Dataset Information

Genome-wide meta-analysis of 158,000 individuals of European ancestry identifies three loci associated with chronic back pain.

ABSTRACT: Back pain is the #1 cause of years lived with disability worldwide, yet surprisingly little is known regarding the biology underlying this symptom. We conducted a genome-wide association study (GWAS) meta-analysis of chronic back pain (CBP). Adults of European ancestry were included from 15 cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and from the UK Biobank interim data release. CBP cases were defined as those reporting back pain present for ?3-6 months; non-cases were included as comparisons ("controls"). Each cohort conducted genotyping using commercially available arrays followed by imputation. GWAS used logistic regression models with additive genetic effects, adjusting for age, sex, study-specific covariates, and population substructure. The threshold for genome-wide significance in the fixed-effect inverse-variance weighted meta-analysis was p<5×10(-8). Suggestive (p<5×10(-7)) and genome-wide significant (p<5×10(-8)) variants were carried forward for replication or further investigation in the remaining UK Biobank participants not included in the discovery sample. The discovery sample comprised 158,025 individuals, including 29,531 CBP cases. A genome-wide significant association was found for the intronic variant rs12310519 in SOX5 (OR 1.08, p = 7.2×10(-10)). This was subsequently replicated in 283,752 UK Biobank participants not included in the discovery sample, including 50,915 cases (OR 1.06, p = 5.3×10(-11)), and exceeded genome-wide significance in joint meta-analysis (OR 1.07, p = 4.5×10(-19)). We found suggestive associations at three other loci in the discovery sample, two of which exceeded genome-wide significance in joint meta-analysis: an intergenic variant, rs7833174, located between CCDC26 and GSDMC (OR 1.05, p = 4.4×10(-13)), and an intronic variant, rs4384683, in DCC (OR 0.97, p = 2.4×10(-10)). In this first reported meta-analysis of GWAS for CBP, we identified and replicated a genetic locus associated with CBP (SOX5). We also identified 2 other loci that reached genome-wide significance in a 2-stage joint meta-analysis (CCDC26/GSDMC and DCC).

SUBMITTER: Suri P

PROVIDER: S-EPMC6159857 | biostudies-literature | 2018 Sep

REPOSITORIES: biostudies-literature

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Genome-wide meta-analysis of 158,000 individuals of European ancestry identifies three loci associated with chronic back pain.

Suri Pradeep P Palmer Melody R MR Tsepilov Yakov A YA Freidin Maxim B MB Boer Cindy G CG Yau Michelle S MS Evans Daniel S DS Gelemanovic Andrea A Bartz Traci M TM Nethander Maria M Arbeeva Liubov L Karssen Lennart L Neogi Tuhina T Campbell Archie A Mellstrom Dan D Ohlsson Claes C Marshall Lynn M LM Orwoll Eric E Uitterlinden Andre A Rotter Jerome I JI Lauc Gordan G Psaty Bruce M BM Karlsson Magnus K MK Lane Nancy E NE Jarvik Gail P GP Polasek Ozren O Hochberg Marc M Jordan Joanne M JM Van Meurs Joyce B J JBJ Jackson Rebecca R Nielson Carrie M CM Mitchell Braxton D BD Smith Blair H BH Hayward Caroline C Smith Nicholas L NL Aulchenko Yurii S YS Williams Frances M K FMK

PLoS genetics 20180927 9

Back pain is the #1 cause of years lived with disability worldwide, yet surprisingly little is known regarding the biology underlying this symptom. We conducted a genome-wide association study (GWAS) meta-analysis of chronic back pain (CBP). Adults of European ancestry were included from 15 cohorts in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and from the UK Biobank interim data release. CBP cases were defined as those reporting back pain present for ≥ ...[more]

PMID: 30261039

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Project description: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.

Project description:Abstract Population stratification, or systematic differences in allele frequencies between subpopulations, can distort the results from genome-wide association studies (GWAS). While GWAS are usually conducted within continental (e.g. European) ancestry groups, sub-groups may have specific population histories that result in enrichment for risk or protective alleles for complex disease. In this analysis, we examined genetic risk for glioma in a US population with predominantly Ashkenazi Jewish (AJ) ancestry. Genotyping data were obtained from three prior glioma case-control studies. Best-guess assignment to one of seven subcontinental European ancestry groups was performed using AIPS (https://github.com/biomedicaldatascience/AIPS). Out of a total of 6,416 cases and 7,441 controls across all three studies, 202 cases (3% of all cases, 63% GBM) and 403 controls (5% of all controls) were assigned to the AJ ancestry group. Unconditional logistic regression was performed for by study (adjusted for age and first two principal components) and then studies were combined using fixed effects meta-analysis. No associations reached genome-wide significance (p< 5x10-8), including those detected in prior pan-European GWAS. A nominally significant association was detected on chromosome 17 in ASPA (rs9904040, MAF=20%, p=2.61x10-6, Odds ratio=2.22 [95% confidence interval=1.59–3.09]) which is in linkage equilibrium (r2=0.0013) with the previously detected glioma risk SNP in TP53 (MAF=0.3% in this analysis, p=0.8801) in the European population. In our prior pan-European meta-analysis (Melin et al., 2017, this SNP was non-significant (p=0.0620). This study failed to replicate many previously identified glioma risk alleles, likely due to diminished power due to small sample size. We did identify a novel risk allele on chromosome 17 in ASPA, which encodes for aspartoacylase (which catalyzes deacylation of N-acetyl_L-aspartic acid). Larger sample sizes identified via targeted recruitment are necessary in order to fully characterize genetic risk for glioma in this population, including assessment of rare (MAF< 5%) risk allele associations.

Dataset Information

Genome-wide meta-analysis of 158,000 individuals of European ancestry identifies three loci associated with chronic back pain.

Publications

Genome-wide meta-analysis of 158,000 individuals of European ancestry identifies three loci associated with chronic back pain.

Similar Datasets

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