Evidence map›Paper›PMID 41907204›Full record

ArticleJournal of inflammation research2026

Integrated Machine Learning and Multi-Omics Analysis Identifies Mitophagy-Related Core Genes and Mechanisms in Non-Alcoholic Fatty Liver Disease.

Yu Yuan, Tianyu Zhang, Chao Song, Chunli Lin, Yuewen Sun, Hongzhen Tang

Abstract read
In one paragraph

Article in Journal of inflammation research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0cells of the map it votes in
0citing papers in PubMed
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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

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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

6 authors.

Yu Yuan *Department of Acupuncture and Tuina, Guangxi University of Chinese Medicine, Nanning, Guangxi Province, 530000, People's Republic of China.
Tianyu Zhang *Department of Acupuncture and Tuina, Guangxi University of Chinese Medicine, Nanning, Guangxi Province, 530000, People's Republic of China.
Chao SongDepartment of Acupuncture and Tuina, Guangxi University of Chinese Medicine, Nanning, Guangxi Province, 530000, People's Republic of China.
Chunli LinDepartment of Acupuncture and Tuina, Guangxi University of Chinese Medicine, Nanning, Guangxi Province, 530000, People's Republic of China.
Yuewen SunDepartment of Scientific Research, Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning, Guangxi Province, 530000, People's Republic of China.
Hongzhen TangDepartment of Scientific Research, Ruikang Hospital Affiliated to Guangxi University of Chinese Medicine, Nanning, Guangxi Province, 530000, People's Republic of China.ORCID 0009-0004-7419-8483

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to systematically screen for mitophagy-related core genes in Non-alcoholic fatty liver disease (NAFLD), elucidate their specific molecular regulatory network, and investigate their functional mechanisms and roles within the immune microenvironment to provide novel targets for disease diagnosis and therapy. Methods: Multiple NAFLD transcriptomic datasets and single-cell RNA sequencing data from the GEO database were integrated. Bioinformatics analysis, Weighted Gene Co-expression Network Analysis (WGCNA), and 11 machine learning algorithms were employed for core gene screening. Functional mechanisms and immune microenvironment characteristics were further investigated using SHAP model interpretability analysis, including detailed immune infiltration analysis, PPI network construction, GSEA, single-cell trajectory inference, and cell-cell communication analysis. Reverse network pharmacology and molecular docking predicted potential targeted compounds. In vitro experiments (Western Blot, qRT-PCR, JC-1 staining) validated core gene expression and mitophagy levels. Results: Five key genes-IGF1, MYH11, HYOU1, SPATA18, and SCD-were identified, demonstrating excellent disease discrimination across multiple cohorts (training set AUC=0.974). These genes were significantly enriched in processes like endoplasmic reticulum stress, mitophagy, and lipid metabolism. Critically, they played crucial roles in reshaping the NAFLD immune microenvironment, characterized by increased macrophage M2 polarization and T cell infiltration, linking mitochondrial dysfunction to inflammatory response. Single-cell analysis revealed their expression heterogeneity across hepatocytes, macrophages, and T cells, along with their involvement in intercellular communication patterns. Experimental validation confirmed aberrant core gene expression and altered mitophagy levels in NAFLD cell models. Conclusion: This study systematically delineates the regulatory network of mitophagy-related core genes in NAFLD and the resultant inflammatory immune microenvironment, offering novel insights and data support for elucidating disease mechanisms, developing early diagnostic biomarkers, and formulating precise therapeutic strategies.

Indexed as

bioinformaticsmachine learningmitophagynon-alcoholic fatty liver disease

Identifiers

PMID41907204
PMCPMC13032741

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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 OpenQuestion graph.