Despite the identification of a growing number of genetic risk loci for substance use traits (SUTs), the impact of these loci on protein abundance and the potential utility of relevant proteins as therapeutic targets are unknown. We conducted a proteome-wide association study (PWAS) in which we integrated human brain proteomes from discovery (Banner; N = 152) and validation (ROSMAP; N = 376) datasets with genome-wide association study (GWAS) summary statistics for 4 SUTs. The 4 samples comprised GWAS of European-ancestry individuals for smoking initiation [Smk] (N = 1,232,091), alcohol use disorder [AUD] (N = 313,959), cannabis use disorder [CUD] (N = 384,032), and opioid use disorder [OUD] (N = 302,585). We conducted transcriptome-wide association studies (TWAS) with human brain transcriptomic data to examine the overlap of genetic effects at the proteomic and transcriptomic levels and characterize significant genes through conditional, colocalization, and fine-mapping analyses. We identified 27 genes (Smk = 21, AUD = 3, CUD = 2, OUD = 1) that were significantly associated with cis-regulated brain protein abundance. Of these, 7 showed evidence for causality (Smk: NT5C2, GMPPB, NQO1, RHOT2, SRR and ACTR1B; and AUD: CTNND1). Cis-regulated transcript levels for 8 genes (Smk = 6, CUD = 1, OUD = 1) were associated with SUTs, indicating that genetic loci could confer risk for these SUTs by modulating both gene expression and proteomic abundance. Functional studies of the high-confidence risk proteins identified here are needed to determine whether they are modifiable targets and useful in developing medications and biomarkers for these SUTs.
This is a preview of subscription content, access via your institution
Subscribe to Journal
Get full journal access for 1 year
only $9.15 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
Degenhardt L, Charlson F, Ferrari A, Santomauro D, Erskine H, Mantilla-Herrara A, et al. The global burden of disease attributable to alcohol and drug use in 195 countries and territories, 1990–2016: a systematic analysis for the Global Burden of Disease Study 2016. Lancet Psychiatry. 2018;5:987–1012.
Degenhardt L, Grebely J, Stone J, Hickman M, Vickerman P, Marshall BDL, et al. Global patterns of opioid use and dependence: harms to populations, interventions, and future action. Lancet. 2019;394:1560–79.
Reitsma MB, Kendrick PJ, Ababneh E, Abbafati C, Abbasi-Kangevari M, Abdoli A, et al. Spatial, temporal, and demographic patterns in prevalence of smoking tobacco use and attributable disease burden in 204 countries and territories, 1990–2019: a systematic analysis from the Global Burden of Disease Study 2019. Lancet. 2021;397:2337–60.
Kendler KS, Jacobson KC, Prescott CA, Neale MC. Specificity of genetic and environmental risk factors for use and abuse/dependence of cannabis, cocaine, hallucinogens, sedatives, stimulants, and opiates in male twins. Am J Psychiatry. 2003;160:687–95.
Verhulst B, Neale MC, Kendler KS. The heritability of alcohol use disorders: a meta-analysis of twin and adoption studies. Psychol Med. 2015;45:1061–72.
Verweij KJH, Zietsch BP, Lynskey MT, Medland SE, Neale MC, Martin NG, et al. Genetic and environmental influences on cannabis use initiation and problematic use: a meta-analysis of twin studies. Addiction. 2010;105:417–30.
Liu M, Jiang Y, Wedow R, Li Y, Brazel DM, Chen F, et al. Association studies of up to 1.2 million individuals yield new insights into the genetic etiology of tobacco and alcohol use. Nat Genet. 2019;51:237–44.
Zhou H, Sealock JM, Sanchez-Roige S, Clarke TK, Levey DF, Cheng Z, et al. Genome-wide meta-analysis of problematic alcohol use in 435,563 individuals yields insights into biology and relationships with other traits. Nat Neurosci. 2020;23:809–18.
Johnson EC, Demontis D, Thorgeirsson TE, Walters RK, Polimanti R, Hatoum AS, et al. A large-scale genome-wide association study meta-analysis of cannabis use disorder. Lancet Psychiatry. 2020;7:1032–45.
Kember RL, Vickers-Smith R, Xu H, Toikumo S, Niarchou M, Zhou H, et al. Cross-ancestry meta-analysis of opioid use disorder uncovers novel loci with predominant effects on brain. medRxiv. 2021 Jan 1;2021.12.13.21267480.
Marees AT, Gamazon ER, Gerring Z, Vorspan F, Fingal J, van den Brink W, et al. Post-GWAS analysis of six substance use traits improves the identification and functional interpretation of genetic risk loci. Drug Alcohol Depend. 2020;206:107703.
Gusev A, Ko A, Shi H, Bhatia G, Chung W, Penninx BWJH, et al. Integrative approaches for large-scale transcriptome-wide association studies. Nat Genet. 2016;48:245–52.
Barbeira AN, Pividori M, Zheng J, Wheeler HE, Nicolae DL, Im HK. Integrating predicted transcriptome from multiple tissues improves association detection. PLOS Genet. 2019;15:e1007889.
Zhu Z, Zhang F, Hu H, Bakshi A, Robinson MR, Powell JE, et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat Genet. 2016;48:481–7.
Giambartolomei C, Vukcevic D, Schadt EE, Franke L, Hingorani AD, Wallace C, et al. Bayesian test for colocalisation between pairs of genetic association studies using summary statistics. PLOS Genet. 2014;10:e1004383.
Keele GR, Zhang T, Pham DT, Vincent M, Bell TA, Hock P, et al. Regulation of protein abundance in genetically diverse mouse populations. Cell Genomics. 2021;1:100003.
Moya-García A, Adeyelu T, Kruger FA, Dawson NL, Lees JG, Overington JP, et al. Structural and functional view of polypharmacology. Sci Rep. 2017;7:10102.
Zheng J, Haberland V, Baird D, Walker V, Haycock PC, Hurle MR, et al. Phenome-wide Mendelian randomization mapping the influence of the plasma proteome on complex diseases. Nat Genet. 2020;52:1122–31.
Beach TG, Adler CH, Sue LI, Serrano G, Shill HA, Walker DG, et al. Arizona study of aging and neurodegenerative disorders and brain and body donation program. Neuropathology. 2015;35:354–89.
Bennett DA, Buchman AS, Boyle PA, Barnes LL, Wilson RS, Schneider JA. Religious orders study and rush memory and aging project. J Alzheimers Dis. 2018;64:S161–89.
Fromer M, Roussos P, Sieberts SK, Johnson JS, Kavanagh DH, Perumal TM, et al. Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nat Neurosci. 2016;19:1442–53.
The GTEx consortium, Aguet F, Anand S, Ardlie Kristin G, Gabriel S, Getz Gad A, et al. The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science. 2020;369:1318–30.
Wingo TS, Liu Y, Gerasimov ES, Gockley J, Logsdon BA, Duong DM, et al. Brain proteome-wide association study implicates novel proteins in depression pathogenesis. Nat Neurosci. 2021;24:810–7.
Wingo AP, Liu Y, Gerasimov ES, Gockley J, Logsdon BA, Duong DM, et al. Integrating human brain proteomes with genome-wide association data implicates new proteins in Alzheimer’s disease pathogenesis. Nat Genet. 2021;53:143–6.
Walker RL, Ramaswami G, Hartl C, Mancuso N, Gandal MJ, de la Torre-Ubieta L, et al. Genetic control of expression and splicing in developing human brain informs disease mechanisms. Cell. 2019;179:750–771.e22.
Dall’Aglio L, Lewis CM, Pain O. Delineating the genetic component of gene expression in major depression. Biol Psychiatry. 2021;89:627–36.
Mancuso N, Freund MK, Johnson R, Shi H, Kichaev G, Gusev A, et al. Probabilistic fine-mapping of transcriptome-wide association studies. Nat Genet. 2019;51:675–82. 2019/03/29 ed
Freshour SL, Kiwala S, Cotto KC, Coffman AC, McMichael JF, Song JJ, et al. Integration of the Drug–Gene Interaction Database (DGIdb 4.0) with open crowdsource efforts. Nucleic Acids Res. 2021;49:D1144–51.
Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, et al. STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019;47:D607–13.
Watanabe K, Taskesen E, van Bochoven A, Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat Commun. 2017;8:1826.
Vink JM, Jansen R, Brooks A, Willemsen G, van Grootheest G, de Geus E, et al. Differential gene expression patterns between smokers and non-smokers: cause or consequence? Addict Biol. 2017;22:550–60.
Kapoor M, Wang JC, Farris SP, Liu Y, McClintick J, Gupta I, et al. Analysis of whole genome-transcriptomic organization in brain to identify genes associated with alcoholism. Transl Psychiatry. 2019;9:89.
Huggett SB, Ikeda AS, Yuan Q, Benca-Bachman CE, Palmer RHC. Genome- and transcriptome-wide splicing associations with problematic alcohol use and alcohol use disorder. bioRxiv. 2021 Jan 1;2021.03.31.437932.
Seney ML, Kim SM, Glausier JR, Hildebrand MA, Xue X, Zong W, et al. Transcriptional alterations in dorsolateral prefrontal cortex and nucleus accumbens implicate neuroinflammation and synaptic remodeling in opioid use disorder. Stress Inflamm Synaptic Remodel Addict. 2021;90:550–62.
Loh PR, Kichaev G, Gazal S, Schoech AP, Price AL. Mixed-model association for biobank-scale datasets. Nat Genet. 2018;50:906–8.
Wingo TS, Gerasimov ES, Liu Y, Duong DM, Vattathil SM, Lori A, et al. Integrating human brain proteomes with genome-wide association data implicates novel proteins in post-traumatic stress disorder. Mol Psychiatry [Internet]. 2022 Apr 21; Available from: https://doi.org/10.1038/s41380-022-01544-4
Liu J, Li X, Luo XJ. Proteome-wide association study provides insights into the genetic component of protein abundance in psychiatric disorders. Biol Psychiatry. 2021;90:781–9.
Pathak GA, Singh K, Wendt FR, Fleming TW, Overstreet C, Koller D, et al. Genetically regulated multi-omics study for symptom clusters of posttraumatic stress disorder highlights pleiotropy with hematologic and cardio-metabolic traits. Mol Psychiatry. 2022;27:1394–404.
Zhao B, Shan Y, Yang Y, Yu Z, Li T, Wang X, et al. Transcriptome-wide association analysis of brain structures yields insights into pleiotropy with complex neuropsychiatric traits. Nat Commun. 2021;12:2878.
Liu Y, Beyer A, Aebersold R. On the dependency of cellular protein levels on mRNA abundance. Cell 2016;165:535–50.
Vogel C, Marcotte EM. Insights into the regulation of protein abundance from proteomic and transcriptomic analyses. Nat Rev Genet. 2012;13:227–32.
Robins C, Liu Y, Fan W, Duong DM, Meigs J, Harerimana NV, et al. Genetic control of the human brain proteome. Am J Hum Genet. 2021;108:400–10.
Yang C, Farias F, Ibanez L, Sadler B, Fernandez MV, Wang F, et al. Genomic and multi-tissue proteomic integration for understanding the biology of disease and other complex traits. 2020; Available from: http://europepmc.org/abstract/PPR/PPR180358
Henneberger C, Papouin T, Oliet SHR, Rusakov DA. Long-term potentiation depends on release of d-serine from astrocytes. Nature 2010;463:232–6.
Papouin T, Ladépêche L, Ruel J, Sacchi S, Labasque M, Hanini M, et al. Synaptic and extrasynaptic NMDA receptors are gated by different endogenous coagonists. Cell 2012;150:633–46.
Yokobayashi E, Ujike H, Kotaka T, Okahisa Y, Takaki M, Kodama M, et al. Association study of serine racemase gene with methamphetamine psychosis. Curr Neuropharmacol. 2011;9:169–75.
Ripke S, Neale BM, Corvin A, Walters JTR, Farh KH, Holmans PA, et al. Biological insights from 108 schizophrenia-associated genetic loci. Nature. 2014;511:421–7.
Balu DT, Li Y, Puhl MD, Benneyworth MA, Basu AC, Takagi S, et al. Multiple risk pathways for schizophrenia converge in serine racemase knockout mice, a mouse model of NMDA receptor hypofunction. Proc Natl Acad Sci. 2013;110:E2400.
Puhl MD, Berg AR, Bechtholt AJ, Coyle JT. Availability of N-methyl-d-aspartate receptor coagonists affects cocaine-induced conditioned place preference and locomotor sensitization: implications for comorbid schizophrenia and substance abuse. J Pharm Exp Ther. 2015;353:465.
Benneyworth MA, Coyle JT. Altered acquisition and extinction of amphetamine-paired context conditioning in genetic mouse models of altered NMDA receptor function. Neuropsychopharmacology. 2012;37:2496–504.
Puhl MD, Desai RI, Takagi S, Presti KT, Doyle MR, Donahue RJ, et al. N-Methyl-d-aspartate receptor co-agonist availability affects behavioral and neurochemical responses to cocaine: insights into comorbid schizophrenia and substance abuse. Addict Biol. 2019;24:40–50.
de Miranda J, Panizzutti R, Foltyn VN, Wolosker H. Cofactors of serine racemase that physiologically stimulate the synthesis of the N-methyl-d-aspartate (NMDA) receptor coagonist d-serine. Proc Natl Acad Sci. 2002;99:14542.
Ramos RJ, Pras-Raves ML, Gerrits J, van der Ham M, Willemsen M, Prinsen H, et al. Vitamin B6 is essential for serine de novo biosynthesis. J Inherit Metab Dis. 2017;40:883–91.
Graham DL, Beio ML, Nelson DL, Berkowitz DB. Human serine racemase: key residues/active site motifs and their relation to enzyme function. Front Mol Biosci [Internet]. 2019;6. Available from: https://www.frontiersin.org/article/10.3389/fmolb.2019.00008
Raboni S, Marchetti M, Faggiano S, Campanini B, Bruno S, Marchesani F, et al. The energy landscape of human serine racemase. Front Mol Biosci [Internet]. 2019;5. Available from: https://www.frontiersin.org/article/10.3389/fmolb.2018.00112
Gabriel HE, Crott JW, Ghandour H, Dallal GE, Choi SW, Keyes MK, et al. Chronic cigarette smoking is associated with diminished folate status, altered folate form distribution, and increased genetic damage in the buccal mucosa of healthy adults. Am J Clin Nutr. 2006;83:835–41.
Skeie E, Strand E, Pedersen ER, Bjørndal B, Bohov P, Berge RK, et al. Circulating B-vitamins and smoking habits are associated with serum polyunsaturated fatty acids in patients with suspected coronary heart disease: a cross-sectional study. PLOS ONE. 2015;10:e0129049.
Ulvik A, Ebbing M, Hustad S, Midttun Ø, Nygård O, Vollset SE, et al. Long- and short-term effects of tobacco smoking on circulating concentrations of B vitamins. Clin Chem. 2010;56:755–63.
This study was supported by the Veterans Integrated Service Network 4 Mental Illness Research, Education and Clinical Center and NIH grants DA046345, AA028292, and AA02636.
HRK is a member of advisory boards for Dicerna Pharmaceuticals, Sophrosyne Pharmaceuticals, and Enthion Pharmaceuticals; a consultant to Sobrera Pharmaceuticals; the recipient of research funding and medication supplies for an investigator-initiated study from Alkermes; and a member of the American Society of Clinical Psychopharmacology’s Alcohol Clinical Trials Initiative, which was supported in the last 3 years by Alkermes, Dicerna, Ethypharm, Lundbeck, Mitsubishi, and Otsuka. JG and HRK are holders of U.S. patent 10,900,082 titled: “Genotype-guided dosing of opioid agonists,” issued 26 January 2021. The other authors have no disclosures to make.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
Toikumo, S., Xu, H., Gelernter, J. et al. Integrating human brain proteomic data with genome-wide association study findings identifies novel brain proteins in substance use traits. Neuropsychopharmacol. 47, 2292–2299 (2022). https://doi.org/10.1038/s41386-022-01406-1