Evidence map›Paper›PMID 41155038›Full record

ArticleBioengineering (Basel, Switzerland)2025

Integrative Bioinformatics-Guided Analysis of Glomerular Transcriptome Implicates Potential Therapeutic Targets and Pathogenesis Mechanisms in IgA Nephropathy.

Tiange Yang, Mengde Dai, Fen Zhang, Weijie Wen

Abstract read
In one paragraph

Article in Bioengineering (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Tiange YangDepartment of Food Science and Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
Mengde DaiDepartment of Food Science and Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
Fen ZhangDepartment of Food Science and Engineering, College of Life Science and Technology, Jinan University, Guangzhou 510632, China.
Weijie WenGuangdong Institute of Gastroenterology, The Sixth Affiliated Hospital of Sun Yat-sen University, Sun Yat-sen University, Guangzhou 510655, China.

Funding

National Natural Science Foundation of China 32372334National Natural Science Foundation of China 82304144
6 · The paper itself

Abstract

(1) Background: IgA nephropathy (IgAN) is a leading cause of chronic kidney disease worldwide. Despite its prevalence, the molecular mechanisms of IgAN remain poorly understood, partly due to limited research scale. Identifying key genes involved in IgAN's pathogenesis is critical for novel diagnostic and therapeutic strategies. (2) Methods: We identified differentially expressed genes (DEGs) by analyzing public datasets from the Gene Expression Omnibus. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses were performed to elucidate the biological roles of DEGs. Hub genes were screened using weighted gene co-expression network analysis combined with machine learning algorithms. Immune infiltration analysis was conducted to explore associations between hub genes and immune cell profiles. The hub genes were validated using receiver operating characteristic curves and area under the curve. (3) Results: We identified 165 DEGs associated with IgAN and revealed pathways such as IL-17 signaling and complement and coagulation cascades, and biological processes including response to xenobiotic stimuli. Four hub genes were screened: three downregulated (FOSB, SLC19A2, PER1) and one upregulated (SOX17). The AUC values for identifying IgAN in the training and testing set ranged from 0.956 to 0.995. Immune infiltration analysis indicated that hub gene expression correlated with immune cell abundance, suggesting their involvement in IgAN's immune pathogenesis. (4) Conclusion: This study identifies FOSB, SLC19A2, PER1, and SOX17 as novel hub genes with high diagnostic accuracy for IgAN. These genes, linked to immune-related pathways such as IL-17 signaling and complement activation, offer promising targets for diagnostic development and therapeutic intervention, enhancing our understanding of IgAN's molecular and immune mechanisms.

Indexed as

bioinformaticsdisease biomarkerIgA nephropathymachine learning

Identifiers

PMID41155038
PMCPMC12561849

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.