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Phenome-wide association studies across large population cohorts support drug target validation

Author

Listed:
  • Dorothée Diogo

    (Merck Sharp & Dohme)

  • Chao Tian

    (23andMe Inc)

  • Christopher S. Franklin

    (Genomics plc)

  • Mervi Alanne-Kinnunen

    (University of Helsinki)

  • Michael March

    (The Children’s Hospital of Philadelphia and University of Pennsylvania)

  • Chris C. A. Spencer

    (Genomics plc)

  • Ciara Vangjeli

    (Genomics plc)

  • Michael E. Weale

    (Genomics plc)

  • Hannele Mattsson

    (University of Helsinki
    National Institute for Health and Welfare)

  • Elina Kilpeläinen

    (University of Helsinki)

  • Patrick M. A. Sleiman

    (The Children’s Hospital of Philadelphia and University of Pennsylvania)

  • Dermot F. Reilly

    (Merck Sharp & Dohme)

  • Joshua McElwee

    (Merck Sharp & Dohme
    Nimbus Therapeutics)

  • Joseph C. Maranville

    (Merck Sharp & Dohme
    Celgene)

  • Arnaub K. Chatterjee

    (Merck Sharp & Dohme
    McKinsey & Co.)

  • Aman Bhandari

    (Merck Sharp & Dohme
    Vertex Pharmaceuticals)

  • Khanh-Dung H. Nguyen

    (Biogen, Research and Early Development)

  • Karol Estrada

    (Biogen, Research and Early Development)

  • Mary-Pat Reeve

    (Eisai)

  • Janna Hutz

    (Eisai)

  • Nan Bing

    (Pfizer)

  • Sally John

    (Biogen, Research and Early Development)

  • Daniel G. MacArthur

    (Broad Institute of MIT and Harvard
    Massachusetts General Hospital)

  • Veikko Salomaa

    (National Institute for Health and Welfare)

  • Samuli Ripatti

    (University of Helsinki
    Broad Institute of MIT and Harvard
    University of Helsinki)

  • Hakon Hakonarson

    (The Children’s Hospital of Philadelphia and University of Pennsylvania)

  • Mark J. Daly

    (Broad Institute of MIT and Harvard
    Massachusetts General Hospital)

  • Aarno Palotie

    (University of Helsinki
    Broad Institute of MIT and Harvard
    Massachusetts General Hospital
    Massachusetts General Hospital)

  • David A. Hinds

    (23andMe Inc)

  • Peter Donnelly

    (Genomics plc)

  • Caroline S. Fox

    (Merck Sharp & Dohme)

  • Aaron G. Day-Williams

    (Merck Sharp & Dohme
    Biogen, Research and Early Development)

  • Robert M. Plenge

    (Merck Sharp & Dohme
    Celgene)

  • Heiko Runz

    (Merck Sharp & Dohme
    Biogen, Research and Early Development)

Abstract

Phenome-wide association studies (PheWAS) have been proposed as a possible aid in drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we select 25 single nucleotide polymorphisms (SNPs) linked through genome-wide association studies (GWAS) to 19 candidate drug targets for common disease indications. We interrogate these SNPs by PheWAS in four large cohorts with extensive health information (23andMe, UK Biobank, FINRISK, CHOP) for association with 1683 binary endpoints in up to 697,815 individuals and conduct meta-analyses for 145 mapped disease endpoints. Our analyses replicate 75% of known GWAS associations (P

Suggested Citation

  • Dorothée Diogo & Chao Tian & Christopher S. Franklin & Mervi Alanne-Kinnunen & Michael March & Chris C. A. Spencer & Ciara Vangjeli & Michael E. Weale & Hannele Mattsson & Elina Kilpeläinen & Patrick , 2018. "Phenome-wide association studies across large population cohorts support drug target validation," Nature Communications, Nature, vol. 9(1), pages 1-13, December.
    • Handle: RePEc:nat:natcom:v:9:y:2018:i:1:d:10.1038_s41467-018-06540-3
    DOI: 10.1038/s41467-018-06540-3
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    Cited by:

    1. Weikang Gong & Yan Fu & Bang-Sheng Wu & Jingnan Du & Liu Yang & Ya-Ru Zhang & Shi-Dong Chen & JuJiao Kang & Ying Mao & Qiang Dong & Lan Tan & Jianfeng Feng & Wei Cheng & Jin-Tai Yu, 2024. "Whole-exome sequencing identifies protein-coding variants associated with brain iron in 29,828 individuals," Nature Communications, Nature, vol. 15(1), pages 1-13, December.
    2. Patrick Wu & QiPing Feng & Vern Eric Kerchberger & Scott D. Nelson & Qingxia Chen & Bingshan Li & Todd L. Edwards & Nancy J. Cox & Elizabeth J. Phillips & C. Michael Stein & Dan M. Roden & Joshua C. D, 2022. "Integrating gene expression and clinical data to identify drug repurposing candidates for hyperlipidemia and hypertension," Nature Communications, Nature, vol. 13(1), pages 1-12, December.
    3. Guanghao Qi & Surya B. Chhetri & Debashree Ray & Diptavo Dutta & Alexis Battle & Samsiddhi Bhattacharjee & Nilanjan Chatterjee, 2024. "Genome-wide large-scale multi-trait analysis characterizes global patterns of pleiotropy and unique trait-specific variants," Nature Communications, Nature, vol. 15(1), pages 1-18, December.

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