category
bioRxiv
date
Mar 1, 2026
slug
status
Published
summary
创新性提出整合GWAS与cWAS的统一分析框架,开发深度加权拟二项式模型解析免疫细胞比例遗传调控机制,首次通过PRS推断遗传调控比例并揭示其与复杂疾病(如1型糖尿病、克罗恩病)的关联。
tags
单细胞测序
type
Post

📄 原文题目

Identifying genetic regulations on immune cell type proportions and their impacts on autoimmune diseases

🔗 原文链接

💡 AI 核心解读

创新性提出整合GWAS与cWAS的统一分析框架,开发深度加权拟二项式模型解析免疫细胞比例遗传调控机制,首次通过PRS推断遗传调控比例并揭示其与复杂疾病(如1型糖尿病、克罗恩病)的关联。

📝 英文原版摘要

Genetic regulation of immune cell composition plays a crucial role in the etiology of complex diseases, yet remains poorly understood. We propose a unified analytical framework that integrates genome-wide association studies (GWAS) of cell type proportions with cell-type-wide association studies (cWAS) to systematically characterize both the genetic regulation of immune cell composition and its downstream effects on disease risk. Using single-cell RNA sequencing data from the OneK1K cohort, we conducted a GWAS of immune cell-type proportions with a depth-weighted quasi-binomial model designed for bounded, overdispersed traits. We identified 47 genome-wide significant loci influencing eight fine-labeled immune cell subtypes. Leveraging these identified genetic effects, we further imputed genetically regulated proportions (GRPs) using polygenic risk score (PRS)-based imputation and assessed their associations with complex diseases through cWAS. We identified five significant cell type-disease associations, including two with type 1 diabetes, two with Crohns disease, and one with ulcerative colitis. Together, our results demonstrate that cell type proportions observed in scRNA-seq can reveal regulatory loci and offer insights into how genetic variations regulate immune cell type proportions to affect disease risk. Although we focused on immune single-cell data, our framework is applicable to other tissues or cellular compositions as scRNA-seq datasets expand.
单细胞转录组学和表面蛋白表达揭示人RPESC-RPE和PSC-RPE中不同的细胞和分子表型ChatSpatial:基于模式约束的智能代理编排,实现可重复和跨平台的空间转录组学
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