Evidence map›Paper›PMID 38784225›Full record

ArticleFrontiers in medicine2024

Identification of CFH and FHL2 as biomarkers for idiopathic pulmonary fibrosis.

Xingchen Liu, Meng Yang, Jiayu Li, Hangxu Liu, Yuchao Dong, Jianming Zheng, Yi Huang

Abstract read
In one paragraph

Article in Frontiers in medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Xingchen Liu *Department of Pathology, The First Affiliated Hospital of Naval Medical University, Navy Medical University, Shanghai, China.
Meng Yang *Department of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Navy Medical University, Shanghai, China.
Jiayu Li *Department of Breast and Thyroid Surgery, The First Affiliated Hospital of Naval Medical University, Navy Medical University, Shanghai, China.
Hangxu LiuDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Navy Medical University, Shanghai, China.
Yuchao DongDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Navy Medical University, Shanghai, China.
Jianming ZhengDepartment of Pathology, The First Affiliated Hospital of Naval Medical University, Navy Medical University, Shanghai, China.
Yi HuangDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Naval Medical University, Navy Medical University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Idiopathic pulmonary fibrosis (IPF) is a fatal disease of unknown etiology with a poor prognosis, characterized by a lack of effective diagnostic and therapeutic interventions. The role of immunity in the pathogenesis of IPF is significant, yet remains inadequately understood. This study aimed to identify potential key genes in IPF and their relationship with immune cells by integrated bioinformatics analysis and verify by Methods: Gene microarray data were obtained from the Gene Expression Omnibus (GEO) for differential expression analysis. The differentially expressed genes (DEGs) were identified and subjected to functional enrichment analysis. By utilizing a combination of three machine learning algorithms, specific genes associated with idiopathic pulmonary fibrosis (IPF) were pinpointed. Then their diagnostic significance and potential co-regulators were elucidated. We further analyzed the correlation between key genes and immune infiltrating cells via single-sample gene set enrichment analysis (ssGSEA). Subsequently, a single-cell RNA sequencing data (scRNA-seq) was used to explore which cell types expressed key genes in IPF samples. Finally, a series of Results: A total of 647 DEGs of IPF were identified based on two datasets, including 225 downregulated genes and 422 upregulated genes. They are closely related to biological functions such as cell migration, structural organization, immune cell chemotaxis, and extracellular matrix. CFH and FHL2 were identified as key genes with diagnostic accuracy for IPF by three machine learning algorithms. Analysis using ssGSEA revealed a significant association of both CFH and FHL2 with diverse immune cells, such as B cells and NK cells. Further scRNA-seq analysis indicated CFH and FHL2 were specifically upregulated in human IPF tissues, which was confirmed by Conclusion: In this study, CFH and FHL2 have been identified as novel potential biomarkers for IPF, with potential diagnostic utility in future clinical applications. Subsequent investigations into the functions of these genes in IPF and their interactions with immune cells may enhance comprehension of the disease's pathogenesis and facilitate the identification of therapeutic targets.

Indexed as

biomarkerCFHFHL2IPFmachine-learning strategies

Identifiers

PMID38784225
PMCPMC11111937

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