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Pairwise effects between lipid GWAS genes modulate lipid plasma levels and cellular uptake

Author

Listed:
  • Magdalena Zimoń

    (University of Heidelberg/EMBL
    European Molecular Biological Laboratory)

  • Yunfeng Huang

    (Translational Biology, Biogen Inc)

  • Anthi Trasta

    (University of Heidelberg/EMBL
    European Molecular Biological Laboratory)

  • Aliaksandr Halavatyi

    (European Molecular Biological Laboratory)

  • Jimmy Z. Liu

    (Translational Biology, Biogen Inc)

  • Chia-Yen Chen

    (Translational Biology, Biogen Inc
    Mass General Hospital)

  • Peter Blattmann

    (University of Heidelberg/EMBL
    European Molecular Biological Laboratory
    Idorsia Pharmaceuticals Ltd)

  • Bernd Klaus

    (European Molecular Biological Laboratory)

  • Christopher D. Whelan

    (Translational Biology, Biogen Inc)

  • David Sexton

    (Translational Biology, Biogen Inc)

  • Sally John

    (Translational Biology, Biogen Inc)

  • Wolfgang Huber

    (European Molecular Biological Laboratory)

  • Ellen A. Tsai

    (Translational Biology, Biogen Inc)

  • Rainer Pepperkok

    (University of Heidelberg/EMBL
    European Molecular Biological Laboratory
    European Molecular Biological Laboratory)

  • Heiko Runz

    (University of Heidelberg/EMBL
    Translational Biology, Biogen Inc)

Abstract

Complex traits are characterized by multiple genes and variants acting simultaneously on a phenotype. However, studying the contribution of individual pairs of genes to complex traits has been challenging since human genetics necessitates very large population sizes, while findings from model systems do not always translate to humans. Here, we combine genetics with combinatorial RNAi (coRNAi) to systematically test for pairwise additive effects (AEs) and genetic interactions (GIs) between 30 lipid genome-wide association studies (GWAS) genes. Gene-based burden tests from 240,970 exomes show that in carriers with truncating mutations in both, APOB and either PCSK9 or LPL (“human double knock-outs”) plasma lipid levels change additively. Genetics and coRNAi identify overlapping AEs for 12 additional gene pairs. Overlapping GIs are observed for TOMM40/APOE with SORT1 and NCAN. Our study identifies distinct gene pairs that modulate plasma and cellular lipid levels primarily via AEs and nominates putative drug target pairs for improved lipid-lowering combination therapies.

Suggested Citation

  • Magdalena Zimoń & Yunfeng Huang & Anthi Trasta & Aliaksandr Halavatyi & Jimmy Z. Liu & Chia-Yen Chen & Peter Blattmann & Bernd Klaus & Christopher D. Whelan & David Sexton & Sally John & Wolfgang Hube, 2021. "Pairwise effects between lipid GWAS genes modulate lipid plasma levels and cellular uptake," Nature Communications, Nature, vol. 12(1), pages 1-16, December.
    • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26761-3
    DOI: 10.1038/s41467-021-26761-3
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    References listed on IDEAS

    as
    1. Claudia Giambartolomei & Damjan Vukcevic & Eric E Schadt & Lude Franke & Aroon D Hingorani & Chris Wallace & Vincent Plagnol, 2014. "Bayesian Test for Colocalisation between Pairs of Genetic Association Studies Using Summary Statistics," PLOS Genetics, Public Library of Science, vol. 10(5), pages 1-15, May.
    2. Tian Ge & Chia-Yen Chen & Yang Ni & Yen-Chen Anne Feng & Jordan W. Smoller, 2019. "Polygenic prediction via Bayesian regression and continuous shrinkage priors," Nature Communications, Nature, vol. 10(1), pages 1-10, December.
    3. Clare Bycroft & Colin Freeman & Desislava Petkova & Gavin Band & Lloyd T. Elliott & Kevin Sharp & Allan Motyer & Damjan Vukcevic & Olivier Delaneau & Jared O’Connell & Adrian Cortes & Samantha Welsh &, 2018. "The UK Biobank resource with deep phenotyping and genomic data," Nature, Nature, vol. 562(7726), pages 203-209, October.
    4. Benjamin B. Sun & Joseph C. Maranville & James E. Peters & David Stacey & James R. Staley & James Blackshaw & Stephen Burgess & Tao Jiang & Ellie Paige & Praveen Surendran & Clare Oliver-Williams & Mi, 2018. "Genomic atlas of the human plasma proteome," Nature, Nature, vol. 558(7708), pages 73-79, June.
    5. Konrad J. Karczewski & Laurent C. Francioli & Grace Tiao & Beryl B. Cummings & Jessica Alföldi & Qingbo Wang & Ryan L. Collins & Kristen M. Laricchia & Andrea Ganna & Daniel P. Birnbaum & Laura D. Gau, 2020. "The mutational constraint spectrum quantified from variation in 141,456 humans," Nature, Nature, vol. 581(7809), pages 434-443, May.
    6. Gibran Hemani & Joseph E. Powell & Huanwei Wang & Konstantin Shakhbazov & Harm-Jan Westra & Tonu Esko & Anjali K. Henders & Allan F. McRae & Nicholas G. Martin & Andres Metspalu & Lude Franke & Grant , 2021. "Phantom epistasis between unlinked loci," Nature, Nature, vol. 596(7871), pages 1-3, August.
    7. Adam E. Locke & Karyn Meltz Steinberg & Charleston W. K. Chiang & Susan K. Service & Aki S. Havulinna & Laurel Stell & Matti Pirinen & Haley J. Abel & Colby C. Chiang & Robert S. Fulton & Anne U. Jack, 2019. "Author Correction: Exome sequencing of Finnish isolates enhances rare-variant association power," Nature, Nature, vol. 575(7783), pages 4-4, November.
    8. Adam E. Locke & Karyn Meltz Steinberg & Charleston W. K. Chiang & Susan K. Service & Aki S. Havulinna & Laurel Stell & Matti Pirinen & Haley J. Abel & Colby C. Chiang & Robert S. Fulton & Anne U. Jack, 2019. "Exome sequencing of Finnish isolates enhances rare-variant association power," Nature, Nature, vol. 572(7769), pages 323-328, August.
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