Evaluating the estimation of genetic correlation and heritability using summary statistics.

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  • Author(s): Zhang J;Zhang J; Schumacher FR; Schumacher FR
  • Source:
    Molecular genetics and genomics : MGG [Mol Genet Genomics] 2021 Nov; Vol. 296 (6), pp. 1221-1234. Date of Electronic Publication: 2021 Sep 29.
  • Publication Type:
    Journal Article
  • Language:
    English
  • Additional Information
    • Source:
      Publisher: Springer-Verlag Country of Publication: Germany NLM ID: 101093320 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1617-4623 (Electronic) Linking ISSN: 16174623 NLM ISO Abbreviation: Mol Genet Genomics Subsets: MEDLINE
    • Publication Information:
      Original Publication: Berlin : Springer-Verlag, c2001-
    • Subject Terms:
    • Abstract:
      While novel statistical methods quantifying the shared heritability of traits and diseases between ancestral distinct populations have been recently proposed, a thorough evaluation of these approaches under differing circumstances remain elusive. Brown et al.2016 proposed the method Popcorn to estimate the shared heritability, i.e. genetic correlation, using only summary statistics. Here, we evaluate Popcorn under several parameters and circumstances: sample size, number of SNPs, sample size of external reference panel, various population pairs, inappropriate external reference panel, and admixed population involved. Our results determined the minimum sample size of the external reference panel, summary statistics, and number of SNPs required to accurately estimate both the genetic correlation and heritability. Moreover, the number of individuals and SNPs required to produce accurate and stable estimates was directly proportional with heritability in Popcorn. Misrepresentation of the reference panel overestimated the genetic correlation by 20% and heritability by 60%. Lastly, applying Popcorn to homogeneous (EUR) and admixed (ASW) populations underestimated the genetic correlation by 15%. Although statistical approaches estimating the shared heritability between ancestral populations will provide novel etiologic insight, caution is required ensuring results are based on the appropriate sample size, number of SNPs, and the generalizability of the reference panel to the discovery populations.
      (© 2021. The Author(s).)
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    • Grant Information:
      R01 CA194393 United States CA NCI NIH HHS; U01 CA194393 United States CA NCI NIH HHS; CA194393 United States CA NCI NIH HHS
    • Contributed Indexing:
      Keywords: Evaluation; Genetic correlation; Heritability; Summary statistics
    • Publication Date:
      Date Created: 20210929 Date Completed: 20211103 Latest Revision: 20220218
    • Publication Date:
      20221213
    • Accession Number:
      PMC8550643
    • Accession Number:
      10.1007/s00438-021-01817-7
    • Accession Number:
      34586498