LD score regression distinguishes confounding from polygenicity in genome-wide association studies

Schizophrenia Working Group of the Psychiatric Genomics Consortium

Research output: Contribution to journalArticle

599 Citations (Scopus)

Abstract

Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.

Original languageEnglish (US)
Pages (from-to)291-295
Number of pages5
JournalNature Genetics
Volume47
Issue number3
DOIs
StatePublished - Feb 25 2015

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Genome-Wide Association Study
Linkage Disequilibrium
Economic Inflation
Sample Size
Population

All Science Journal Classification (ASJC) codes

  • Genetics

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LD score regression distinguishes confounding from polygenicity in genome-wide association studies. / Schizophrenia Working Group of the Psychiatric Genomics Consortium.

In: Nature Genetics, Vol. 47, No. 3, 25.02.2015, p. 291-295.

Research output: Contribution to journalArticle

Schizophrenia Working Group of the Psychiatric Genomics Consortium 2015, 'LD score regression distinguishes confounding from polygenicity in genome-wide association studies', Nature Genetics, vol. 47, no. 3, pp. 291-295. https://doi.org/10.1038/ng.3211
Schizophrenia Working Group of the Psychiatric Genomics Consortium. LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nature Genetics. 2015 Feb 25;47(3):291-295. https://doi.org/10.1038/ng.3211
Schizophrenia Working Group of the Psychiatric Genomics Consortium. / LD score regression distinguishes confounding from polygenicity in genome-wide association studies. In: Nature Genetics. 2015 ; Vol. 47, No. 3. pp. 291-295.
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abstract = "Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.",
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