medRxivGenetic & Genomic MedicinePreprint
Chronic pain gene expression changes in the brain and relationships with clinical traits
Keira J.A. JohnstoniD, Alanna C. CoteiD, Emily M. HicksiD, Jessica JohnsoniD, Laura M. HuckinsiD
Abstract
BackgroundChronic pain is a common, poorly-understood condition. Genetic studies including genome wide association studies (GWAS) identify many relevant variants, which have yet to be translated into full understanding of chronic pain. Transcriptome wide association study using transcriptomic imputation (TI) methods such as S-PrediXcan can help bridge this genotype-phenotype gap. MethodsWe carried out TI using S-PrediXcan to identify genetically regulated gene expression (GREX) in thirteen brain tissues and whole blood associated with Multisite Chronic Pain (MCP). We then imputed GREX for over 31,000 Mount Sinai BioMe participants and performed phenome-wide association study (PheWAS) to investigate clinical relationships in chronic pain associated gene expression changes. ResultsWe identified 95 experiment-wide significant gene-tissue associations (p<7.97x10-7), including 35 unique genes, and an additional 134 gene-tissue associations reaching within-tissue significance, including 53 additional unique genes. Of 89 unique genes total, 59 were novel for MCP and 18 are established drug targets. Chronic pain GREX for 10 unique genes was significantly associated with cardiac dysrhythmia, metabolic syndrome, disc disorders/ dorsopathies, joint/ligament sprain, anemias, and neurological disorder phecodes. PheWAS analyses adjusting for mean painscore showed associations were not driven by mean painscore. ConclusionsWe carried out the largest TWAS of any chronic pain trait to date. Results highlight potential causal genes in chronic pain development, and tissue and direction of effect. Several gene results were also drug targets. PheWAS results showed significant association for phecodes including cardiac dysrhythmia and metabolic syndrome, indicating potential shared mechanisms.
- organism: human
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 1
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