Automated extraction of clinical traits of multiple sclerosis in electronic medical records.

The clinical course of multiple sclerosis (MS) is highly variable, and research data collection is costly and time consuming. We evaluated natural language processing techniques applied to electronic medical records (EMR) to identify MS patients and the key clinical traits of their disease course.We used four algorithms based on ICD-9 codes, text keywords, and medications […]

Interrogating the complex role of chromosome 16p13.13 in multiple sclerosis susceptibility: independent genetic signals in the CIITA-CLEC16A-SOCS1 gene complex.

Multiple sclerosis (MS) is a neurodegenerative, autoimmune disease of the central nervous system, and numerous studies have shown that MS has a strong genetic component. Independent studies to identify MS-associated genes have often indicated multiple signals in physically close genomic regions, although by their proximity it is not always clear if these data indicate redundant […]

A knowledge-driven interaction analysis reveals potential neurodegenerative mechanism of multiple sclerosis susceptibility.

Gene-gene interactions are proposed as an important component of the genetic architecture of complex diseases, and are just beginning to be evaluated in the context of genome-wide association studies (GWAS). In addition to detecting epistasis, a benefit to interaction analysis is that it also increases power to detect weak main effects. We conducted a knowledge-driven […]

Evidence for polygenic susceptibility to multiple sclerosis–the shape of things to come.

It is well established that the risk of developing multiple sclerosis is substantially increased in the relatives of affected individuals and that most of this increase is genetically determined. The observed pattern of familial recurrence risk has long suggested that multiple variants are involved, but it has proven difficult to identify individual risk variants and […]