Scott Frodsham, Brigham Young University
Life Sciences
The goal of this study is to better understand if the genetic variants that strongly correlate with an increased risk of developing multiple sclerosis (MS) also increase the risk of developing diseases that commonly co-occur with MS. This relationship can be determined by comparing genetic data of patients diagnosed exclusively with MS to the genetic data of patients diagnosed with both MS and one of its comorbid diseases. Many electronic medical records (EMR) collected at medical institutions are made available for research purposes. The EMRs of individuals contained in the database that will be used for this study are linked to corresponding genetic information. Data extraction via computer algorithm will be executed to identify patients who, because of their respective diagnoses, will provide meaningful data for analysis. The case group for individuals diagnosed with just MS and have available genetic information consists of 1003 individuals. Applying a basic algorithm (ICD-9 billing codes) to this group has shown preliminary data on patients with MS and one other comorbidity as follows: Hypertension, 192 patients; anxiety, 17 patients; hypothyroidism, 84 patients; Type 1 diabetes, 24 patients; inflammatory bowel disease, 12 patients; migraine, 116 patients; restless leg syndrome, 14 patients; rheumatoid arthritis, 28 patients. The algorithms will be modified to find and include more patients for analysis. We will enhance patient identification by including medications and text keyword searches of clinical notes in the search. Genetic analysis will be performed on the final dataset.