The type 2 diabetes risk allele of TMEM154-rs6813195 associates with decreased beta cell function in a study of 6,486 Danes

A trans-ethnic meta-analysis of type 2 diabetes genome-wide association studies has identified seven novel susceptibility variants in or near TMEM154, SSR1/RREB1, FAF1, POU5F1/TCF19, LPP, ARL15 and ABCB9/MPHOSPH9. The aim of our study was to investigate associations between these novel risk variants and type 2 diabetes and pre-diabetic traits in a Danish population-based study with measurements of plasma glucose and serum insulin after an oral glucose tolerance test in order to elaborate on the physiological impact of the variants.Case-control analyses were performed in up to 5,777 patients with type 2 diabetes and 7,956 individuals with normal fasting glucose levels. Quantitative trait analyses were performed in up to 5,744 Inter99 participants naïve to glucose-lowering medication. Significant associations between TMEM154-rs6813195 and the beta cell measures insulinogenic index and disposition index and between FAF1-rs17106184 and 2-hour serum insulin levels were selected for further investigation in additional Danish studies and results were combined in meta-analyses including up to 6,486 Danes.We confirmed associations with type 2 diabetes for five of the seven SNPs (TMEM154-rs6813195, FAF1-rs17106184, POU5F1/TCF19-rs3130501, ARL15-rs702634 and ABCB9/MPHOSPH9-rs4275659). The type 2 diabetes risk C-allele of TMEM154-rs6813195 associated with decreased disposition index (n=5,181, β=-0.042, p=0.012) and insulinogenic index (n=5,181, β=-0.032, p=0.043) in Inter99 and these associations remained significant in meta-analyses including four additional Danish studies (disposition index n=6,486, β=-0.042, p=0.0044; and insulinogenic index n=6,486, β=-0.037, p=0.0094). The type 2 diabetes risk G-allele of FAF1-rs17106184 associated with increased levels of 2-hour serum insulin (n=5,547, β=0.055, p=0.017) in Inter99 and also when combining effects with three additional Danish studies (n=6,260, β=0.062, p=0.0040).Studies of type 2 diabetes intermediary traits suggest the diabetogenic impact of the C-allele of TMEM154-rs6813195 is mediated through reduced beta cell function. The impact of the diabetes risk G-allele of FAF1-rs17106184 on increased 2-hour insulin levels is however unexplained

Studies of the Association of Arg72Pro of Tumor Suppressor Protein p53 with Type 2 Diabetes in a Combined Analysis of 55,521 Europeans

A study of 222 candidate genes in type 2 diabetes reported association of variants in RAPGEF1, ENPP1, TP53, NRF1, SLC2A2, SLC2A4 and FOXC2 with type 2 diabetes in 4,805 Finnish individuals. We aimed to replicate these associations in a Danish case-control study and to substantiate any replicated associations in meta-analyses. Furthermore, we evaluated the impact on diabetes-related intermediate traits in a population-based sample of middle-aged Danes.We genotyped nine lead variants in the seven genes in 4,973 glucose-tolerant and 3,612 type 2 diabetes Danish individuals. In meta-analyses we combined case-control data from the DIAGRAM+ Consortium (n = 47,117) and the present genotyping results. The quantitative trait studies involved 5,882 treatment-naive individuals from the Danish Inter99 study.None of the nine investigated variants were significantly associated with type 2 diabetes in the Danish samples. However, for all nine variants the estimate of increase in type 2 diabetes risk was observed for the same allele as previously reported. In a meta-analysis of published and online data including 55,521 Europeans the G-allele of rs1042522 in TP53 showed significant association with type 2 diabetes (OR = 1.06 95% CI 1.02-1.11, p = 0.0032). No substantial associations with diabetes-related intermediary phenotypes were found.The G-allele of TP53 rs1042522 is associated with an increased prevalence of type 2 diabetes in a combined analysis of 55,521 Europeans

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.Peer reviewe

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways.Peer reviewe

Meta-analysis of the effect of the C-allele of <i>TMEM154</i>-rs6813195 on insulinogenic index in 6,486 individuals from the Inter99 study (n = 5,181), Health 2008 study (n = 592), ADIGEN controls (n = 246), ADIGEN obese cases (n = 165) and Danish Family study (n = 302).

<p>Gray diamond represents combined change per risk allele and the 95% confidence interval. Gray squares represent effects size estimates (beta coefficients) in single studies sized according to their weight in the meta-analyses. The horizontal lines through the gray squares represent the 95% confidence interval. ob, obese. <i>p</i>, <i>P</i>-value. CI, confidence interval. W(fixed), study weight in the fixed effect meta-analysis.</p

Meta-analysis of the effect of the G-allele of <i>FAF1</i>-rs17106184 on 2-hour serum insulin in 6,260 individuals from the Inter99 study (n = 5,547), ADIGEN controls (n = 246), ADIGEN obese cases (n = 165) and Danish Family study (n = 302).

<p>Gray diamond represents combined change per risk allele and the 95% confidence interval. Gray squares represent effects size estimates (beta coefficients) in single studies sized according to their weight in the meta-analyses. The horizontal lines through the gray squares represent the 95% confidence interval. ob, obese. <i>p</i>, <i>P</i>-value. CI, confidence interval. W(fixed), study weight in the fixed effect meta-analysis.</p

T2D case-control analyses of up to 5,777 patients from Inter99 (n = 320), Health 2006 (n = 166), Health 2008 (n = 18), Steno Diabetes Center (n = 1,424), ADDITION (n = 1,870) and Vejle Biobank (n = 1,979) and up to 7,956 individuals with normal fasting glucose from Inter99 (n = 4,590), Health 2006 (n = 2,412), Health 2008 (n = 528) and Vejle Biobank (n = 426).

<p>Number of cases vs. number of controls is shown as 0/1/2 risk alleles. Odds ratios (OR) and <i>P</i>-values (<i>P</i>) are adjusted for age and sex. OR_adjBMI and <i>P</i>_adjBMI are adjusted for age, sex and BMI. SNP, single nucleotide polymorphism. RA, risk allele. RAF, risk allele frequency. CI, confidence interval.</p><p>T2D case-control analyses of up to 5,777 patients from Inter99 (n = 320), Health 2006 (n = 166), Health 2008 (n = 18), Steno Diabetes Center (n = 1,424), ADDITION (n = 1,870) and Vejle Biobank (n = 1,979) and up to 7,956 individuals with normal fasting glucose from Inter99 (n = 4,590), Health 2006 (n = 2,412), Health 2008 (n = 528) and Vejle Biobank (n = 426).</p

Associations between the seven T2D risk variants and quantitative traits in up to 5,744 Danish individuals naive to glucose-lowering medication.

<p>Raw data are mean±SD or median (interquartile range) and are stratified according to genotype. Values of serum insulin and derived indexes of insulinogenic index, ISI_Matsuda, disposition index and BIGTT-AIR were natural logarithmical (ln) transformed before analysis. Effects represent beta coefficients and are shown for the T2D risk allele. <i>P</i>-values (<i>P</i>) are adjusted for age (BIGTT-AIR and BIGTT-SI) or sex and age (all other traits). <i>P</i>_adjBMI are <i>P</i>-values adjusted for age, sex and BMI. All analyses assume an additive genetic model. SE, standard error.</p><p>Associations between the seven T2D risk variants and quantitative traits in up to 5,744 Danish individuals naive to glucose-lowering medication.</p