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Quantifying multi-ethnic representation in genetic studies of high mortality diseases

Most GWASs were performed using study populations with Caucasian ethnicity or ancestry, and findings from one ethnic subpopulation might not always translate to another. We curated 4,573 genetic studies on 763 human diseases and identified 3,461 disease-susceptible SNPs with genome-wide significance...

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Autores principales: Chen, Rong, Dudley, Joel T., Ruau, David, Butte, Atul J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Informatics Association 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3392055/
https://www.ncbi.nlm.nih.gov/pubmed/22779041
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author Chen, Rong
Dudley, Joel T.
Ruau, David
Butte, Atul J.
author_facet Chen, Rong
Dudley, Joel T.
Ruau, David
Butte, Atul J.
author_sort Chen, Rong
collection PubMed
description Most GWASs were performed using study populations with Caucasian ethnicity or ancestry, and findings from one ethnic subpopulation might not always translate to another. We curated 4,573 genetic studies on 763 human diseases and identified 3,461 disease-susceptible SNPs with genome-wide significance; only 10% of these had been validated in at least two different ethnic populations. SNPs for autoimmune diseases demonstrated the lowest percentage of cross-ethnicity validation. We used the mortality data from the Center for Disease Control and Prevention and identified 19 diseases killing over 10,000 Americans per year that were still lacking publications of even a single cross-ethnic SNP. Fifteen of these diseases had never been studied in large GWAS in non-Caucasian populations, including chronic liver diseases and cirrhosis, leukemia, and non-Hodgkin’s lymphoma. Our results demonstrate that diseases killing most Americans are still lacking genetic studies across ethnicities.
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spelling pubmed-33920552012-07-09 Quantifying multi-ethnic representation in genetic studies of high mortality diseases Chen, Rong Dudley, Joel T. Ruau, David Butte, Atul J. AMIA Jt Summits Transl Sci Proc Articles Most GWASs were performed using study populations with Caucasian ethnicity or ancestry, and findings from one ethnic subpopulation might not always translate to another. We curated 4,573 genetic studies on 763 human diseases and identified 3,461 disease-susceptible SNPs with genome-wide significance; only 10% of these had been validated in at least two different ethnic populations. SNPs for autoimmune diseases demonstrated the lowest percentage of cross-ethnicity validation. We used the mortality data from the Center for Disease Control and Prevention and identified 19 diseases killing over 10,000 Americans per year that were still lacking publications of even a single cross-ethnic SNP. Fifteen of these diseases had never been studied in large GWAS in non-Caucasian populations, including chronic liver diseases and cirrhosis, leukemia, and non-Hodgkin’s lymphoma. Our results demonstrate that diseases killing most Americans are still lacking genetic studies across ethnicities. American Medical Informatics Association 2012-03-19 /pmc/articles/PMC3392055/ /pubmed/22779041 Text en ©2012 AMIA - All rights reserved. This is an Open Access article: verbatim copying and redistribution of this article are permitted in all media for any purpose
spellingShingle Articles
Chen, Rong
Dudley, Joel T.
Ruau, David
Butte, Atul J.
Quantifying multi-ethnic representation in genetic studies of high mortality diseases
title Quantifying multi-ethnic representation in genetic studies of high mortality diseases
title_full Quantifying multi-ethnic representation in genetic studies of high mortality diseases
title_fullStr Quantifying multi-ethnic representation in genetic studies of high mortality diseases
title_full_unstemmed Quantifying multi-ethnic representation in genetic studies of high mortality diseases
title_short Quantifying multi-ethnic representation in genetic studies of high mortality diseases
title_sort quantifying multi-ethnic representation in genetic studies of high mortality diseases
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3392055/
https://www.ncbi.nlm.nih.gov/pubmed/22779041
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