Identifying drug targets for neurological and psychiatric disease via genetics and the brain transcriptome

Baird, Denis A; Liu, Jimmy Z; Zheng, Jie; Sieberts, Solveig K; Perumal, Thanneer; Elsworth, Benjamin; Richardson, Tom G; Chen, Chia-Yen; Carrasquillo, Minerva M; Allen, Mariet; Reddy, Joseph S; De Jager, Philip L; Ertekin-Taner, Nilufer; Mangravite, Lara M; Logsdon, Ben; Estrada, Karol; Haycock, Philip C; Hemani, Gibran; Runz, Heiko; Smith, George Davey; Gaunt, Tom R; Amp-Ad, eQTL working group

Identifying drug targets for neurological and psychiatric disease via genetics and the brain transcriptome

Denis A Baird, Jimmy Z Liu, Jie Zheng, Solveig K Sieberts, Thanneer Perumal, Benjamin Elsworth, Tom G Richardson, Chia-Yen Chen, Minerva M Carrasquillo, Mariet Allen, Joseph S Reddy, Philip L De Jager, Nilufer Ertekin-Taner, Lara M Mangravite, Ben Logsdon, Karol Estrada, Philip C Haycock, Gibran Hemani, Heiko Runz, George Davey Smith, Tom R Gaunt and eQTL working group Amp-Ad

PLOS Genetics, 2021, vol. 17, issue 1, 1-26

Abstract: Discovering drugs that efficiently treat brain diseases has been challenging. Genetic variants that modulate the expression of potential drug targets can be utilized to assess the efficacy of therapeutic interventions. We therefore employed Mendelian Randomization (MR) on gene expression measured in brain tissue to identify drug targets involved in neurological and psychiatric diseases. We conducted a two-sample MR using cis-acting brain-derived expression quantitative trait loci (eQTLs) from the Accelerating Medicines Partnership for Alzheimer’s Disease consortium (AMP-AD) and the CommonMind Consortium (CMC) meta-analysis study (n = 1,286) as genetic instruments to predict the effects of 7,137 genes on 12 neurological and psychiatric disorders. We conducted Bayesian colocalization analysis on the top MR findings (using P

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pgen00:1009224

DOI: 10.1371/journal.pgen.1009224

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