Analysis of 72,469 UK Biobank exomes links rare variants to male-pattern hair loss.

Male-pattern hair loss (MPHL) is common and highly heritable. While genome-wide association studies (GWAS) have generated insights into the contribution of common variants to MPHL etiology, the relevance of rare variants remains unclear. To determine the contribution of rare variants to MPHL etiology, we perform gene-based and single-variant analyses in exome-sequencing data from 72,469 male UK Biobank participants. While our population-level risk prediction suggests that rare variants make only a minor contribution to general MPHL risk, our rare variant collapsing tests identified a total of five significant gene associations. These findings provide additional evidence for previously implicated genes (EDA2R, WNT10A) and highlight novel risk genes at and beyond GWAS loci (HEPH, CEPT1, EIF3F). Furthermore, MPHL-associated genes are enriched for genes considered causal for monogenic trichoses. Together, our findings broaden the MPHL-associated allelic spectrum and provide insights into MPHL pathobiology and a shared basis with monogenic hair loss disorders.

The influence of regression models on genome-wide association studies of alcohol dependence: a comparison of binary and quantitative analyses.

INTRODUCTION: Genome-wide association studies (GWAS) of alcohol dependence syndrome (ADS) offer a platform to detect genetic risk loci. However, the majority of the ADS GWAS undertaken, to date, have utilized a case-control design and have failed to identify consistently replicable loci with the exception of protective variants within the alcohol metabolizing genes, notably ADH1B. The ADS phenotype shows considerable variability which means that the use of quantitative variables as a proxy for the severity of ADS has the potential to facilitate identification of risk loci by increasing statistical power. The current study aims to examine the influences of using binary and adjusted quantitative measures of ADS on GWAS outcomes and on calculated polygenic risk scores (PRS). METHODS: A GWAS was performed in 1251 healthy controls with no history of excess alcohol use and 739 patients with ADS classified using binary DMS-IV criteria. Two additional GWAS were undertaken using a quantitative score based on DSM-IV criteria, which were applied assuming both normal and non-normal distributions of the phenotypic variables. PRS analyses were performed utilizing the data from the binary and the quantitative trait analyses. RESULTS: No associations were identified at genome-wide significance in any of the individual GWAS; results were comparable in all three. The top associated single nucleotide polymorphism was located on the alcohol dehydrogenase gene cluster on chromosome 4, consistent with previous ADS GWAS. The quantitative trait analysis adjusted for the distribution of the criterion score and the associated PRS had the smallest standard errors and thus the greatest precision. CONCLUSION: Further exploitation of the use of qualitative trait analysis in GWAS in ADS is warranted.