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Summary statistic analyses can mistake confounding bias for heritability

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  • John B Holmes, Melbourne Integrative Genomics, School of Mathematics and Statistics, University of Melbourne, Melbourne, Australia.
  • ,
  • Doug Speed
  • David J Balding, UCL Genetics Institute, University College London (UCL), London, United Kingdom.

Linkage disequilibrium SCore regression (LDSC) has become a popular approach to estimate confounding bias, heritability, and genetic correlation using only genome-wide association study (GWAS) test statistics. SumHer is a newly introduced alternative with similar aims. We show using theory and simulations that both approaches fail to adequately account for confounding bias, even when the assumed heritability model is correct. Consequently, these methods may estimate heritability poorly if there was an inadequate adjustment for confounding in the original GWAS analysis. We also show that the choice of a summary statistic for use in LDSC or SumHer can have a large impact on resulting inferences. Further, covariate adjustments in the original GWAS can alter the target of heritability estimation, which can be problematic for test statistics from a meta-analysis of GWAS with different covariate adjustments.

Original languageEnglish
JournalGenetic Epidemiology
Pages (from-to)930-940
Number of pages11
Publication statusPublished - Dec 2019

Bibliographical note

© 2019 Wiley Periodicals, Inc.

    Research areas

  • GWAS, heritability estimation, misspecified models

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