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Liu W, Deng W, Chen M, Dong Z, Zhu B, Yu Z, Tang D, Sauler M, Lin C, Wain LV, Cho MH, Kaminski N, Zhao H. A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases. PLoS Genet 2023; 19:e1010825. [PMID: 37523391 PMCID: PMC10414598 DOI: 10.1371/journal.pgen.1010825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2022] [Revised: 08/10/2023] [Accepted: 06/12/2023] [Indexed: 08/02/2023] Open
Abstract
Finding disease-relevant tissues and cell types can facilitate the identification and investigation of functional genes and variants. In particular, cell type proportions can serve as potential disease predictive biomarkers. In this manuscript, we introduce a novel statistical framework, cell-type Wide Association Study (cWAS), that integrates genetic data with transcriptomics data to identify cell types whose genetically regulated proportions (GRPs) are disease/trait-associated. On simulated and real GWAS data, cWAS showed good statistical power with newly identified significant GRP associations in disease-associated tissues. More specifically, GRPs of endothelial and myofibroblasts in lung tissue were associated with Idiopathic Pulmonary Fibrosis and Chronic Obstructive Pulmonary Disease, respectively. For breast cancer, the GRP of blood CD8+ T cells was negatively associated with breast cancer (BC) risk as well as survival. Overall, cWAS is a powerful tool to reveal cell types associated with complex diseases mediated by GRPs.
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Affiliation(s)
- Wei Liu
- Program of Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
| | - Wenxuan Deng
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
| | - Ming Chen
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
| | - Zihan Dong
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
| | - Biqing Zhu
- Program of Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
| | - Zhaolong Yu
- Program of Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
| | - Daiwei Tang
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
| | - Maor Sauler
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, Yale University, New Haven, Connecticut, United States of America
| | - Chen Lin
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
| | - Louise V. Wain
- Department of Health Sciences, University of Leicester, Leicester, United Kingdom
- National Institute for Health Research, Leicester Respiratory Biomedical Research Centre, Glenfield Hospital, Leicester, United Kingdom
| | - Michael H. Cho
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
- Pulmonary and Critical Care Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts, United States of America
| | - Naftali Kaminski
- Pulmonary, Critical Care and Sleep Medicine, Yale School of Medicine, Yale University, New Haven, Connecticut, United States of America
| | - Hongyu Zhao
- Program of Computational Biology and Bioinformatics, Yale University, New Haven, Connecticut, United States of America
- Department of Biostatistics, Yale School of Public Health, Yale University, New Haven, Connecticut, United States of America
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Alter P, Baker JR, Dauletbaev N, Donnelly LE, Pistenmaa C, Schmeck B, Washko G, Vogelmeier CF. Update in Chronic Obstructive Pulmonary Disease 2019. Am J Respir Crit Care Med 2020; 202:348-355. [PMID: 32407642 PMCID: PMC8054880 DOI: 10.1164/rccm.202002-0370up] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- Peter Alter
- Department of Medicine, Pulmonary and Critical Care Medicine, Member of the German Center for Lung Research (DZL)
| | - Jonathan R. Baker
- Airway Disease, National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Nurlan Dauletbaev
- Department of Medicine, Pulmonary and Critical Care Medicine, Member of the German Center for Lung Research (DZL),Department of Pediatrics, Faculty of Medicine, McGill University, Montreal, Quebec, Canada,Faculty of Medicine and Healthcare, al-Farabi Kazakh National University, Almaty, Kazakhstan; and
| | - Louise E. Donnelly
- Airway Disease, National Heart and Lung Institute, Imperial College London, London, United Kingdom
| | - Carrie Pistenmaa
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Bernd Schmeck
- Department of Medicine, Pulmonary and Critical Care Medicine, Member of the German Center for Lung Research (DZL),Institute for Lung Research, Member of the DZL and of the German Center of Infection Research (DZIF), and,Center for Synthetic Microbiology (SYNMIKRO), Philipps University of Marburg, Marburg, Germany
| | - George Washko
- Brigham and Women’s Hospital, Harvard Medical School, Boston, Massachusetts
| | - Claus F. Vogelmeier
- Department of Medicine, Pulmonary and Critical Care Medicine, Member of the German Center for Lung Research (DZL)
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