A method to estimate the contribution of regional genetic associations to complex traits from summary association statistics

Sci Rep. 2016 Jun 8;6:27644. doi: 10.1038/srep27644.

Abstract

Despite considerable efforts, known genetic associations only explain a small fraction of predicted heritability. Regional associations combine information from multiple contiguous genetic variants and can improve variance explained at established association loci. However, regional associations are not easily amenable to estimation using summary association statistics because of sensitivity to linkage disequilibrium (LD). We now propose a novel method, LD Adjusted Regional Genetic Variance (LARGV), to estimate phenotypic variance explained by regional associations using summary statistics while accounting for LD. Our method is asymptotically equivalent to a multiple linear regression model when no interaction or haplotype effects are present. It has several applications, such as ranking of genetic regions according to variance explained or comparison of variance explained by two or more regions. Using height and BMI data from the Health Retirement Study (N = 7,776), we show that most genetic variance lies in a small proportion of the genome and that previously identified linkage peaks have higher than expected regional variance.

MeSH terms

  • Algorithms
  • Genetic Association Studies / methods*
  • Genetic Linkage
  • Genetic Variation
  • Genome-Wide Association Study / methods
  • Genotype
  • Humans
  • Linkage Disequilibrium
  • Models, Genetic*
  • Models, Statistical*
  • Multifactorial Inheritance*
  • Phenotype
  • Polymorphism, Single Nucleotide