Neurology Neuroimmunology & NeuroinflammationGeneticsPeer-reviewed journal article
Gene-environment interactions in Multiple Sclerosis: a UK Biobank study
Benjamin M. JacobsiD, Alastair John NoyceiD, Jonathan Paul BestwickiD, Daniel BeleteiD, Gavin GiovannoniiD, Ruth DobsoniD
Abstract
ImportanceMultiple Sclerosis (MS) is a neuro-inflammatory disorder caused by a combination of environmental exposures and genetic risk factors. We sought to determine whether genetic risk modifies the effect of environmental MS risk factors. MethodsPeople with MS were identified within UK Biobank using ICD10-coded MS or self-report. Associations between environmental risk factors and MS risk were quantified with a case-control design using multivariable logistic regression. Polygenic risk scores (PRS) were derived using the clumping-and-thresholding approach with external weights from the largest genome-wide association study of MS. Separate scores were created including (PRSMHC) and excluding (PRSNon-MHC) the MHC locus. The best performing PRS were identified in 30% of the cohort and validated in the remaining 70%. Interaction between environmental and genetic risk factors was quantified using the Attributable Proportion due to interaction (AP) and multiplicative interaction. ResultsData were available for 2250 people with MS and 486,000 controls. Childhood obesity, earlier age at menarche, and smoking were associated with MS. The optimal PRS were strongly associated with MS in the validation cohort (PRSMHC: Nagelkerkes Pseudo-R2 0.033, p=3.92x10-111; PRSNon-MHC: Nagelkerkes Pseudo-R2 0.013, p=3.73x10-43). There was strong evidence of interaction between polygenic risk for MS and childhood obesity (PRSMHC: AP=0.17, 95% CI 0.06 - 0.25, p=0.004; PRSNon-MHC: AP=0.17, 95% CI 0.06 - 0.27, p=0.006). Conclusions and RelevanceThis study provides novel evidence for an interaction between childhood obesity and a high burden of autosomal genetic risk. These findings may have significant implications for our understanding of MS biology and inform targeted prevention strategies.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 61
- FWCI
- 6.50
- Field percentile
- top 2%
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