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Motivation: In genome-wide association studies (GWAS) examining hundreds of thousands of genetic markers, the potentially high number of false positive findings requires statistical correction for multiple testing. Permutation tests are considered the gold standard for multiple testing correction in GWAS, because they simultaneously provide unbiased type I error control and high power. At the same time, they demand heavy computational effort, especially with large-scale datasets of modern GWAS. In recent years, the computational problem has been circumvented by using approximations to permutation tests, which, however, may be biased. Results: We have tackled the original computational problem of permutation testing in GWAS and herein present a permutation test algorithm one or more orders of magnitude faster than existing implementations, which enables efficient permutation testing on a genome-wide scale. Our algorithm does not rely on any kind of approximation and hence produces unbiased results identical to a standard permutation test. A noteworthy feature of our algorithm is a particularly effective performance when analyzing high-density marker sets. [ABSTRACT FROM AUTHOR]

Background: A recent genome-wide association (GWA) study of U.S. Caucasians suggested that eight single nucleotide polymorphisms (SNPs) in CTNNBL1 are associated with obesity and increased fat mass. We analysed the respective SNPs in data from our previously published GWA for early onset obesity (case-control design), in GWA data from a population-based cohort of adults, and in an independent family-based obesity study. We investigated whether variants in CTNNBL1 (including rs6013029) and in three other genes (SH3PXD2B, SLIT3 and FLJ42133,) were associated with obesity. Methods: The GWA studies were carried out using Affymetrix® SNP Chips with approximately 500,000 markers each. In the families, SNP rs6013029 was genotyped using the TaqMan® allelic discrimination assay. The German case-control GWA included 487 extremely obese children and adolescents and 442 healthy lean individuals. The adult GWA included 1,644 individuals from a German population-based study (KORA). The 775 independent German families consisted of extremely obese children and adolescents and their parents. Results: We found no evidence for an association of the reported variants in CTNNBL1 with early onset obesity or increased BMI. Further, in our family-based study we found no evidence for over-transmission of the rs6013029 risk-allele T to obese children. Additionally, we found no evidence for an association of SH3PXD2B, SLIT3 and FLJ42133 variants in our two GWA samples. Conclusion: We detected no confirmation of the recent association of variants in CTNNBL1 with obesity in a population of Central European ancestry. [ABSTRACT FROM AUTHOR]

A genome-wide association (GWA) study with pooled DNA in adult attention-deficit/hyperactivity disorder (ADHD) employing ~500K SNP markers identifies novel risk genes and reveals remarkable overlap with findings from recent GWA scans in substance use disorders. Comparison with results from our previously reported high-resolution linkage scan in extended pedigrees confirms several chromosomal loci, including 16q23.1-24.3 which also reached genome-wide significance in a recent meta-analysis of seven linkage studies (Zhou et al. in Am J Med Genet Part B, 2008). The findings provide additional support for a common effect of genes coding for cell adhesion molecules (e.g., CDH13, ASTN2) and regulators of synaptic plasticity (e.g., CTNNA2, KALRN) despite the complex multifactorial etiologies of adult ADHD and addiction vulnerability. [ABSTRACT FROM AUTHOR]

Summary: PERMORY is software for accelerated permutation testing of genome-wide association studies (GWAS). We have parallelized PERMORY using the Message-Passing Interface resulting in a nearly linear speedup. Furthermore, we added accelerated analysis of GWAS using quantitative phenotypes, and an accurate estimation of the effective number of independent tests.Availability and implementation: Free download from http://permory.orgContact: rpahl@staff.uni-marburg.de; volker.steiss@mni.thm.de [ABSTRACT FROM AUTHOR]

The article discusses a study which aims to identify the genetic variants that influence the trait of attention-deficit/hyperactivity disorder (ADHD), the most common childhood onset psychiatric condition, that has shown to be highly heritable. The study used case-control analyses of 896 cases and found no genome-wide significant associations. The study found that candidate gene findings that suggest the effects of ADHD risk variants are very small.

The article discusses a study which aims to identify genetic variants that influence the trait of genomewide significant level in attention-deficit/hyperactivity disorder (ADHD). The disorder is one of the most common psychiatric phenotypes that affect children and teenagers. The study use data from different projects and HapMap single nucleotide polymorphisms were assigned. The study reveals that an analysis of candidate genes may be involved in ADHD, yet no genomewide associations were found.