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      Genome-wide association study in individuals of European and African ancestry and multi-trait analysis of opioid use disorder identifies 19 independent genome-wide significant risk loci

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          Abstract

          Despite the large toll of opioid use disorder (OUD), genome-wide association studies (GWAS) of OUD to date have yielded few susceptibility loci. We performed a large-scale GWAS of OUD in individuals of European (EUR) and African (AFR) ancestry, optimizing genetic informativeness by performing MTAG (Multi-trait analysis of GWAS) with genetically correlated substance use disorders (SUDs). Meta-analysis included seven cohorts: the Million Veteran Program, Psychiatric Genomics Consortium, iPSYCH, FinnGen, Partners Biobank, BioVU, and Yale-Penn 3, resulting in a total N = 639,063 ( N cases = 20,686;N effective = 77,026) across ancestries. OUD cases were defined as having a lifetime OUD diagnosis, and controls as anyone not known to meet OUD criteria. We estimated SNP-heritability (h 2 SNP) and genetic correlations (r g). Based on genetic correlation, we performed MTAG on OUD, alcohol use disorder (AUD), and cannabis use disorder (CanUD). A leave-one-out polygenic risk score (PRS) analysis was performed to compare OUD and OUD-MTAG PRS as predictors of OUD case status in Yale-Penn 3. The EUR meta-analysis identified three genome-wide significant (GWS; p ≤ 5 × 10 8) lead SNPs—one at FURIN (rs11372849; p = 9.54 × 10 10) and two OPRM1 variants (rs1799971, p = 4.92 × 10 09; rs79704991, p = 1.11 × 10 08; r 2 = 0.02). Rs1799971 (p = 4.91 × 10 08) and another OPRM1 variant (rs9478500; p = 1.95 × 10 08; r 2 = 0.03) were identified in the cross-ancestry meta-analysis. Estimated h 2 SNP was 12.75%, with strong r g with CanUD (r g = 0.82; p = 1.14 × 10 47) and AUD (r g = 0.77; p = 6.36 × 10 78). The OUD-MTAG resulted in a GWAS N equivalent = 128,748 and 18 independent GWS loci, some mapping to genes or gene regions that have previously been associated with psychiatric or addiction phenotypes. The OUD-MTAG PRS accounted for 3.81% of OUD variance (beta = 0.61;s.e. = 0.066; p = 2.00 × 10 16) compared to 2.41% (beta = 0.45; s.e. = 0.058; p = 2.90 × 10 13) explained by the OUD PRS. The current study identified OUD variant associations at OPRM1, single variant associations with FURIN, and 18 GWS associations in the OUD-MTAG. The genetic architecture of OUD is likely influenced by both OUD-specific loci and loci shared across SUDs.

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          Diagnostic and Statistical Manual of Mental Disorders

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            A global reference for human genetic variation

            The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
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              LD Score regression distinguishes confounding from polygenicity in genome-wide association studies.

              Both polygenicity (many small genetic effects) and confounding biases, such as cryptic relatedness and population stratification, can yield an inflated distribution of test statistics in genome-wide association studies (GWAS). However, current methods cannot distinguish between inflation from a true polygenic signal and bias. We have developed an approach, LD Score regression, that quantifies the contribution of each by examining the relationship between test statistics and linkage disequilibrium (LD). The LD Score regression intercept can be used to estimate a more powerful and accurate correction factor than genomic control. We find strong evidence that polygenicity accounts for the majority of the inflation in test statistics in many GWAS of large sample size.
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                Author and article information

                Contributors
                joel.gelernter@yale.edu
                Journal
                Mol Psychiatry
                Mol Psychiatry
                Molecular Psychiatry
                Nature Publishing Group UK (London )
                1359-4184
                1476-5578
                25 July 2022
                25 July 2022
                2022
                : 27
                : 10
                : 3970-3979
                Affiliations
                [1 ]GRID grid.47100.32, ISNI 0000000419368710, Yale School of Medicine, ; New Haven, CT USA
                [2 ]VA Connecticut Healthcare Center, West Haven, CT USA
                [3 ]GRID grid.266100.3, ISNI 0000 0001 2107 4242, University of California San Diego, ; La Jolla, CA USA
                [4 ]GRID grid.412807.8, ISNI 0000 0004 1936 9916, Vanderbilt University Medical Center, ; Nashville, TN USA
                [5 ]GRID grid.4367.6, ISNI 0000 0001 2355 7002, Washington University St. Louis Medical School, ; St. Louis, MO USA
                [6 ]GRID grid.7048.b, ISNI 0000 0001 1956 2722, Biomedicine, Aarhus University, ; Aarhus, Denmark
                [7 ]GRID grid.452548.a, ISNI 0000 0000 9817 5300, Lundbeck Foundation Initiative for Integrative Psychiatric Research, iPSYCH, ; Aarhus, Denmark
                [8 ]Center for Genomics and Personalized Medicine, Aarhus, Denmark
                [9 ]GRID grid.25879.31, ISNI 0000 0004 1936 8972, University of Pennsylvania Perelman School of Medicine, ; Philadelphia, PA USA
                [10 ]GRID grid.410355.6, ISNI 0000 0004 0420 350X, Crescenz VA Medical Center, ; Philadelphia, PA USA
                [11 ]GRID grid.257413.6, ISNI 0000 0001 2287 3919, Indiana University School of Medicine, ; Indianapolis, IN USA
                Author information
                http://orcid.org/0000-0002-0540-6080
                http://orcid.org/0000-0002-7694-6391
                http://orcid.org/0000-0001-6052-156X
                http://orcid.org/0000-0001-8431-9569
                http://orcid.org/0000-0002-2108-6822
                http://orcid.org/0000-0003-0394-777X
                http://orcid.org/0000-0001-9124-2766
                http://orcid.org/0000-0001-8627-7219
                http://orcid.org/0000-0002-5236-168X
                http://orcid.org/0000-0001-8820-2659
                http://orcid.org/0000-0003-0344-9690
                http://orcid.org/0000-0002-0313-793X
                http://orcid.org/0000-0003-0745-6046
                http://orcid.org/0000-0002-1018-0450
                http://orcid.org/0000-0002-4067-1859
                Article
                1709
                10.1038/s41380-022-01709-1
                9718667
                35879402
                b9b40d3f-18b6-47a8-8a43-16d27ea57aeb
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/

                History
                : 12 May 2022
                : 8 July 2022
                Funding
                Funded by: FundRef https://doi.org/10.13039/100000026, U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (NIDA);
                Award ID: R01DA054869
                Award ID: DP1 DA054394
                Award ID: R01DA054869
                Award ID: R01DA054869
                Award ID: K02 DA032573
                Award ID: R33 DA047527
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000027, U.S. Department of Health & Human Services | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA);
                Award ID: R01 AA026364
                Award ID: T32 AA028259
                Award ID: K01 AA028292
                Award ID: U24 AA020794
                Award ID: U01 AA020790
                Award ID: U10 AA013566
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/100000738, U.S. Department of Veterans Affairs (Department of Veterans Affairs);
                Award ID: I01CX001849
                Award ID: I01BX003342
                Award ID: I01BX003342
                Award ID: I01BX003342
                Award ID: I01BX004820
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA)
                Funded by: FundRef https://doi.org/10.13039/100000882, Brain Research Foundation (BRF);
                Funded by: FundRef https://doi.org/10.13039/100000025, U.S. Department of Health & Human Services | NIH | National Institute of Mental Health (NIMH);
                Award ID: F32 MH122058
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (NIDA)
                Funded by: FundRef https://doi.org/10.13039/501100003554, Lundbeckfonden (Lundbeck Foundation);
                Award ID: R102-A9118
                Award ID: R155-2014-1724
                Award ID: R248-2017-2003
                Award ID: R155-2014-1724
                Award ID: R248-2017-2003
                Award Recipient :
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Alcohol Abuse and Alcoholism (NIAAA)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (NIDA)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (NIDA)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (NIDA)
                Funded by: U.S. Department of Health & Human Services | NIH | National Institute on Drug Abuse (NIDA)
                Categories
                Immediate Communication
                Custom metadata
                © The Author(s), under exclusive licence to Springer Nature Limited 2022

                Molecular medicine
                genetics,addiction
                Molecular medicine
                genetics, addiction

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