We sought to determine whether genetic risk modifies the effect of environmental risk factors for multiple sclerosis (MS). To test this hypothesis, we tested for statistical interaction between polygenic risk scores (PRS) capturing genetic susceptibility to MS and environmental risk factors for MS in UK Biobank.
People with MS were identified within UK Biobank using ICD-10–coded MS or self-report. Associations between environmental risk factors and MS risk were quantified with a case-control design using multivariable logistic regression. 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 major histocompatibility complex (MHC) (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.
Data were available for 2,250 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: Nagelkerke’s pseudo-R2 0.033, p = 3.92 x 10–111; PRSnon-MHC: Nagelkerke’s pseudo-R2 0.013, p = 3.73 x 10–43). 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).
This 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.