PT  - JOURNAL ARTICLE
AU  - Po-Ru Loh
AU  - Gaurav Bhatia
AU  - Alexander Gusev
AU  - Hilary K Finucane
AU  - Brendan K Bulik-Sullivan
AU  - Samuela J Pollack
AU  - Schizophrenia Working Group of the Psychiatric Genomics Consortium
AU  - Teresa R de Candia
AU  - Sang Hong Lee
AU  - Naomi R Wray
AU  - Kenneth S Kendler
AU  - Michael C O’Donovan
AU  - Benjamin M Neale
AU  - Nick Patterson
AU  - Alkes L Price
TI  - Contrasting regional architectures of schizophrenia and other complex diseases using fast variance components analysis
AID  - 10.1101/016527
DP  - 2015 Jan 01
TA  - bioRxiv
PG  - 016527
4099  - http://biorxiv.org/content/early/2015/03/13/016527.short
4100  - http://biorxiv.org/content/early/2015/03/13/016527.full
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 ≥76% 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) for 13 of 36 pairs of GERA diseases; genetic correlations were consistently stronger (1.3x on average) than correlations of overall disease liabilities. To accomplish these analyses, we developed a novel, fast algorithm for multi-component, multitrait variance components analysis that overcomes prior computational barriers that made such analyses intractable at this scale.