Year: 2026
Type: preprint
Abstract: Motivation Genetically supported drug targets are an estimated 2.6 times more likely to succeed clinically, yet a disease association alone does not show which protein to target, in which direction, or what other effects may follow. This currently requires chaining separate tools. Results drugMR is a Nextflow pipeline that, from GWAS and pQTL summary statistics, runs cis -Mendelian randomisation, colocalisation, SMR-HEIDI with bulk and/or single-cell QTLs, three-trait colocalisation and a phenome-wide screen for adverse effects and repurposing. Datasets are added through a manifest, every step runs in containers on a laptop, cluster or cloud, and results are explored in a dashboard. Applied to schizophrenia with brain pQTLs, drugMR tested 2,019 proteins in 4 h 19 min and prioritised 58 proteogenomic targets, 22 with multi-omic support; 4 had potential adverse effects. Availability and implementation drugMR: https://github.com/guillermocomesa_nacimadevila/drugMR ; documentation: https://guillermocomesanacimadevila.github.io/drugMR/ . Demo data: https://doi.org/10.5281/zenodo.22917384 .
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: green
OpenAlex ID: W7221120917