RESUMEN
Genome-wide association (GWA) studies identified novel gene variants that are associated with type 2 diabetes. However, results were not always consistent across different populations. Thus, the aims of this study were (i) to replicate findings from previous GWA studies in mainly Northern European populations using data from the German KORA 500 K diabetes project and (ii) to assess the impact of BMI on associations between single nucleotide polymorphisms (SNPs) and type 2 diabetes. The KORA 500 K diabetes project includes 433 cases with validated type 2 diabetes and 1 438 nondiabetic controls from two population-based KORA surveys. Genotyping was performed using the Affymetrix GeneChip Human Mapping 500 K Array Set. We investigated associations between SNPs and type 2 diabetes in 10 genes that have been reported to increase the risk of type 2 diabetes or were in complete or near-complete linkage disequilibrium with these variants. SNPs in the CDKAL1 gene showed the strongest association with type 2 diabetes [range of age and sex-adjusted odds ratios (OR): 1.30-1.39, p-values 0.0008-0.0004]. In addition, we found evidence for association of SNPs in the genes PPARG, IGF2BP2, HHEX, TCF7L2, and FTO with type 2 diabetes in the same directions as previously described (p<0.05), but not for WFS1, CDKN2A/B, KCNJ11, or EXT2. Adjustment for BMI slightly strengthened the link between CDKAL1 and type 2 diabetes, but had almost no impact on the other associations. We conclude that gene variants of CDKAL1, PPARG, IGF2BP2, HHEX, TCF7L2, and FTO predispose to type 2 diabetes in the German KORA 500 K study population. These associations appear to be independent of BMI.
Asunto(s)
Quinasa 5 Dependiente de la Ciclina/genética , Diabetes Mellitus Tipo 2/genética , Predisposición Genética a la Enfermedad , PPAR gamma/genética , Polimorfismo de Nucleótido Simple/genética , Proteínas de Unión al ARN/genética , Población Blanca/genética , Adulto , Anciano , Índice de Masa Corporal , Inhibidor p15 de las Quinasas Dependientes de la Ciclina/genética , Inhibidor p16 de la Quinasa Dependiente de Ciclina/genética , Femenino , Alemania , Proteínas de Homeodominio/genética , Humanos , Masculino , Proteínas de la Membrana/genética , Persona de Mediana Edad , N-Acetilglucosaminiltransferasas/genética , Canales de Potasio de Rectificación Interna/genética , Factores de Transcripción TCF/genética , Proteína 2 Similar al Factor de Transcripción 7 , Factores de Transcripción/genética , ARNt MetiltransferasasRESUMEN
This article considers the problem of comparing several treatments (dose levels, interventions, etc.) with the best, where the best treatment is unknown and the treatments are ordered in some sense. Order relations among treatments often occur quite naturally in practice. They may be ordered according to increasing risks, such as tolerability or safety problems with increasing dose levels in a dose-response study, for example. We tackle the problem of constructing a lower confidence bound for the smallest index of all treatments being at most marginally less effective than the (best) treatment having the largest effect. Such a bound ensures at confidence level 1 -alpha that all treatments with lower indices are relevantly less effective than the best competitor. We derive a multiple testing strategy that results in sharp confidence bounds. The proposed lower confidence bound is compared with those derived from other testing strategies. We further derive closed-form expressions for power and sample size calculations. Finally, we investigate several real data sets to illustrate various applications of our methods.
