circulating proinsulin levels are associated with impaired β-cell function, raised glucose levels, insulin resistance, and type 2 diabetes (T2D). Studies of the insulin processing pathway could provide new insights about T2D pathophysiology. RESEARCH DESIGN AND METHODS We have conducted a meta-analysis of genome-wide association tests of ∼2.5 million genotyped or imputed single nucleotide polymorphisms (SNPs) and fasting proinsulin levels in 10,701 nondiabetic adults of European ancestry, with follow-up of 23 loci in up to 16,378 individuals, using additive genetic models adjusted for age, sex, fasting insulin, and study-specific covariates. RESULTS Nine SNPs at eight loci were associated with proinsulin levels (P < 5 × 10(-8)). Two loci (LARP6 and SGSM2) have not been previously related to metabolic traits, one (MADD) has been associated with fasting glucose, one (PCSK1) has been implicated in obesity, and four (TCF7L2, SLC30A8, VPS13C/C2CD4A/B, and ARAP1, formerly CENTD2) increase T2D risk. The proinsulin-raising allele of ARAP1 was associated with a lower fasting glucose (P = 1.7 × 10(-4)), improved β-cell function (P = 1.1 × 10(-5)), and lower risk of T2D (odds ratio 0.88; P = 7.8 × 10(-6)). Notably, PCSK1 encodes the protein prohormone convertase 1/3, the first enzyme in the insulin processing pathway. A genotype score composed of the nine proinsulin-raising alleles was not associated with coronary disease in two large case-control datasets. CONCLUSIONS We have identified nine genetic variants associated with fasting proinsulin. Our findings illuminate the biology underlying glucose homeostasis and T2D development in humans and argue against a direct role of proinsulin in coronary artery disease pathogenesis.
Collapse
Affiliation(s)
- Rona J. Strawbridge
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Josée Dupuis
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts
| | - Inga Prokopenko
- Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford, U.K
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K
| | - Adam Barker
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, U.K
| | - Emma Ahlqvist
- Department of Clinical Sciences, Diabetes and Endocrinology, University Hospital and Malmö, Lund University, Malmö, Sweden
| | - Denis Rybin
- Boston University Data Coordinating Center, Boston, Massachusetts
| | - John R. Petrie
- BHF Cardiovascular Research Centre, University of Glasgow, Glasgow, U.K
| | - Mary E. Travers
- Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford, U.K
| | - Nabila Bouatia-Naji
- Université Lille-Nord de France, Lille, France
- CNRS UMR 8199, Institut Pasteur de Lille, Lille, France
| | - Antigone S. Dimas
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Alexandra Nica
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, U.K
| | - Eleanor Wheeler
- Metabolic Disease Group, Wellcome Trust Sanger Institute, Hinxton, Cambridge, U.K
| | - Han Chen
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Benjamin F. Voight
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Center for Human Genetic Research and Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, Massachusetts
| | - Jalal Taneera
- Department of Clinical Sciences, Diabetes and Endocrinology, University Hospital and Malmö, Lund University, Malmö, Sweden
| | - Stavroula Kanoni
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, U.K
- Department of Dietetics-Nutrition, Harokopio University, Athens, Greece
| | - John F. Peden
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K
- Department of Cardiovascular Medicine, University of Oxford, Oxford, U.K
| | - Fabiola Turrini
- Department of Clinical Sciences, Diabetes and Endocrinology, University Hospital and Malmö, Lund University, Malmö, Sweden
- Department of Medicine, University of Verona, Verona, Italy
| | - Stefan Gustafsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Carina Zabena
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, Spain
- Fundación Investigación Biomédica del Hospital Clínico San Carlos, Madrid, Spain
| | - Peter Almgren
- Department of Clinical Sciences, Diabetes and Endocrinology, University Hospital and Malmö, Lund University, Malmö, Sweden
| | - David J.P. Barker
- Heart Research Center, Oregon Health and Science University, Portland, Oregon
| | - Daniel Barnes
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, U.K
| | - Elaine M. Dennison
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, U.K
| | - Johan G. Eriksson
- National Institute for Health and Welfare, Helsinki, Finland
- Helsinki University Central Hospital, Unit of General Practice, Helsinki, Finland
- Folkhälsan Research Centre, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
| | - Per Eriksson
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Elodie Eury
- Université Lille-Nord de France, Lille, France
- CNRS UMR 8199, Institut Pasteur de Lille, Lille, France
| | - Lasse Folkersen
- Experimental Cardiovascular Research Unit, Department of Medicine Solna, Karolinska Institutet, Stockholm, Sweden
| | - Caroline S. Fox
- National Heart, Lung, and Blood Institute’s Framingham Heart Study, Framingham, Massachusetts
- Division of Endocrinology, Diabetes, and Hypertension, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Timothy M. Frayling
- Institute of Biomedical and Clinical Sciences, Peninsula Medical School, University of Exeter, Exeter, U.K
| | - Anuj Goel
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K
- Department of Cardiovascular Medicine, University of Oxford, Oxford, U.K
| | - Harvest F. Gu
- Endocrinology and Diabetes Unit, Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Momoko Horikoshi
- Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford, U.K
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K
| | - Bo Isomaa
- Folkhälsan Research Centre, Helsinki, Finland
- Malmska Municipal Health Care Center and Hospital, Jakobstad, Finland
| | - Anne U. Jackson
- Center for Statistical Genetics, Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan
| | - Karen A. Jameson
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, U.K
| | - Eero Kajantie
- National Institute for Health and Welfare, Helsinki, Finland
- Hospital for Children and Adolescents, Helsinki University Central Hospital and University of Helsinki, Helsinki, Finland
| | - Julie Kerr-Conte
- Université Lille-Nord de France, Lille, France
- INSERM UMR 859, Lille, France
| | - Teemu Kuulasmaa
- Department of Medicine, University of Kuopio and Kuopio University Hospital, Kuopio, Finland
| | - Johanna Kuusisto
- Department of Medicine, University of Kuopio and Kuopio University Hospital, Kuopio, Finland
| | - Ruth J.F. Loos
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, U.K
| | - Jian'an Luan
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, U.K
| | - Konstantinos Makrilakis
- First Department of Propaedeutic Medicine, Laiko General Hospital, Athens University Medical School, Athens, Greece
| | - Alisa K. Manning
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - María Teresa Martínez-Larrad
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, Spain
- Fundación Investigación Biomédica del Hospital Clínico San Carlos, Madrid, Spain
| | - Narisu Narisu
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Maria Nastase Mannila
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital Solna, Stockholm, Sweden
| | - John Öhrvik
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Clive Osmond
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, U.K
| | - Laura Pascoe
- Institute of Cell and Molecular Biosciences, Newcastle University, Newcastle, U.K
| | - Felicity Payne
- Metabolic Disease Group, Wellcome Trust Sanger Institute, Hinxton, Cambridge, U.K
| | - Avan A. Sayer
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, U.K
| | - Bengt Sennblad
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Angela Silveira
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Alena Stančáková
- Department of Medicine, University of Kuopio and Kuopio University Hospital, Kuopio, Finland
| | - Kathy Stirrups
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, U.K
| | - Amy J. Swift
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Ann-Christine Syvänen
- Department of Medical Sciences, Molecular Medicine, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Tiinamaija Tuomi
- Folkhälsan Research Centre, Helsinki, Finland
- Department of Medicine, Helsinki University Central Hospital, and Research Program of Molecular Medicine, University of Helsinki, Helsinki, Finland
| | - Ferdinand M. van 't Hooft
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Mark Walker
- Institute of Cellular Medicine, Newcastle University, Newcastle, U.K
| | - Michael N. Weedon
- Institute of Biomedical and Clinical Sciences, Peninsula Medical School, University of Exeter, Exeter, U.K
| | - Weijia Xie
- Institute of Biomedical and Clinical Sciences, Peninsula Medical School, University of Exeter, Exeter, U.K
| | - Björn Zethelius
- Department of Public Health and Caring Sciences, Uppsala University, Uppsala, Sweden
| | | | | | | | | | | | - Halit Ongen
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K
- Department of Cardiovascular Medicine, University of Oxford, Oxford, U.K
- Department of Cardiovascular Medicine, University of Oxford, John Radcliffe Hospital, Headington, Oxford, U.K
| | - Anders Mälarstig
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital Solna, Stockholm, Sweden
| | | | - Danish Saleheen
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, U.K
- Center for Non-Communicable Diseases Pakistan, Karachi, Pakistan
| | - John Chambers
- Epidemiology and Biostatistics, Imperial College London, Norfolk Place, London, U.K
- Cardiology, Ealing Hospital NHS Trust, Middlesex, U.K
| | - Sarah Parish
- Clinical Trial Service Unit, University of Oxford, Oxford, U.K
| | - John Danesh
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, U.K
| | - Jaspal Kooner
- Cardiology, Ealing Hospital NHS Trust, Middlesex, U.K
- National Heart and Lung Institute, Imperial College London, London, U.K
| | - Claes-Göran Östenson
- Endocrinology and Diabetes Unit, Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Lars Lind
- Department of Medical Sciences, Molecular Medicine, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Cyrus C. Cooper
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, U.K
| | - Manuel Serrano-Ríos
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas (CIBERDEM), Madrid, Spain
- Fundación Investigación Biomédica del Hospital Clínico San Carlos, Madrid, Spain
| | - Ele Ferrannini
- Department of Internal Medicine and CNR Institute of Clinical Physiology, University of Pisa School of Medicine, Pisa, Italy
| | - Tom J. Forsen
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Vaasa Health Care Center, Vaasa, Finland
| | - Robert Clarke
- Clinical Trial Service Unit, University of Oxford, Oxford, U.K
| | - Maria Grazia Franzosi
- Department of Cardiovascular Research, Mario Negri Institute for Pharmacological Research, Milan, Italy
| | - Udo Seedorf
- Leibniz Institute for Arteriosclerosis Research, University of Münster, Münster, Germany
| | - Hugh Watkins
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K
- Department of Cardiovascular Medicine, University of Oxford, Oxford, U.K
| | - Philippe Froguel
- Université Lille-Nord de France, Lille, France
- CNRS UMR 8199, Institut Pasteur de Lille, Lille, France
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, U.K
| | - Paul Johnson
- Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford, U.K
- DRWF Human Islet Isolation Facility and Oxford Islet Transplant Programme, University of Oxford, Oxford, U.K
| | - Panos Deloukas
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, U.K
| | | | - Markku Laakso
- Department of Medicine, University of Kuopio and Kuopio University Hospital, Kuopio, Finland
| | - Emmanouil T. Dermitzakis
- Department of Genetic Medicine and Development, University of Geneva Medical School, Geneva, Switzerland
| | - Michael Boehnke
- Center for Statistical Genetics, Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor, Michigan
| | - Mark I. McCarthy
- Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford, U.K
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, U.K
| | - Nicholas J. Wareham
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, U.K
| | - Leif Groop
- Department of Clinical Sciences, Diabetes and Endocrinology, University Hospital and Malmö, Lund University, Malmö, Sweden
| | - François Pattou
- Université Lille-Nord de France, Lille, France
- INSERM UMR 859, Lille, France
| | - Anna L. Gloyn
- Oxford Centre for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford, U.K
| | | | - Valeriya Lyssenko
- Department of Clinical Sciences, Diabetes and Endocrinology, University Hospital and Malmö, Lund University, Malmö, Sweden
| | - James B. Meigs
- General Medicine Division, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| | - Inês Barroso
- Metabolic Disease Group, Wellcome Trust Sanger Institute, Hinxton, Cambridge, U.K
- University of Cambridge Metabolic Research Laboratories, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, U.K
| | - Richard M. Watanabe
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, California
- Department of Physiology and Biophysics, Keck School of Medicine, University of Southern California, Los Angeles, California
| | - Erik Ingelsson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Claudia Langenberg
- MRC Epidemiology Unit, Institute of Metabolic Science, Addenbrooke's Hospital, Cambridge, U.K
| | - Anders Hamsten
- Atherosclerosis Research Unit, Department of Medicine Solna, Karolinska Institutet, Karolinska University Hospital Solna, Stockholm, Sweden
| | - Jose C. Florez
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
- Center for Human Genetic Research and Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
| |
Collapse
|
167
|
Ketterer C, Müssig K, Heni M, Dudziak K, Randrianarisoa E, Wagner R, Machicao F, Stefan N, Holst JJ, Fritsche A, Häring HU, Staiger H. Genetic variation within the TRPM5 locus associates with prediabetic phenotypes in subjects at increased risk for type 2 diabetes. Metabolism 2011; 60:1325-33. [PMID: 21489577 DOI: 10.1016/j.metabol.2011.02.002] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/23/2010] [Revised: 01/28/2011] [Accepted: 02/04/2011] [Indexed: 01/17/2023]
Abstract
The functional knockout of the calcium-sensitive, nonselective cation channel TRPM5 alters glucose-induced insulin secretion and glucose tolerance. We hypothesized that genetic variation in the TRPM5 gene may contribute to prediabetic phenotypes, including pancreatic β-cell dysfunction. We genotyped 1798 white subjects at increased type 2 diabetes mellitus risk for 9 TRPM5 single nucleotide polymorphisms (namely, rs2301696, rs800344, rs800345, rs800347, rs800348, rs2074234, rs2301698, rs886277, and rs2301699) and also performed correlational analyses with metabolic traits. An oral glucose tolerance test (OGTT) was conducted on all subjects, and a subset (n = 525) additionally underwent a hyperinsulinemic-euglycemic clamp. The 9 chosen single nucleotide polymorphisms cover 100% of the common genetic variation (minor allele frequency ≥0.05) within the TRPM5 locus (D' = 1.0; r² ≥ 0.8). Rs800344, rs800345, and rs2301699 were significantly associated with area under the curve (AUC) glucose during the OGTT in the additive and dominant models after adjustment for sex, age, and body mass index (all Ps ≤ .0025). Furthermore, rs800344 was significantly associated with 2-hour glucose in the dominant model (P = .0009). After stratification for sex, rs2301699 was significantly associated with the ratio of AUC insulin 0 to 30 minutes to AUC glucose 0 to 30 minutes in women (P = .0097), but not in men (P = .3), in the dominant model. Female minor allele carriers of rs2301699 showed significantly lower glucagon-like peptide-1 levels at 30 minutes during the OGTT compared with major allele homozygotes (P = .0124), whereas in male subjects, no significant differences were found (P = .3). In our German population, the common TRPM5 variants are likely to be associated with prediabetic phenotypes; and this may in turn contribute to the development of type 2 diabetes mellitus.
Collapse
Affiliation(s)
- Caroline Ketterer
- Division of Endocrinology, Diabetology, Angiology, Nephrology, and Clinical Chemistry, Department of Internal Medicine, Eberhard Karls University Tübingen, Otfried-Müller-Str. 10, 72076 Tübingen, Germany
| | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
168
|
Wagner R, Dudziak K, Herzberg-Schäfer SA, Machicao F, Stefan N, Staiger H, Häring HU, Fritsche A. Glucose-raising genetic variants in MADD and ADCY5 impair conversion of proinsulin to insulin. PLoS One 2011; 6:e23639. [PMID: 21887289 PMCID: PMC3161735 DOI: 10.1371/journal.pone.0023639] [Citation(s) in RCA: 34] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2011] [Accepted: 07/21/2011] [Indexed: 01/13/2023] Open
Abstract
Introduction Recent meta-analyses of genome-wide association studies revealed new genetic loci associated with fasting glycemia. For several of these loci, the mechanism of action in glucose homeostasis is unclear. The objective of the study was to establish metabolic phenotypes for these genetic variants to deliver clues to their pathomechanism. Methods In this cross-sectional study 1782 non-diabetic volunteers at increased risk for type 2 diabetes underwent an oral glucose tolerance test. Insulin, C-peptide and proinsulin were measured and genotyping was performed for 12 single nucleotide polymorphisms (SNP) in or near the genes GCK (rs4607517), DGKB (rs2191349), GCKR (rs780094), ADCY5 (rs11708067), MADD (rs7944584), ADRA2A (rs10885122), FADS1 (rs174550), CRY2 (rs11605924), SLC2A2 (rs11920090), PROX1 (rs340874), GLIS3 (rs7034200) and C2CD4B (rs11071657). Parameters of insulin secretion (AUC Insulin0–30/AUC Glucose0–30, AUC C-peptide0–120/AUC Glucose0–120), proinsulin-to-insulin conversion (fasting proinsulin, fasting proinsulin/insulin, AUC Proinsulin0–120/AUCInsulin0–120) and insulin resistance (HOMA-IR, Matsuda-Index) were assessed. Results After adjustment for confounding variables, the effect alleles of the ADCY5 and MADD SNPs were associated with an impaired proinsulin-to-insulin conversion (p = 0.002 and p = 0.0001, respectively). GLIS3 was nominally associated with impaired proinsulin-to-insulin conversion and insulin secretion. The diabetogenic alleles of DGKB and PROX1 were nominally associated with reduced insulin secretion. Nominally significant effects on insulin sensitivity could be found for MADD and PROX1. Discussion By examining parameters of glucose-stimulated proinsulin-to-insulin conversion during an OGTT, we show that the SNP in ADCY5 is implicated in defective proinsulin-to-insulin conversion. In addition, we confirmed previous findings on the role of a genetic variant in MADD on proinsulin-to-insulin conversion. These effects may also be related to neighboring regions of the genome.
Collapse
Affiliation(s)
- Robert Wagner
- Department of Internal Medicine, Division of Endocrinology, Diabetology, Angiology, Nephrology and Clinical Chemistry, Eberhard Karls University Tübingen, Member of the German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Katarzyna Dudziak
- Department of Internal Medicine, Division of Endocrinology, Diabetology, Angiology, Nephrology and Clinical Chemistry, Eberhard Karls University Tübingen, Member of the German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Silke A. Herzberg-Schäfer
- Department of Internal Medicine, Division of Endocrinology, Diabetology, Angiology, Nephrology and Clinical Chemistry, Eberhard Karls University Tübingen, Member of the German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Fausto Machicao
- Department of Internal Medicine, Division of Endocrinology, Diabetology, Angiology, Nephrology and Clinical Chemistry, Eberhard Karls University Tübingen, Member of the German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Norbert Stefan
- Department of Internal Medicine, Division of Endocrinology, Diabetology, Angiology, Nephrology and Clinical Chemistry, Eberhard Karls University Tübingen, Member of the German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Harald Staiger
- Department of Internal Medicine, Division of Endocrinology, Diabetology, Angiology, Nephrology and Clinical Chemistry, Eberhard Karls University Tübingen, Member of the German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Hans-Ulrich Häring
- Department of Internal Medicine, Division of Endocrinology, Diabetology, Angiology, Nephrology and Clinical Chemistry, Eberhard Karls University Tübingen, Member of the German Center for Diabetes Research (DZD), Tübingen, Germany
| | - Andreas Fritsche
- Department of Internal Medicine, Division of Endocrinology, Diabetology, Angiology, Nephrology and Clinical Chemistry, Eberhard Karls University Tübingen, Member of the German Center for Diabetes Research (DZD), Tübingen, Germany
- Department of Internal Medicine, Division of Nutritional and Preventive Medicine, Tübingen, Germany
- * E-mail:
| |
Collapse
|
169
|
Sousa AG, Selvatici L, Krieger JE, Pereira AC. Association between genetics of diabetes, coronary artery disease, and macrovascular complications: exploring a common ground hypothesis. Rev Diabet Stud 2011; 8:230-44. [PMID: 22189546 DOI: 10.1900/rds.2011.8.230] [Citation(s) in RCA: 23] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/06/2023] Open
Abstract
Type 2 diabetes and coronary artery disease (CAD) are conditions that cause a substantial public health burden. Since both conditions often coexist in the same individual, it has been hypothesized that they have a common effector. Insulin and hyperglycemia are assumed to play critical roles in this scenario. In recent years, many genetic risk factors for both diabetes and CAD have been discovered, mainly through genome-wide association studies. Genetic aspects of diabetes, diabetic macrovascular complications, and CAD are assumed to have intersections leading to the common effector hypothesis. However, only a few genetic risk factors could be identified that modulate the risk for both conditions. Polymorphisms in TCF7L2 and near the CDKN2A/B genes seem to be of great importance in this regard since they appear to modulate both conditions, and they are not necessarily related to insulinism, or hyperglycemia, for CAD development. Other issues related to this hypothesis, such as the problems of phenotype heterogeneity, are also of interest. Recent studies have contributed to a better understanding of the complex genetics of diabetic macrovascular complications. Much effort is still needed to clarify the associations in the genetics of diabetes, and cardiovascular disease. At present, there is little genetic evidence to support a common effector hypothesis, other than insulin or hyperglycemia, for the association between these conditions.
Collapse
Affiliation(s)
- André G Sousa
- Laboratory of Genetics and Molecular Cardiology, Heart Institute, University of Sao Paulo Medical School, Sao Paulo, Brazil
| | | | | | | |
Collapse
|
170
|
Windholz J, Kovacs P, Tönjes A, Dittrich K, Blüher S, Kiess W, Stumvoll M, Körner A. Effects of genetic variants in ADCY5, GIPR, GCKR and VPS13C on early impairment of glucose and insulin metabolism in children. PLoS One 2011; 6:e22101. [PMID: 21789219 PMCID: PMC3137620 DOI: 10.1371/journal.pone.0022101] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2011] [Accepted: 06/17/2011] [Indexed: 02/07/2023] Open
Abstract
Objective Recent genome-wide association studies identified novel candidate genes for fasting and 2 h blood glucose and insulin levels in adults. We investigated the role of four of these loci (ADCY5, GIPR, GCKR and VPS13C) in early impairment of glucose and insulin metabolism in children. Research Design and Methods We genotyped four variants (rs2877716; rs1260326; rs10423928; rs17271305) in 638 Caucasian children with detailed metabolic testing including an oGTT and assessed associations with measures of glucose and insulin metabolism (including fasting blood glucose, insulin levels and insulin sensitivity/secretion indices) by linear regression analyses adjusted for age, sex, BMI-SDS and pubertal stage. Results The major allele (C) of rs2877716 (ADCY5) was nominally associated with decreased fasting plasma insulin (P = 0.008), peak insulin (P = 0.009) and increased QUICKI (P = 0.016) and Matsuda insulin sensitivity index (P = 0.013). rs17271305 (VPS13C) was nominally associated with 2 h blood glucose (P = 0.009), but not with any of the insulin or insulin sensitivity parameters. We found no association of the GIPR and GCKR variants with parameters of glucose and insulin metabolism. None of the variants correlated with anthropometric traits such as height, WHR or BMI-SDS, which excluded potential underlying associations with obesity. Conclusions Our data on obese children indicate effects of genetic variation within ADCY5 in early impairment of insulin metabolism and VPS13C in early impairment of blood glucose homeostasis.
Collapse
Affiliation(s)
- Jan Windholz
- University Hospital for Children and Adolescents, University of Leipzig, Leipzig, Germany
| | - Peter Kovacs
- Interdisciplinary Center for Clinical Research, University of Leipzig, Leipzig, Germany
- * E-mail:
| | - Anke Tönjes
- Department of Medicine, University of Leipzig, Leipzig, Germany
- Leipzig University Medical Center, IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
| | - Kathrin Dittrich
- University Hospital for Children and Adolescents, University of Leipzig, Leipzig, Germany
| | - Susann Blüher
- University Hospital for Children and Adolescents, University of Leipzig, Leipzig, Germany
- Leipzig University Medical Center, IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
| | - Wieland Kiess
- University Hospital for Children and Adolescents, University of Leipzig, Leipzig, Germany
| | - Michael Stumvoll
- Department of Medicine, University of Leipzig, Leipzig, Germany
- Leipzig University Medical Center, IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
| | - Antje Körner
- University Hospital for Children and Adolescents, University of Leipzig, Leipzig, Germany
- Leipzig University Medical Center, IFB Adiposity Diseases, University of Leipzig, Leipzig, Germany
| |
Collapse
|
171
|
Silbernagel G, Renner W, Grammer TB, Hügl SR, Bertram J, Kleber ME, Hoffmann MM, Winkelmann BR, März W, Boehm BO. Association of TCF7L2 SNPs with age at onset of type 2 diabetes and proinsulin/insulin ratio but not with glucagon-like peptide 1. Diabetes Metab Res Rev 2011; 27:499-505. [PMID: 21384500 DOI: 10.1002/dmrr.1194] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Variants in TCF7L2 have been associated with the age at onset of type 2 diabetes in Mexican Americans. However, there is a lack of data on this relationship in Caucasians. Furthermore, risk alleles in TCF7L2 have been suggested to account for decreased conversion of proinsulin to insulin and decreased expression of GLP-1. We investigated the effect of the allelic variants rs1225537 and rs7903146 in TCF7L2 on the age at onset of type 2 diabetes, the plasma concentrations of proinsulin and GLP-1, and the ratio of proinsulin to insulin in a German cohort. METHODS We studied 3185 participants of the LUdwigshafen RIsk and Cardiovascular health (LURIC) study. Among these, 1021 subjects had type 2 diabetes. Data on age at onset of diabetes were available in 925 subjects. OGTTs were performed in a subgroup not previously known to have diabetes. RESULTS Carriers of the risk alleles in rs1225537 and rs7901346 had increased risk of type 2 diabetes and elevated HbA(1c) (all p < 0.001). The risk alleles were also associated with early onset of type 2 diabetes, decreased insulin secretion and markedly increased proinsulin and proinsulin to insulin ratio (all p < 0.03). GLP-1 was not significantly related to the TCF7L2 genotype. CONCLUSIONS Our data demonstrate that TCF7L2 variants are associated with an early age of onset of type 2 diabetes in Caucasians and affects the conversion of proinsulin to insulin. However, TCF7L2 is not consistently associated with fasting GLP-1.
Collapse
Affiliation(s)
- Guenther Silbernagel
- Department of Internal Medicine, Division of Endocrinology, Diabetology, Nephrology, Vascular Disease, and Clinical Chemistry, Eberhard-Karls-University Tübingen, Tübingen, Germany
| | | | | | | | | | | | | | | | | | | |
Collapse
|
172
|
Barker A, Sharp SJ, Timpson NJ, Bouatia-Naji N, Warrington NM, Kanoni S, Beilin LJ, Brage S, Deloukas P, Evans DM, Grontved A, Hassanali N, Lawlor DA, Lecoeur C, Loos RJ, Lye SJ, McCarthy MI, Mori TA, Ndiaye NC, Newnham JP, Ntalla I, Pennell CE, St Pourcain B, Prokopenko I, Ring SM, Sattar N, Visvikis-Siest S, Dedoussis GV, Palmer LJ, Froguel P, Smith GD, Ekelund U, Wareham NJ, Langenberg C. Association of genetic Loci with glucose levels in childhood and adolescence: a meta-analysis of over 6,000 children. Diabetes 2011; 60:1805-12. [PMID: 21515849 PMCID: PMC3114379 DOI: 10.2337/db10-1575] [Citation(s) in RCA: 91] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
OBJECTIVE To investigate whether associations of common genetic variants recently identified for fasting glucose or insulin levels in nondiabetic adults are detectable in healthy children and adolescents. RESEARCH DESIGN AND METHODS A total of 16 single nucleotide polymorphisms (SNPs) associated with fasting glucose were genotyped in six studies of children and adolescents of European origin, including over 6,000 boys and girls aged 9-16 years. We performed meta-analyses to test associations of individual SNPs and a weighted risk score of the 16 loci with fasting glucose. RESULTS Nine loci were associated with glucose levels in healthy children and adolescents, with four of these associations reported in previous studies and five reported here for the first time (GLIS3, PROX1, SLC2A2, ADCY5, and CRY2). Effect sizes were similar to those in adults, suggesting age-independent effects of these fasting glucose loci. Children and adolescents carrying glucose-raising alleles of G6PC2, MTNR1B, GCK, and GLIS3 also showed reduced β-cell function, as indicated by homeostasis model assessment of β-cell function. Analysis using a weighted risk score showed an increase [β (95% CI)] in fasting glucose level of 0.026 mmol/L (0.021-0.031) for each unit increase in the score. CONCLUSIONS Novel fasting glucose loci identified in genome-wide association studies of adults are associated with altered fasting glucose levels in healthy children and adolescents with effect sizes comparable to adults. In nondiabetic adults, fasting glucose changes little over time, and our results suggest that age-independent effects of fasting glucose loci contribute to long-term interindividual differences in glucose levels from childhood onwards.
Collapse
Affiliation(s)
- Adam Barker
- Medical Research Council Epidemiology Unit, Addenbrooke’s Hospital, Institute of Metabolic Science, Cambridge, U.K
| | - Stephen J. Sharp
- Medical Research Council Epidemiology Unit, Addenbrooke’s Hospital, Institute of Metabolic Science, Cambridge, U.K
| | - Nicholas J. Timpson
- MRC Centre for Causal Analyses in Translational Epidemiology (MRC CAiTE), University of Bristol, Bristol, U.K
- School of Social and Community Medicine, University of Bristol, Bristol, U.K
| | - Nabila Bouatia-Naji
- CNRS UMR 8199, Institut Pasteur de Lille, Lille, France
- Lille Nord de France University, Lille, France
| | - Nicole M. Warrington
- School of Women’s and Infants’ Health, The University of Western Australia, Perth, Western Australia
| | - Stavroula Kanoni
- Department of Nutrition-Dietetics, Harokopio University, Athens, Greece
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, U.K
| | - Lawrence J. Beilin
- School of Medicine and Pharmacology, The University of Western Australia, Perth, Western Australia
| | - Soren Brage
- Medical Research Council Epidemiology Unit, Addenbrooke’s Hospital, Institute of Metabolic Science, Cambridge, U.K
| | - Panos Deloukas
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, U.K
| | - David M. Evans
- MRC Centre for Causal Analyses in Translational Epidemiology (MRC CAiTE), University of Bristol, Bristol, U.K
- School of Social and Community Medicine, University of Bristol, Bristol, U.K
| | | | - Neelam Hassanali
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, U.K
| | - Deborah A. Lawlor
- MRC Centre for Causal Analyses in Translational Epidemiology (MRC CAiTE), University of Bristol, Bristol, U.K
- School of Social and Community Medicine, University of Bristol, Bristol, U.K
| | - Cecile Lecoeur
- CNRS UMR 8199, Institut Pasteur de Lille, Lille, France
- Lille Nord de France University, Lille, France
| | - Ruth J.F. Loos
- Medical Research Council Epidemiology Unit, Addenbrooke’s Hospital, Institute of Metabolic Science, Cambridge, U.K
| | - Stephen J. Lye
- Samuel Lunenfeld Research Institute, Mount Sinai Hospital, University of Toronto, Toronto, Canada
| | - Mark I. McCarthy
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, U.K
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K
| | - Trevor A. Mori
- School of Medicine and Pharmacology, The University of Western Australia, Perth, Western Australia
| | - Ndeye Coumba Ndiaye
- “Cardiovascular Genetics” Research Unit, Université Henri Poincaré, Nancy, France
| | - John P. Newnham
- School of Women’s and Infants’ Health, The University of Western Australia, Perth, Western Australia
| | - Ioanna Ntalla
- Department of Nutrition-Dietetics, Harokopio University, Athens, Greece
| | - Craig E. Pennell
- School of Women’s and Infants’ Health, The University of Western Australia, Perth, Western Australia
| | - Beate St Pourcain
- School of Social and Community Medicine, University of Bristol, Bristol, U.K
- The Avon Longitudinal Study of Parents and Children, University of Bristol, Bristol, U.K
| | - Inga Prokopenko
- Oxford Centre for Diabetes, Endocrinology and Metabolism, University of Oxford, Oxford, U.K
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, U.K
| | - Susan M. Ring
- School of Social and Community Medicine, University of Bristol, Bristol, U.K
- The Avon Longitudinal Study of Parents and Children, University of Bristol, Bristol, U.K
| | - Naveed Sattar
- British Heart Foundation Glasgow Cardiovascular Research Centre, University of Glasgow, Glasgow, U.K
| | | | | | - Lyle J. Palmer
- Ontario Institute for Cancer Research, University of Toronto, Toronto, Canada
| | - Philippe Froguel
- CNRS UMR 8199, Institut Pasteur de Lille, Lille, France
- Lille Nord de France University, Lille, France
- Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, U.K
| | - George Davey Smith
- MRC Centre for Causal Analyses in Translational Epidemiology (MRC CAiTE), University of Bristol, Bristol, U.K
- School of Social and Community Medicine, University of Bristol, Bristol, U.K
| | - Ulf Ekelund
- Medical Research Council Epidemiology Unit, Addenbrooke’s Hospital, Institute of Metabolic Science, Cambridge, U.K
- School of Health and Medical Sciences, Örebro University, Örebro, Sweden
| | - Nicholas J. Wareham
- Medical Research Council Epidemiology Unit, Addenbrooke’s Hospital, Institute of Metabolic Science, Cambridge, U.K
| | - Claudia Langenberg
- Medical Research Council Epidemiology Unit, Addenbrooke’s Hospital, Institute of Metabolic Science, Cambridge, U.K
- Corresponding author: Claudia Langenberg,
| |
Collapse
|
173
|
Simonis-Bik AMC, Boomsma DI, Dekker JM, Diamant M, de Geus EJC, 't Hart LM, Heine RJ, Kramer MHH, Maassen JA, Mari A, Tura A, Willemsen G, Eekhoff EMW. The heritability of beta cell function parameters in a mixed meal test design. Diabetologia 2011; 54:1043-51. [PMID: 21311857 PMCID: PMC3071945 DOI: 10.1007/s00125-011-2060-5] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/01/2010] [Accepted: 01/04/2011] [Indexed: 01/26/2023]
Abstract
AIMS/HYPOTHESIS We estimated the heritability of individual differences in beta cell function after a mixed meal test designed to assess a wide range of classical and model-derived beta cell function parameters. METHODS A total of 183 healthy participants (77 men), recruited from the Netherlands Twin Register, took part in a 4 h protocol, which included a mixed meal test. Participants were Dutch twin pairs and their siblings, aged 20 to 49 years. All members within a family were of the same sex. Insulin sensitivity, insulinogenic index, insulin response and postprandial glycaemia were assessed, as well as model-derived parameters of beta cell function, in particular beta cell glucose sensitivity and insulin secretion rates. Genetic modelling provided the heritability of all traits. Multivariate genetic analyses were performed to test for overlap in the genetic factors influencing beta cell function, waist circumference and insulin sensitivity. RESULTS Significant heritabilities were found for insulinogenic index (63%), beta cell glucose sensitivity (50%), insulin secretion during the first 2 h postprandial (42-47%) and postprandial glycaemia (43-52%). Genetic factors influencing beta cell glucose sensitivity and insulin secretion during the first 30 postprandial min showed only negligible overlap with the genetic factors that influence waist circumference and insulin sensitivity. CONCLUSIONS/INTERPRETATION The highest heritability for postprandial beta cell function was found for the insulinogenic index, but the most specific indices of heritability of beta cell function appeared to be beta cell glucose sensitivity and the insulin secretion rate during the first 30 min after a mixed meal.
Collapse
Affiliation(s)
- A M C Simonis-Bik
- Diabetes Center, VU University Medical Center, ZH 4A62, PO Box 7057, 1007 MB, Amsterdam, the Netherlands.
| | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
174
|
Stančáková A, Paananen J, Soininen P, Kangas AJ, Bonnycastle LL, Morken MA, Collins FS, Jackson AU, Boehnke ML, Kuusisto J, Ala-Korpela M, Laakso M. Effects of 34 risk loci for type 2 diabetes or hyperglycemia on lipoprotein subclasses and their composition in 6,580 nondiabetic Finnish men. Diabetes 2011; 60:1608-16. [PMID: 21421807 PMCID: PMC3292337 DOI: 10.2337/db10-1655] [Citation(s) in RCA: 64] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
OBJECTIVE We investigated the effects of 34 genetic risk variants for hyperglycemia/type 2 diabetes on lipoprotein subclasses and particle composition in a large population-based cohort. RESEARCH DESIGN AND METHODS The study included 6,580 nondiabetic Finnish men from the population-based Metabolic Syndrome in Men (METSIM) study (aged 57 ± 7 years; BMI 26.8 ± 3.7 kg/m(2)). Genotyping of 34 single nucleotide polymorphism (SNPs) for hyperglycemia/type 2 diabetes was performed. Proton nuclear magnetic resonance spectroscopy was used to measure particle concentrations of 14 lipoprotein subclasses and their composition in native serum samples. RESULTS The glucose-increasing allele of rs780094 in GCKR was significantly associated with low concentrations of VLDL particles (independently of their size) and small LDL and was nominally associated with low concentrations of intermediate-density lipoprotein, all LDL subclasses, and high concentrations of very large and large HDL particles. The glucose-increasing allele of rs174550 in FADS1 was significantly associated with high concentrations of very large and large HDL particles and nominally associated with low concentrations of all VLDL particles. SNPs rs10923931 in NOTCH2 and rs757210 in HNF1B genes showed nominal or significant associations with several lipoprotein traits. The genetic risk score of 34 SNPs was not associated with any of the lipoprotein subclasses. CONCLUSIONS Four of the 34 risk loci for type 2 diabetes or hyperglycemia (GCKR, FADS1, NOTCH2, and HNF1B) were significantly associated with lipoprotein traits. A GCKR variant predominantly affected the concentration of VLDL, and the FADS1 variant affected very large and large HDL particles. Only a limited number of risk loci for hyperglycemia/type 2 diabetes significantly affect lipoprotein metabolism.
Collapse
MESH Headings
- Adaptor Proteins, Signal Transducing/genetics
- Cholesterol, VLDL/blood
- Delta-5 Fatty Acid Desaturase
- Diabetes Mellitus, Type 2/blood
- Diabetes Mellitus, Type 2/genetics
- Fatty Acid Desaturases/blood
- Genotype
- Humans
- Hyperglycemia/blood
- Hyperglycemia/genetics
- Lipoproteins, HDL/blood
- Lipoproteins, IDL/blood
- Lipoproteins, LDL/blood
- Lipoproteins, VLDL/blood
- Magnetic Resonance Spectroscopy
- Male
- Middle Aged
- Polymorphism, Single Nucleotide/genetics
- Receptor, Notch2/blood
- White People
Collapse
Affiliation(s)
- Alena Stančáková
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Jussi Paananen
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Pasi Soininen
- Computational Medicine Research Group, Institute of Clinical Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland
- NMR Metabonomics Laboratory, Laboratory of Chemistry, Department of Biosciences, University of Eastern Finland, Kuopio, Finland
| | - Antti J. Kangas
- Computational Medicine Research Group, Institute of Clinical Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland
| | - Lori L. Bonnycastle
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Mario A. Morken
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Francis S. Collins
- National Human Genome Research Institute, National Institutes of Health, Bethesda, Maryland
| | - Anne U. Jackson
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan
| | - Michael L. Boehnke
- Center for Statistical Genetics, Department of Biostatistics, University of Michigan School of Public Health, Ann Arbor, Michigan
| | - Johanna Kuusisto
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Mika Ala-Korpela
- Computational Medicine Research Group, Institute of Clinical Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland
- NMR Metabonomics Laboratory, Laboratory of Chemistry, Department of Biosciences, University of Eastern Finland, Kuopio, Finland
- Department of Internal Medicine and Biocenter Oulu, Clinical Research Center, University of Oulu, Oulu, Finland
| | - Markku Laakso
- Department of Medicine, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
- Corresponding author: Markku Laakso,
| |
Collapse
|
175
|
Kim OY, Lim HH, Yang LI, Chae JS, Lee JH. Fatty acid desaturase (FADS) gene polymorphisms and insulin resistance in association with serum phospholipid polyunsaturated fatty acid composition in healthy Korean men: cross-sectional study. Nutr Metab (Lond) 2011; 8:24. [PMID: 21513558 PMCID: PMC3111337 DOI: 10.1186/1743-7075-8-24] [Citation(s) in RCA: 30] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2010] [Accepted: 04/23/2011] [Indexed: 11/15/2022] Open
Abstract
Background We investigated the relationship between fatty acid desaturase (FADS) gene polymorphisms and insulin resistance (IR) in association with serum phospholipid polyunsaturated fatty acid (FA) composition in healthy Korean men. Methods Healthy men (n = 576, 30 ~ 79 years old) were genotyped for rs174537 near FADS1 (FEN1-10154G>T), FADS2 (rs174575C>G, rs2727270C>T), and FADS3 (rs1000778C>T) SNPs. Dietary intake, serum phospholipid FA composition and HOMA-IR were measured. Results Fasting insulin and HOMA-IR were significantly higher in the rs174575G allele carriers than the CC homozygotes, but lower in the rs2727270T allele carriers than the CC homozygotes. The proportion of linoleic acid (18:2ω-6, LA) was higher in the minor allele carriers of FEN1-10154G>T, rs174575C>G and rs2727270C>T than the major homozygotes, respectively. On the other hand, the proportions of dihomo-γ-linolenic acid (20:3ω-6, DGLA) and arachidonic acid (20:4ω-6, AA) in serum phospholipids were significantly lower in the minor allele carriers of FEN1-10154 G>T carriers and rs2727270C>T than the major homozygotes respectively. AA was also significantly lower in the rs1000778T allele carriers than the CC homozygotes. HOMA-IR positively correlated with LA and DGLA and negatively with AA/DGLA in total subjects. Interestingly, rs174575G allele carriers showed remarkably higher HOMA-IR than the CC homozygotes when subjects had higher proportions of DLGA (≥1.412% in total serum phospholipid FA composition) (P for interaction = 0.009) or of AA (≥4.573%) (P for interaction = 0.047). Conclusion HOMA-IR is associated with FADS gene cluster as well as with FA composition in serum phospholipids. Additionally, HOMA-IR may be modulated by the interaction between rs174575C>G and the proportion of DGLA or AA in serum phospholipids.
Collapse
Affiliation(s)
- Oh Yoen Kim
- Yonsei University Research Institute of Science for Aging, Yonsei University, Seoul, Korea.,Clinical Nutrigenetics/Nutrigenomics Lab, Dept of Food and Nutrition, Yonsei University, Seoul, Korea
| | - Hyo Hee Lim
- Clinical Nutrigenetics/Nutrigenomics Lab, Dept of Food and Nutrition, Yonsei University, Seoul, Korea
| | - Long In Yang
- Clinical Nutrigenetics/Nutrigenomics Lab, Dept of Food and Nutrition, Yonsei University, Seoul, Korea
| | - Jey Sook Chae
- Yonsei University Research Institute of Science for Aging, Yonsei University, Seoul, Korea.,Clinical Nutrigenetics/Nutrigenomics Lab, Dept of Food and Nutrition, Yonsei University, Seoul, Korea
| | - Jong Ho Lee
- Yonsei University Research Institute of Science for Aging, Yonsei University, Seoul, Korea.,Clinical Nutrigenetics/Nutrigenomics Lab, Dept of Food and Nutrition, Yonsei University, Seoul, Korea
| |
Collapse
|
176
|
Grarup N, Overvad M, Sparsø T, Witte DR, Pisinger C, Jørgensen T, Yamauchi T, Hara K, Maeda S, Kadowaki T, Hansen T, Pedersen O. The diabetogenic VPS13C/C2CD4A/C2CD4B rs7172432 variant impairs glucose-stimulated insulin response in 5,722 non-diabetic Danish individuals. Diabetologia 2011; 54:789-94. [PMID: 21249489 DOI: 10.1007/s00125-010-2031-2] [Citation(s) in RCA: 27] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/08/2010] [Accepted: 12/06/2010] [Indexed: 02/06/2023]
Abstract
AIMS/HYPOTHESIS A genome-wide association study in the Japanese population reported two genome-wide significant loci associated with type 2 diabetes of which the VPS13C/C2CD4A/C2CD4B locus was replicated in Europeans. We looked for potential associations between the diabetogenic VPS13C/C2CD4A/C2CD4B rs7172432 variant and diabetes-related intermediary traits. METHODS We genotyped the rs7172432 variant in the population-based Inter99 cohort (n = 6,784) and analysed quantitative diabetes-related traits in 5,722 non-diabetic participants who all were examined by an OGTT. RESULTS The diabetes-associated A allele was associated with 0.60 cm higher waist circumference (p = 0.004), 0.037 mmol/l higher fasting plasma glucose (p = 4 × 10(-5)) and 0.11 mmol/l higher plasma glucose at 30 min during an OGTT (p = 4 × 10(-4)). In analyses adjusted for concomitant insulin sensitivity levels the diabetogenic allele was associated with a lower acute glucose-stimulated insulin response (GSIR) as estimated by 30 min serum insulin (β = -0.039, p = 2 × 10(-7)), insulinogenic index (β = -0.057, p = 1 × 10(-8)) and BIGTT-acute insulin release (β = -0.041, p = 9 × 10(-9)). As rs7172432 is situated in a region previously associated with glycaemic traits, we tested linkage disequilibrium (LD) with the reported regional lead single-nucleotide polymorphisms for fasting (rs11071657) and 2 h plasma glucose (rs17271305), and performed conditional analyses of rs7172432. Rs7172432 showed moderate LD with rs11071657 and rs17271305 (R (2) < 0.34) and we found strong association by almost unchanged effect sizes of rs7172432 with plasma glucose and estimates of GSIR in analyses conditional on rs11071657 and rs17271305. CONCLUSIONS/INTERPRETATION The diabetogenic VPS13C/C2CD4A/C2CD4B rs7172432 A allele associates with GSIR in non-diabetic individuals from the general population, suggesting an impaired beta cell function as an intermediary diabetes-related trait.
Collapse
Affiliation(s)
- N Grarup
- Marie Krogh Center for Metabolic Research, Section of Metabolic Genetics, Faculty of Health Sciences, University of Copenhagen, Universitetsparken 1-3, 2100 Copenhagen, Denmark.
| | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
177
|
Chang CL, Cai JJ, Cheng PJ, Chueh HY, Hsu SYT. Identification of metabolic modifiers that underlie phenotypic variations in energy-balance regulation. Diabetes 2011; 60:726-34. [PMID: 21300845 PMCID: PMC3046833 DOI: 10.2337/db10-1331] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
OBJECTIVE Although recent studies have shown that human genomes contain hundreds of loci that exhibit signatures of positive selection, variants that are associated with adaptation in energy-balance regulation remain elusive. We reasoned that the difficulty in identifying such variants could be due to heterogeneity in selection pressure and that an integrative approach that incorporated experiment-based evidence and population genetics-based statistical judgments would be needed to reveal important metabolic modifiers in humans. RESEARCH DESIGN AND METHODS To identify common metabolic modifiers that underlie phenotypic variation in diabetes-associated or obesity-associated traits in humans, or both, we screened 207 candidate loci for regulatory single nucleotide polymorphisms (SNPs) that exhibited evidence of gene-environmental interactions. RESULTS Three SNPs (rs3895874, rs3848460, and rs937301) at the 5' gene region of human GIP were identified as prime metabolic-modifier candidates at the enteroinsular axis. Functional studies have shown that GIP promoter reporters carrying derived alleles of these three SNPs (haplotype GIP(-1920A)) have significantly lower transcriptional activities than those with ancestral alleles at corresponding positions (haplotype GIP(-1920G)). Consistently, studies of pregnant women who have undergone a screening test for gestational diabetes have shown that patients with a homozygous GIP(-1920A/A) genotype have significantly lower serum concentrations of glucose-dependent insulinotropic polypeptide (GIP) than those carrying an ancestral GIP(-1920G) haplotype. After controlling for a GIPR variation, we showed that serum glucose concentrations of patients carrying GIP(-1920A/A) homozygotes are significantly higher than that of those carrying an ancestral GIP(-1920G) haplotype (odds ratio 3.53). CONCLUSIONS Our proof-of-concept study indicates that common regulatory GIP variants impart a difference in GIP and glucose metabolism. The study also provides a rare example that identified the common variant-common phenotypic variation pattern based on evidence of moderate gene-environmental interactions.
Collapse
Affiliation(s)
- Chia Lin Chang
- Department of Obstetrics and Gynecology, Chang Gung Memorial Hospital Linkou Medical Center, Chang Gung University, Kweishan, Taoyuan, Taiwan
| | - James J. Cai
- Department of Biology, Stanford University, Stanford, California
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, Texas
| | - Po Jen Cheng
- Department of Obstetrics and Gynecology, Chang Gung Memorial Hospital Linkou Medical Center, Chang Gung University, Kweishan, Taoyuan, Taiwan
| | - Ho Yen Chueh
- Department of Obstetrics and Gynecology, Chang Gung Memorial Hospital Linkou Medical Center, Chang Gung University, Kweishan, Taoyuan, Taiwan
| | - Sheau Yu Teddy Hsu
- Reproductive Biology and Stem Cell Research Program, Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, California
- Corresponding author: Sheau Yu Teddy Hsu,
| |
Collapse
|
178
|
Vangipurapu J, Stančáková A, Pihlajamäki J, Kuulasmaa TM, Kuulasmaa T, Paananen J, Kuusisto J, Ferrannini E, Laakso M. Association of indices of liver and adipocyte insulin resistance with 19 confirmed susceptibility loci for type 2 diabetes in 6,733 non-diabetic Finnish men. Diabetologia 2011; 54:563-71. [PMID: 21153532 DOI: 10.1007/s00125-010-1977-4] [Citation(s) in RCA: 33] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2010] [Accepted: 10/20/2010] [Indexed: 12/25/2022]
Abstract
AIMS/HYPOTHESIS Of the confirmed type 2 diabetes susceptibility loci only a few are known to affect insulin sensitivity. We examined the association of indices of hepatic and adipocyte insulin resistance (IR) with 19 confirmed type 2 diabetes risk loci in a large population-based study. METHODS Non-diabetic participants (n = 8,460, age 57.3 ± 7.0 years, BMI 26.8 ± 3.8 kg/m(2); mean ± SD) from a population-based cohort underwent an OGTT. Of them, 6,733 non-diabetic men were genotyped for single nucleotide polymorphisms (SNPs) in or near PPARG2 (also known as PPARG), KCNJ11, TCF7L2, SLC30A8, HHEX, CDKN2B, IGF2BP2, CDKAL1, HNF1B, WFS1, JAZF1, CDC123, TSPAN8, THADA, ADAMTS9, NOTCH2, KCNQ1, MTNR1B and SNP rs7480010. We investigated hepatic IR with a new index of liver IR. The adipocyte IR index was defined as a product of fasting NEFA and plasma insulin levels. RESULTS Type 2 diabetes risk SNPs in or near KCNJ11 and HHEX were significantly (p < 0.0013), and those in or near CDKN2B, NOTCH2 and MTNR1B were nominally (p < 0.05), associated with decreased liver IR index. The Pro12 allele of PPARG2 was significantly associated with a high adipocyte IR index and nominally associated with high liver IR. CONCLUSIONS/INTERPRETATION The Pro12 allele of PPARG2 seems to impair insulin's antilipolytic effect, leading to high NEFA release in the fasting state and IR. In addition, the type 2 diabetes risk alleles of KCNJ11 and HHEX, which are known to impair insulin secretion, were associated with increased hepatic insulin sensitivity.
Collapse
Affiliation(s)
- J Vangipurapu
- Department of Medicine, University of Eastern Finland, Kuopio University Hospital, 70210, Kuopio, Finland
| | | | | | | | | | | | | | | | | |
Collapse
|
179
|
Abstract
BACKGROUND
Type 2 diabetes (T2D) is a complex disorder that is affected by multiple genetic and environmental factors. Extensive efforts have been made to identify the disease-affecting genes to better understand the disease pathogenesis, find new targets for clinical therapy, and allow prediction of disease.
CONTENT
Our knowledge about the genes involved in disease pathogenesis has increased substantially in recent years, thanks to genomewide association studies and international collaborations joining efforts to collect the huge numbers of individuals needed to study complex diseases on a population level. We have summarized what we have learned so far about the genes that affect T2D risk and their functions. Although more than 40 loci associated with T2D or glycemic traits have been reported and reproduced, only a minor part of the genetic component of the disease has been explained, and the causative variants and affected genes are unknown for many of the loci.
SUMMARY
Great advances have recently occurred in our understanding of the genetics of T2D, but much remains to be learned about the disease etiology. The genetics of T2D has so far been driven by technology, and we now hope that next-generation sequencing will provide important information on rare variants with stronger effects. Even when variants are known, however, great effort will be required to discover how they affect disease risk.
Collapse
Affiliation(s)
- Emma Ahlqvist
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Tarunveer Singh Ahluwalia
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Skåne University Hospital, Malmö, Sweden
| | - Leif Groop
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University, Skåne University Hospital, Malmö, Sweden
| |
Collapse
|
180
|
Abstract
The use of mouse models in medical research has greatly contributed to our understanding of the development of type 2 diabetes mellitus and the mechanisms of disease progression in the context of insulin resistance and β-cell dysfunction. Maintenance of glucose homeostasis involves a complex interplay of many genes and their actions in response to exogenous stimuli. In recent years, the availability of large population-based cohorts and the capacity to genotype enormous numbers of common genetic variants have driven various large-scale genome-wide association studies, which has greatly accelerated the identification of novel genes likely to be involved in the development of type 2 diabetes. The increasing demand for verifying novel genes is met by the timely development of new mouse resources established as various collaborative projects involving major transgenic and phenotyping centres and laboratories worldwide. The surge of new data will ultimately enable translational research into potential improvement and refinement of current type 2 diabetes therapy options, and hopefully restore quality of life for patients.
Collapse
|
181
|
Kröger J, Zietemann V, Enzenbach C, Weikert C, Jansen EH, Döring F, Joost HG, Boeing H, Schulze MB. Erythrocyte membrane phospholipid fatty acids, desaturase activity, and dietary fatty acids in relation to risk of type 2 diabetes in the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study. Am J Clin Nutr 2011; 93:127-42. [PMID: 20980488 DOI: 10.3945/ajcn.110.005447] [Citation(s) in RCA: 196] [Impact Index Per Article: 15.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022] Open
Abstract
BACKGROUND The long-term role of fatty acids (FAs) in the cause of diabetes remains largely unclear. OBJECTIVE We aimed to investigate erythrocyte membrane FAs, desaturase activity, and dietary FAs in relation to the incidence of type 2 diabetes. DESIGN We applied a nested case-cohort design (n = 2724, including 673 incident diabetes cases) within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam Study, which involves 27,548 middle-aged subjects. Thirty erythrocyte membrane FAs (percentage of total FAs) and FA intake (percentage of total fat) were measured at baseline, and physician-confirmed incident diabetes was assessed during a mean follow-up of 7.0 y. We evaluated Δ⁵ desaturase (D5D) and Δ⁶ desaturase (D6D) activity by using FA product-to-precursor ratios (traditional approach) and by investigating variants in FADS1 and FADS2 genes that encode these desaturases (Mendelian randomization approach). RESULTS As a main finding, erythrocyte 16:1n-7 and 18:3n-6 and FA ratios, which reflect stearoyl coenzyme A desaturase (SCD) and D6D activity, were directly related to diabetes risk in multivariable-adjusted models [relative risks (95% CIs) comparing extreme quintiles: 16:1n-7, 2.11 (1.46, 3.05); 18:3n-6, 2.00 (1.38, 2.88); SCD, 2.61 (1.75, 3.89); and D6D, 2.46 (1.67, 3.63)], whereas the FA ratio that reflects D5D activity was inversely associated with risk [0.46 (0.31, 0.70)]. The Mendelian randomization approach corroborated the direct relation for D6D activity and tended to support the inverse relation for D5D activity. Proportions of dietary FAs showed only modest to low correlations with erythrocyte FAs and were not significantly associated with risk. CONCLUSION The FA profile of erythrocyte membrane phospholipids and activity of desaturase enzymes are strongly linked to the incidence of type 2 diabetes.
Collapse
Affiliation(s)
- Janine Kröger
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbrücke, Nuthetal, Germany.
| | | | | | | | | | | | | | | | | |
Collapse
|
182
|
Cottingham C, Chen H, Chen Y, Peng Y, Wang Q. Genetic variations of α(2)-adrenergic receptors illuminate the diversity of receptor functions. CURRENT TOPICS IN MEMBRANES 2011; 67:161-90. [PMID: 21771490 DOI: 10.1016/b978-0-12-384921-2.00008-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
|
183
|
Abstract
The physiologic hallmarks of type 2 diabetes are insulin resistance in hepatic and peripheral tissues and pancreatic β-cell dysfunction. Thus, genetic loci underlying susceptibility to type 2 diabetes are likely to map to one of these endophenotypes. Genome-wide association studies have now identified up to 38 susceptibility loci for type 2 diabetes and a number of other loci underlying variation in type 2 diabetes-related quantitative traits. The majority are of unknown biology or map to pancreatic β-cell dysfunction. A seemingly disproportionate minority map to insulin resistance. We briefly discuss the known insulin resistance loci identified from genome-wide association, and then discuss reasons why additional insulin resistance loci have not been identified. We present alternative views that may partly explain the apparent dearth of insulin resistance loci contributing to genetic susceptibility to type 2 diabetes, rather than focus on traditional issues such as study design and sampling, which have been addressed elsewhere.
Collapse
Affiliation(s)
- Richard M Watanabe
- Department of Preventive Medicine, Keck School of Medicine of USC, Los Angeles, CA 90089-9011, USA.
| |
Collapse
|
184
|
Contribution of Diet and Genes to Polyunsaturated Fatty Acid Composition. CURRENT CARDIOVASCULAR RISK REPORTS 2010. [DOI: 10.1007/s12170-010-0140-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
|
185
|
Abstract
For the past two decades, genetics has been widely explored as a tool for unraveling the pathogenesis of diabetes. Many risk alleles for type 2 diabetes and hyperglycemia have been detected in recent years through massive genome-wide association studies and evidence exists that most of these variants influence pancreatic β-cell function. However, risk alleles in five loci seem to have a primary impact on insulin sensitivity. Investigations of more detailed physiologic phenotypes, such as the insulin response to intravenous glucose or the incretion hormones, are now emerging and give indications of more specific pathologic mechanisms for diabetes-related risk variants. Such studies have shed light on the function of some loci but also underlined the complex nature of disease mechanism. In the future, sequencing-based discovery of low-frequency variants with higher impact on intermediate diabetes-related traits is a likely scenario and identification of new pathways involved in type 2 diabetes predisposition will offer opportunities for the development of novel therapeutic and preventative approaches.
Collapse
Affiliation(s)
- Niels Grarup
- Diabetes Genetics, Hagedorn Research Institute, Gentofte, Denmark
| | - Thomas Sparsø
- Diabetes Genetics, Hagedorn Research Institute, Gentofte, Denmark
| | - Torben Hansen
- Hagedorn Research Institute, Niels Steensens Vej 1, 2820 Gentofte, Denmark
| |
Collapse
|
186
|
Abstract
Over the past 3 years, there has been a dramatic increase in the number of confirmed type 2 diabetes (T2D) susceptibility loci, most arising through the implementation of genome-wide association studies (GWAS). However, progress toward the understanding of disease mechanisms has been slowed by modest effect sizes and the fact that most GWAS signals map away from coding sequence: the presumption is that their effects are mediated through regulation of nearby transcripts, but the identities of the genes concerned are often far from clear. In this review we describe the progress that has been made to date in translating association signals into molecular mechanisms with a focus on the most tractable signals (eg, KCNJ11/ABCC8, SLC30A8, GCKR) and those in which human, animal, and cellular models (FTO, TCF7L2, G6PC2) have provided insights into the role in T2D pathogenesis. Finally, the challenges for the field with the advent of genome-scale next-generation resequencing efforts are discussed.
Collapse
Affiliation(s)
- Martijn van de Bunt
- Diabetes Research Laboratories, Oxford Centre for Diabetes Endocrinology & Metabolism, Churchill Hospital, University of Oxford, Headington, Oxford, OX3 7LJ, UK.
| | | |
Collapse
|
187
|
Petrie JR, Pearson ER, Sutherland C. Implications of genome wide association studies for the understanding of type 2 diabetes pathophysiology. Biochem Pharmacol 2010; 81:471-7. [PMID: 21111713 DOI: 10.1016/j.bcp.2010.11.010] [Citation(s) in RCA: 41] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2010] [Revised: 11/12/2010] [Accepted: 11/12/2010] [Indexed: 12/20/2022]
Abstract
The rapid rise in prevalence of type 2 diabetes mellitus (T2DM) has been driven by changes in environmental factors - primarily increased caloric intake and reduced energy expenditure - resulting in reduced whole body insulin sensitivity (often termed insulin resistance). Insulin resistance has been proposed to be a major driver of progression to T2DM. However, of 38 individual susceptibility loci for T2DM recently identified by genome wide association studies, by far the majority code for proteins involved in β-cell function. In this review, we discuss the possible reasons for the paucity of insulin resistance genes and ask whether the new genetic susceptibility data should focus attention on β-cell targets in the development of therapies for T2DM.
Collapse
Affiliation(s)
- John R Petrie
- BHF Glasgow Cardiovascular Research Centre, University of Glasgow, 126 University Place, Glasgow G11 6TA, United Kingdom.
| | | | | |
Collapse
|
188
|
Hu C, Zhang R, Wang C, Wang J, Ma X, Hou X, Lu J, Yu W, Jiang F, Bao Y, Xiang K, Jia W. Variants from GIPR, TCF7L2, DGKB, MADD, CRY2, GLIS3, PROX1, SLC30A8 and IGF1 are associated with glucose metabolism in the Chinese. PLoS One 2010; 5:e15542. [PMID: 21103350 PMCID: PMC2984505 DOI: 10.1371/journal.pone.0015542] [Citation(s) in RCA: 67] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2010] [Accepted: 10/05/2010] [Indexed: 12/13/2022] Open
Abstract
Background Recent meta-analysis of genome-wide association studies in European descent samples identified novel loci influencing glucose and insulin related traits. In the current study, we aimed to evaluate the association between these loci and traits related to glucose metabolism in the Chinese. Methods/Principal Findings We genotyped seventeen single nucleotide polymorphisms (SNPs) from fifteen loci including GIPR, ADCY5, TCF7L2, VPS13C, DGKB, MADD, ADRA2A, FADS1, CRY2, SLC2A2, GLIS3, PROX1, C2CD4B, SLC30A8 and IGF1 in 6,822 Shanghai Chinese Hans comprising 3,410 type 2 diabetic patients and 3,412 normal glucose regulation subjects. MADD rs7944584 showed strong association to type 2 diabetes (p = 3.5×10−6, empirical p = 0.0002) which was not observed in the European descent populations. SNPs from GIPR, TCF7L2, CRY2, GLIS3 and SLC30A8 were also associated with type 2 diabetes (p = 0.0487∼2.0×10−8). Further adjusting age, gender and BMI as confounders found PROX1 rs340874 was associated with type 2 diabetes (p = 0.0391). SNPs from DGKB, MADD and SLC30A8 were associated with fasting glucose while PROX1 rs340874 was significantly associated with OGTT 2-h glucose (p = 0.0392∼0.0014, adjusted for age, gender and BMI), the glucose-raising allele also showed association to lower insulin secretion. IGF1 rs35767 showed significant association to both fasting and 2-h insulin levels as well as insulin secretion and sensitivity indices (p = 0.0160∼0.0035, adjusted for age, gender and BMI). Conclusions/Significance Our results indicated that SNPs from GIPR, TCF7L2, DGKB, MADD, CRY2, GLIS3, PROX1, SLC30A8 and IGF1 were associated with traits related to glucose metabolism in the Chinese population.
Collapse
Affiliation(s)
- Cheng Hu
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, People's Republic of China
- Shanghai Diabetes Institute, Shanghai, People's Republic of China
- Shanghai Clinical Center for Diabetes, Shanghai, People's Republic of China
| | - Rong Zhang
- Shanghai Diabetes Institute, Shanghai, People's Republic of China
- Shanghai Clinical Center for Diabetes, Shanghai, People's Republic of China
| | - Congrong Wang
- Shanghai Diabetes Institute, Shanghai, People's Republic of China
- Shanghai Clinical Center for Diabetes, Shanghai, People's Republic of China
| | - Jie Wang
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, People's Republic of China
- Shanghai Clinical Center for Diabetes, Shanghai, People's Republic of China
| | - Xiaojing Ma
- Shanghai Diabetes Institute, Shanghai, People's Republic of China
- Shanghai Clinical Center for Diabetes, Shanghai, People's Republic of China
| | - Xuhong Hou
- Shanghai Diabetes Institute, Shanghai, People's Republic of China
- Shanghai Clinical Center for Diabetes, Shanghai, People's Republic of China
| | - Jingyi Lu
- Shanghai Diabetes Institute, Shanghai, People's Republic of China
- Shanghai Clinical Center for Diabetes, Shanghai, People's Republic of China
| | - Weihui Yu
- Shanghai Diabetes Institute, Shanghai, People's Republic of China
- Shanghai Clinical Center for Diabetes, Shanghai, People's Republic of China
| | - Feng Jiang
- Shanghai Diabetes Institute, Shanghai, People's Republic of China
- Shanghai Clinical Center for Diabetes, Shanghai, People's Republic of China
| | - Yuqian Bao
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, People's Republic of China
- Shanghai Clinical Center for Diabetes, Shanghai, People's Republic of China
| | - Kunsan Xiang
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, People's Republic of China
- Shanghai Diabetes Institute, Shanghai, People's Republic of China
- Shanghai Clinical Center for Diabetes, Shanghai, People's Republic of China
| | - Weiping Jia
- Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, People's Republic of China
- Shanghai Diabetes Institute, Shanghai, People's Republic of China
- Shanghai Clinical Center for Diabetes, Shanghai, People's Republic of China
- * E-mail:
| |
Collapse
|
189
|
Stitzel ML, Sethupathy P, Pearson DS, Chines PS, Song L, Erdos MR, Welch R, Parker SCJ, Boyle AP, Scott LJ, Margulies EH, Boehnke M, Furey TS, Crawford GE, Collins FS. Global epigenomic analysis of primary human pancreatic islets provides insights into type 2 diabetes susceptibility loci. Cell Metab 2010; 12:443-55. [PMID: 21035756 PMCID: PMC3026436 DOI: 10.1016/j.cmet.2010.09.012] [Citation(s) in RCA: 144] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/07/2010] [Revised: 07/22/2010] [Accepted: 08/26/2010] [Indexed: 01/17/2023]
Abstract
Identifying cis-regulatory elements is important to understanding how human pancreatic islets modulate gene expression in physiologic or pathophysiologic (e.g., diabetic) conditions. We conducted genome-wide analysis of DNase I hypersensitive sites, histone H3 lysine methylation modifications (K4me1, K4me3, K79me2), and CCCTC factor (CTCF) binding in human islets. This identified ∼18,000 putative promoters (several hundred unannotated and islet-active). Surprisingly, active promoter modifications were absent at genes encoding islet-specific hormones, suggesting a distinct regulatory mechanism. Of 34,039 distal (nonpromoter) regulatory elements, 47% are islet unique and 22% are CTCF bound. In the 18 type 2 diabetes (T2D)-associated loci, we identified 118 putative regulatory elements and confirmed enhancer activity for 12 of 33 tested. Among six regulatory elements harboring T2D-associated variants, two exhibit significant allele-specific differences in activity. These findings present a global snapshot of the human islet epigenome and should provide functional context for noncoding variants emerging from genetic studies of T2D and other islet disorders.
Collapse
Affiliation(s)
- Michael L Stitzel
- Genome Technology Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD 20892, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | |
Collapse
|
190
|
Ketterer C, Müssig K, Machicao F, Stefan N, Fritsche A, Häring HU, Staiger H. Genetic variation within the NR1H2 gene encoding liver X receptor β associates with insulin secretion in subjects at increased risk for type 2 diabetes. J Mol Med (Berl) 2010; 89:75-81. [PMID: 21042792 DOI: 10.1007/s00109-010-0687-1] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2010] [Revised: 08/23/2010] [Accepted: 09/08/2010] [Indexed: 01/17/2023]
Abstract
The liver X receptors (LXRs)-α and -β play a crucial role in control of insulin production and secretion in pancreatic β-cells. We hypothesized that common variants in the NR1H2 and NR1H3 genes, encoding LXR-β and -α, respectively, may alter pancreatic β-cell function. One thousand five hundred seventy-four subjects of European ancestry with elevated risk for type 2 diabetes were genotyped for the two NR1H2 single nucleotide polymorphisms (SNPs) rs2248949 and rs1405655 and for the four NR1H3 SNPs rs11039149, rs3758673, rs12221497 and rs2279238, and association studies with metabolic traits were performed. Metabolic characterization comprised an oral glucose tolerance test (OGTT) in all participants and, in addition, a hyperinsulinemic-euglycemic clamp and an intravenous glucose tolerance test (IVGTT) in subsets. One hundred per cent of common genetic variation (minor allele frequency ≥1%) within the NR1H2 and NR1H3 loci (D' = 1.0; r² ≥ 0.8) were covered by the six chosen tagging SNPs. NR1H2 rs2248949 was nominally associated with OGTT-derived first-phase insulin secretion and proinsulin conversion to insulin and significantly associated with the AUC of insulin levels during the IVGTT (p = 0.007) after adjustment for age, gender, BMI and insulin sensitivity in the dominant model, with the minor allele conferring reduced pancreatic β-cell function to the carriers. In subjects of European ancestry at increased risk for type 2 diabetes, common variation within the NR1H2 gene impaired insulin secretion, which may facilitate the development of type 2 diabetes.
Collapse
Affiliation(s)
- Caroline Ketterer
- Division of Endocrinology, Diabetology, Angiology, Nephrology, and Clinical Chemistry, Department of Internal Medicine, Eberhard Karls University Tübingen, German Center for Diabetes Research (DZD), Otfried-Müller-Str. 10, 72076, Tübingen, Germany
| | | | | | | | | | | | | |
Collapse
|
191
|
|
192
|
Abstract
Type 2 diabetes mellitus has been at the forefront of human diseases and phenotypes studied by new genetic analyses. Thanks to genome-wide association studies, we have made substantial progress in elucidating the genetic basis of type 2 diabetes. This review summarizes the concept, history, and recent discoveries produced by genome-wide association studies for type 2 diabetes and glycemic traits, with a focus on the key notions we have gleaned from these efforts. Genome-wide association findings have illustrated novel pathways, pointed toward fundamental biology, confirmed prior epidemiological observations, drawn attention to the role of β-cell dysfunction in type 2 diabetes, explained ~10% of disease heritability, tempered our expectations with regard to their use in clinical prediction, and provided possible targets for pharmacotherapy and pharmacogenetic clinical trials. We can apply these lessons to future investigation so as to improve our understanding of the genetic basis of type 2 diabetes.
Collapse
Affiliation(s)
- Liana K. Billings
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
| | - Jose C. Florez
- Center for Human Genetic Research, Massachusetts General Hospital, Boston, Massachusetts
- Department of Medicine, Harvard Medical School, Boston, Massachusetts
- Diabetes Research Center (Diabetes Unit), Department of Medicine, Massachusetts General Hospital, Boston, Massachusetts
- Program in Medical and Population Genetics, Broad Institute, Cambridge, Massachusetts
| |
Collapse
|
193
|
Abstract
Diversities in human physiology have been partially shaped by adaptation to natural environments and changing cultures. Recent genomic analyses have revealed single nucleotide polymorphisms (SNPs) that are associated with adaptations in immune responses, obvious changes in human body forms, or adaptations to extreme climates in select human populations. Here, we report that the human GIP locus was differentially selected among human populations based on the analysis of a nonsynonymous SNP (rs2291725). Comparative and functional analyses showed that the human GIP gene encodes a cryptic glucose-dependent insulinotropic polypeptide (GIP) isoform (GIP55S or GIP55G) that encompasses the SNP and is resistant to serum degradation relative to the known mature GIP peptide. Importantly, we found that GIP55G, which is encoded by the derived allele, exhibits a higher bioactivity compared with GIP55S, which is derived from the ancestral allele. Haplotype structure analysis suggests that the derived allele at rs2291725 arose to dominance in East Asians ∼8100 yr ago due to positive selection. The combined results suggested that rs2291725 represents a functional mutation and may contribute to the population genetics observation. Given that GIP signaling plays a critical role in homeostasis regulation at both the enteroinsular and enteroadipocyte axes, our study highlights the importance of understanding adaptations in energy-balance regulation in the face of the emerging diabetes and obesity epidemics.
Collapse
|
194
|
Müssig K, Staiger H, Machicao F, Häring HU, Fritsche A. Genetic variants in MTNR1B affecting insulin secretion. Ann Med 2010; 42:387-93. [PMID: 20597807 DOI: 10.3109/07853890.2010.502125] [Citation(s) in RCA: 26] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
The incidence of type 2 diabetes mellitus has markedly increased worldwide over the past decades. Pancreatic beta-cell dysfunction as well as central and peripheral insulin resistance appears to be elementary features in the pathophysiology of type 2 diabetes mellitus. Major environmental conditions predisposing to the development of type 2 diabetes are excessive food intake and sedentary life-style on the background of a genetic predisposition. Recent genome-wide association studies identified several novel type 2 diabetes risk genes, with impaired pancreatic beta-cell function as the underlying mechanism of increased diabetes risk in the majority of genes. Many of the novel type 2 diabetes risk genes, including MTNR1B which encodes one of the two known human melatonin receptors, were unexpected at first glance. However, previous animal as well as human studies already pointed to a significant impact of the melatonin system on the regulation of glucose homeostasis, in addition to its well known role in modulation of sleep and circadian rhythms. This brief review aims to give an overview of how alterations in the melatonin system could contribute to an increased diabetes risk, paying special attention to the role of melatonin receptors in pancreatic beta-cell function.
Collapse
Affiliation(s)
- Karsten Müssig
- Division of Endocrinology, Diabetology, Angiology, Nephrology, and Clinical Chemistry, Department of Internal Medicine, Eberhard Karls University, Member of the German Centre for Diabetes Research (DZD), 72076 Tübingen, Germany
| | | | | | | | | |
Collapse
|
195
|
Bi M, Kao WHL, Boerwinkle E, Hoogeveen RC, Rasmussen-Torvik LJ, Astor BC, North KE, Coresh J, Köttgen A. Association of rs780094 in GCKR with metabolic traits and incident diabetes and cardiovascular disease: the ARIC Study. PLoS One 2010; 5:e11690. [PMID: 20661421 PMCID: PMC2908550 DOI: 10.1371/journal.pone.0011690] [Citation(s) in RCA: 49] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2010] [Accepted: 06/17/2010] [Indexed: 02/02/2023] Open
Abstract
Objective The minor T-allele of rs780094 in the glucokinase regulator gene (GCKR) associates with a number of metabolic traits including higher triglyceride levels and improved glycemic regulation in study populations of mostly European ancestry. Using data from the Atherosclerosis Risk in Communities (ARIC) Study, we sought to replicate these findings, examine them in a large population-based sample of African American study participants, and to investigate independent associations with other metabolic traits in order to determine if variation in GKCR contributes to their observed clustering. In addition, we examined the association of rs780094 with incident diabetes, coronary heart disease (CHD), and stroke over up mean follow-up times of 8, 15, and 15 years, respectively. Research Design and Methods Race-stratified analyses were conducted among 10,929 white and 3,960 black participants aged 45–64 at baseline assuming an additive genetic model and using linear and logistic regression and Cox proportional hazards models. Results Previous findings replicated among white participants in multivariable adjusted models: the T-allele of rs780094 was associated with lower fasting glucose (p = 10−7) and insulin levels (p = 10−6), lower insulin resistance (HOMA-IR, p = 10−9), less prevalent diabetes (p = 10−6), and higher CRP (p = 10−8), 2-h postprandial glucose (OGTT, p = 10−6), and triglyceride levels (p = 10−31). Moreover, the T-allele was independently associated with higher HDL cholesterol levels (p = 0.022), metabolic syndrome prevalence (p = 0.043), and lower beta-cell function measured as HOMA-B (p = 0.011). Among black participants, the T-allele was associated only with higher triglyceride levels (p = 0.004) and lower insulin levels (p = 0.002) and HOMA-IR (p = 0.013). Prospectively, the T-allele was associated with reduced incidence of diabetes (p = 10−4) among white participants, but not with incidence of CHD or stroke. Conclusions Our findings indicate rs780094 has independent associations with multiple metabolic traits as well as incident diabetes, but not incident CHD or stroke. The magnitude of association between the SNP and most traits was of lower magnitude among African American compared to white participants.
Collapse
Affiliation(s)
- Mark Bi
- School of Biological Sciences, University of Nebraska at Lincoln, Lincoln, Nebraska, United States of America
| | - Wen Hong Linda Kao
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Eric Boerwinkle
- Human Genetics Center and Division of Epidemiology, University of Texas Health Science Center at Houston, Houston, Texas, United States of America
| | - Ron C. Hoogeveen
- Department of Medicine, Baylor College of Medicine, Houston, Texas, United States of America
| | - Laura J. Rasmussen-Torvik
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, Minnesota, United States of America
| | - Brad C. Astor
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Kari E. North
- Department of Epidemiology and Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, North Carolina, United States of America
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Anna Köttgen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
- Renal Division, University Hospital Freiburg, Freiburg, Germany
- * E-mail:
| |
Collapse
|