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Rank-based genome-wide analysis reveals the association of Ryanodine receptor-2 gene variants with childhood asthma among human populations

BACKGROUND: The standard approach to determine unique or shared genetic factors across populations is to identify risk alleles in one population and investigate replication in others. However, since populations differ in DNA sequence information, allele frequencies, effect sizes, and linkage disequi...

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Autores principales: Ding, Lili, Abebe, Tilahun, Beyene, Joseph, Wilke, Russell A, Goldberg, Arnon, Woo, Jessica G, Martin, Lisa J, Rothenberg, Marc E, Rao, Marepalli, Hershey, Gurjit K Khurana, Chakraborty, Ranajit, Mersha, Tesfaye B
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3708719/
https://www.ncbi.nlm.nih.gov/pubmed/23829686
http://dx.doi.org/10.1186/1479-7364-7-16
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author Ding, Lili
Abebe, Tilahun
Beyene, Joseph
Wilke, Russell A
Goldberg, Arnon
Woo, Jessica G
Martin, Lisa J
Rothenberg, Marc E
Rao, Marepalli
Hershey, Gurjit K Khurana
Chakraborty, Ranajit
Mersha, Tesfaye B
author_facet Ding, Lili
Abebe, Tilahun
Beyene, Joseph
Wilke, Russell A
Goldberg, Arnon
Woo, Jessica G
Martin, Lisa J
Rothenberg, Marc E
Rao, Marepalli
Hershey, Gurjit K Khurana
Chakraborty, Ranajit
Mersha, Tesfaye B
author_sort Ding, Lili
collection PubMed
description BACKGROUND: The standard approach to determine unique or shared genetic factors across populations is to identify risk alleles in one population and investigate replication in others. However, since populations differ in DNA sequence information, allele frequencies, effect sizes, and linkage disequilibrium patterns, SNP association using a uniform stringent threshold on p values may not be reproducible across populations. Here, we developed rank-based methods to investigate shared or population-specific loci and pathways for childhood asthma across individuals of diverse ancestry. We performed genome-wide association studies on 859,790 SNPs genotyped in 527 affected offspring trios of European, African, and Hispanic ancestry using publically available asthma database in the Genotypes and Phenotypes database. RESULTS: Rank-based analyses showed that there are shared genetic factors for asthma across populations, more at the gene and pathway levels than at the SNP level. Although the top 1,000 SNPs were not shared, 11 genes (RYR2, PDE4D, CSMD1, CDH13, ROBO2, RBFOX1, PTPRD, NPAS3, PDE1C, SEMA5A, and CTNNA2) mapped by these SNPs were shared across populations. Ryanodine receptor 2 (RYR2, a statin response-related gene) showed the strongest association in European (p value = 2.55 × 10(−7)) and was replicated in African (2.57 × 10(−4)) and Hispanic (1.18 × 10(−3)) Americans. Imputation analyses based on the 1000 Genomes Project uncovered additional RYR2 variants associated with asthma. Network and functional ontology analyses revealed that RYR2 is an integral part of dermatological or allergic disorder biological networks, specifically in the functional classes involving inflammatory, eosinophilic, and respiratory diseases. CONCLUSION: Our rank-based genome-wide analysis revealed for the first time an association of RYR2 variants with asthma and replicated previously discovered PDE4D asthma gene across human populations. The replication of top-ranked asthma genes across populations suggests that such loci are less likely to be false positives and could indicate true associations. Variants that are associated with asthma across populations could be used to identify individuals who are at high risk for asthma regardless of genetic ancestry.
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spelling pubmed-37087192013-07-15 Rank-based genome-wide analysis reveals the association of Ryanodine receptor-2 gene variants with childhood asthma among human populations Ding, Lili Abebe, Tilahun Beyene, Joseph Wilke, Russell A Goldberg, Arnon Woo, Jessica G Martin, Lisa J Rothenberg, Marc E Rao, Marepalli Hershey, Gurjit K Khurana Chakraborty, Ranajit Mersha, Tesfaye B Hum Genomics Primary Research BACKGROUND: The standard approach to determine unique or shared genetic factors across populations is to identify risk alleles in one population and investigate replication in others. However, since populations differ in DNA sequence information, allele frequencies, effect sizes, and linkage disequilibrium patterns, SNP association using a uniform stringent threshold on p values may not be reproducible across populations. Here, we developed rank-based methods to investigate shared or population-specific loci and pathways for childhood asthma across individuals of diverse ancestry. We performed genome-wide association studies on 859,790 SNPs genotyped in 527 affected offspring trios of European, African, and Hispanic ancestry using publically available asthma database in the Genotypes and Phenotypes database. RESULTS: Rank-based analyses showed that there are shared genetic factors for asthma across populations, more at the gene and pathway levels than at the SNP level. Although the top 1,000 SNPs were not shared, 11 genes (RYR2, PDE4D, CSMD1, CDH13, ROBO2, RBFOX1, PTPRD, NPAS3, PDE1C, SEMA5A, and CTNNA2) mapped by these SNPs were shared across populations. Ryanodine receptor 2 (RYR2, a statin response-related gene) showed the strongest association in European (p value = 2.55 × 10(−7)) and was replicated in African (2.57 × 10(−4)) and Hispanic (1.18 × 10(−3)) Americans. Imputation analyses based on the 1000 Genomes Project uncovered additional RYR2 variants associated with asthma. Network and functional ontology analyses revealed that RYR2 is an integral part of dermatological or allergic disorder biological networks, specifically in the functional classes involving inflammatory, eosinophilic, and respiratory diseases. CONCLUSION: Our rank-based genome-wide analysis revealed for the first time an association of RYR2 variants with asthma and replicated previously discovered PDE4D asthma gene across human populations. The replication of top-ranked asthma genes across populations suggests that such loci are less likely to be false positives and could indicate true associations. Variants that are associated with asthma across populations could be used to identify individuals who are at high risk for asthma regardless of genetic ancestry. BioMed Central 2013-07-05 /pmc/articles/PMC3708719/ /pubmed/23829686 http://dx.doi.org/10.1186/1479-7364-7-16 Text en Copyright © 2013 Ding et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Primary Research
Ding, Lili
Abebe, Tilahun
Beyene, Joseph
Wilke, Russell A
Goldberg, Arnon
Woo, Jessica G
Martin, Lisa J
Rothenberg, Marc E
Rao, Marepalli
Hershey, Gurjit K Khurana
Chakraborty, Ranajit
Mersha, Tesfaye B
Rank-based genome-wide analysis reveals the association of Ryanodine receptor-2 gene variants with childhood asthma among human populations
title Rank-based genome-wide analysis reveals the association of Ryanodine receptor-2 gene variants with childhood asthma among human populations
title_full Rank-based genome-wide analysis reveals the association of Ryanodine receptor-2 gene variants with childhood asthma among human populations
title_fullStr Rank-based genome-wide analysis reveals the association of Ryanodine receptor-2 gene variants with childhood asthma among human populations
title_full_unstemmed Rank-based genome-wide analysis reveals the association of Ryanodine receptor-2 gene variants with childhood asthma among human populations
title_short Rank-based genome-wide analysis reveals the association of Ryanodine receptor-2 gene variants with childhood asthma among human populations
title_sort rank-based genome-wide analysis reveals the association of ryanodine receptor-2 gene variants with childhood asthma among human populations
topic Primary Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3708719/
https://www.ncbi.nlm.nih.gov/pubmed/23829686
http://dx.doi.org/10.1186/1479-7364-7-16
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