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Exploration of ferroptosis-related biomarkers and regulatory mechanisms in two diseases (sarcopenia and idiopathic pulmonary fibrosis) based on transcriptome and machine learning

Year: 2026
Type: article
Abstract: Sarcopenia (SP) and idiopathic pulmonary fibrosis (IPF) are debilitating diseases, but share ferroptosis-related biomarkers and their regulatory mechanisms in both remain unclear, hindering targeted research and therapy. In this study, ferroptosis-related genes (FeRGs), as well as training sets and test sets related to SP and IPF, were obtained from public databases. After the identification of disease-related differentially expressed genes (DEGs), DEGs shared by SP and IPF were obtained through intersection (genes with consistent DEG change trends across each disease) and union analyses. These shared DEGs were then intersected with FeRGs to obtain candidate genes. Machine learning algorithms and the Wilcoxon rank-sum test were used to confirm the biomarkers, and nomograms were constructed and evaluated. Meanwhile, in-depth studies such as functional enrichment, immune infiltration, drug prediction, and molecular docking were conducted on the biomarkers. Initially, a total of 26 candidate genes were identified. After screening, DDIT4 and MGST1 were identified as ferroptosis-related biomarkers shared by the two diseases, and both were significantly upregulated in the SP and IPF groups. The area under the curve values of the constructed nomograms were 0.91 (for SP) and 0.79 (for IPF), respectively. The p -values of the Hosmer-Lemeshow test for the calibration curves (0.856 and 0.205) were both >0.05, and the DCA showed good performance. The two biomarkers showed differences in enriched pathways. A total of 5 differential immune cells shared by the two diseases were identified, and the biomarkers participated in immune regulation by targeting specific immune cells. Good binding activity (Vina Score < −5.0) was observed between Trichostatin A and both biomarkers. DDIT4 and MGST1 were shared ferroptosis-related biomarkers for SP and IPF. Nomograms enabled reliable prediction, and trichostatin A was a potential targeted drug. These findings supported mechanistic research and targeted therapy for both diseases. • First identification of cross-disease shared biomarkers: Through bioinformatics and machine learning, DDIT4 and MGST1 were identified for the first time as shared ferroptosis-related biomarkers in both sarcopenia (SP) and idiopathic pulmonary fibrosis (IPF), with both significantly upregulated in the two diseases. • Construction of high-precision predictive models: The nomogram models based on these two genes demonstrated excellent predictive ability for SP and IPF (AUC of 0.91 and 0.79, respectively), providing novel molecular tools for early auxiliary diagnosis of both conditions. • Elucidation of differential regulatory mechanisms: GSEA revealed that DDIT4 is primarily enriched in protein synthesis and post-transcriptional regulatory pathways, while MGST1 is mainly involved in oxidative stress and inflammatory responses. Both genes drive ferroptosis through distinct yet partially complementary pathways in SP and IPF. • Revelation of shared immune microenvironment characteristics: Five differentially infiltrated immune cells (e.g., MDSC, Treg) were identified as common to both diseases. The biomarkers participate in disease progression by targeting specific immune cells (e.g., MGST1 positively correlated with Treg), unveiling cross-disease immune regulatory patterns. • Identification of a potential cross-disease therapeutic agent: Molecular docking predicted that Trichostatin A exhibits good binding activity with both DDIT4 and MGST1 proteins (Vina Score < -5.0), suggesting its potential as a candidate compound for simultaneously intervening in SP and IPF.
DOI: 10.1016/j.exger.2026.113150
Language: English
Field: Medicine
Open Access status: gold
Estimated APC paid: $3,400
OpenAlex ID: W7156060769
FWCI:
Cites: 50
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