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. 2021 Sep;46(10):1788-1801.
doi: 10.1038/s41386-021-01023-4. Epub 2021 May 25.

Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics

Max Lam  1   2   3   4   5 Chia-Yen Chen  3   6   7 Tian Ge  2   7 Yan Xia  8   9 David W Hill  10   11 Joey W Trampush  12 Jin Yu  1 Emma Knowles  13   14   15 Gail Davies  10   11 Eli A Stahl  16   17   18 Laura Huckins  17   18 David C Liewald  11 Srdjan Djurovic  19   20 Ingrid Melle  21 Andrea Christoforou  22   23 Ivar Reinvang  24 Pamela DeRosse  1   4   25 Astri J Lundervold  26 Vidar M Steen  20   23 Thomas Espeseth  21   24 Katri Räikkönen  27 Elisabeth Widen  28 Aarno Palotie  28   29   30 Johan G Eriksson  31   32   33 Ina Giegling  34 Bettina Konte  34 Annette M Hartmann  34 Panos Roussos  17   18   35 Stella Giakoumaki  36 Katherine E Burdick  17   35   37 Antony Payton  38 William Ollier  39   40 Ornit Chiba-Falek  41 Deborah C Koltai  42 Anna C Need  43 Elizabeth T Cirulli  44 Aristotle N Voineskos  45 Nikos C Stefanis  46   47   48 Dimitrios Avramopoulos  49   50 Alex Hatzimanolis  46   47   48 Nikolaos Smyrnis  46   47 Robert M Bilder  51 Nelson B Freimer  51 Tyrone D Cannon  52   53 Edythe London  51 Russell A Poldrack  54 Fred W Sabb  55 Eliza Congdon  51 Emily Drabant Conley  56 Matthew A Scult  57   58 Dwight Dickinson  59 Richard E Straub  60 Gary Donohoe  61 Derek Morris  61 Aiden Corvin  62 Michael Gill  62 Ahmad R Hariri  58 Daniel R Weinberger  60 Neil Pendleton  63 Panos Bitsios  64 Dan Rujescu  34 Jari Lahti  27   65 Stephanie Le Hellard  20   23 Matthew C Keller  66 Ole A Andreassen  21   67 Ian J Deary  10   11 David C Glahn  13   14   15 Hailiang Huang  2   3 Chunyu Liu  8   9 Anil K Malhotra  1   4   25 Todd Lencz  68   69   70
Affiliations

Identifying nootropic drug targets via large-scale cognitive GWAS and transcriptomics

Max Lam et al. Neuropsychopharmacology. 2021 Sep.

Abstract

Broad-based cognitive deficits are an enduring and disabling symptom for many patients with severe mental illness, and these impairments are inadequately addressed by current medications. While novel drug targets for schizophrenia and depression have emerged from recent large-scale genome-wide association studies (GWAS) of these psychiatric disorders, GWAS of general cognitive ability can suggest potential targets for nootropic drug repurposing. Here, we (1) meta-analyze results from two recent cognitive GWAS to further enhance power for locus discovery; (2) employ several complementary transcriptomic methods to identify genes in these loci that are credibly associated with cognition; and (3) further annotate the resulting genes using multiple chemoinformatic databases to identify "druggable" targets. 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. Actin and chromatin binding gene sets were identified as novel pathways that could be targeted via drug repurposing. Leveraging our transcriptomic and chemoinformatic databases, we identified 16 putative genes targeted by existing drugs potentially available for cognitive repurposing.

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Figures

Fig. 1
Fig. 1. Workflow for the present study.
The overall data analytic strategy follows a broad strategy of (i) locus discovery, (ii) gene-based characterization, and (iii) gene-to-drug annotations. The green box at top summarizes locus discovery procedures and characterization of results. Yellow box summarizes downstream analysis of summary statistics, resulting in a set of genes available for druggability analysis displayed at figure bottom (red brackets). At each step, location of further details in Tables, Figures, and Supplementary Materials is specified. SMR summary statistics mendelian randomization, FUMA functional mapping and annotation of GWAS, eQTL expression quantitative trait locus, rQTL ribosomal occupancy qtl, sQTL splicing qtl, evQTL expression variation qtl.
Fig. 2
Fig. 2. GWAS association plots for Cognitive MTAG.
A QQ-plot. B SNP annotation plot. C Manhattan plot for General Cognitive Ability. D Venn Diagram showing loci overlap for input GWAS and MTAG results. E MAGMA gene property analysis for overall GTEXv7. F MAGMA gene property analysis using BrainSpan.
Fig. 3
Fig. 3. Venn diagram of “High Confidence” genes and gene identification approaches.
Genes highlighted in blue were deemed as most likely having gene targets that were suitable for nootropic re-purposing.

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