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Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics

BACKGROUND: Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variati...

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Autores principales: Hodonsky, Chani J., Baldassari, Antoine R., Bien, Stephanie A., Raffield, Laura M., Highland, Heather M., Sitlani, Colleen M., Wojcik, Genevieve L., Tao, Ran, Graff, Marielisa, Tang, Weihong, Thyagarajan, Bharat, Buyske, Steve, Fornage, Myriam, Hindorff, Lucia A., Li, Yun, Lin, Danyu, Reiner, Alex P., North, Kari E., Loos, Ruth J. F., Kooperberg, Charles, Avery, Christy L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071748/
https://www.ncbi.nlm.nih.gov/pubmed/32171239
http://dx.doi.org/10.1186/s12864-020-6626-9
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author Hodonsky, Chani J.
Baldassari, Antoine R.
Bien, Stephanie A.
Raffield, Laura M.
Highland, Heather M.
Sitlani, Colleen M.
Wojcik, Genevieve L.
Tao, Ran
Graff, Marielisa
Tang, Weihong
Thyagarajan, Bharat
Buyske, Steve
Fornage, Myriam
Hindorff, Lucia A.
Li, Yun
Lin, Danyu
Reiner, Alex P.
North, Kari E.
Loos, Ruth J. F.
Kooperberg, Charles
Avery, Christy L.
author_facet Hodonsky, Chani J.
Baldassari, Antoine R.
Bien, Stephanie A.
Raffield, Laura M.
Highland, Heather M.
Sitlani, Colleen M.
Wojcik, Genevieve L.
Tao, Ran
Graff, Marielisa
Tang, Weihong
Thyagarajan, Bharat
Buyske, Steve
Fornage, Myriam
Hindorff, Lucia A.
Li, Yun
Lin, Danyu
Reiner, Alex P.
North, Kari E.
Loos, Ruth J. F.
Kooperberg, Charles
Avery, Christy L.
author_sort Hodonsky, Chani J.
collection PubMed
description BACKGROUND: Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. RESULTS: We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. CONCLUSION: This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations.
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spelling pubmed-70717482020-03-18 Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics Hodonsky, Chani J. Baldassari, Antoine R. Bien, Stephanie A. Raffield, Laura M. Highland, Heather M. Sitlani, Colleen M. Wojcik, Genevieve L. Tao, Ran Graff, Marielisa Tang, Weihong Thyagarajan, Bharat Buyske, Steve Fornage, Myriam Hindorff, Lucia A. Li, Yun Lin, Danyu Reiner, Alex P. North, Kari E. Loos, Ruth J. F. Kooperberg, Charles Avery, Christy L. BMC Genomics Research Article BACKGROUND: Quantitative red blood cell (RBC) traits are highly polygenic clinically relevant traits, with approximately 500 reported GWAS loci. The majority of RBC trait GWAS have been performed in European- or East Asian-ancestry populations, despite evidence that rare or ancestry-specific variation contributes substantially to RBC trait heritability. Recently developed combined-phenotype methods which leverage genetic trait correlation to improve statistical power have not yet been applied to these traits. Here we leveraged correlation of seven quantitative RBC traits in performing a combined-phenotype analysis in a multi-ethnic study population. RESULTS: We used the adaptive sum of powered scores (aSPU) test to assess combined-phenotype associations between ~ 21 million SNPs and seven RBC traits in a multi-ethnic population (maximum n = 67,885 participants; 24% African American, 30% Hispanic/Latino, and 43% European American; 76% female). Thirty-nine loci in our multi-ethnic population contained at least one significant association signal (p < 5E-9), with lead SNPs at nine loci significantly associated with three or more RBC traits. A majority of the lead SNPs were common (MAF > 5%) across all ancestral populations. Nineteen additional independent association signals were identified at seven known loci (HFE, KIT, HBS1L/MYB, CITED2/FILNC1, ABO, HBA1/2, and PLIN4/5). For example, the HBA1/2 locus contained 14 conditionally independent association signals, 11 of which were previously unreported and are specific to African and Amerindian ancestries. One variant in this region was common in all ancestries, but exhibited a narrower LD block in African Americans than European Americans or Hispanics/Latinos. GTEx eQTL analysis of all independent lead SNPs yielded 31 significant associations in relevant tissues, over half of which were not at the gene immediately proximal to the lead SNP. CONCLUSION: This work identified seven loci containing multiple independent association signals for RBC traits using a combined-phenotype approach, which may improve discovery in genetically correlated traits. Highly complex genetic architecture at the HBA1/2 locus was only revealed by the inclusion of African Americans and Hispanics/Latinos, underscoring the continued importance of expanding large GWAS to include ancestrally diverse populations. BioMed Central 2020-03-14 /pmc/articles/PMC7071748/ /pubmed/32171239 http://dx.doi.org/10.1186/s12864-020-6626-9 Text en © The Author(s). 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research Article
Hodonsky, Chani J.
Baldassari, Antoine R.
Bien, Stephanie A.
Raffield, Laura M.
Highland, Heather M.
Sitlani, Colleen M.
Wojcik, Genevieve L.
Tao, Ran
Graff, Marielisa
Tang, Weihong
Thyagarajan, Bharat
Buyske, Steve
Fornage, Myriam
Hindorff, Lucia A.
Li, Yun
Lin, Danyu
Reiner, Alex P.
North, Kari E.
Loos, Ruth J. F.
Kooperberg, Charles
Avery, Christy L.
Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics
title Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics
title_full Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics
title_fullStr Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics
title_full_unstemmed Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics
title_short Ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics
title_sort ancestry-specific associations identified in genome-wide combined-phenotype study of red blood cell traits emphasize benefits of diversity in genomics
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7071748/
https://www.ncbi.nlm.nih.gov/pubmed/32171239
http://dx.doi.org/10.1186/s12864-020-6626-9
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