A genome-wide association study of red blood cell traits using the Electronic Medical Record

Iftikhar J. Kullo, Keyue Ding, Hayan Jouni, Carin Y. Smith, Christopher G. Chute

Research output: Contribution to journalArticle

84 Scopus citations

Abstract

Background: The Electronic Medical Record (EMR) is a potential source for high throughput phenotyping to conduct genome-wide association studies (GWAS), including those of medically relevant quantitative traits. We describe use of the Mayo Clinic EMR to conduct a GWAS of red blood cell (RBC) traits in a cohort of patients with peripheral arterial disease (PAD) and controls without PAD. Methodology and Principal Findings: Results for hemoglobin level, hematocrit, RBC count, mean corpuscular volume, mean corpuscular hemoglobin, and mean corpuscular hemoglobin concentration were extracted from the EMR from January 1994 to September 2009. Out of 35,159 RBC trait values in 3,411 patients, we excluded 12,864 values in 1,165 patients that had been measured during hospitalization or in the setting of hematological disease, malignancy, or use of drugs that affect RBC traits, leaving a final genotyped sample of 3,012, 80% of whom had ≥2 measurements. The median of each RBC trait was used in the genetic analyses, which were conducted using an additive model that adjusted for age, sex, and PAD status. We identified four genomic loci that were associated (P<5×10-8) with one or more of the RBC traits (HBLS1/MYB on 6q23.3, TMPRSS6 on 22q12.3, HFE on 6p22.1, and SLC17A1 on 6p22.2). Three of these loci (HBLS1/MYB, TMPRSS6, and HFE) had been identified in recent GWAS and the allele frequencies, effect sizes, and the directions of effects of the replicated SNPs were similar to the prior studies. Conclusions: Our results demonstrate feasibility of using the EMR to conduct high throughput genomic studies of medically relevant quantitative traits.

Original languageEnglish (US)
Article numbere13011
JournalPloS one
Volume5
Issue number9
DOIs
StatePublished - 2010

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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