Association analysis of the IGF1 gene with childhood growth, IGF-1 concentrations and type 1 diabetes.

AIMS/HYPOTHESIS: Insulin-like growth factor-1 is a major childhood growth factor and promotes pancreatic islet cell survival and growth in vitro. We hypothesised that genetic variation in IGF1 might be associated with childhood growth, glucose metabolism and type 1 diabetes risk. We therefore examined the association between common genetic variation in IGF1 and predisposition to type 1 diabetes, childhood growth and metabolism. MATERIALS AND METHODS: Variants in IGF1 were identified by direct resequencing of the exons, exon-intron boundaries and 5' and 3' regions in 32 unrelated type 1 diabetes patients. A tagging subset of these variants was genotyped in a collection of type 1 diabetes families (3,121 parent-child trios). We also genotyped a previously reported CA repeat in the region 5' to IGF1. A subset of seven tag single nucleotide polymorphism (SNPs) that captured variants with minor allele frequency (MAF) > or =0.05 was genotyped in 902 children from the Avon Longitudinal Study of Parents And Children with data on growth, IGF-1 concentrations, insulin secretion and insulin action. RESULTS: Resequencing detected 27 SNPs in IGF1, of which 11 had a MAF > 0.05 and were novel. Variants with MAF > or = 0.10 were captured by a set of four tag-SNPs. These SNPs showed no association with type 1 diabetes. In children, global variation in IGF1 was weakly associated with IGF-1 concentrations, but not with other phenotypes. The CA repeat in the region 5' to IGF1 showed no association with any phenotype. CONCLUSIONS/INTERPRETATION: Common genetic variation in IGF1 alters IGF-1 concentrations but is not associated with growth, glucose metabolism or type 1 diabetes

Common variants at 10 Genomic loci influence hemoglobin A1C levels via glycemic and nonglycemic pathways

OBJECTIVE: Glycated hemoglobin (HbA(1c)), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA(1c). We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA(1c) levels. RESEARCH DESIGN AND METHODS: We studied associations with HbA(1c) in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA(1c) loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening. RESULTS: Ten loci reached genome-wide significant association with HbA(1c), including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10(−26)), HFE (rs1800562/P = 2.6 × 10(−20)), TMPRSS6 (rs855791/P = 2.7 × 10(−14)), ANK1 (rs4737009/P = 6.1 × 10(−12)), SPTA1 (rs2779116/P = 2.8 × 10(−9)) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10(−9)), and four known HbA(1c) loci: HK1 (rs16926246/P = 3.1 × 10(−54)), MTNR1B (rs1387153/P = 4.0 × 10(−11)), GCK (rs1799884/P = 1.5 × 10(−20)) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10(−18)). We show that associations with HbA(1c) are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA(1c)) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA(1c). CONCLUSIONS: GWAS identified 10 genetic loci reproducibly associated with HbA(1c). Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA(1c) levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA(1c)

Evaluation of four novel genetic variants affecting hemoglobin A1c levels in a population-based type 2 diabetes cohort (the HUNT2 study)

<p>Abstract</p> <p>Background</p> <p>Chronic hyperglycemia confers increased risk for long-term diabetes-associated complications and repeated hemoglobin A1c (HbA1c) measures are a widely used marker for glycemic control in diabetes treatment and follow-up. A recent genome-wide association study revealed four genetic loci, which were associated with HbA1c levels in adults with type 1 diabetes. We aimed to evaluate the effect of these loci on glycemic control in type 2 diabetes.</p> <p>Methods</p> <p>We genotyped 1,486 subjects with type 2 diabetes from a Norwegian population-based cohort (HUNT2) for single-nucleotide polymorphisms (SNPs) located near the <it>BNC2</it>, <it>SORCS1</it>, <it>GSC </it>and <it>WDR72 </it>loci. Through regression models, we examined their effects on HbA1c and non-fasting glucose levels individually and in a combined genetic score model.</p> <p>Results</p> <p>No significant associations with HbA1c or glucose levels were found for the <it>SORCS1</it>, <it>BNC2</it>, <it>GSC </it>or <it>WDR72 </it>variants (all <it>P</it>-values > 0.05). Although the observed effects were non-significant and of much smaller magnitude than previously reported in type 1 diabetes, the <it>SORCS1 </it>risk variant showed a direction consistent with increased HbA1c and glucose levels, with an observed effect of 0.11% (<it>P </it>= 0.13) and 0.13 mmol/l (<it>P </it>= 0.43) increase per risk allele for HbA1c and glucose, respectively. In contrast, the <it>WDR72 </it>risk variant showed a borderline association with reduced HbA1c levels (<it>β </it>= -0.21, <it>P </it>= 0.06), and direction consistent with decreased glucose levels (<it>β </it>= -0.29, <it>P </it>= 0.29). The allele count model gave no evidence for a relationship between increasing number of risk alleles and increasing HbA1c levels (<it>β </it>= 0.04, <it>P </it>= 0.38).</p> <p>Conclusions</p> <p>The four recently reported SNPs affecting glycemic control in type 1 diabetes had no apparent effect on HbA1c in type 2 diabetes individually or by using a combined genetic score model. However, for the <it>SORCS1 </it>SNP, our findings do not rule out a possible relationship with HbA1c levels. Hence, further studies in other populations are needed to elucidate whether these novel sequence variants, especially rs1358030 near the <it>SORCS1 </it>locus, affect glycemic control in type 2 diabetes.</p

Secretory granule neuroendocrine protein 1 (SGNE1) genetic variation and glucose intolerance in severe childhood and adult obesity

<p>Abstract</p> <p>Background</p> <p>7B2 is a regulator/activator of the prohormone convertase 2 which is involved in the processing of numerous neuropeptides, including insulin, glucagon and pro-opiomelanocortin. We have previously described a suggestive genetic linkage peak with childhood obesity on chr15q12-q14, where the 7B2 encoding gene, <it>SGNE1 </it>is located. The aim of this study is to analyze associations of <it>SGNE1 </it>genetic variation with obesity and metabolism related quantitative traits.</p> <p>Methods</p> <p>We screened <it>SGNE1 </it>for genetic variants in obese children and genotyped 12 frequent single nucleotide polymorphisms (SNPs). Case control analyses were performed in 1,229 obese (534 children and 695 adults), 1,535 individuals with type 2 diabetes and 1,363 controls, all French Caucasians. We also studied 4,922 participants from the D.E.S.I.R prospective population-based cohort.</p> <p>Results</p> <p>We did not find any association between <it>SGNE1 </it>SNPs and childhood or adult obesity. However, the 5' region SNP -1,701A>G associated with higher area under glucose curve after oral glucose tolerance test (p = 0.0005), higher HOMA-IR (p = 0.005) and lower insulinogenic index (p = 0.0003) in obese children. Similar trends were found in obese adults. SNP -1,701A>G did not associate with risk of T2D but tends to associate with incidence of type 2 diabetes (HR = 0.75 95%CI [0.55–1.01]; p = 0.06) in the prospective cohort.</p> <p>Conclusion</p> <p><it>SGNE1 </it>genetic variation does not contribute to obesity and common forms of T2D but may worsen glucose intolerance and insulin resistance, especially in the background of severe and early onset obesity. Further molecular studies are required to understand the molecular bases involved in this process.</p

Associations of Common Genetic Variants With Age-Related Changes in Fasting and Postload Glucose: Evidence From 18 Years of Follow-Up of the Whitehall II Cohort

OBJECTIVE In the general, nondiabetic population, fasting glucose increases only slightly over time, whereas 2-h postload glucose shows a much steeper age-related rise. The reasons underlying these different age trajectories are unknown. We investigated whether common genetic variants associated with fasting and 2-h glucose contribute to age-related changes of these traits.RESEARCH DESIGN AND METHODS We studied 5,196 nondiabetic participants of the Whitehall 11 cohort (aged 40-78 years) attending up to four 5-yearly oral glucose tolerance tests. A genetic score was calculated separately for fasting and 2-h glucose, including 16 and 5 single nucleotide polymorphisms, respectively. Longitudinal modeling with age centered at 55 years was used to study the effects of each genotype and genetic score on fasting and 2-h glucose and their interactions with age, adjusting for sex and time-varying BMI.RESULTS The fasting glucose genetic score was significantly associated with fasting glucose with a 0,029 mmol/L (95% CI 0.023-0.034) difference (P = 2.76 x 10(-21)) per genetic score point, an association that remained constant over time (age interaction P = 0.17). Two-hour glucose levels differed by 0.076 mmol/L (0.047-0.105) per genetic score point (P = 3.1 x 10(-7)); notably, this effect became stronger with increasing age by 0.006 mmol/L (0.003-0.009) per genetic score point per year (age interaction P = 3.0 x 10(-5)), resulting in diverging age trajectories by genetic score.CONCLUSIONS Common genetic variants contribute to the age-related rise of 2-h glucose levels, whereas associations of variants for fasting glucose are constant over time, in line with stable age trajectories of fasting glucose. Diabetes 60:16171623, 201

Association between FTO variant and change in body weight and its interaction with dietary factors: the DiOGenes study

Although FTO is an established obesity-susceptibility locus, it remains unknown whether it influences weight change in adult life and whether diet attenuates this association. Therefore, we investigated the association of FTO-rs9939609 with changes in weight and waist circumference (WC) during 6.8 years follow-up in a large-scale prospective study and examined whether these associations were modified by dietary energy percentage from fat, protein, carbohydrate, or glycemic index (GI). This study comprised data from five countries of European Prospective Investigation into Cancer and Nutrition (EPIC) and was designed as a case-cohort study for weight gain. Analyses included 11,091 individuals, of whom 5,584 were cases (age (SD), 47.6 (7.5) years), defined as those with the greatest unexplained annual weight gain during follow-up and 5,507 were noncases (48.0 (7.3) years), who were compared in our case-noncase (CNC) analyses. Furthermore, 6,566 individuals (47.9 (7.3) years) selected from the total sample (all noncases and 1,059 cases) formed the random subcohort (RSC), used for continuous trait analyses. Interactions were tested by including interaction terms in the models. In the RSC-analyses, FTO-rs9939609 was associated with BMI (β (SE), 0.17 (0.08) kg·m(-2)/allele; P = 0.034) and WC (0.47 (0.21) cm/allele; P = 0.026) at baseline, but not with weight change (5.55 (12.5) g·year(-1)/allele; P = 0.66) during follow up. In the CNC-analysis, FTO-rs9939609 was associated with increased risk of being a weight-gainer (OR: 1.1; P = 0.045). We observed no interaction between FTO-rs9939609 and dietary fat, protein and carbohydrate, and GI on BMI and WC at baseline or on change in weight and WC. FTO-rs9939609 is associated with BMI and WC at baseline, but association with weight gain is weak and only observed for extreme gain. Dietary factors did not influence the associations