title: THE CHALLENGES IN USING ELECTRONIC HEALTH RECORDS FOR PHARMACOGENOMICS AND PRECISION MEDICINE RESEARCH.
abstract: Access and utilization of electronic health records with extensive medication lists and genetic profiles is rapidly advancing discoveries in pharmacogenomics. In this study, we analyzed ~116,000 variants on the Illumina Metabochip for response to antihypertensive and lipid lowering medications in African American adults from BioVU, the Vanderbilt University Medical Center's biorepository linked to de-identified electronic health records. Our study population included individuals who were prescribed an antihypertensive or lipid lowering medication, and who had both pre- and post-medication blood pressure or low-density lipoprotein cholesterol (LDL-C) measurements, respectively. Among those with pre- and post-medication systolic and diastolic blood pressure measurements (n=2,268), the average change in systolic and diastolic blood pressure was -0.6 mg Hg and -0.8 mm Hg, respectively. Among those with pre- and post-medication LDL-C measurements (n=1,244), the average change in LDL-C was -26.3 mg/dL. SNPs were tested for an association with change and percent change in blood pressure or blood levels of LDL-C. After adjustment for multiple testing, we did not observe any significant associations, and we were not able to replicate previously reported associations, such as in APOE and LPA, from the literature. The present study illustrates the benefits and challenges with using electronic health records linked to biorepositories for pharmacogenomic studies.
authors.affiliation: Eastern Virginia Medical School, Norfolk, VA, 23507, USA, lapersm@evms.edu.
authors.forename: Sarah M
authors.initials: SM
authors.lastname: Laper
authors.forename: Nicole A
authors.initials: NA
authors.lastname: Restrepo
authors.forename: Dana C
authors.initials: DC
authors.lastname: Crawford
mesh_terms: D000328:Adult; D001741:Black or African American / Q000235:genetics; D000368:Aged; D000369:Aged, 80 and over; D001057:Apolipoproteins E / Q000235:genetics; D001794:Blood Pressure / Q000235:genetics; D008078:Cholesterol, LDL / Q000097:blood / Q000235:genetics; D019295:Computational Biology / Q000379:methods / Q000706:statistics & numerical data; D057286:Electronic Health Records / Q000706:statistics & numerical data*; D005260:Female; D056726:Genetic Association Studies; D006801:Humans; D007004:Hypoglycemic Agents / Q000494:pharmacology; D000960:Hypolipidemic Agents / Q000494:pharmacology; D017270:Lipoprotein(a) / Q000235:genetics; D008297:Male; D008875:Middle Aged; D010597:Pharmacogenetics / Q000379:methods* / Q000706:statistics & numerical data; D020641:Polymorphism, Single Nucleotide; D057285:Precision Medicine / Q000379:methods* / Q000706:statistics & numerical data; D055815:Young Adult
chemical_list: D001057:Apolipoproteins E; D008078:Cholesterol, LDL; D007004:Hypoglycemic Agents; D000960:Hypolipidemic Agents; D017270:Lipoprotein(a)