Abstract
Specific and sensitive diagnostic biomarkers for unstable angina (UA) are currently scarce. The diagnosis of UA usually relies on medical history and physician experience. This study aimed to analyze the expression profiles of microRNAs (miRNAs) in the serum extracellular vesicles (EVs) of UA patients, thus identifying potential diagnostic biomarkers of UA. This study is a prospective study and participants were recruited randomly. A total of 142 patients with UA, 8 with non-ST-elevation myocardial infarction (NSTEMI), and 8 with stable angina (SA) at Nanjing Hospital of Traditional Chinese Medicine Affiliated with Nanjing University of Chinese Medicine from January 2019 to February 2022 were recruited. Fifty-eight healthy volunteers (HVs) were recruited to the control group during the same period. Differentially expressed miRNAs in serum exosomes of UA patients were first identified by high-throughput sequencing, followed by verification via quantitative reverse transcription polymerase chain reaction (qRT-PCR), and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Our findings aim to explore their diagnostic potentials in UA, and their biological functions, as well as the correlation between conventional biochemical indexes of UA. MiR-127, miR-150, and miR-145 were differentially expressed miRNAs in the serum EVs of 8 UA patients, 8 NSTEMI patients, 8 SA patients, and 8 HVs by high-throughput sequencing, which were downregulated in UA patients versus HVs. Moreover, the relative levels of differentially expressed miRNAs in the serum EVs of the remaining UA patients and HVs were measured by qRT-PCR. The area under the curve of miR-127, miR-150, and miR-145 in distinguishing UA patients from HVs was 0.872, 0.856, and 0.803, respectively. Notably, the area under the curve of the combination of the three differentially expressed miRNAs for diagnosing UA was 0.944. A GO analysis revealed that miR-127, miR-150, and miR-145 were mainly enriched in cell adhesion and migration, whereas KEGG pathway enrichment analysis showed that they were enriched in the PI3K-Akt, MAPK, and Hippo signaling pathways. Multivariable logistic regression analysis identified cardiac troponin I (cTnI) (P=0.0006), miR-127 (P=0.0001), miR-150 (P=0.0004), and miR-145 (P=0.0005) as independent risk factors for UA. Spearman's rank correlation test showed a significant correlation between cTnI and miR-127 (r=0.1988, P=0.0067). MiR-127, miR-150, and miR-145 in serum EVs are closely linked with UA and serve as novel diagnostic biomarkers.
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