Mar 14, 2015

Contrasting regional architectures of schizophrenia and other complex diseases using fast variance components analysis

BioRxiv : the Preprint Server for Biology
Po-Ru LohAlkes L Price

Abstract

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.

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Mentioned in this Paper

Genome-Wide Association Study
Genome
Schizophrenia
palmitoyl glycol chitosan
Genomics
Contrast Used
Analysis
Polygene
Single Nucleotide Polymorphism
Cohort

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