多尺度数据整合解码慢性肾病风险基因。

IF 2.2 4区 医学 Q2 UROLOGY & NEPHROLOGY BMC Nephrology Pub Date : 2024-10-18 DOI:10.1186/s12882-024-03798-2
Shiqi Ding, Jing Guo, Huimei Chen, Enrico Petretto
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引用次数: 0

摘要

背景:慢性肾脏病(CKD)影响着全球10%以上的人口,最近高通量分析技术的进步正在揭示这种疾病背后复杂的生理学。通过整合全基因组关联研究(GWAS)、RNA测序(RNA-seq/RNA阵列)和单细胞RNA测序(scRNA-seq)数据,我们的研究旨在探索与CKD特征相关的基因和细胞类型:从 GWAS 目录和英国生物库(UKB)数据库中获取了终末期肾衰竭(ESRD)和 eGFR 下降(CKD)伴或不伴糖尿病和(微)蛋白尿的 GWAS 总结数据。两个基因表达总库(GEO)转录组数据集用于确定 CKD 患者与健康人之间的肾小球和肾小管基因表达差异。两个 scRNA-seq 数据集用于获取单细胞水平的关键基因表达。对这些 CKD 风险基因的表达谱、差异表达基因(DEGs)、基因-基因相互作用和通路富集进行了分析:结果:在不同的 CKD 性状中,GWAS 共鉴定出 779 个不同的 SNPs,涉及 681 个基因。虽然这些风险基因中有许多是肾功能衰竭、eGFR下降和(微)蛋白尿等CKD特质所特有的,但它们有共同的通路,包括细胞外基质(ECM)。与健康对照组相比,CKD 肾脏的肾小球和肾小管 DEGs 上调富集了 ECM 模型,成纤维细胞/肌成纤维细胞中普遍表达 COL1A2 等相关胶原基因。此外,包括 T 细胞分化在内的免疫反应在 CKD 肾脏中也出现失调。晚期荚膜细胞特征基因 THSD7A 在荚膜细胞中富集,但在 CKD 中下调。我们还强调,受调控的 CKD 风险基因主要在肾小管细胞和免疫细胞中表达:我们的综合分析强调了与肾脏特质的发病机制相关的基因、通路和相关细胞类型,为进一步从机理上研究了解 CKD 的发病机制奠定了基础。
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Multi-scalar data integration decoding risk genes for chronic kidney disease.

Background: Chronic Kidney Disease (CKD) impacts over 10% of the global population, and recent advancements in high-throughput analytical technologies are uncovering the complex physiology underlying this condition. By integrating Genome-Wide Association Studies (GWAS), RNA sequencing (RNA-seq/RNA array), and single-cell RNA sequencing (scRNA-seq) data, our study aimed to explore the genes and cell types relevant to CKD traits.

Methods: GWAS summary data for end-stage renal failure (ESRD) and decreased eGFR (CKD) with or without diabetes and (micro)proteinuria were obtained from the GWAS Catalog and the UK Biobank (UKB) database. Two gene Expression Omnibus (GEO) transcriptome datasets were used to establish glomerular and tubular gene expression differences between CKD patients and healthy individuals. Two scRNA-seq datasets were utilized to obtain the expression of key genes at the single-cell level. The expression profile, differentially expressed genes (DEGs), gene-gene interaction, and pathway enrichment were analysed for these CKD risk genes.

Results: A total of 779 distinct SNPs were identified from GWAS across different CKD traits, involving 681 genes. While many of these risk genes are specific to the CKD traits of renal failure, decreased eGFR, and (micro)proteinuria, they share common pathways, including extracellular matrix (ECM). ECM modeling was enriched in upregulated glomerular and tubular DEGs from CKD kidneys compared to healthy controls, with the expression of relevant collagen genes, such as COL1A2, prevalent in fibroblasts/myofibroblasts. Additionally, immune responses, including T cell differentiation, were dysregulated in CKD kidneys. The late podocyte signature gene THSD7A was enriched in podocytes but downregulated in CKD. We also highlighted that the regulated risk genes of CKD are mainly expressed in tubular cells and immune cells in the kidney.

Conclusions: Our integrated analysis highlight the genes, pathways, and relevant cell types associational with the pathogenesis of kidney traits, as a basis for further mechanistic studies to understand the pathogenesis of CKD.

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来源期刊
BMC Nephrology
BMC Nephrology UROLOGY & NEPHROLOGY-
CiteScore
4.30
自引率
0.00%
发文量
375
审稿时长
3-8 weeks
期刊介绍: BMC Nephrology is an open access journal publishing original peer-reviewed research articles in all aspects of the prevention, diagnosis and management of kidney and associated disorders, as well as related molecular genetics, pathophysiology, and epidemiology.
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