RT Journal Article
SR Electronic
T1 Phenome-wide association studies (PheWAS) across large “real-world data” population cohorts support drug target validation
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 218875
DO 10.1101/218875
A1 Dorothée Diogo
A1 Chao Tian
A1 Christopher S. Franklin
A1 Mervi Alanne-Kinnunen
A1 Michael March
A1 Chris C. A. Spencer
A1 Ciara Vangjeli
A1 Michael E. Weale
A1 Hannele Mattsson
A1 Elina Kilpeläinen
A1 Patrick M.A. Sleiman
A1 Dermot F. Reilly
A1 Joshua McElwee
A1 Joseph C. Maranville
A1 Arnaub K Chatterjee
A1 Aman Bhandari
A1 the 23andMe Research Team
A1 Mary-Pat Reeve
A1 Janna Hutz
A1 Nan Bing
A1 Sally John
A1 Daniel MacArthur
A1 Veikko Salomaa
A1 Samuli Ripatti
A1 Hakon Hakonarson
A1 Mark J. Daly
A1 Aarno Palotie
A1 David Hinds
A1 Peter Donnelly
A1 Caroline S. Fox
A1 Aaron Day-Williams
A1 Robert M. Plenge
A1 Heiko Runz
YR 2017
UL http://biorxiv.org/content/early/2017/11/13/218875.abstract
AB Phenome-wide association studies (PheWAS), which assess whether a genetic variant is associated with multiple phenotypes across a phenotypic spectrum, have been proposed as a possible aid to drug development through elucidating mechanisms of action, identifying alternative indications, or predicting adverse drug events (ADEs). Here, we evaluate whether PheWAS can inform target validation during drug development. We selected 25 single nucleotide polymorphisms (SNPs) linked through genome-wide association studies (GWAS) to 19 candidate drug targets for common disease therapeutic indications. We independently interrogated these SNPs through PheWAS in four large “real-world data” cohorts (23andMe, UK Biobank, FINRISK, CHOP) for association with a total of 1,892 binary endpoints. We then conducted meta-analyses for 145 harmonized disease endpoints in up to 697,815 individuals and joined results with summary statistics from 57 published GWAS. Our analyses replicate 70% of known GWAS associations and identify 10 novel associations with study-wide significance after multiple test correction (P<1.8x10-6; out of 72 novel associations with FDR<0.1). By leveraging directionality and point estimate of the effect sizes, we describe new associations that may predict ADEs, e.g., acne, high cholesterol, gout and gallstones for rs738409 (p.I148M) in PNPLA3; or asthma for rs1990760 (p.T946A) in IFIH1. We further propose how quantitative estimates of genetic safety/efficacy profiles can be used to help prioritize candidate targets for a specific indication. Our results demonstrate PheWAS as a powerful addition to the toolkit for drug discovery.One Sentence Summary Matching genetics with phenotypes in 800,000 individuals predicts efficacy and on-target safety of future drugs.