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

Lili Ding, Tilahun Abebe, Joseph Beyene, Russell A. Wilke, Arnon Goldberg, Jessica G. Woo, Lisa J. Martin, Marc E. Rothenberg, Marepalli Rao, Gurjit K. Khurana Hershey, Ranajit Chakraborty, Tesfaye B. Mersha

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Abstract

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.

Original languageEnglish
Article number16
JournalHuman Genomics
Volume7
Issue number1
DOIs
StatePublished - 2013

Fingerprint

Ryanodine Receptor Calcium Release Channel
Genome-Wide Association Study
Asthma
Population
Genes
Single Nucleotide Polymorphism
Hispanic Americans
Genome
Databases
Hydroxymethylglutaryl-CoA Reductase Inhibitors
Linkage Disequilibrium
Gene Frequency
Alleles
Genotype
Phenotype

Keywords

  • 1000 Genomes project
  • Ancestry
  • Asthma
  • DbGaP
  • GWAS
  • Imputation
  • Networks/pathways
  • RYR2
  • Rank analysis
  • Trans-ancestral analysis

Cite this

Ding, Lili ; Abebe, Tilahun ; Beyene, Joseph ; Wilke, Russell A. ; Goldberg, Arnon ; Woo, Jessica G. ; Martin, Lisa J. ; Rothenberg, Marc E. ; Rao, Marepalli ; Khurana Hershey, Gurjit K. ; 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. In: Human Genomics. 2013 ; Vol. 7, No. 1.
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abstract = "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.",
keywords = "1000 Genomes project, Ancestry, Asthma, DbGaP, GWAS, Imputation, Networks/pathways, RYR2, Rank analysis, Trans-ancestral analysis",
author = "Lili Ding and Tilahun Abebe and Joseph Beyene and Wilke, {Russell A.} and Arnon Goldberg and Woo, {Jessica G.} and Martin, {Lisa J.} and Rothenberg, {Marc E.} and Marepalli Rao and {Khurana Hershey}, {Gurjit K.} and Ranajit Chakraborty and Mersha, {Tesfaye B.}",
year = "2013",
doi = "10.1186/1479-7364-7-16",
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journal = "Human Genomics",
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Ding, L, Abebe, T, Beyene, J, Wilke, RA, Goldberg, A, Woo, JG, Martin, LJ, Rothenberg, ME, Rao, M, Khurana Hershey, GK, Chakraborty, R & Mersha, TB 2013, 'Rank-based genome-wide analysis reveals the association of Ryanodine receptor-2 gene variants with childhood asthma among human populations', Human Genomics, vol. 7, no. 1, 16. https://doi.org/10.1186/1479-7364-7-16

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; Khurana Hershey, Gurjit K.; Chakraborty, Ranajit; Mersha, Tesfaye B.

In: Human Genomics, Vol. 7, No. 1, 16, 2013.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Rank-based genome-wide analysis reveals the association of Ryanodine receptor-2 gene variants with childhood asthma among human populations

AU - Ding, Lili

AU - Abebe, Tilahun

AU - Beyene, Joseph

AU - Wilke, Russell A.

AU - Goldberg, Arnon

AU - Woo, Jessica G.

AU - Martin, Lisa J.

AU - Rothenberg, Marc E.

AU - Rao, Marepalli

AU - Khurana Hershey, Gurjit K.

AU - Chakraborty, Ranajit

AU - Mersha, Tesfaye B.

PY - 2013

Y1 - 2013

N2 - 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.

AB - 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.

KW - 1000 Genomes project

KW - Ancestry

KW - Asthma

KW - DbGaP

KW - GWAS

KW - Imputation

KW - Networks/pathways

KW - RYR2

KW - Rank analysis

KW - Trans-ancestral analysis

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