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HCNetlas:一个用于辅助疾病遗传分析的人类细胞类型特异性基因网络参考数据库。

HCNetlas: A reference database of human cell type-specific gene networks to aid disease genetic analyses.

作者信息

Yu Jiwon, Cha Junha, Koh Geon, Lee Insuk

机构信息

Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Republic of Korea.

POSTECH Biotech Center, Pohang University of Science and Technology (POSTECH), Pohang, Republic of Korea.

出版信息

PLoS Biol. 2025 Feb 5;23(2):e3002702. doi: 10.1371/journal.pbio.3002702. eCollection 2025 Feb.

DOI:10.1371/journal.pbio.3002702
PMID:39908239
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11798474/
Abstract

Cell type-specific actions of disease genes add a significant layer of complexity to the genetic architecture underlying diseases, obscuring our understanding of disease mechanisms. Single-cell omics have revealed the functional roles of genes at the cellular level, identifying cell types critical for disease progression. Often, a gene impact on disease through its altered network within specific cell types, rather than mere changes in expression levels. To explore the cell type-specific roles of disease genes, we developed HCNetlas (human cell network atlas), a resource cataloging cell type-specific gene networks (CGNs) for various healthy tissue cells. We also devised 3 network analysis methods to investigate cell type-specific functions of disease genes. These methods involve comparing HCNetlas CGNs with those derived from disease-affected tissue samples. These methods find that systemic lupus erythematosus genes predominantly function in myeloid cells, and Alzheimer's disease genes mainly play roles in inhibitory and excitatory neurons. Additionally, they suggest that many lung cancer-related genes may exert their roles in immune cells. These findings suggest that HCNetlas has the potential to link disease-associated genes to cell types of action, facilitating development of cell type-resolved diagnostics and therapeutic strategies for complex human diseases.

摘要

疾病基因的细胞类型特异性作用给疾病潜在的遗传结构增添了显著的复杂性,模糊了我们对疾病机制的理解。单细胞组学揭示了基因在细胞水平上的功能作用,确定了对疾病进展至关重要的细胞类型。通常,基因通过其在特定细胞类型内改变的网络影响疾病,而不仅仅是表达水平的变化。为了探索疾病基因的细胞类型特异性作用,我们开发了HCNetlas(人类细胞网络图谱),这是一个为各种健康组织细胞编目细胞类型特异性基因网络(CGNs)的资源。我们还设计了3种网络分析方法来研究疾病基因的细胞类型特异性功能。这些方法包括将HCNetlas CGNs与来自疾病影响组织样本的CGNs进行比较。这些方法发现,系统性红斑狼疮基因主要在髓细胞中发挥作用,而阿尔茨海默病基因主要在抑制性和兴奋性神经元中起作用。此外,它们表明许多肺癌相关基因可能在免疫细胞中发挥作用。这些发现表明,HCNetlas有潜力将疾病相关基因与作用细胞类型联系起来,促进针对复杂人类疾病的细胞类型解析诊断和治疗策略的开发。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d982/11798474/ddfa66f31ba6/pbio.3002702.g006.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d982/11798474/629dec42e9ad/pbio.3002702.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d982/11798474/7371f2c9ac6e/pbio.3002702.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d982/11798474/98e0c7330b66/pbio.3002702.g003.jpg
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