TY - JOUR
T1 - Identifying drug targets for neurological and psychiatric disease via genetics and the brain transcriptome
AU - AMP-AD eQTL working group
AU - Baird, Denis A.
AU - Liu, Jimmy Z.
AU - Zheng, Jie
AU - Sieberts, Solveig K.
AU - Perumal, Thanneer
AU - Elsworth, Benjamin
AU - Richardson, Tom G.
AU - Chen, Chia Yen
AU - Carrasquillo, Minerva M.
AU - Allen, Mariet
AU - Reddy, Joseph S.
AU - de Jager, Philip L.
AU - Ertekin-Taner, Nilufer
AU - Mangravite, Lara M.
AU - Logsdon, Ben
AU - Estrada, Karol
AU - Haycock, Philip C.
AU - Hemani, Gibran
AU - Runz, Heiko
AU - Smith, George Davey
AU - Gaunt, Tom R.
AU - Agarwal, Devika
AU - Airey, David
AU - Allen, Mariet
AU - Amberkar, Sandeep
AU - Beckmann, Noam
AU - Canet-Aviles, Rosa
AU - Calley, John
AU - Carrasquillo, Minerva
AU - Dang, Kristen
AU - Degner, Jacob
AU - Drake, Derek
AU - Ebert, Philip
AU - Eddy, James
AU - Ergun, Ayla
AU - Ertekin-Taner, Nilufer
AU - Estrada, Karol
AU - Gaiteri, Chris
AU - Liu, Yushi
AU - Logsdon, Ben
AU - Hide, Winston
AU - Johnson, Toby
AU - Mangravite, Lara
AU - Mollon, Jennifer
AU - Mostafavi, Sara
AU - Perumal, Thanner
AU - Petanceska, Suzana
AU - Raj, Towfique
AU - Reddy, Joseph
AU - Ried, Janina
N1 - Publisher Copyright:
Copyright: © 2021 Baird et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
PY - 2021/1/8
Y1 - 2021/1/8
N2 - 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<6x10-7 as evidence threshold, Bonferroni-corrected for 80,557 MR tests) to confirm sharing of the same causal variants between gene expression and trait in each genomic region. We then intersected the colocalized genes with known monogenic disease genes recorded in Online Mendelian Inheritance in Man (OMIM) and with genes annotated as drug targets in the Open Targets platform to identify promising drug targets. 80 eQTLs showed MR evidence of a causal effect, from which we prioritised 47 genes based on colocalization with the trait. We causally linked the expression of 23 genes with schizophrenia and a single gene each with anorexia, bipolar disorder and major depressive disorder within the psychiatric diseases and 9 genes with Alzheimer’s disease, 6 genes with Parkinson’s disease, 4 genes with multiple sclerosis and two genes with amyotrophic lateral sclerosis within the neurological diseases we tested. From these we identified five genes (ACE, GPNMB, KCNQ5, RERE and SUOX) as attractive drug targets that may warrant follow-up in functional studies and clinical trials, demonstrating the value of this study design for discovering drug targets in neuropsychiatric diseases.
AB - 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<6x10-7 as evidence threshold, Bonferroni-corrected for 80,557 MR tests) to confirm sharing of the same causal variants between gene expression and trait in each genomic region. We then intersected the colocalized genes with known monogenic disease genes recorded in Online Mendelian Inheritance in Man (OMIM) and with genes annotated as drug targets in the Open Targets platform to identify promising drug targets. 80 eQTLs showed MR evidence of a causal effect, from which we prioritised 47 genes based on colocalization with the trait. We causally linked the expression of 23 genes with schizophrenia and a single gene each with anorexia, bipolar disorder and major depressive disorder within the psychiatric diseases and 9 genes with Alzheimer’s disease, 6 genes with Parkinson’s disease, 4 genes with multiple sclerosis and two genes with amyotrophic lateral sclerosis within the neurological diseases we tested. From these we identified five genes (ACE, GPNMB, KCNQ5, RERE and SUOX) as attractive drug targets that may warrant follow-up in functional studies and clinical trials, demonstrating the value of this study design for discovering drug targets in neuropsychiatric diseases.
UR - http://www.scopus.com/inward/record.url?scp=85099855620&partnerID=8YFLogxK
U2 - 10.1371/journal.pgen.1009224
DO - 10.1371/journal.pgen.1009224
M3 - Article
C2 - 33417599
AN - SCOPUS:85099855620
SN - 1553-7390
VL - 17
JO - PLoS Genetics
JF - PLoS Genetics
IS - 1
M1 - e1009224
ER -