电池类型
细胞
生物
疾病
孟德尔遗传
基因
遗传学
计算生物学
单细胞分析
基因表达
表型
细胞生物学
医学
病理
作者
Idan Hekselman,Assaf Vital,Maya Ziv-Agam,Lior Kerber,Ido Yairi,Esti Yeger‐Lotem
出处
期刊:eLife
[eLife Sciences Publications, Ltd.]
日期:2024-01-10
卷期号:13
被引量:2
摘要
Mendelian diseases tend to manifest clinically in certain tissues, yet their affected cell types typically remain elusive. Single-cell expression studies showed that overexpression of disease-associated genes may point to the affected cell types. Here, we developed a method that infers disease-affected cell types from the preferential expression of disease-associated genes in cell types (PrEDiCT). We applied PrEDiCT to single-cell expression data of six human tissues, to infer the cell types affected in Mendelian diseases. Overall, we inferred the likely affected cell types for 328 diseases. We corroborated our findings by literature text-mining, expert validation, and recapitulation in mouse corresponding tissues. Based on these findings, we explored characteristics of disease-affected cell types, showed that diseases manifesting in multiple tissues tend to affect similar cell types, and highlighted cases where gene functions could be used to refine inference. Together, these findings expand the molecular understanding of disease mechanisms and cellular vulnerability.
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