RT Journal Article SR Electronic T1 Contrasting regional architectures of schizophrenia and other complex diseases using fast variance components analysis JF bioRxiv FD Cold Spring Harbor Laboratory SP 016527 DO 10.1101/016527 A1 Po-Ru Loh A1 Gaurav Bhatia A1 Alexander Gusev A1 Hilary K Finucane A1 Brendan K Bulik-Sullivan A1 Samuela J Pollack A1 Schizophrenia Working Group of the Psychiatric Genomics Consortiumy A1 Teresa R de Candia A1 Sang Hong Lee A1 Naomi R Wray A1 Kenneth S Kendler A1 Michael C O’Donovan A1 Benjamin M Neale A1 Nick Patterson A1 Alkes L Price YR 2015 UL http://biorxiv.org/content/early/2015/06/05/016527.abstract AB Heritability analyses of GWAS cohorts have yielded important insights into complex disease architecture, and increasing sample sizes hold the promise of further discoveries. Here, we analyze the genetic architecture of schizophrenia in 49,806 samples from the PGC, and nine complex diseases in 54,734 samples from the GERA cohort. For schizophrenia, we infer an overwhelmingly polygenic disease architecture in which ≥71% of 1Mb genomic regions harbor at least one variant influencing schizophrenia risk. We also observe significant enrichment of heritability in GC-rich regions and in higher-frequency SNPs for both schizophrenia and GERA diseases. In bivariate analyses, we observe significant genetic correlations (ranging from 0.18 to 0.85) among several pairs of GERA diseases; genetic correlations were on average 1.3x stronger than correlations of overall disease liabilities. To accomplish these analyses, we developed a fast algorithm for multi-component, multi-trait variance components analysis that overcomes prior computational barriers that made such analyses intractable at this scale.