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  • Title: Association between VDR polymorphisms and multiple sclerosis: systematic review and updated meta-analysis of case-control studies.
    Author: Zhang YJ, Zhang L, Chen SY, Yang GJ, Huang XL, Duan Y, Yang LJ, Ye DQ, Wang J.
    Journal: Neurol Sci; 2018 Feb; 39(2):225-234. PubMed ID: 29110148.
    Abstract:
    Vitamin D receptor (VDR) polymorphisms have been inconsistently investigated in multiple sclerosis (MS). However, published studies demonstrated differences concerning design and effect size. A meta-analysis is necessary to determine the magnitude of the association between VDR polymorphisms and MS risk. The aim of the current study was to quantify the magnitude of the association between BsmI, FokI, ApaI, and TaqI VDR polymorphisms and MS risk. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we conducted a systematic search and meta-analysis of the VDR gene polymorphisms and the risk of MS. The pooled odds ratios (OR) and 95% confidence interval (CI) were calculated by using Stata Version 11.0 with dominant and recessive models and allele analyses. A total of 4013 cases and 4218 controls in 24 case-control studies were included in the meta-analyses. The results did not indicate an association between any of the VDR polymorphisms and the risk of MS among overall populations, Asians, and Caucasians. However, our subgroup analysis suggests that the A allele was associated with MS risk in Asian populations (P = 0.005, OR = 1.267, 95% CI 1.074-1.496). Interestingly, the sensitivity analysis excluding studies with controls not in HWE showed insignificant association between the A allele and MS risk (P = 0.211), which was different from those in the non-sensitivity analysis. Our preliminary results indicate the VDR gene ApaI, BsmI, FokI, and TaqI polymorphisms may not be associated with elevated MS risk among overall populations. But ApaI polymorphism may confer different susceptibility to MS among different populations, and more well-designed studies with a large sample size are still needed to validate our results.
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