Cross-Disease Transcriptomic Signatures Shared by NAFLD and MI: Multicohort Machine-Learning Analysis and Exploratory IDI1 Expression Assessment

Int J Mol Sci. 2026 Oct 21;27(20):9390. doi: 10.3390/ijms27209390.

ABSTRACT

The molecular features shared by non-alcoholic fatty liver disease (NAFLD) and myocardial infarction (MI) remain incompletely understood. We analyzed six microarray cohorts from the GEO database to identify shared disease-associated transcriptomic features across independent NAFLD and MI populations. Weighted gene co-expression network analysis, differential expression analysis, and fuzzy c-means clustering across ordered cross-sectional NAFLD groups were used to define candidate genes. LASSO regression, random forest, and SVM-RFE identified consensus computational candidates, which were examined using exploratory classification, receiver operating characteristic curves, calibration curves, decision curve analysis, and SHapley Additive exPlanations. IDI1 was selected for exploratory expression assessment by qPCR in patients with established MI and in a mouse model of acute ischemic myocardial injury. Fifty-three shared candidate genes were identified, and five genes were retained by all three feature-selection methods. Single-gene ROC analyses showed SULF2, GADD45A, LIN7A, and IDI1 within the analyzed case-control datasets. IDI1 expression was higher in patients with MI than in healthy controls (p = 0.004), as well as in mice blood (p = 0.034) and infarcted myocardium (p = 0.0072) following LAD ligation. These findings indicate shared transcriptomic links between NAFLD and MI, supporting an association between IDI1 and myocardial injury.

PMID:42942156 | DOI:10.3390/ijms27209390