Modeling the cumulative genetic risk for multiple sclerosis from genome-wide association data.

ABSTRACT:

Background

Multiple sclerosis (MS) is the most common cause of chronic neurologic disability beginning in early to middle adult life. Results from recent genome-wide association studies (GWAS) have substantially lengthened the list of disease loci and provide convincing evidence supporting a multifactorial and polygenic model of inheritance. Nevertheless, the knowledge of MS genetics remains incomplete, with many risk alleles still to be revealed.

Methods

We used a discovery GWAS dataset (8,844 samples, 2,124 cases and 6,720 controls) and a multi-step logistic regression protocol to identify novel genetic associations. The emerging genetic profile included 350 independent markers and was used to calculate and estimate the cumulative genetic risk in an independent validation

SUBMITTER: Wang JH 

PROVIDER: S-EPMC3092088 | biostudies-literature | 2011 Jan

REPOSITORIES: biostudies-literature