Identifying Nootropic Drug Targets via Large-Scale Cognitive GWAS and Transcriptomics
Authors: Lam Max , Chia-Yen Chen , Yan Xia , Hill W. David , Trampush Joey W. , Yu Jin , Knowles Emma , Davies Gail , Stahl Eli , Huckins Laura , Liewald David C. , Djurovic Srdjan , Melle Ingrid , Christoforou Andrea , Reinvang Ivar , DeRosse Pamela , Lundervold Astri J. , Steen Vidar M. , Espeseth Thomas , Räikkönen Katri , Widen Elisabeth , Palotie Aarno , Eriksson Johan G. , Giegling Ina , Konte Bettina , Hartmann Annette M. , Roussos Panos , Giakoumaki Stella , Burdick Katherine E. , Payton Antony , Ollier William , Chiba-Falek Ornit , Koltai Deborah K. , Need Anna C. , Cirulli Elizabeth T. , Voineskos Aristotle N. , Stefanis Nikos C. , Avramopoulos Dimitrios , Hatzimanolis Alex , Smyrnis Nikolaos , Bilder Robert M. , Freimer Nelson A. , Cannon Tyrone D. , London Edythe , Poldrack Russell A. , Sabb Fred W. , Congdon Eliza , Conley Emily Drabant , Scult Matthew A. , Dickinson Dwight , Straub Richard E. , Donohoe Gary , Morris Derek , Corvin Aiden , Gill Michael , Hariri Ahmad R. , Weinberger Daniel R. , Pendleton Neil , Bitsios Panos , Rujescu Dan , Lahti Jari , Hellard Stephanie Le , Keller Matthew C. , Andreassen Ole A. , Deary Ian J. , Glahn David C. , Chunyu Liu , Malhotra Anil K. , Lencz Todd 
Published: February 2020

Background

Cognitive traits demonstrate significant genetic correlations with many psychiatric disorders and other health-related traits. Many neuropsychiatric and neurodegenerative disorders are marked by cognitive deficits. Therefore, genome-wide association studies (GWAS) of general cognitive ability might suggest potential targets for nootropic drug repurposing. Our previous effort to identify “druggable genes” (i.e., GWAS-identified genes that produce proteins targeted by known small molecules) was modestly powered due to the small cognitive GWAS sample available at the time. Since then, two large cognitive GWAS meta-analyses have reported 148 and 205 genome-wide significant loci, respectively. Additionally, large-scale gene expression databases, derived from post-mortem human brain, have recently been made available for GWAS annotation. Here, we 1) reconcile results from these two cognitive GWAS meta-analyses to further enhance power for locus discovery; 2) employ several complementary transcriptomic methods to identify genes in these loci with variants that are credibly associated with cognition; and 3) further annotate the resulting genes to identify “druggable” targets.

Methods

GWAS summary statistics were harmonized and jointly analysed using Multi-Trait Analysis of GWAS [MTAG], which is optimized for handling sample overlaps. Downstream gene identification was carried out using MAGMA, S-PrediXcan/S-TissueXcan Transcriptomic Wide Analysis, and eQTL mapping, as well as more recently developed methods that integrate GWAS and eQTL data via Summary-statistics Mendelian Randomization [SMR] and linkage methods [HEIDI], Available brain-specific eQTL databases included GTEXv7, BrainEAC, CommonMind, ROSMAP, and PsychENCODE. Intersecting credible genes were then annotated against multiple chemoinformatic databases [DGIdb, KI, and a published review on “druggability”].

Results

Using our meta-analytic data set (N = 373,617) we identified 241 independent cognition-associated loci (29 novel), and 76 genes were identified by 2 or more methods of gene identification. 26 genes were associated with general cognitive ability via SMR, 16 genes via STissueXcan/S-PrediXcan, 47 genes via eQTL mapping, and 68 genes via MAGMA pathway analysis. The use of the HEIDI test permitted the exclusion of candidate genes that may have been artifactually associated to cognition due to linkage, rather than direct causal or indirect pleiotropic effects. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging on our various transcriptome and pathway analyses, as well as available chemoinformatic databases, we identified 16 putative genes that may suggest drug targets with nootropic properties.

Discussion

Results converged on several categories of significant drug targets, including serotonergic and glutamatergic genes, voltage-gated ion channel genes, carbonic anhydrase genes, and phosphodiesterase genes. The current results represent the first efforts to apply a multi-method approach to integrate gene expression and SNP level data to identify credible actionable genes for general cognitive ability.