Optimizing multiple sclerosis diagnosis: gene expression and genomic association.

ABSTRACT:

Objective

The diagnosis of multiple sclerosis (MS) at disease onset is sometimes masqueraded by other diagnostic options resembling MS clinically or radiologically (NonMS). In the present study we utilized findings of large-scale Genome-Wide Association Studies (GWAS) to develop a blood gene expression-based classification tool to assist in diagnosis during the first demyelinating event.

Methods

We have merged knowledge of 110 MS susceptibility genes gained from MS GWAS studies together with our experimental results of differential blood gene expression profiling between 80 MS and 31 NonMS patients. Multiple classification algorithms were applied to this cohort to construct a diagnostic classifier that correctly distinguished between MS and NonMS patients. Accuracy of the cl

SUBMITTER: Gurevich M 

PROVIDER: S-EPMC4369276 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature