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

Authors :
Aarno Palotie
Arnaub K. Chatterjee
Hakon Hakonarson
Heiko Runz
Samuli Ripatti
Dermot F. Reilly
Veikko Salomaa
Michael E. March
Daniel G. MacArthur
Sally John
Hannele Mattsson
Michael E. Weale
Mark J. Daly
Aman Bhandari
David A. Hinds
Aaron G. Day-Williams
Mervi Alanne-Kinnunen
Elina Kilpeläinen
Dorothée Diogo
Janna Hutz
Chris C. A. Spencer
Nan Bing
Khanh-Dung H. Nguyen
Christopher S. Franklin
Mary-Pat Reeve
Karol Estrada
Robert M. Plenge
Joshua McElwee
Peter Donnelly
Ciara Vangjeli
Chao Tian
Caroline S. Fox
Patrick M. A. Sleiman
Joseph C. Maranville
Institute for Molecular Medicine Finland
University of Helsinki
Centre of Excellence in Complex Disease Genetics
Clinicum
Samuli Olli Ripatti / Principal Investigator
Biostatistics Helsinki
Department of Public Health
Aarno Palotie / Principal Investigator
Complex Disease Genetics
Genomics of Neurological and Neuropsychiatric Disorders
Source :
Nature Communications, Nature Communications, Vol 9, Iss 1, Pp 1-13 (2018)
Publication Year :
2017

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<br />Testing the association between genetic variants and a range of phenotypes can assist drug development. Here, in a phenome-wide association study in up to 697,815 individuals, Diogo et al. identify genotype–phenotype associations predicting efficacy, alternative indications or adverse drug effects.

Details

ISSN :
20411723
Volume :
9
Issue :
1
Database :
OpenAIRE
Journal :
Nature communications
Accession number :
edsair.doi.dedup.....4f8e9e4e09560f2e89e5a7b3bde30020