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Bivariate causal mixture model quantifies polygenic overlap between complex traits beyond genetic correlation.

Oleksandr Frei1, Dominic Holland2,3, Olav B Smeland4,5

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|June 5, 2019
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Summary
This summary is machine-generated.

A new tool, MiXeR, quantifies shared genetic influences across complex traits using genome-wide association studies (GWAS) summary statistics. It reveals significant polygenic overlap between schizophrenia and bipolar disorder, and even between schizophrenia and educational attainment, despite low genetic correlation.

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Area of Science:

  • Genetics
  • Psychiatric Genetics
  • Statistical Genetics

Background:

  • Genome-wide association studies (GWAS) indicate substantial shared genetic factors underlying complex human traits and disorders.
  • Understanding the genetic architecture of complex traits, particularly mental disorders, is crucial for advancing biological insights and therapeutic strategies.

Purpose of the Study:

  • To introduce MiXeR, a novel statistical tool for quantifying polygenic overlap between traits using GWAS summary statistics, independent of genetic correlation.
  • To elucidate the unique and shared genetic components contributing to complex phenotypes.

Main Methods:

  • MiXeR utilizes GWAS summary statistics to estimate the proportion of shared and unique polygenic influences across different traits.
  • Results are visualized using Venn diagrams to represent the overlap in causal variants.
  • Analysis was conducted at 90% SNP-heritability explained for each phenotype.

Main Results:

  • MiXeR estimated 8.3K causal variants for schizophrenia and 6.4K for bipolar disorder, with 6.2K shared between them.
  • The tool identified significant polygenic overlap between schizophrenia and educational attainment, sharing 8.3K causal variants despite a near-zero genetic correlation.
  • An additional 2.5K variants were uniquely associated with educational attainment.

Conclusions:

  • MiXeR provides a robust method to quantify polygenic overlap, offering insights into the genetic architecture of complex traits.
  • The findings highlight substantial shared genetic influences between seemingly disparate traits like schizophrenia and educational attainment.
  • This approach enhances our understanding of cross-trait genetic architectures by considering polygenicity, discoverability, and heritability.