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Large candidate gene association study reveals genetic risk factors and therapeutic targets for fibromyalgia.

ABSTRACT: OBJECTIVE:Fibromyalgia (FM) represents a complex disorder that is characterized by widespread pain and tenderness and is frequently accompanied by additional somatic and cognitive/affective symptoms. Genetic risk factors are known to contribute to the etiology of the syndrome. The aim of this study was to examine >350 genes for association with FM, using a large-scale candidate gene approach. METHODS:The study group comprised 496 patients with FM (cases) and 348 individuals with no chronic pain (controls). Genotyping was performed using a dedicated gene array chip, the Pain Research Panel, which assays variants characterizing >350 genes known to be involved in the biologic pathways relevant to nociception, inflammation, and mood. Association testing was performed using logistic regression. RESULTS:Significant differences in allele frequencies between cases and controls were observed for 3 genes: GABRB3 (rs4906902; P = 3.65 × 10(-6)), TAAR1 (rs8192619; P = 1.11 × 10(-5)), and GBP1 (rs7911; P = 1.06 × 10(-4)). These 3 genes and 7 other genes with suggestive evidence for association were examined in a second, independent cohort of patients with FM and control subjects who were genotyped using the Perlegen 600K platform. Evidence of association in the replication cohort was observed for TAAR1, RGS4, CNR1, and GRIA4. CONCLUSION:Variation in these 4 replicated genes may serve as a basis for development of new diagnostic approaches, and the products of these genes may contribute to the pathophysiology of FM and represent potential targets for therapeutic action.

SUBMITTER: Smith SB

PROVIDER: S-EPMC3237946 | biostudies-literature | 2012 Feb

REPOSITORIES: biostudies-literature

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Large candidate gene association study reveals genetic risk factors and therapeutic targets for fibromyalgia.

Smith Shad B SB Maixner Dylan W DW Fillingim Roger B RB Slade Gary G Gracely Richard H RH Ambrose Kirsten K Zaykin Dmitri V DV Hyde Craig C John Sally S Tan Keith K Maixner William W Diatchenko Luda L

Arthritis and rheumatism 20120201 2

<h4>Objective</h4>Fibromyalgia (FM) represents a complex disorder that is characterized by widespread pain and tenderness and is frequently accompanied by additional somatic and cognitive/affective symptoms. Genetic risk factors are known to contribute to the etiology of the syndrome. The aim of this study was to examine >350 genes for association with FM, using a large-scale candidate gene approach.<h4>Methods</h4>The study group comprised 496 patients with FM (cases) and 348 individuals with n ...[more]

PMID: 21905019

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Project description:BackgroundImputation from genotyping array to whole-genome sequence variants using resequencing of representative reference populations enhances our ability to map genetic factors affecting complex phenotypes in livestock species. The accumulation of knowledge about gene function in human and laboratory animals can provide substantial advantage for genomic research in livestock species.ResultsIn this study, 201,388 pigs from three commercial Danish breeds genotyped with low to medium (8.5k to 70k) SNP arrays were imputed to whole genome sequence variants using a two-step approach. Both imputation steps achieved high accuracies, and in total this yielded 26,447,434 markers on 18 autosomes. The average estimated imputation accuracy of markers with minor allele frequency ≥ 0.05 was 0.94. To overcome the memory consumption of running genome-wide association study (GWAS) for each breed, we performed within-breed subpopulation GWAS then within-breed meta-analysis for average daily weight gain (ADG), followed by a multi-breed meta-analysis of GWAS summary statistics. We identified 15 quantitative trait loci (QTL). Our post-GWAS analysis strategy to prioritize of candidate genes including information like gene ontology, mammalian phenotype database, differential expression gene analysis of high and low feed efficiency pig and human GWAS catalog for height, obesity, and body mass index, we proposed MRAP2, LEPROT, PMAIP1, ENSSSCG00000036234, BMP2, ELFN1, LIG4 and FAM155A as the candidate genes with biological support for ADG in pigs.ConclusionOur post-GWAS analysis strategy helped to identify candidate genes not just by distance to the lead SNP but also by multiple sources of biological evidence. Besides, the identified QTL overlap with genes which are known for their association with human growth-related traits. The GWAS with this large data set showed the power to map the genetic factors associated with ADG in pigs and have added to our understanding of the genetics of growth across mammalian species.

Project description:BackgroundThis study was designed to identify common genetic susceptibility and shared genetic variants associated with acute radiation-induced toxicity across 4 cancer types (prostate, head and neck, breast, and lung).MethodsA genome-wide association study meta-analysis was performed using 19 cohorts totaling 12 042 patients. Acute standardized total average toxicity (STATacute) was modelled using a generalized linear regression model for additive effect of genetic variants, adjusted for demographic and clinical covariates (rSTATacute). Linkage disequilibrium score regression estimated shared single-nucleotide variation (SNV-formerly SNP)-based heritability of rSTATacute in all patients and for each cancer type.ResultsShared SNV-based heritability of STATacute among all cancer types was estimated at 10% (SE = 0.02) and was higher for prostate (17%, SE = 0.07), head and neck (27%, SE = 0.09), and breast (16%, SE = 0.09) cancers. We identified 130 suggestive associated SNVs with rSTATacute (5.0 × 10‒8 < P < 1.0 × 10‒5) across 25 genomic regions. rs142667902 showed the strongest association (effect allele A; effect size ‒0.17; P = 1.7 × 10‒7), which is located near DPPA4, encoding a protein involved in pluripotency in stem cells, which are essential for repair of radiation-induced tissue injury. Gene-set enrichment analysis identified 'RNA splicing via endonucleolytic cleavage and ligation' (P = 5.1 × 10‒6, P = .079 corrected) as the top gene set associated with rSTATacute among all patients. In silico gene expression analysis showed that the genes associated with rSTATacute were statistically significantly up-regulated in skin (not sun exposed P = .004 corrected; sun exposed P = .026 corrected).ConclusionsThere is shared SNV-based heritability for acute radiation-induced toxicity across and within individual cancer sites. Future meta-genome-wide association studies among large radiation therapy patient cohorts are worthwhile to identify the common causal variants for acute radiotoxicity across cancer types.

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Large candidate gene association study reveals genetic risk factors and therapeutic targets for fibromyalgia.

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Large candidate gene association study reveals genetic risk factors and therapeutic targets for fibromyalgia.

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