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 (Ncases = 20,686;Neffective = 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 (h2SNP) and genetic correlations (rg). 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; r2 = 0.02). Rs1799971 (p = 4.91 × 10-08) and another OPRM1 variant (rs9478500; p = 1.95 × 10-08; r2 = 0.03) were identified in the cross-ancestry meta-analysis. Estimated h2SNP was 12.75%, with strong rg with CanUD (rg = 0.82; p = 1.14 × 10-47) and AUD (rg = 0.77; p = 6.36 × 10-78). The OUD-MTAG resulted in a GWAS Nequivalent = 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. 

/pdf/genome-wide-association-study-in-individuals-of-european-and-1i223jzv.pdf

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

Opioid use disorder (OUD) and mental disorders are often comorbid, with increased morbidity and mortality. The causes underlying this relationship are poorly understood. Although these conditions are highly heritable, their shared genetic vulnerabilities remain unaccounted for. We applied the conditional/conjunctional false discovery rate (cond/conjFDR) approach to analyse summary statistics from independent genome wide association studies of OUD, schizophrenia (SCZ), bipolar disorder (BD) and major depression (MD) of European ancestry. Next, we characterized the identified shared loci using biological annotation resources. OUD data were obtained from the Million Veteran Program, Yale‐Penn and Study of Addiction: Genetics and Environment (SAGE) (15 756 cases, 99 039 controls). SCZ (53 386 cases, 77 258 controls), BD (41 917 cases, 371 549 controls) and MD (170 756 cases, 329 443 controls) data were provided by the Psychiatric Genomics Consortium. We discovered genetic enrichment for OUD conditional on associations with SCZ, BD, MD and vice versa, indicating polygenic overlap with identification of 14 novel OUD loci at condFDR < 0.05 and 7 unique loci shared between OUD and SCZ (n = 2), BD (n = 2) and MD (n = 7) at conjFDR < 0.05 with concordant effect directions, in line with estimated positive genetic correlations. Two loci were novel for OUD, one for BD and one for MD. Three OUD risk loci were shared with more than one psychiatric disorder, at DRD2 on chromosome 11 (BD and MD), at FURIN on chromosome 15 (SCZ, BD and MD) and at the major histocompatibility complex region (SCZ and MD). Our findings provide new insights into the shared genetic architecture between OUD and SCZ, BD and MD, indicating a complex genetic relationship, suggesting overlapping neurobiological pathways.

/pdf/genome-wide-analyses-reveal-novel-opioid-use-disorder-loci-28mzrtui.pdf

Genome‐wide analyses reveal novel opioid use disorder loci and genetic overlap with schizophrenia, bipolar disorder, and major depression

Abstract Opioid use disorder (OUD) and mental disorders are often comorbid, with increased morbidity and mortality. The causes underlying this relationship are poorly understood. Although these conditions are highly heritable, their shared genetic vulnerabilities remain unaccounted for. We applied the conditional/conjunctional false discovery rate (cond/conjFDR) approach to analyse summary statistics from independent genome wide association studies of OUD, SCZ, BD and MD. Next, we characterized the identified shared loci using biological annotation resources. OUD data was obtained from the Million Veteran Program (15,756 cases 99,039 controls). SCZ (53,386 cases 77,258 controls), BD (41,917 cases 371,549 controls) and MD (170,756 cases 329,443 controls) data was provided by the Psychiatric Genomics Consortium. We discovered genetic enrichment for OUD conditional on associations with SCZ, BD, MD and vice versa, indicating polygenic overlap with identification of 14 novel OUD loci at condFDR&lt;0.05 and 7 unique loci shared between OUD and SCZ (n=2), BD (n=2) and MD (n=7) at conjFDR&lt;0.05 with concordant effect directions, in line with estimated positive genetic correlations. Two loci were novel for OUD, one for BD and one for MD. Three OUD risk loci were shared with more than one psychiatric disorder, at DRD2 on chromosome 11 (BD and MD), at FURIN on chromosome 15 (SCZ, BD and MD), and at the major histocompatibility complex region (SCZ and MD). Our findings provide new insights into the shared genetic architecture between OUD and SCZ, BD, and MD, indicating a complex genetic relationship, suggesting overlapping neurobiological pathways. 

Genome-wide analyses reveal novel opioid use disorder loci and genetic overlap with schizophrenia, bipolar disorder, and major depression

Abstract Smoking behaviors and alcohol use disorder (AUD), moderately heritable traits, commonly co-occur in the general population. Single-trait genome-wide association studies (GWAS) have identified multiple loci for smoking and AUD. However, GWASs that have aimed to identify loci contributing to comorbid smoking and AUD have used small samples and thus have not been highly informative. Applying multi-trait analysis of GWASs (MTAG), we conducted a joint GWAS of smoking and AUD with data from the Million Veteran Program (N=318,694). By leveraging GWAS summary statistics for AUD, MTAG identified 21 genome-wide significant (GWS) loci associated with smoking initiation and 18 loci associated with smoking cessation compared to 16 and 8 loci, respectively, identified by single-trait GWAS. The novel loci for smoking behaviors identified by MTAG included those previously associated with psychiatric or substance use traits. Colocalization analysis identified 10 loci shared by AUD and smoking status traits, all of which achieved GWS in MTAG, including variants on SIX3, NCAM1 , and near DRD2 . Functional annotation of the MTAG variants highlighted biologically important regions on ZBTB20, DRD2, PPP6C , and GCKR that contribute to smoking behaviors. In contrast, MTAG of smoking behaviors and alcohol consumption (AC) did not enhance discovery compared with single-trait GWAS for smoking behaviors. We conclude that using MTAG to augment the power of GWAS enables the identification of novel genetic variants for commonly comorbid phenotypes, providing new insights into their pleiotropic effects on smoking behavior and AUD. 

Multi-trait genome-wide association analyses leveraging alcohol use disorder findings identify novel loci for smoking behaviors in the Million Veteran Program

Background: Impulsivity is a multidimensional heritable phenotype that broadly refers to the tendency to act prematurely and is associated with multiple forms of psychopathology. Methods: We performed genome-wide association studies (GWAS) of eight impulsive personality traits from the Barratt Impulsiveness Scale and the short UPPS-P Impulsive Personality Scale (N=123,509-133,517 23andMe research participants of European ancestry), and a measure of Drug Experimentation (N=130,684). Because these GWAS implicated the gene CADM2, we next performed a phenome-wide study (PheWAS) in a multi-ancestral 23andMe cohort (N=3,229,317, European; N=579,623, Latinx; N=199,663, African American). Finally, we produced Cadm2 knock-out mice and tested them using a battery of behavioral impulsivity tasks. Results: In humans, impulsive personality traits showed modest chip-heritability (~6-10%), and moderate genetic correlations (rg=.20-.50) with other personality traits, and various psychiatric and medical traits. We replicated associations from earlier GWAS of these traits and found novel associations including DRD2, CRHR1, FOXP2, TCF4, PTPRF. PheWAS for CADM2 identified associations with 378 traits in European participants, and 47 traits in Latinx participants, replicating associations with risky behaviors, and revealing novel associations including allergies, anxiety, irritable bowel syndrome, and migraine. Cadm2 knock-out mice showed reduced impulsivity in the 5-choice serial reaction time task, while heterozygote mice showed lower risky behavior in the mouse Iowa gambling task. Conclusions: Our results further establish the role of CADM2 in impulsivity and numerous other psychiatric and somatic traits across ancestries. Additionally, we demonstrate that deletion of Cadm2 in mice influences behavior in assays designed to measure impulsive and risky behavior.

/pdf/cadm2-is-implicated-in-impulsive-personality-traits-by-19beo7pi.pdf

CADM2 is implicated in impulsive personality traits by genome- and phenome-wide association studies in humans, with further support from studies of Cadm2 mutant mice

Opioid addiction (OA) has strong heritability, yet few genetic variant associations have been robustly identified. Only rs1799971, the A118G variant in OPRM1, has been identified as a genome-wide significant association with OA and independently replicated. We applied genomic structural equation modeling to conduct a GWAS of the new Genetics of Opioid Addiction Consortium (GENOA) data and published studies (Psychiatric Genomics Consortium, Million Veteran Program, and Partners Health), comprising 23,367 cases and effective sample size of 88,114 individuals of European ancestry. Genetic correlations among the various OA phenotypes were uniformly high (rg > 0.9). We observed the strongest evidence to date for OPRM1: lead SNP rs9478500 (p=2.56×10−9). Gene-based analyses identified novel genome-wide significant associations with PPP6C and FURIN. Variants within these loci appear to be pleiotropic for addiction and related traits.

/pdf/multi-trait-genome-wide-association-study-of-opioid-3yez23rlt4.pdf

Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond

Genome-wide association studies (GWAS) have made impactful discoveries for complex diseases, often by amassing very large sample sizes. Yet, GWAS of many diseases remain underpowered, especially for non-European ancestries. One cost-effective approach to increase sample size is to combine existing case-only cohorts with public controls, but this approach is limited by the need for a large overlap in variants across genotyping arrays and the scarcity of non-European controls. We developed and validated a protocol, Genotyping Array-WGS Merge (GAWMerge), for combining genotypes from arrays and whole genome sequencing, ensuring complete variant overlap, and allowing for diverse samples like Trans-Omics for Precision Medicine to be used. Our protocol involves phasing, imputation, and filtering. We illustrated its ability to control type I error and recover known disease-associated signals across technologies, independent datasets, and ancestries in smoking-related cohorts. GAWMerge enables genetic studies to leverage existing cohorts to validly increase sample size and enhance discovery.

https://www.biorxiv.org/content/biorxiv/early/2021/10/20/2021.10.19.464854.full.pdf

Expanding the pool of public controls for GWAS via a method for combining genotypes from arrays and sequencing

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Multi-trait genome-wide association study of opioid addiction: OPRM1 and beyond

Expanding the pool of public controls for GWAS via a method for combining genotypes from arrays and sequencing