Cargando…
A Genome-Wide Association Study of Red Blood Cell Traits Using the Electronic Medical Record
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...
Autores principales: | , , , , |
---|---|
Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2010
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2946914/ https://www.ncbi.nlm.nih.gov/pubmed/20927387 http://dx.doi.org/10.1371/journal.pone.0013011 |
_version_ | 1782187344768532480 |
---|---|
author | Kullo, Iftikhar J. Ding, Keyue Jouni, Hayan Smith, Carin Y. Chute, Christopher G. |
author_facet | Kullo, Iftikhar J. Ding, Keyue Jouni, Hayan Smith, Carin Y. Chute, Christopher G. |
author_sort | Kullo, Iftikhar J. |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-2946914 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2010 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-29469142010-10-06 A Genome-Wide Association Study of Red Blood Cell Traits Using the Electronic Medical Record Kullo, Iftikhar J. Ding, Keyue Jouni, Hayan Smith, Carin Y. Chute, Christopher G. PLoS One Research Article 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. Public Library of Science 2010-09-28 /pmc/articles/PMC2946914/ /pubmed/20927387 http://dx.doi.org/10.1371/journal.pone.0013011 Text en Kullo et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Kullo, Iftikhar J. Ding, Keyue Jouni, Hayan Smith, Carin Y. Chute, Christopher G. A Genome-Wide Association Study of Red Blood Cell Traits Using the Electronic Medical Record |
title | A Genome-Wide Association Study of Red Blood Cell Traits Using the Electronic Medical Record |
title_full | A Genome-Wide Association Study of Red Blood Cell Traits Using the Electronic Medical Record |
title_fullStr | A Genome-Wide Association Study of Red Blood Cell Traits Using the Electronic Medical Record |
title_full_unstemmed | A Genome-Wide Association Study of Red Blood Cell Traits Using the Electronic Medical Record |
title_short | A Genome-Wide Association Study of Red Blood Cell Traits Using the Electronic Medical Record |
title_sort | genome-wide association study of red blood cell traits using the electronic medical record |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2946914/ https://www.ncbi.nlm.nih.gov/pubmed/20927387 http://dx.doi.org/10.1371/journal.pone.0013011 |
work_keys_str_mv | AT kulloiftikharj agenomewideassociationstudyofredbloodcelltraitsusingtheelectronicmedicalrecord AT dingkeyue agenomewideassociationstudyofredbloodcelltraitsusingtheelectronicmedicalrecord AT jounihayan agenomewideassociationstudyofredbloodcelltraitsusingtheelectronicmedicalrecord AT smithcariny agenomewideassociationstudyofredbloodcelltraitsusingtheelectronicmedicalrecord AT chutechristopherg agenomewideassociationstudyofredbloodcelltraitsusingtheelectronicmedicalrecord AT kulloiftikharj genomewideassociationstudyofredbloodcelltraitsusingtheelectronicmedicalrecord AT dingkeyue genomewideassociationstudyofredbloodcelltraitsusingtheelectronicmedicalrecord AT jounihayan genomewideassociationstudyofredbloodcelltraitsusingtheelectronicmedicalrecord AT smithcariny genomewideassociationstudyofredbloodcelltraitsusingtheelectronicmedicalrecord AT chutechristopherg genomewideassociationstudyofredbloodcelltraitsusingtheelectronicmedicalrecord |