Unknown

Dataset Information

0

A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases.


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.

SUBMITTER: Liu W 

PROVIDER: S-EPMC10414598 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

altmetric image

Publications

A statistical framework to identify cell types whose genetically regulated proportions are associated with complex diseases.

Liu Wei W   Deng Wenxuan W   Chen Ming M   Dong Zihan Z   Zhu Biqing B   Yu Zhaolong Z   Tang Daiwei D   Sauler Maor M   Lin Chen C   Wain Louise V LV   Cho Michael H MH   Kaminski Naftali N   Zhao Hongyu H  

PLoS genetics 20230731 7


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 an  ...[more]

Similar Datasets

| S-EPMC3277619 | biostudies-literature
| S-EPMC5106012 | biostudies-literature
2024-03-13 | GSE261205 | GEO
| S-EPMC5094043 | biostudies-literature
| S-EPMC11661334 | biostudies-literature
| S-EPMC3826950 | biostudies-literature
| S-EPMC7660930 | biostudies-literature
| S-EPMC3553935 | biostudies-literature
| S-EPMC6127182 | biostudies-literature
| S-EPMC3621641 | biostudies-literature