Cross Platform Blood Transcriptomics Identifies a Two-gene Classifier for Coronary Artery Disease Detection
Year: 2026
Type: article
Abstract: Aim: Coronary artery disease (CAD) remains a major global health burden, and currently available blood biomarkers lack sensitivity for early detection.This study aimed to identify and validate circulating mRNA and long non-coding RNA (lncRNA) biomarkers of CAD and to develop a predictive transcriptomic model. Materials and Methods:We analyzed plasma RNA-seq data from stable CAD patients and healthy controls (GSE208194) and validated findings in an independent peripheral blood microarray cohort (GSE113079).Differential expression was assessed using a threshold of |log 2 fold-change| ≥1 and false-discovery rate <0.05.Enrichment analysis of gene ontology and Kyoto Encyclopedia of Genes and Genomes pathways was performed.A predictive model was constructed using logistic regression model-penalized logistic regression, with hyperparameters tuned within a nested crossvalidation framework, and evaluated in the independent validation cohort.Results: A total of 182 transcripts (177 mRNAs, 5 lncRNAs) were differentially expressed, with 91% down-regulated in CAD.Enrichment analysis revealed coordinated dysregulation of ribosomal biogenesis, cytoplasmic translation, mitochondrial oxidative phosphorylation, and p53/NF-κB inflammatory pathways.Cross-platform validation confirmed 85 transcripts, indicating a robust expression signature.The predictive model selected two genes, NEUROD2 and RPS27, achieving an external area under the curve of 0.820 in the validation cohort.Conclusion: Blood transcriptomic profiling identifies a reproducible CAD-associated expression signature and supports a concise two-gene classifier reflecting inflammatory and metabolic stress-related pathways.These findings provide a framework for the further development of blood-based transcriptomic assays and warrant validation in larger, diverse populations to define clinical utility in cardiovascular risk assessment.
Source: Namık Kemal Tıp Dergisi
Authors: Bilge Eren YAMASAN, Selçuk KORKMAZ
Institution: Trakya University
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: diamond
OpenAlex ID: W7164916814