Abstract
Whether ST-segment (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) should be regarded as distinct pathophysiological entities is a matter of debate. We tested the hypothesis that peripheral blood gene-expression profiles at presentation distinguish STEMI from NSTEMI. We performed a case-control study collecting whole-blood from 60 STEMI and 58 NSTEMI (defined according to the third universal definition of MI) consecutive patients on hospital admission. We used RNA-sequencing for the discovery phase, comparing 15 STEMI vs. 15 NSTEMI patients, matched for age, sex, and cardiovascular risk factors, and quantitative PCR in the remaining unmatched patients for validating top-significant genes. Gene-level differential expression analysis identified significant differences in the expression of 323 genes: 153 genes withstood correction for admission cardiac troponin I (cTnI), differentiating the two conditions independently of myocardial necrosis extent. Functional annotation analysis uncovered divergent modulation in leukocyte and platelet activation, cell migration, and mitochondrial respiratory processes. Linear regression analysis revealed gene expression patterns on admission predicting infarct size, as indexed by cTnI peak (R2 = 0.58–0.75). Our results unveil distinctive pathological traits for these two MI subtypes and provide insights into the early assessment of injury extent. This could translate into RNA-based disease-specific biomarkers for precision diagnosis and risk stratification.
Highlights
Whether ST-segment (STEMI) and non-ST-segment elevation myocardial infarction (NSTEMI) should be regarded as distinct pathophysiological entities is a matter of debate
Patients selected for the exploratory phase (n = 30; STEMI n = 15 vs. NSTEMI n = 15) had no history of previous Acute myocardial infarction (AMI) or stroke and no incident diabetes or chronic kidney disease (CKD)
STEMI and NSTEMI patients had no substantial differences in blood tests, body mass index, major medications on admission, time-to-presentation after symptom onset, and left ventricular ejection fraction (LVEF)
Summary
An expanded Methods section is available in the Supplementary Information file. Study design. In the RNA-Seq discovery analysis, comparing 15 vs 15 patients allowed achieving a statistical power of 99% to detect differences among the means ≥2.0 (effect size), with a biological coefficient of variation (BCV) = 0.2 (estimated from sequencing data obtained in preliminary experiments), a sequencing depth = 20 reads (corresponding to low expression levels), and a significance level α = 10−4. Normalization procedures are crucial in RNA-Seq data analysis since they deeply affect the number and effect size of differentially expressed (DE) genes detected. We deemed genes as significantly different at a false discovery rate (FDR)-adjusted P-value < 0.05 Analyses were performed both without and with correction for cTnI levels at presentation, assuming that transcriptional responses and expression levels are influenced both by disease-specific phenotypes and the entity of the cardiac damage after AMI. We assessed the correlation between RT-qPCR average normalized expression values (ΔCq) and RNA-Seq mean normalized counts (in log[2] scale), by computing the Pearson’s correlation coefficient (r), the coefficient of determination (R2), and the significance P-value
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