Evidence map›Paper›PMID 40496889›Full record

ArticleComputational and structural biotechnology journal2025

Deciphering mitochondrial dysfunction in keratoconus: Insights into ACSL4 from machine learning-based bulk and single-cell transcriptome analyses and experimental validation.

Yuchen Cai, Tianyi Zhou, Xueyao Cai, Wenjun Shi, Hao Sun, Yao Fu

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2025. 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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2 · The registry

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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

6 authors.

Yuchen CaiDepartment of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Tianyi ZhouDepartment of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xueyao CaiDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Wenjun ShiDepartment of Plastic and Reconstructive Surgery, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Hao SunDepartment of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yao FuDepartment of Ophthalmology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Keratoconus (KC) is a prevalent ectatic corneal disease and the leading cause of corneal transplantation globally. Despite evidence of mitochondrial abnormalities in KC, the underlying mechanisms remain unclear. Our aim was to investigate the role of mitochondrial dysfunction in this pathological condition. Based on transcriptomics datasets of KC, mitochondria-related differentially expressed genes (mDEGs) were identified and analyzed for potential functional pathways, protein-protein interaction (PPI), and gene regulatory networks. Hub genes were further screened and validated by multiple machine learning (ML) algorithms, followed by a comprehensive visualization of single-cell atlas and immune landscape. Additionally, bioinformatic results were validated through quantitative PCR, Western blot, and transcriptomics analysis in an in vitro KC model based on matrix stiffness using human stromal keratocytes. In total, 104 mDEGs were identified, enriched in pathways related to oxidative stress, apoptotic mitochondrial changes, ferroptosis, and inflammatory responses. Nine characteristic genes (CYP24A1, ACSL4, ACADL, HELZ2, AMT, DEPTOR, TUBA1A, TYMS, and ACSL5) were selected and validated using multiple ML models. Single cell sequencing data highlighted ACSL4 as the most promising biomarker, primarily expressed in corneal stromal cells (CSCs). Immune infiltration analysis revealed that ACSL4 was positively associated with monocytes and negatively correlated with eosinophils in KC. In cellular experiments, ACSL4 expression was significantly upregulated in response to decreased substrate stiffness, suggesting its critical role in KC development. These findings suggest a mitochondrial-related molecular mechanism implicated in KC pathogenesis. The identified pivotal biomarker ACSL4 provides a novel framework for future mechanistic and therapeutic studies of KC.

Indexed as

ACSL4Corneal stromal cellsKeratoconusMitochondrial dysfunctionSingle cell transcriptome

Identifiers

PMID40496889
PMCPMC12149552

What Socratic holds

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LicenceCC BY-NC-ND
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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.