4.6 Article

Capturing SNP Association across the NK Receptor and HLA Gene Regions in Multiple Sclerosis by Targeted Penalised Regression Models

Journal

GENES
Volume 13, Issue 1, Pages -

Publisher

MDPI
DOI: 10.3390/genes13010087

Keywords

multiple sclerosis (MS); genetic wide association study (GWAS); single nucleotide polymorphisms (SNPs); natural killer cells; human leukocyte antigen (HLA) complex; natural killer gene complex (NKC); leukocyte receptor complex (LRC); multi-variate regression analysis; elastic net; gene-gene interaction

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This study re-analyzed existing datasets using advanced statistical methods and identified new association signals for Multiple Sclerosis (MS) predisposition. The study also found that gene variants involved in oxidative stress were associated with MS.
Conventional genome-wide association studies (GWASs) of complex traits, such as Multiple Sclerosis (MS), are reliant on per-SNP p-values and are therefore heavily burdened by multiple testing correction. Thus, in order to detect more subtle alterations, ever increasing sample sizes are required, while ignoring potentially valuable information that is readily available in existing datasets. To overcome this, we used penalised regression incorporating elastic net with a stability selection method by iterative subsampling to detect the potential interaction of loci with MS risk. Through re-analysis of the ANZgene dataset (1617 cases and 1988 controls) and an IMSGC dataset as a replication cohort (1313 cases and 1458 controls), we identified new association signals for MS predisposition, including SNPs above and below conventional significance thresholds while targeting two natural killer receptor loci and the well-established HLA loci. For example, rs2844482 (98.1% iterations), otherwise ignored by conventional statistics (p = 0.673) in the same dataset, was independently strongly associated with MS in another GWAS that required more than 40 times the number of cases (~45 K). Further comparison of our hits to those present in a large-scale meta-analysis, confirmed that the majority of SNPs identified by the elastic net model reached conventional statistical GWAS thresholds (p < 5 x 10(-8)) in this much larger dataset. Moreover, we found that gene variants involved in oxidative stress, in addition to innate immunity, were associated with MS. Overall, this study highlights the benefit of using more advanced statistical methods to (re-)analyse subtle genetic variation among loci that have a biological basis for their contribution to disease risk.

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