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1.  No Interactions Between Previously Associated 2-Hour Glucose Gene Variants and Physical Activity or BMI on 2-Hour Glucose Levels 
Scott, Robert A. | Chu, Audrey Y. | Grarup, Niels | Manning, Alisa K. | Hivert, Marie-France | Shungin, Dmitry | Tönjes, Anke | Yesupriya, Ajay | Barnes, Daniel | Bouatia-Naji, Nabila | Glazer, Nicole L. | Jackson, Anne U. | Kutalik, Zoltán | Lagou, Vasiliki | Marek, Diana | Rasmussen-Torvik, Laura J. | Stringham, Heather M. | Tanaka, Toshiko | Aadahl, Mette | Arking, Dan E. | Bergmann, Sven | Boerwinkle, Eric | Bonnycastle, Lori L. | Bornstein, Stefan R. | Brunner, Eric | Bumpstead, Suzannah J. | Brage, Soren | Carlson, Olga D. | Chen, Han | Chen, Yii-Der Ida | Chines, Peter S. | Collins, Francis S. | Couper, David J. | Dennison, Elaine M. | Dowling, Nicole F. | Egan, Josephine S. | Ekelund, Ulf | Erdos, Michael R. | Forouhi, Nita G. | Fox, Caroline S. | Goodarzi, Mark O. | Grässler, Jürgen | Gustafsson, Stefan | Hallmans, Göran | Hansen, Torben | Hingorani, Aroon | Holloway, John W. | Hu, Frank B. | Isomaa, Bo | Jameson, Karen A. | Johansson, Ingegerd | Jonsson, Anna | Jørgensen, Torben | Kivimaki, Mika | Kovacs, Peter | Kumari, Meena | Kuusisto, Johanna | Laakso, Markku | Lecoeur, Cécile | Lévy-Marchal, Claire | Li, Guo | Loos, Ruth J.F. | Lyssenko, Valeri | Marmot, Michael | Marques-Vidal, Pedro | Morken, Mario A. | Müller, Gabriele | North, Kari E. | Pankow, James S. | Payne, Felicity | Prokopenko, Inga | Psaty, Bruce M. | Renström, Frida | Rice, Ken | Rotter, Jerome I. | Rybin, Denis | Sandholt, Camilla H. | Sayer, Avan A. | Shrader, Peter | Schwarz, Peter E.H. | Siscovick, David S. | Stančáková, Alena | Stumvoll, Michael | Teslovich, Tanya M. | Waeber, Gérard | Williams, Gordon H. | Witte, Daniel R. | Wood, Andrew R. | Xie, Weijia | Boehnke, Michael | Cooper, Cyrus | Ferrucci, Luigi | Froguel, Philippe | Groop, Leif | Kao, W.H. Linda | Vollenweider, Peter | Walker, Mark | Watanabe, Richard M. | Pedersen, Oluf | Meigs, James B. | Ingelsson, Erik | Barroso, Inês | Florez, Jose C. | Franks, Paul W. | Dupuis, Josée | Wareham, Nicholas J. | Langenberg, Claudia
Diabetes  2012;61(5):1291-1296.
Gene–lifestyle interactions have been suggested to contribute to the development of type 2 diabetes. Glucose levels 2 h after a standard 75-g glucose challenge are used to diagnose diabetes and are associated with both genetic and lifestyle factors. However, whether these factors interact to determine 2-h glucose levels is unknown. We meta-analyzed single nucleotide polymorphism (SNP) × BMI and SNP × physical activity (PA) interaction regression models for five SNPs previously associated with 2-h glucose levels from up to 22 studies comprising 54,884 individuals without diabetes. PA levels were dichotomized, with individuals below the first quintile classified as inactive (20%) and the remainder as active (80%). BMI was considered a continuous trait. Inactive individuals had higher 2-h glucose levels than active individuals (β = 0.22 mmol/L [95% CI 0.13–0.31], P = 1.63 × 10−6). All SNPs were associated with 2-h glucose (β = 0.06–0.12 mmol/allele, P ≤ 1.53 × 10−7), but no significant interactions were found with PA (P > 0.18) or BMI (P ≥ 0.04). In this large study of gene–lifestyle interaction, we observed no interactions between genetic and lifestyle factors, both of which were associated with 2-h glucose. It is perhaps unlikely that top loci from genome-wide association studies will exhibit strong subgroup-specific effects, and may not, therefore, make the best candidates for the study of interactions.
doi:10.2337/db11-0973
PMCID: PMC3331745  PMID: 22415877
2.  Genome-Wide Association Identifies Nine Common Variants Associated With Fasting Proinsulin Levels and Provides New Insights Into the Pathophysiology of Type 2 Diabetes 
Strawbridge, Rona J. | Dupuis, Josée | Prokopenko, Inga | Barker, Adam | Ahlqvist, Emma | Rybin, Denis | Petrie, John R. | Travers, Mary E. | Bouatia-Naji, Nabila | Dimas, Antigone S. | Nica, Alexandra | Wheeler, Eleanor | Chen, Han | Voight, Benjamin F. | Taneera, Jalal | Kanoni, Stavroula | Peden, John F. | Turrini, Fabiola | Gustafsson, Stefan | Zabena, Carina | Almgren, Peter | Barker, David J.P. | Barnes, Daniel | Dennison, Elaine M. | Eriksson, Johan G. | Eriksson, Per | Eury, Elodie | Folkersen, Lasse | Fox, Caroline S. | Frayling, Timothy M. | Goel, Anuj | Gu, Harvest F. | Horikoshi, Momoko | Isomaa, Bo | Jackson, Anne U. | Jameson, Karen A. | Kajantie, Eero | Kerr-Conte, Julie | Kuulasmaa, Teemu | Kuusisto, Johanna | Loos, Ruth J.F. | Luan, Jian'an | Makrilakis, Konstantinos | Manning, Alisa K. | Martínez-Larrad, María Teresa | Narisu, Narisu | Nastase Mannila, Maria | Öhrvik, John | Osmond, Clive | Pascoe, Laura | Payne, Felicity | Sayer, Avan A. | Sennblad, Bengt | Silveira, Angela | Stančáková, Alena | Stirrups, Kathy | Swift, Amy J. | Syvänen, Ann-Christine | Tuomi, Tiinamaija | van 't Hooft, Ferdinand M. | Walker, Mark | Weedon, Michael N. | Xie, Weijia | Zethelius, Björn | Ongen, Halit | Mälarstig, Anders | Hopewell, Jemma C. | Saleheen, Danish | Chambers, John | Parish, Sarah | Danesh, John | Kooner, Jaspal | Östenson, Claes-Göran | Lind, Lars | Cooper, Cyrus C. | Serrano-Ríos, Manuel | Ferrannini, Ele | Forsen, Tom J. | Clarke, Robert | Franzosi, Maria Grazia | Seedorf, Udo | Watkins, Hugh | Froguel, Philippe | Johnson, Paul | Deloukas, Panos | Collins, Francis S. | Laakso, Markku | Dermitzakis, Emmanouil T. | Boehnke, Michael | McCarthy, Mark I. | Wareham, Nicholas J. | Groop, Leif | Pattou, François | Gloyn, Anna L. | Dedoussis, George V. | Lyssenko, Valeriya | Meigs, James B. | Barroso, Inês | Watanabe, Richard M. | Ingelsson, Erik | Langenberg, Claudia | Hamsten, Anders | Florez, Jose C.
Diabetes  2011;60(10):2624-2634.
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.
doi:10.2337/db11-0415
PMCID: PMC3178302  PMID: 21873549
3.  Epigenetic Gene Promoter Methylation at Birth Is Associated With Child’s Later Adiposity 
Diabetes  2011;60(5):1528-1534.
OBJECTIVE
Fixed genomic variation explains only a small proportion of the risk of adiposity. In animal models, maternal diet alters offspring body composition, accompanied by epigenetic changes in metabolic control genes. Little is known about whether such processes operate in humans.
RESEARCH DESIGN AND METHODS
Using Sequenom MassARRAY we measured the methylation status of 68 CpGs 5′ from five candidate genes in umbilical cord tissue DNA from healthy neonates. Methylation varied greatly at particular CpGs: for 31 CpGs with median methylation ≥5% and a 5–95% range ≥10%, we related methylation status to maternal pregnancy diet and to child’s adiposity at age 9 years. Replication was sought in a second independent cohort.
RESULTS
In cohort 1, retinoid X receptor-α (RXRA) chr9:136355885+ and endothelial nitric oxide synthase (eNOS) chr7:150315553+ methylation had independent associations with sex-adjusted childhood fat mass (exponentiated regression coefficient [β] 17% per SD change in methylation [95% CI 4–31], P = 0.009, n = 64, and β = 20% [9–32], P < 0.001, n = 66, respectively) and %fat mass (β = 10% [1–19], P = 0.023, n = 64 and β =12% [4–20], P = 0.002, n = 66, respectively). Regression analyses including sex and neonatal epigenetic marks explained >25% of the variance in childhood adiposity. Higher methylation of RXRA chr9:136355885+, but not of eNOS chr7:150315553+, was associated with lower maternal carbohydrate intake in early pregnancy, previously linked with higher neonatal adiposity in this population. In cohort 2, cord eNOS chr7:150315553+ methylation showed no association with adiposity, but RXRA chr9:136355885+ methylation showed similar associations with fat mass and %fat mass (β = 6% [2–10] and β = 4% [1–7], respectively, both P = 0.002, n = 239).
CONCLUSIONS
Our findings suggest a substantial component of metabolic disease risk has a prenatal developmental basis. Perinatal epigenetic analysis may have utility in identifying individual vulnerability to later obesity and metabolic disease.
doi:10.2337/db10-0979
PMCID: PMC3115550  PMID: 21471513
4.  Epigenetic gene promoter methylation at birth is associated with child’s later adiposity 
Diabetes  2011;60(5):1528-1534.
Objective
Fixed genomic variation explains only a small proportion of the risk of adiposity. In animal models, maternal diet alters offspring body composition, accompanied by epigenetic changes in metabolic control genes. Little is known about whether such processes operate in humans.
Research Design and Methods
Using Sequenom MassARRAY we measured the methylation status of 68 CpGs 5′ from five candidate genes in umbilical cord tissue DNA from healthy neonates. Methylation varied greatly at particular CpGs: for 31 CpGs with median methylation ≥5% and a 5-95% range ≥10% we related methylation status to maternal pregnancy diet and to child’s adiposity at age 9 years. Replication was sought in a second independent cohort.
Results
In cohort 1, RXRA chr9:136355885+ and eNOS chr7:150315553+ methylation had independent associations with sex-adjusted childhood fat mass (exponentiated regression coefficient (β) 17% per standard deviation change in methylation (95% confidence interval (CI) 4 to 31%), P=0.009, n=64 and β=20% (9 to 32%), P<0.001, n=66, respectively) and %fat mass (β=10% (1 to 19%), P=0.023, n=64 and β=12% (4 to 20%), P=0.002, n=66, respectively). Regression analyses including sex and neonatal epigenetic marks explained >25% of the variance in childhood adiposity. Higher methylation of RXRA chr9:136355885+, but not of eNOS chr7:150315553+, was associated with lower maternal carbohydrate intake in early pregnancy, previously linked with higher neonatal adiposity in this population. In cohort 2, cord eNOS chr7:150315553+ methylation showed no association with adiposity, but RXRA chr9:136355885+ methylation showed similar associations with fat mass and %fat mass (β=6% (2 to 10%) and β=4% (1 to 7%), respectively, both P=0.002, n=239).
Conclusions
Our findings suggest a substantial component of metabolic disease risk has a prenatal developmental basis. Perinatal epigenetic analysis may have utility in identifying individual vulnerability to later obesity and metabolic disease.
doi:10.2337/db10-0979
PMCID: PMC3115550  PMID: 21471513
5.  Detailed Physiologic Characterization Reveals Diverse Mechanisms for Novel Genetic Loci Regulating Glucose and Insulin Metabolism in Humans 
Diabetes  2010;59(5):1266-1275.
OBJECTIVE
Recent genome-wide association studies have revealed loci associated with glucose and insulin-related traits. We aimed to characterize 19 such loci using detailed measures of insulin processing, secretion, and sensitivity to help elucidate their role in regulation of glucose control, insulin secretion and/or action.
RESEARCH DESIGN AND METHODS
We investigated associations of loci identified by the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) with circulating proinsulin, measures of insulin secretion and sensitivity from oral glucose tolerance tests (OGTTs), euglycemic clamps, insulin suppression tests, or frequently sampled intravenous glucose tolerance tests in nondiabetic humans (n = 29,084).
RESULTS
The glucose-raising allele in MADD was associated with abnormal insulin processing (a dramatic effect on higher proinsulin levels, but no association with insulinogenic index) at extremely persuasive levels of statistical significance (P = 2.1 × 10−71). Defects in insulin processing and insulin secretion were seen in glucose-raising allele carriers at TCF7L2, SCL30A8, GIPR, and C2CD4B. Abnormalities in early insulin secretion were suggested in glucose-raising allele carriers at MTNR1B, GCK, FADS1, DGKB, and PROX1 (lower insulinogenic index; no association with proinsulin or insulin sensitivity). Two loci previously associated with fasting insulin (GCKR and IGF1) were associated with OGTT-derived insulin sensitivity indices in a consistent direction.
CONCLUSIONS
Genetic loci identified through their effect on hyperglycemia and/or hyperinsulinemia demonstrate considerable heterogeneity in associations with measures of insulin processing, secretion, and sensitivity. Our findings emphasize the importance of detailed physiological characterization of such loci for improved understanding of pathways associated with alterations in glucose homeostasis and eventually type 2 diabetes.
doi:10.2337/db09-1568
PMCID: PMC2857908  PMID: 20185807
6.  Evaluating the Role of LPIN1 Variation in Insulin Resistance, Body Weight, and Human Lipodystrophy in U.K. Populations 
Diabetes  2008;57(9):2527-2533.
OBJECTIVE— Loss of lipin 1 activity causes lipodystrophy and insulin resistance in the fld mouse, and LPIN1 expression and common genetic variation were recently suggested to influence adiposity and insulin sensitivity in humans. We aimed to conduct a comprehensive association study to clarify the influence of common LPIN1 variation on adiposity and insulin sensitivity in U.K. populations and to examine the role of LPIN1 mutations in insulin resistance syndromes.
RESEARCH DESIGN AND METHOD— Twenty-two single nucleotide polymorphisms tagging common LPIN1 variation were genotyped in Medical Research Council (MRC) Ely (n = 1,709) and Hertfordshire (n = 2,901) population-based cohorts. LPIN1 exons, exon/intron boundaries, and 3′ untranslated region were sequenced in 158 patients with idiopathic severe insulin resistance (including 23 lipodystrophic patients) and 48 control subjects.
RESULTS— We found no association between LPIN1 single nucleotide polymorphisms and fasting insulin but report a nominal association between rs13412852 and BMI (P = 0.042) in a meta-analysis of 8,504 samples from in-house and publicly available studies. Three rare nonsynonymous variants (A353T, R552K, and G582R) were detected in severely insulin-resistant patients. However, these did not cosegregate with disease in affected families, and Lipin1 protein expression and phosphorylation in patients with variants were indistinguishable from those in control subjects.
CONCLUSIONS— Our data do not support a major effect of common LPIN1 variation on metabolic traits and suggest that mutations in LPIN1 are not a common cause of lipodystrophy in humans. The nominal associations with BMI and other metabolic traits in U.K. cohorts require replication in larger cohorts.
doi:10.2337/db08-0422
PMCID: PMC2518506  PMID: 18591397
7.  Evaluating the role of LPIN1 variation on insulin resistance, body weight and human lipodystrophy in UK populations 
Diabetes  2008;57(9):2527-2533.
OBJECTIVE:
Loss of Lpin1 activity causes lipodystrophy and insulin resistance in the fld mouse, and LPIN1 expression and common genetic variation were recently suggested to influence adiposity and insulin sensitivity in humans. We aimed to conduct a comprehensive association study to clarify the influence of LPIN1 common variation on adiposity and insulin sensitivity in UK populations, and to examine the role of LPIN1 mutations in insulin resistance syndromes.
RESEARCH DESIGN AND METHOD:
Twenty-two SNPs tagging LPIN1 common variation were genotyped in MRC Ely (N = 1709) and Hertfordshire (N = 2901) population-based cohorts. LPIN1 exons, exon/intron boundaries and 3′UTR were sequenced in 158 patients with idiopathic severe insulin resistance (including 23 lipodystrophic patients), and 48 controls.
RESULTS:
We found no association between LPIN1 SNPs and fasting insulin, but report a nominal association between rs13412852 and BMI (P = 0.042) in a meta-analysis of 8504 samples from in-house and publicly available studies. Three rare nonsynonymous variants (A353T, R552K and G582R) were detected in severely insulin resistant patients. However, these did not co-segregate with disease in affected families and Lipin1 protein expression and phosphorylation in patients with variants was indistinguishable from controls.
CONCLUSIONS:
Our data do not support a major effect of LPIN1 common variation on metabolic traits and suggest that mutations in LPIN1 are not a common cause of lipodystrophy in humans. The nominal associations with BMI and other metabolic traits in UK cohorts require replication in larger cohorts.
doi:10.2337/db08-0422
PMCID: PMC2518506  PMID: 18591397

Results 1-7 (7)