Improved detection of common variants associated with schizophrenia and bipolar disorder using pleiotropy-informed conditional false discovery rate.

ABSTRACT: Several lines of evidence suggest that genome-wide association studies (GWAS) have the potential to explain more of the "missing heritability" of common complex phenotypes. However, reliable methods to identify a larger proportion of single nucleotide polymorphisms (SNPs) that impact disease risk are currently lacking. Here, we use a genetic pleiotropy-informed conditional false discovery rate (FDR) method on GWAS summary statistics data to identify new loci associated with schizophrenia (SCZ) and bipolar disorders (BD), two highly heritable disorders with significant missing heritability. Epidemiological and clinical evidence suggest similar disease characteristics and overlapping genes between SCZ and BD. Here, we computed conditional Q-Q curves of data from the Psychiatric Genome Consor

SUBMITTER: Andreassen OA 

PROVIDER: S-EPMC3636100 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature