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In patients with type 2 diabetes, sleep-disordered breathing is a widespread cause of deteriorated quality of life. However, robust prevalence estimates for sleep-disordered breathing in patients with type 2 diabetes are limited due to scarce data. We investigated sex differences in sleep-disordered breathing prevalence and its modulators in the DIACORE SDB substudy, a sample of outpatient type 2 diabetes. 721 participants were tested for sleep-disordered breathing using a two-channel sleep apnoea monitoring device. Patients were stratified according to the severity of sleep-disordered breathing, defined as an apnoea-hypopnoea index

Height, adiposity, and fat distribution differ in men and women and, in part, may explain sex differences in susceptibilities to complex diseases like cardiovascular disease. Genome-wide association studies (GWAS) of these traits have previously reported sexually dimorphic associations, yet studies have primarily been limited to interrogation of variants with genome wide significant main effects only. Because of these biological differences by sex and as there is growing interest in the study of gene-environment interactions in the context of GWAS in general, we conducted sex-specific meta-analyses of 9 phenotypes: height (HT), weight (WT), body mass index (BMI), waist circumference (WC), hip circumference (HIP), WC/HC ratio (WHR), WC adjusted for BMI (WCadjBMI), HC adjusted for BMI (HCadjBMI), and WHR adjusted for BMI (WHRadjBMI). In the discovery stage, we performed sex-specific meta-analyses of 46 GWAS, comprising 60,586 men and 73,137 women. Each study used an additive model to test up to ∼2.8M imputed SNPs for association with inverse-normal transformed phenotypes. From our first scan based on the sex-specific association P-values (P women , P men ) across all phenotypes, we selected 619 independent SNPs at a false discovery rate (FDR) of 5% to take forward to replication. We also conducted a second scan based on the P-value for sex difference (P sex-diff ) with better power to detect signals of opposite effect direction, yet we did not detect any signal at FDR of 5%. Follow-up of the 619 SNPs in up to 62,395 men and 74,657 women, many of which were genotyped on Metabochip, a custom Illumina iSelect array to which we submitted sex-specific SNPs, resulted in 205 loci with genome-wide significanct (P women or P men < 5x10 -8 ) p values in the combined discovery and follow-up analysis. For those 205 loci, we found 4 loci with significant (P sex-diff < 0.05/205) and 14 loci with suggestive (P sex-diff GRB14 , 1q41 , VEGFA , ADAMTS9), known anthropometric trait associations without any prior evidence for sexual-dimorphism ( 14q23.1, 3q21.3, 6q14.1, 4q12, 12q24.31, SEC16B, 17q21.32 , and 13q31.3 ), and novel sex-specific associations with anthropometric traits ( 5q11.2, 5q23.1, PPARG, 2q37.1, 17p11.2 , and 5q35.1 ). Interestingly, we found that our replicated loci for WHR/WC were enriched with markers with sex-differences, and that these genetic effects were uniformly stronger in women compared to men. Collectively, these results underscore the gain from sex-stratified GWAS in order to better pinpoint the genetics of complex traits and illustrate a sexually dimorphic genetic underpinning to some of these traits. Our results more globally emphasize the need to consider gene-environment interaction when searching for genes influencing risk to complex disease.

Fragestellung: Es wird vermutet, dass das Cytokin Interleukin-6 eine kausale Rolle in der Entstehung von Diabetes mellitus Typ 2 (T2DM) spielt. In zahlreichen kleineren Studien wurden die zwei im Promoterbereich liegenden Einzelnukleotidpolymorphismen (SNPs) -174G>C (rs1800795) und -573G>C (rs1800796) des fur Interleukin-6 kodierenden IL6-Gens auf ihren Zusammenhang mit T2DM untersucht. Die vorliegenden Ergebnisse waren jedoch nicht eindeutig. Um den Zusammenhang zwischen den beiden IL6-Varianten und T2DM zu klaren, wurde eine auf Individualdaten beruhende Meta-Analyse publizierter und unpublizierter Studien initiiert. Methodik: Nach einer systematischen Literaturrecherche sowie Rekrutierung aller verfugbaren publizierten und unpublizierten Studien, wurden die Individualdaten im Studienzentrum (Institut fur Epidemiologie des Helmholtz Zentrum Munchen, Neuherberg) gesammelt und auf Plausibilitat gepruft. Studienspezifische Assoziationsschatzer zum Zusammenhang zwischen den IL6-Varianten und dem Phanotyp T2DM – und wo verfugbar dem Phanotyp Nuchternglucose – wurden mittels multivariablen Regressionsmodellen mithilfe der Statistiksoftware SAS Version 9.1 berechnet. Die Heterogenitat zwischen den studienspezifischen Schatzern wurde untersucht und die Schatzer mit der „inverse-variance fixed-effect“ Methode zusammengefasst, da die Heterogenitat sehr gering war. Ergebnisse: Der Analysedatensatz umfasste fur den dichotomen Phanotyp T2DM Individualdaten von uber 20.000 Teilnehmern aus 21 publizierten und unpublizierten Studien, fur den quantitativen Phanotyp Nuchternglucose Individualdaten von uber 10.000 Teilnehmern aus acht publizierten und unpublizierten Studien. Die GC- und CC-Genotypen des IL6–174G>C Polymorphismus waren mit einem erniedrigten T2DM-Risiko (OR=0.91; P=0.04) und erniedrigter Nuchternglucose assoziiert (beta=-0.09mmol/l; P=0.01). Es gab keinen Hinweis auf eine Assoziation zwischen IL6–573G>C and T2DM. Schlussfolgerungen: Die Assoziationen zwischen dem IL6–174 C-Allel und reduziertem T2DM-Risiko sowie erniedrigten Nuchternglucosespiegeln, die in dieser bisher grosten auf Individualdaten basierenden Assoziationsanalyse fur T2DM entdeckt wurden, liefern weitere Hinweise dafur, dass Immunmediatoren in kausalem Zusammenhang mit T2DM stehen.

It is well established that odds ratios estimated by logistic regression are subject to bias if exposure is measured with error. The dependence of this bias on exposure parameter values, particularly for multiplicative measurement error, and its implications in epidemiology are not, however, as fully acknowledged. We have been motivated by a German West case-control study on lung cancer and residential radon, where restriction to a subgroup exhibiting larger mean and variance of exposure than the entire group has shown higher odds ratio estimates as compared to the full analysis. By means of correction formulae and simulations, we show that bias from additive classical type error depends on the exposure variance, not on the exposure mean, and that bias from multiplicative classical type error depends on the geometric standard deviation (in other words on the coefficient of variation of exposure), but not on the geometric mean of exposure. Bias from additive or multiplicative Berkson type error is independent of exposure distribution parameters. This indicates that there is a potential of differential bias between groups where these parameters vary. Such groups are commonly compared in epidemiology: for example when the results of subgroup analyses are contrasted or meta-analyses are performed. For the German West radon study, we show that the difference of measurement error bias between the subgroup and the entire group exhibits the same direction but not the same dimension as the observed results. Regarding meta-analysis of five European radon studies, we find that a study such as this German study will necessarily result in smaller odds ratio estimates than other studies due to the smaller exposure variance and coefficient of variation of exposure. Therefore, disregard of measurement error can not only lead to biased estimates, but also to inconsistent results and wrongly concluded effect differences between groups.

Identification of genetic variants affecting complex traits such as obesity is confounded by many types of bias, especially when effect sizes are small. Given our findings of a positive association between rs7566605 and body mass index in four out of five separate samples, a false positive finding cannot be ruled out with certainty but seems unlikely. Meta-analyses of multiple large studies will help refine the estimate of the effects of rs7566605 on body mass index.