scholarly journals Genome-wide association study and multi-trait analysis of opioid use disorder identifies novel associations in 639,709 individuals of European and African ancestry

2021 ◽  
Author(s):  
Joseph D. Deak ◽  
Hang Zhou ◽  
Marco Galimberti ◽  
Daniel Levey ◽  
Frank R. Wendt ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Opioid Use Disorder ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Opioid Use ◽  
Total N ◽  
Trait Analysis ◽  
Genome Wide

AbstractBackgroundDespite the large toll of opioid use disorder (OUD), genome-wide association studies (GWAS) of OUD to date have yielded few susceptibility loci.MethodsWe 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 (MVP), Psychiatric Genomics Consortium (PGC), iPSYCH, FinnGen, Partners Biobank, BioVU, and Yale-Penn 3, resulting in a total N=639,709 (Ncases=20,858) across ancestries. OUD cases were defined as having 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).ResultsThe 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=1.37×10−08; r2=0.02). Rs1799971 (p=4.91×10−08) and another OPRM1 variant (rs9478500; p=1.95×10−8; 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 18 GWS loci, all of which map to genes or gene regions that have previously been associated with psychiatric or addiction phenotypes.ConclusionsWe identified multiple OUD variant associations at OPRM1, single variant associations with FURIN, and 18 GWS associations in the OUD-MTAG. OUD is likely influenced by both OUD-specific loci and loci shared across SUDs.

scholarly journals Cross-ancestry meta-analysis of opioid use disorder uncovers novel loci with predominant effects on brain

2021 ◽  
Author(s):  
Rachel L Kember ◽  
Rachel A. Vickers-Smith ◽  
Heng Xu ◽  
Sylvanus Toikumo ◽  
Maria Niarchou ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Opioid Use Disorder ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Opioid Use ◽  
Opioid Prescription ◽  
Genome Wide ◽  
The Cross

Despite an estimated twin heritability of ~50%, genome-wide association studies (GWAS) of opioid use disorder (OUD) have revealed few genome-wide significant (GWS) loci, with replicated findings only in European-ancestry individuals. To identify novel loci, including those in non-European ancestries, and improve our understanding of the biology of OUD, we conducted a cross-ancestry meta-analysis using the Million Veteran Program (MVP). OUD cases in MVP had at least 1 International Classification of Diseases (ICD)-9 or ICD-10 code for opioid abuse or dependence (N=31,473). Opioid-exposed controls (N=394,471) had one or more outpatient opioid prescription fills. We conducted GWAS for each major ancestral group in MVP: African Americans (AAs; N=88,498), European Americans (EAs; N=302,585), and Hispanic Americans (HAs; N=34,861), followed by a cross-ancestry meta-analysis. Ten loci were GWS in the cross-ancestry meta-analysis, 8 of them novel. In addition to the known coding variant rs1799971 in OPRM1, which was the lead SNP genome-wide (p=6.78x10-10), and a recently reported exonic variant in FURIN, we identified intronic variants in RABEPK, FBXW4, NCAM1, and KCNN1. Ancestry-specific analyses identified an additional novel locus for each of the 3 ancestry groups. A supplementary meta-analysis within EAs that included MVP and other samples identified a locus in TSNARE1, which was also GWS in the cross-ancestry meta-analysis of all datasets. Gene-based association analyses identified 1 gene in AAs (CHRM2) and 3 in EAs (OPRM1, DRD2, and FTO). Significant genetic correlations (rg's) were identified for 127 traits, including positive correlations with schizophrenia, problematic alcohol use, and major depressive disorder. The most significantly enriched cell type group was the central nervous system with gene-expression enrichment identified in brain regions previously associated with substance use disorders. With a case sample 50% larger than that of the previous largest GWAS, we identified 14 loci for OUD, including 12 novel loci, some of which were ancestry specific. These findings increase our understanding of the biological pathways involved in OUD, which can inform preventive, diagnostic, and therapeutic efforts and thereby help to address the opioid epidemic.

scholarly journals Cross-ancestry meta-analysis of opioid use disorder uncovers novel loci with predominant effects on brain

2021 ◽  
Author(s):  
Rachel Kember ◽  
Rachel Vickers-Smith ◽  
Heng Xu ◽  
Sylvanus Toikumo ◽  
Maria Niarchou ◽  
...  
Keyword(s):  
Association Studies ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Opioid Use Disorder ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Opioid Use ◽  
Opioid Prescription ◽  
Genome Wide ◽  
The Cross

Abstract Despite an estimated twin heritability of ~50%, genome-wide association studies (GWAS) of opioid use disorder (OUD) have revealed few genome-wide significant (GWS) loci, with replicated findings only in European-ancestry individuals. To identify novel loci, including those in non-European ancestries, and improve our understanding of the biology of OUD, we conducted a cross-ancestry meta-analysis using the Million Veteran Program (MVP). OUD cases in MVP had at least 1 International Classification of Diseases (ICD)-9 or ICD-10 code for opioid abuse or dependence (N=31,473). Opioid-exposed controls (N=394,471) had one or more outpatient opioid prescription fills. We conducted GWAS for each major ancestral group in MVP: African Americans (AAs; N=88,498), European Americans (EAs; N=302,585), and Hispanic Americans (HAs; N=34,861), followed by a cross-ancestry meta-analysis. Ten loci were GWS in the cross-ancestry meta-analysis, 8 of them novel. In addition to the known coding variant rs1799971 in OPRM1, which was the lead SNP genome-wide (p=6.78x10−10), and a recently reported exonic variant in FURIN, we identified intronic variants in RABEPK, FBXW4, NCAM1, and KCNN1. Ancestry-specific analyses identified an additional novel locus for each of the 3 ancestry groups. A supplementary meta-analysis within EAs that included MVP and other samples identified a locus in TSNARE1, which was also GWS in the cross-ancestry meta-analysis of all datasets. Gene-based association analyses identified 1 gene in AAs (CHRM2) and 3 in EAs (OPRM1, DRD2, and FTO). Significant genetic correlations (rg’s) were identified for 127 traits, including positive correlations with schizophrenia, problematic alcohol use, and major depressive disorder. The most significantly enriched cell type group was the central nervous system with gene-expression enrichment identified in brain regions previously associated with substance use disorders. With a case sample 50% larger than that of the previous largest GWAS, we identified 14 loci for OUD, including 12 novel loci, some of which were ancestry specific. These findings increase our understanding of the biological pathways involved in OUD, which can inform preventive, diagnostic, and therapeutic efforts and thereby help to address the opioid epidemic.

scholarly journals A combined analysis of genetically correlated traits identifies 107 loci associated with intelligence

2017 ◽  
Author(s):  
W. D. Hill ◽  
G. Davies ◽  
A. M. McIntosh ◽  
C. R. Gale ◽  
I. J. Deary
Keyword(s):  
Household Income ◽  
Association Studies ◽  
Meta Analysis ◽  
Genetic Correlations ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Correlated Traits ◽  
Single Measure ◽  
Combined Analysis ◽  
Genome Wide

AbstractIntelligence, or general cognitive function, is phenotypically and genetically correlated with many traits, including many physical and mental health variables. Both education and household income are strongly genetically correlated with intelligence, at rg =0.73 and rg =0.70 respectively. This allowed us to utilize a novel approach, Multi-Trait Analysis of Genome-wide association studies (MTAG; Turley et al. 2017), to combine two large genome-wide association studies (GWASs) of education and household income to increase power in the largest GWAS on intelligence so far (Sniekers et al. 2017). This study had four goals: firstly, to facilitate the discovery of new genetic loci associated with intelligence; secondly, to add to our understanding of the biology of intelligence differences; thirdly, to examine whether combining genetically correlated traits in this way produces results consistent with the primary phenotype of intelligence; and, finally, to test how well this new meta-analytic data sample on intelligence predict phenotypic intelligence variance in an independent sample. We apply MTAG to three large GWAS: Sniekers et al (2017) on intelligence, Okbay et al. (2016) on Educational attainment, and Hill et al. (2016) on household income. By combining these three samples our functional sample size increased from 78 308 participants to 147 194. We found 107 independent loci associated with intelligence, implicating 233 genes, using both SNP-based and gene-based GWAS. We find evidence that neurogenesis may explain some of the biological differences in intelligence as well as genes expressed in the synapse and those involved in the regulation of the nervous system. We show that the results of our combined analysis demonstrate the same pattern of genetic correlations as a single measure/the simple measure of intelligence, providing support for the meta-analysis of these genetically-related phenotypes. We find that our MTAG meta-analysis of intelligence shows similar genetic correlations to 26 other phenotypes when compared with a GWAS consisting solely of cognitive tests. Finally, using an independent sample of 6 844 individuals we were able to predict 7% of intelligence using SNP data alone.

scholarly journals Largest genome-wide association study for PTSD identifies genetic risk loci in European and African ancestries and implicates novel biological pathways

2018 ◽  
Author(s):  
Caroline M. Nievergelt ◽  
Adam X. Maihofer ◽  
Torsten Klengel ◽  
Elizabeth G. Atkinson ◽  
Chia-Yen Chen ◽  
...  
Keyword(s):  
Genome Wide Association Study ◽  
Association Studies ◽  
Meta Analysis ◽  
African Ancestry ◽  
Genetic Correlations ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Post Traumatic Stress ◽  
Genome Wide

AbstractPost-traumatic stress disorder (PTSD) is a common and debilitating disorder. The risk of PTSD following trauma is heritable, but robust common variants have yet to be identified by genome-wide association studies (GWAS). We have collected a multi-ethnic cohort including over 30,000 PTSD cases and 170,000 controls. We first demonstrate significant genetic correlations across 60 PTSD cohorts to evaluate the comparability of these phenotypically heterogeneous studies. In this largest GWAS meta-analysis of PTSD to date we identify a total of 6 genome-wide significant loci, 4 in European and 2 in African-ancestry analyses. Follow-up analyses incorporated local ancestry and sex-specific effects, and functional studies. Along with other novel genes, a non-coding RNA (ncRNA) and a Parkinson’s Disease gene,PARK2, were associated with PTSD. Consistent with previous reports, SNP-based heritability estimates for PTSD range between 10-20%. Despite a significant shared liability between PTSD and major depressive disorder, we show evidence that some of our loci may be specific to PTSD. These results demonstrate the role of genetic variation contributing to the biology of differential risk for PTSD and the necessity of expanding GWAS beyond European ancestry.

Genome-Wide Association Studies Identify Two Novel Loci Conferring Susceptibility to Diabetic Retinopathy in Japanese Patients with Type 2 Diabetes

2021 ◽  
Author(s):  
Minako Imamura ◽  
Atsushi Takahashi ◽  
Masatoshi Matsunami ◽  
Momoko Horikoshi ◽  
Minoru Iwata ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Diabetic Retinopathy ◽  
Association Studies ◽  
Meta Analysis ◽  
Japanese Patients ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Stage 1

Abstract Several reports have suggested that genetic susceptibility contributes to the development and progression of diabetic retinopathy. We aimed to identify genetic loci that confer susceptibility to diabetic retinopathy in Japanese patients with type 2 diabetes. We analysed 5 790 508 single nucleotide polymorphisms (SNPs) in 8880 Japanese patients with type 2 diabetes, 4839 retinopathy cases and 4041 controls, as well as 2217 independent Japanese patients with type 2 diabetes, 693 retinopathy cases, and 1524 controls. The results of these two genome-wide association studies (GWAS) were combined with an inverse variance meta-analysis (Stage-1), followed by de novo genotyping for the candidate SNP loci (p < 1.0 × 10−4) in an independent case–control study (Stage-2, 2260 cases and 723 controls). After combining the association data (Stage-1 and -2) using meta-analysis, the associations of two loci reached a genome-wide significance level: rs12630354 near STT3B on chromosome 3, p = 1.62 × 10−9, odds ratio (OR) = 1.17, 95% confidence interval (CI) 1.11–1.23, and rs140508424 within PALM2 on chromosome 9, p = 4.19 × 10−8, OR = 1.61, 95% CI 1.36–1.91. However, the association of these two loci were not replicated in Korean, European, or African American populations. Gene-based analysis using Stage-1 GWAS data identified a gene-level association of EHD3 with susceptibility to diabetic retinopathy (p = 2.17 × 10−6). In conclusion, we identified two novel SNP loci, STT3B and PALM2, and a novel gene, EHD3, that confers susceptibility to diabetic retinopathy; however, further replication studies are required to validate these associations.

scholarly journals A meta-analysis of genome-wide association studies for average daily gain and lean meat percentage in two Duroc pig populations

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shenping Zhou ◽  
Rongrong Ding ◽  
Fanming Meng ◽  
Xingwang Wang ◽  
Zhanwei Zhuang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Growth And Development ◽  
Genetic Architecture ◽  
Association Studies ◽  
Meta Analysis ◽  
Average Daily Gain ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Daily Gain

Abstract Background Average daily gain (ADG) and lean meat percentage (LMP) are the main production performance indicators of pigs. Nevertheless, the genetic architecture of ADG and LMP is still elusive. Here, we conducted genome-wide association studies (GWAS) and meta-analysis for ADG and LMP in 3770 American and 2090 Canadian Duroc pigs. Results In the American Duroc pigs, one novel pleiotropic quantitative trait locus (QTL) on Sus scrofa chromosome 1 (SSC1) was identified to be associated with ADG and LMP, which spans 2.53 Mb (from 159.66 to 162.19 Mb). In the Canadian Duroc pigs, two novel QTLs on SSC1 were detected for LMP, which were situated in 3.86 Mb (from 157.99 to 161.85 Mb) and 555 kb (from 37.63 to 38.19 Mb) regions. The meta-analysis identified ten and 20 additional SNPs for ADG and LMP, respectively. Finally, four genes (PHLPP1, STC1, DYRK1B, and PIK3C2A) were detected to be associated with ADG and/or LMP. Further bioinformatics analysis showed that the candidate genes for ADG are mainly involved in bone growth and development, whereas the candidate genes for LMP mainly participated in adipose tissue and muscle tissue growth and development. Conclusions We performed GWAS and meta-analysis for ADG and LMP based on a large sample size consisting of two Duroc pig populations. One pleiotropic QTL that shared a 2.19 Mb haplotype block from 159.66 to 161.85 Mb on SSC1 was found to affect ADG and LMP in the two Duroc pig populations. Furthermore, the combination of single-population and meta-analysis of GWAS improved the efficiency of detecting additional SNPs for the analyzed traits. Our results provide new insights into the genetic architecture of ADG and LMP traits in pigs. Moreover, some significant SNPs associated with ADG and/or LMP in this study may be useful for marker-assisted selection in pig breeding.

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