دورية أكاديمية

Identifying functional subtypes of IgA nephropathy based on three machine learning algorithms and WGCNA

التفاصيل البيبلوغرافية
العنوان: Identifying functional subtypes of IgA nephropathy based on three machine learning algorithms and WGCNA
المؤلفون: Hongbiao Ren, Wenhua Lv, Zhenwei Shang, Liangshuang Li, Qi Shen, Shuai Li, Zerun Song, Xiangshu Cheng, Xin Meng, Rui Chen, Ruijie Zhang
المصدر: BMC Medical Genomics, Vol 17, Iss 1, Pp 1-16 (2024)
بيانات النشر: BMC, 2024.
سنة النشر: 2024
المجموعة: LCC:Internal medicine
LCC:Genetics
مصطلحات موضوعية: IgA nephropathy, WGCNA, Immune cell infiltration analysis, Viral infection, Bacterial infection, Functional subtypes, Internal medicine, RC31-1245, Genetics, QH426-470
الوصف: Abstract Background IgA nephropathy (IgAN) is one of the most common primary glomerulonephritis, which is a significant cause of renal failure. At present, the classification of IgAN is often limited to pathology, and its molecular mechanism has not been established. Therefore we aim to identify subtypes of IgAN at the molecular level and explore the heterogeneity of subtypes in terms of immune cell infiltration, functional level. Methods Two microarray datasets (GSE116626 and GSE115857) were downloaded from GEO. Differential expression genes (DEGs) for IgAN were screened with limma. Three unsupervised clustering algorithms (hclust, PAM, and ConsensusClusterPlus) were combined to develop a single-sample subtype random forest classifier (SSRC). Functional subtypes of IgAN were defined based on functional analysis and current IgAN findings. Then the correlation between IgAN subtypes and clinical features such as eGFR and proteinuria was evaluated by using Pearson method. Subsequently, subtype heterogeneity was verified by subtype-specific modules identification based on weighted gene co-expression network analysis(WGCNA) and immune cell infiltration analysis based on CIBERSORT algorithm. Results We identified 102 DEGs as marker genes for IgAN and three functional subtypes namely: viral-hormonal, bacterial-immune and mixed type. We screened seventeen genes specific to viral hormonal type (ATF3, JUN and FOS etc.), and seven genes specific to bacterial immune type (LIF, C19orf51 and SLPI etc.). The subtype-specific genes showed significantly high correlation with proteinuria and eGFR. The WGCNA modules were in keeping with functions of the IgAN subtypes where the MEcyan module was specific to the viral-hormonal type and the MElightgreen module was specific to the bacterial-immune type. The results of immune cell infiltration revealed subtype-specific cell heterogeneity which included significant differences in T follicular helper cells, resting NK cells between viral-hormone type and control group; significant differences in eosinophils, monocytes, macrophages, mast cells and other cells between bacterial-immune type and control. Conclusion In this study, we identified three functional subtypes of IgAN for the first time and specific expressed genes for each subtype. Then we constructed a subtype classifier and classify IgAN patients into specific subtypes, which may be benefit for the precise treatment of IgAN patients in future.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1755-8794
Relation: https://doaj.org/toc/1755-8794
DOI: 10.1186/s12920-023-01702-9
URL الوصول: https://doaj.org/article/c83baa51a1244a3cb967df3810dba0e3
رقم الأكسشن: edsdoj.83baa51a1244a3cb967df3810dba0e3
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:17558794
DOI:10.1186/s12920-023-01702-9