Identification of basement membrane markers in diabetic kidney disease and immune infiltration by using bioinformatics analysis and experimental verification

IF 1.9 4区 生物学 Q4 CELL BIOLOGY IET Systems Biology Pub Date : 2023-09-30 DOI:10.1049/syb2.12078
Rui Shi, Wen-Man Zhao, Li Zhu, Rui-Feng Wang, De-Guang Wang
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Abstract

Diabetic kidney disease (DKD) is the leading cause of chronic kidney disease worldwide. Basement membranes (BMs) are ubiquitous extracellular matrices which are affected in many diseases including DKD. Here, the authors aimed to identify BM-related markers in DKD and explored the immune cell infiltration in this process. The expression profiles of three datasets were downloaded from the Gene Expression Omnibus database. BM-related differentially expression genes (DEGs) were identified and Kyoto encyclopaedia of genes and genomes pathway enrichment analysis were applied to biological functions. Immune cell infiltration and immune function in the kidneys of patients with DKD and healthy controls were evaluated and compared using the ssGSEA algorithm. The association of hub genes and immune cells and immune function were explored. A total of 30 BM-related DEGs were identified. The functional analysis showed that BM-related DEGs were notably associated with basement membrane alterations. Crucially, BM-related hub genes in DKD were finally identified, which were able to distinguish patients with DKD from controls. Moreover, the authors observed that laminin subunit gamma 1(LAMC1) expression was significantly high in HK2 cells treated with high glucose. Immunohistochemistry results showed that, compared with those in db/m mouse kidneys, the levels of LAMC1 in db/db mouse kidneys were significantly increased. The biomarkers genes may prove crucial for DKD treatment as they could be targeted in future DKD treatment protocols.

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应用生物信息学分析和实验验证鉴定糖尿病肾病和免疫浸润的基底膜标志物。
糖尿病肾病(DKD)是全球慢性肾脏疾病的主要病因。基底膜(BM)是普遍存在的细胞外基质,在包括DKD在内的许多疾病中受到影响。在这里,作者旨在鉴定DKD中的BM相关标志物,并探索这一过程中的免疫细胞浸润。从基因表达综合数据库下载三个数据集的表达谱。鉴定BM相关差异表达基因(DEGs),并将京都基因百科全书和基因组途径富集分析应用于生物学功能。使用ssGSEA算法评估和比较DKD患者和健康对照的肾脏中的免疫细胞浸润和免疫功能。探讨了中枢基因与免疫细胞及免疫功能的关系。共鉴定出30个BM相关DEG。功能分析表明,BM相关的DEG与基底膜改变显著相关。至关重要的是,DKD中的BM相关枢纽基因最终被鉴定出来,能够区分DKD患者和对照组。此外,作者观察到层粘连蛋白亚单位γ1(LAMC1)在用高糖处理的HK2细胞中的表达显著高。免疫组织化学结果显示,与db/m小鼠肾脏相比,db/db小鼠肾脏中LAMC1的水平显著升高。生物标志物基因可能对DKD治疗至关重要,因为它们可能成为未来DKD治疗方案的靶点。
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来源期刊
IET Systems Biology
IET Systems Biology 生物-数学与计算生物学
CiteScore
4.20
自引率
4.30%
发文量
17
审稿时长
>12 weeks
期刊介绍: IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches. Papers that analyse genomic data in order to identify variables and basic relationships between them are considered if the results provide a basis for mathematical modelling and simulation of cellular dynamics. Manuscripts on molecular and cell biological studies are encouraged if the aim is a systems approach to dynamic interactions within and between cells. The scope includes the following topics: Genomics, transcriptomics, proteomics, metabolomics, cells, tissue and the physiome; molecular and cellular interaction, gene, cell and protein function; networks and pathways; metabolism and cell signalling; dynamics, regulation and control; systems, signals, and information; experimental data analysis; mathematical modelling, simulation and theoretical analysis; biological modelling, simulation, prediction and control; methodologies, databases, tools and algorithms for modelling and simulation; modelling, analysis and control of biological networks; synthetic biology and bioengineering based on systems biology.
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