Integrated Transcriptomic and Machine Learning Analyses Identify KCNN3 and TLR10 as Candidate Cell-Type-Associated Molecules in Idiopathic Membranous Nephropathy

转录组 计算生物学 医学 生物信息学 免疫组织化学 免疫荧光 基因表达 人工智能 机器学习 膜性肾病 肾病 病理 钥匙(锁) 基因签名 生物 基因 肾 候选基因 肾活检 细胞 足细胞 朴素贝叶斯分类器 基因表达谱
作者
Binran Zhao,Fugang Liu,Boji Xie,Shuting Pang,Qiuyan Tan,Shanshan Li,Mingxing Wei,Yian Huang,Yuting Wei,Wenqi Luo,Peng Wang,Jinxia Su,Bijun Li,Rirong Yang,Wei Li
出处
期刊:International Journal of General Medicine [Dove Medical Press]
卷期号:Volume 19: 1-23
标识
DOI:10.2147/ijgm.s633417
摘要

Purpose: Idiopathic membranous nephropathy (IMN) is a common immune-mediated glomerular disease, but the key molecules driving its progression remain unclear. This study integrated bulk RNA sequencing (RNA-seq), machine learning, and single-cell RNA sequencing (scRNA-seq) to screen and preliminarily validate key molecules, providing a basis for subsequent research. Patients and Methods: We analyzed our published urinary bulk RNA-seq data, as well as IMN kidney datasets obtained from the GEO database. Differentially expressed genes were identified and subjected to enrichment analysis. Three machine learning algorithms screened key genes. ScRNA-seq data were used to identify the cell types expressing the key genes and to perform CellChat analysis. Immunohistochemistry validated key gene expression, and immunofluorescence explored their cellular localization. External GEO datasets validated expression differences and diagnostic performance. Results: We identified 94 genes commonly upregulated in both urine and kidney tissues, enriched in transmembrane transport pathways. Two key genes, KCNN3 and TLR10, were identified by machine learning. Single-cell analysis suggested KCNN3 enrichment in podocytes and TLR10 in dendritic cells (DCs), and CellChat analysis predicted potential crosstalk between these cell types through the CXCL12-CXCR4 axis. Immunohistochemistry confirmed their elevated expression in IMN kidneys. Immunofluorescence showed spatial associations of KCNN3 with podocytes and TLR10 with DCs. External validation showed expression trends of KCNN3 and TLR10 were not entirely consistent across datasets, with combined AUCs of 0.705 and 0.748 in two validation sets, showing no significant improvement over single-gene models. Conclusion: KCNN3 and TLR10 may serve as cell type-associated candidate molecules in IMN, warranting further investigation into their functions and underlying mechanisms.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
娃娃哈发布了新的文献求助10
刚刚
1秒前
得鹿梦鱼发布了新的文献求助100
1秒前
1秒前
雅琪发布了新的文献求助10
1秒前
1秒前
葱花完成签到,获得积分20
1秒前
2秒前
2秒前
所所的应助被兮兮采纳,获得10
4秒前
Ava的应助被SUGATATA采纳,获得10
4秒前
4秒前
4秒前
4秒前
yga18完成签到,获得积分10
5秒前
葱花发布了新的文献求助10
5秒前
5秒前
旺仔小馒头完成签到,获得积分20
5秒前
King16发布了新的文献求助10
6秒前
任淮南发布了新的文献求助10
7秒前
璀璨发布了新的文献求助10
7秒前
7秒前
9秒前
9秒前
YYMY2022完成签到,获得积分10
9秒前
My发布了新的文献求助10
10秒前
10秒前
10秒前
英俊的铭的应助被lq采纳,获得10
10秒前
11秒前
包容寒蕾发布了新的文献求助60
11秒前
娃娃哈发布了新的文献求助10
11秒前
12秒前
传奇3的应助被韩沐沐采纳,获得10
12秒前
12秒前
Viper的应助被听话的八宝粥采纳,获得30
13秒前
万能图书馆的应助被任淮南采纳,获得10
13秒前
周铭鉴发布了新的文献求助10
13秒前
丘比特的应助被听话的八宝粥采纳,获得20
13秒前
科學飛龍獸的应助被ash采纳,获得30
13秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Das Matthäusevangelium: Kapitel 1:1–17 1000
IRTSD: Open-Source Data and Toolset for Electromagnetic Transient Analysis of Disturbances and IBR Control Malfunctions in Transmission Systems 1000
Comprehensive Medicinal Chemistry IV (4th Edition) 800
Entre Praga y Madrid : los contactos checoslovaco-españoles (1948-1977) 600
A REVIEW OF THE V-22 DYNAMICS VALIDATION PROGRAM 600
Les Mots du discours 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8120985
求助须知:如何正确求助?哪些是违规求助? 9525521
关于积分的说明 21556884
捐赠科研通 7699529
什么是DOI,文献DOI怎么找? 3415236
关于科研通互助平台的介绍 2541021
邀请新用户注册赠送积分活动 2455486