Polygenic regression uncovers trait-relevant cellular contexts through pathway activation transformation of single-cell RNA sequencing data

Yunlong Ma; Chunyu Deng; Yijun Zhou; Yaru Zhang; Fei Qiu; Dingping Jiang; Gongwei Zheng; Jingjing Li; Jianwei Shuai; Yan Zhang; Jian Yang; Jianzhong Su

doi:10.1016/j.xgen.2023.100383

Polygenic regression uncovers trait-relevant cellular contexts through pathway activation transformation of single-cell RNA sequencing data

Cell Genom. 2023 Aug 18;3(9):100383. doi: 10.1016/j.xgen.2023.100383. eCollection 2023 Sep 13.

Authors

Yunlong Ma^{1

2}, Chunyu Deng³, Yijun Zhou^{1

2}, Yaru Zhang^{1

2}, Fei Qiu¹, Dingping Jiang¹, Gongwei Zheng¹, Jingjing Li¹, Jianwei Shuai², Yan Zhang³, Jian Yang^{4

5}, Jianzhong Su^{1

2}

Affiliations

¹ School of Biomedical Engineering, School of OphthalmoFlogy & Optometry and Eye Hospital, Wenzhou Medical University, Wenzhou, Zhejiang 325027, China.
² Oujiang Laboratory, Zhejiang Lab for Regenerative Medicine, Vision and Brain Health, Wenzhou, Zhejiang 325101, China.
³ School of Life Science and Technology, Harbin Institute of Technology, Harbin, Heilongjiang 150080, China.
⁴ School of Life Sciences, Westlake University, Hangzhou, Zhejiang 310012, China.
⁵ Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang 310024, China.

Abstract

Advances in single-cell RNA sequencing (scRNA-seq) techniques have accelerated functional interpretation of disease-associated variants discovered from genome-wide association studies (GWASs). However, identification of trait-relevant cell populations is often impeded by inherent technical noise and high sparsity in scRNA-seq data. Here, we developed scPagwas, a computational approach that uncovers trait-relevant cellular context by integrating pathway activation transformation of scRNA-seq data and GWAS summary statistics. scPagwas effectively prioritizes trait-relevant genes, which facilitates identification of trait-relevant cell types/populations with high accuracy in extensive simulated and real datasets. Cellular-level association results identified a novel subpopulation of naive CD8⁺ T cells related to COVID-19 severity and oligodendrocyte progenitor cell and microglia subsets with critical pathways by which genetic variants influence Alzheimer's disease. Overall, our approach provides new insights for the discovery of trait-relevant cell types and improves the mechanistic understanding of disease variants from a pathway perspective.

Keywords: GWAS; genetic variants; risk genes; single-cell RNA sequencing; trait-relevant cell types.