Powerful Predisposition Gene Identification for Ischemic Stroke

One of the limitations of ischemic stroke genetics studies is the treatment of all ischemic stroke as one phenotype, rather than dividing cases into the pathophysiologically-distinct subtypes of cardiac embolism (CE), large artery atherosclerosis (LAA), and lacunar infarction (LI). It is not known whether stroke subtypes aggregate within families: in a genome-wide association study of sibling pairs with ischemic stroke there was only moderate concordance of ischemic stroke subtypes, though this concordance increased when limiting analysis to young stroke. Adding to the confusion, recent work has suggested shared genetic risk between subtypes, though the few successful stroke genetic analyses limited cases to specific subtypes: chromosome 9p21 locus increases risk for LAA stroke and the atrial fibrillation locus 4q2517, increases risk for CE stroke. To reduce the cognitive effort and physical review of charts when generating stroke study cohorts and to automatically increase sample sizes of all ischemic stroke and its subtypes for genetic studies, the field of stroke genetics has great need for automation of ischemic stroke phenotyping into the main subtypes. This work is the first step towards that automation process.

Selected Publications, Posters, and Presentations

  • Mowery DL, Hill B, Zhang M, Chapman WW, Cannon-Albright L, Majersik JJ. A Comparison of Stroke Classifiers Leveraging Hospital Billing Codes versus Natural Language Processing. AMIA Annu Symp 2017. Washington, DC.
  • Mowery D, Hill B, Chapman W, Cannon-Albright Lisa, Majersik J. Development of a knowledge base to support the automatic classification of a computable ischemic stroke phenotype from electronic medical records. Neurology: Genetics; 2017. http://ng.neurology.org/content/3/1_Supplement_1/S12.full.pdf; presented at: Ischemic Stroke Genetics Consortium 2016. Milan, Italy.
  • Mowery DL, Chapman BE, Conway M, South BR, Madden E, Keyhani S, Chapman WW. Extracting a Stroke Phenotype Risk Factor from Veteran Health Administration Clinical Reports: An Information Content Analysis. Journal of Biomedical Semantics. 2016. 7:26
  • Mowery DL, Chapman WW, Chapman BE, Conway M, South BR, Madden E, Keyhani S. Evaluating the Usage of Sections, Structures, and Expressions for Reporting and Extracting a Stroke Phenotype Risk Factor. Intelligent Systems for Molecular Biology: Phenotype Day 2015. Dublin, Ireland.
  • PI: 
    Danielle Mowery
    Wendy Chapman