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Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations
Background: Thousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Moreover, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8307403/ https://www.ncbi.nlm.nih.gov/pubmed/34356065 http://dx.doi.org/10.3390/genes12071049 |
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author | Wen, Jia Xie, Munan Rowland, Bryce Rosen, Jonathan D. Sun, Quan Chen, Jiawen Tapia, Amanda L. Qian, Huijun Kowalski, Madeline H. Shan, Yue Young, Kristin L. Graff, Marielisa Argos, Maria Avery, Christy L. Bien, Stephanie A. Buyske, Steve Yin, Jie Choquet, Hélène Fornage, Myriam Hodonsky, Chani J. Jorgenson, Eric Kooperberg, Charles Loos, Ruth J. F. Liu, Yongmei Moon, Jee-Young North, Kari E. Rich, Stephen S. Rotter, Jerome I. Smith, Jennifer A. Zhao, Wei Shang, Lulu Wang, Tao Zhou, Xiang Reiner, Alexander P. Raffield, Laura M. Li, Yun |
author_facet | Wen, Jia Xie, Munan Rowland, Bryce Rosen, Jonathan D. Sun, Quan Chen, Jiawen Tapia, Amanda L. Qian, Huijun Kowalski, Madeline H. Shan, Yue Young, Kristin L. Graff, Marielisa Argos, Maria Avery, Christy L. Bien, Stephanie A. Buyske, Steve Yin, Jie Choquet, Hélène Fornage, Myriam Hodonsky, Chani J. Jorgenson, Eric Kooperberg, Charles Loos, Ruth J. F. Liu, Yongmei Moon, Jee-Young North, Kari E. Rich, Stephen S. Rotter, Jerome I. Smith, Jennifer A. Zhao, Wei Shang, Lulu Wang, Tao Zhou, Xiang Reiner, Alexander P. Raffield, Laura M. Li, Yun |
author_sort | Wen, Jia |
collection | PubMed |
description | Background: Thousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Moreover, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed. Methods: To derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including n = 229 African American and n = 381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, n = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (n = 27,955) and Hispanic/Latino (n = 28,324) ancestry participants. Results: Our results revealed 24 suggestive signals (p < 1 × 10(−4)) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (n = 802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN. Conclusions: These analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel. |
format | Online Article Text |
id | pubmed-8307403 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-83074032021-07-25 Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations Wen, Jia Xie, Munan Rowland, Bryce Rosen, Jonathan D. Sun, Quan Chen, Jiawen Tapia, Amanda L. Qian, Huijun Kowalski, Madeline H. Shan, Yue Young, Kristin L. Graff, Marielisa Argos, Maria Avery, Christy L. Bien, Stephanie A. Buyske, Steve Yin, Jie Choquet, Hélène Fornage, Myriam Hodonsky, Chani J. Jorgenson, Eric Kooperberg, Charles Loos, Ruth J. F. Liu, Yongmei Moon, Jee-Young North, Kari E. Rich, Stephen S. Rotter, Jerome I. Smith, Jennifer A. Zhao, Wei Shang, Lulu Wang, Tao Zhou, Xiang Reiner, Alexander P. Raffield, Laura M. Li, Yun Genes (Basel) Article Background: Thousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Moreover, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed. Methods: To derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including n = 229 African American and n = 381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, n = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (n = 27,955) and Hispanic/Latino (n = 28,324) ancestry participants. Results: Our results revealed 24 suggestive signals (p < 1 × 10(−4)) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (n = 802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN. Conclusions: These analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel. MDPI 2021-07-08 /pmc/articles/PMC8307403/ /pubmed/34356065 http://dx.doi.org/10.3390/genes12071049 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wen, Jia Xie, Munan Rowland, Bryce Rosen, Jonathan D. Sun, Quan Chen, Jiawen Tapia, Amanda L. Qian, Huijun Kowalski, Madeline H. Shan, Yue Young, Kristin L. Graff, Marielisa Argos, Maria Avery, Christy L. Bien, Stephanie A. Buyske, Steve Yin, Jie Choquet, Hélène Fornage, Myriam Hodonsky, Chani J. Jorgenson, Eric Kooperberg, Charles Loos, Ruth J. F. Liu, Yongmei Moon, Jee-Young North, Kari E. Rich, Stephen S. Rotter, Jerome I. Smith, Jennifer A. Zhao, Wei Shang, Lulu Wang, Tao Zhou, Xiang Reiner, Alexander P. Raffield, Laura M. Li, Yun Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations |
title | Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations |
title_full | Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations |
title_fullStr | Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations |
title_full_unstemmed | Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations |
title_short | Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations |
title_sort | transcriptome-wide association study of blood cell traits in african ancestry and hispanic/latino populations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8307403/ https://www.ncbi.nlm.nih.gov/pubmed/34356065 http://dx.doi.org/10.3390/genes12071049 |
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