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Reevaluation of SNP heritability in complex human traits

by Cai, Na , Johnson, Michael R , Nejentsev, Sergey , Speed, Doug , Balding, David J

in 631/114/794 / 631/208/205/2138 / 692/308/2056 / Agriculture / Alleles / Analysis / Animal Genetics and Genomics / Biomedicine / Cancer Research / Case-Control Studies / Chromosome Fragile Sites / Cohort Studies / Computer Simulation / Consortia / Data processing / Datasets / Deoxyribonuclease / Deoxyribonuclease I / Estimates / Gene Frequency / Gene Function / Genetic Association Studies / Genome-Wide Association Study - methods / Genomes / Genotypes / Heritability / Human Genetics / Humans / Hypersensitivity / Inheritance Patterns / Linkage disequilibrium / Models, Genetic / Multifactorial Inheritance - genetics / Polymorphism, Single Nucleotide - genetics / Quantitative Trait, Heritable / Single-nucleotide polymorphism / Studies

2017

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Reevaluation of SNP heritability in complex human traits

by Cai, Na , Johnson, Michael R , Nejentsev, Sergey , Speed, Doug , Balding, David J

2017

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Reevaluation of SNP heritability in complex human traits

by Cai, Na , Johnson, Michael R , Nejentsev, Sergey , Speed, Doug , Balding, David J

2017

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Journal Article

Reevaluation of SNP heritability in complex human traits

Cai, Na,

Johnson, Michael R,

Nejentsev, Sergey,

Speed, Doug,

Balding, David J

2017

Overview

By analyzing imputed genetic data for 42 human traits, Doug Speed and colleagues derive a model that describes how heritability varies with minor allele frequency, linkage disequilibrium and genotype certainty. Using this model, they show that common SNPs contribute substantially more heritability than previously thought. SNP heritability, the proportion of phenotypic variance explained by SNPs, has been reported for many hundreds of traits. Its estimation requires strong prior assumptions about the distribution of heritability across the genome, but current assumptions have not been thoroughly tested. By analyzing imputed data for a large number of human traits, we empirically derive a model that more accurately describes how heritability varies with minor allele frequency (MAF), linkage disequilibrium (LD) and genotype certainty. Across 19 traits, our improved model leads to estimates of common SNP heritability on average 43% (s.d. 3%) higher than those obtained from the widely used software GCTA and 25% (s.d. 2%) higher than those from the recently proposed extension GCTA-LDMS. Previously, DNase I hypersensitivity sites were reported to explain 79% of SNP heritability; using our improved heritability model, their estimated contribution is only 24%.

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Publisher

Nature Publishing Group US,Nature Publishing Group

Subject

/ Alleles

/ Animal Genetics and Genomics