The clinical course of multiple sclerosis (MS) is highly variable, and research data collection is costly and time-consuming. Much is known about the genetic risk of acquiring MS, but little is understood about the effect of genetics on the clinical course. This work uses natural language processing techniques applied to electronic medical records (EMR) to identify MS patients and key clinical traits of disease course. 5,789 individuals with MS were identified by algorithm. Algorithms were also developed with high precision and specificity to extract detailed features of the clinical course of MS, including clinical subtype, presence of oligoclonal bands, year of diagnosis, year and origin of first symptom, Expanded Disability Status Scale scores, timed 25-foot walk scores, and MS medications. DNA was available for 1,221 individuals through BioVU. These samples and 2,587 control samples were genotyped on the ImmunoChip. After extensive sample and SNP quality control, replication of known MS risk loci confirmed that the genetic architecture of this EMR-derived population is similar to that of other published MS datasets. Genetic analyses of seven clinical traits were performed using the data extracted from the medical records: age at diagnosis, age and CNS origin of first neurological symptom, presence of oligoclonal bands, Multiple Sclerosis Severity Score, timed 25-foot walk, and time to secondary progressive MS. No outstanding results were observed, but many interesting results require further investigation. This work shows the potential of using EMR-derived data in research studies of disease course.
| Identifer | oai:union.ndltd.org:VANDERBILT/oai:VANDERBILTETD:etd-11302013-193738 |
| Date | 09 December 2013 |
| Creators | Davis, Mary Feller |
| Contributors | William S. Bush, Jonathan L. Haines, Subramaniam Sriram, Joshua C. Denny, Thomas M. Aune |
| Publisher | VANDERBILT |
| Source Sets | Vanderbilt University Theses |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.library.vanderbilt.edu/available/etd-11302013-193738/ |
| Rights | restrictone, I hereby certify that, if appropriate, I have obtained and attached hereto a written permission statement from the owner(s) of each third party copyrighted matter to be included in my thesis, dissertation, or project report, allowing distribution as specified below. I certify that the version I submitted is the same as that approved by my advisory committee. I hereby grant to Vanderbilt University or its agents the non-exclusive license to archive and make accessible, under the conditions specified below, my thesis, dissertation, or project report in whole or in part in all forms of media, now or hereafter known. I retain all other ownership rights to the copyright of the thesis, dissertation or project report. I also retain the right to use in future works (such as articles or books) all or part of this thesis, dissertation, or project report. |
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