Pleiotropic shared heritability quantifies the shared genetic variance of common diseases
Abstract The overall contribution of pleiotropy to disease architectures is unknown, as most studies estimate genetic correlations with each auxiliary disease in turn. Here we propose a method—pleiotropic shared heritability with bias correction (PHBC)—to estimate the liability-scale genetic variance of a target disease that is shared with a specific set of auxiliary diseases ( $${{h}^{2}}_{\mathrm{pleio}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:msup> <mml:mrow> <mml:mi>h</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msup> </mml:mrow> <mml:mrow> <mml:mi>pleio</mml:mi> </mml:mrow> </mml:msub> </mml:math> ). PHBC estimates $${{h}^{2}}_{\mathrm{pleio}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:msup> <mml:mrow> <mml:mi>h</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msup> </mml:mrow> <mml:mrow> <mml:mi>pleio</mml:mi> </mml:mrow> </mml:msub> </mml:math> from a genetic correlation matrix using a Monte Carlo bias correction procedure to account for sampling noise. The average ratio of $${{h}^{2}}_{\mathrm{pleio}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msub> <mml:mrow> <mml:msup> <mml:mrow> <mml:mi>h</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msup> </mml:mrow> <mml:mrow> <mml:mi>pleio</mml:mi> </mml:mrow> </mml:msub> </mml:math> to total single-nucleotide polymorphism heritability ( $${{h}^{2}}_{\mathrm{pleio}}/{h}^{2}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mrow> <mml:msup> <mml:mrow> <mml:mi>h</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msup> </mml:mrow> <mml:mrow> <mml:mi>pleio</mml:mi> </mml:mrow> </mml:msub> <mml:mo>/</mml:mo> <mml:msup> <mml:mrow> <mml:mi>h</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msup> </mml:mrow> </mml:math> ) across 15 UK Biobank diseases (spanning seven disease categories) was 27 ± 3%, increasing to 48 ± 5% when expanding to 62 auxiliary diseases/traits. $${{h}^{2}}_{\mathrm{pleio}}/{h}^{2}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mrow> <mml:msup> <mml:mrow> <mml:mi>h</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msup> </mml:mrow> <mml:mrow> <mml:mi>pleio</mml:mi> </mml:mrow> </mml:msub> <mml:mo>/</mml:mo> <mml:msup> <mml:mrow> <mml:mi>h</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msup> </mml:mrow> </mml:math> was broadly distributed across disease categories, decreasing only modestly when removing the most informative auxiliary disease categories. The average $${{h}^{2}}_{\mathrm{pleio}}/{h}^{2}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:msub> <mml:mrow> <mml:msup> <mml:mrow> <mml:mi>h</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msup> </mml:mrow> <mml:mrow> <mml:mi>pleio</mml:mi> </mml:mrow> </mml:msub> <mml:mo>/</mml:mo> <mml:msup> <mml:mrow> <mml:mi>h</mml:mi> </mml:mrow> <mml:mn>2</mml:mn> </mml:msup> </mml:mrow> </mml:math> was 1.51 ± 0.16-times larger than the proportion of total phenotypic variance explained by auxiliary diseases, implying higher pleiotropy for genetic effects. In summary, roughly half of common disease heritability is pleiotropic with a broad range of diseases.
Authors
- Xilin Jiang (ORCID: https://orcid.org/0000-0001-6773-9182)
- Kangcheng Hou (ORCID: https://orcid.org/0000-0001-7110-5596)
- Steven Gazal (ORCID: https://orcid.org/0000-0003-4510-5730)
- Gaspard Kerner (ORCID: https://orcid.org/0000-0003-0146-9428)
- Michael Inouye (ORCID: https://orcid.org/0000-0001-9413-6520)
- Benjamin J. Strober (ORCID: https://orcid.org/0000-0003-2969-2808)
- Alkes L. Price (ORCID: https://orcid.org/0000-0002-2971-7975)
- John Danesh
- Yujie Zhao (ORCID: https://orcid.org/0009-0009-1472-3959)
- Wei Cheng (ORCID: https://orcid.org/0000-0003-1118-1743)
Institutions
- Broad Institute (US)
- University of Southern California (US)
- Boston Children's Hospital (US)
- Zhejiang Normal University (CN)
- Harvard University (US)
- Baker Heart and Diabetes Institute (AU)
- University of Cambridge (GB)
- Fudan University (CN)
- Wellcome Sanger Institute (GB)
- British Heart Foundation (GB)
- National Institute for Health and Care Research (GB)
- Shanghai Institute for Science of Science (CN)
- Cancer Research And Biostatistics (US)
- Cambridge University Health Partners (GB)
- Health Data Research UK (GB)
- Shanghai Center for Brain Science and Brain-Inspired Technology (CN)
Publication Details
- Journal
- Nature Genetics
- Published
- 2026-06-09
- DOI
- https://doi.org/10.1038/s41588-026-02607-w
- Primary Topic
- Genetic Associations and Epidemiology
- Type
- article
- Field-Weighted Citation Impact
- 0.00