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Accuracy of triggering receptor expressed on myeloid cells 1 in diagnosis and prognosis of acute myocardial infarction: a prospective cohort study.


ABSTRACT:

Background

Acute myocardial infarction (AMI) is one of the fatal cardiac emergencies. The detection of triggering receptor expressed on myeloid cells 1 (TREM1), a cell surface immunoglobulin that amplifies pro-inflammatory responses, screened by bioinformatics was shown to be significant in diagnosing and predicting the prognosis of AMI.

Methods

GSE66360, GSE61144 and GSE60993 were downloaded from the Gene Expression Omnibus (GEO) database to explore the differentially expressed genes (DEGs) between AMI and control groups using R software. A total of 147 patients in total were prospectively enrolled from October 2018 to June 2019 and divided into two groups, the normal group (n = 35) and the AMI group (n = 112). Plasma was collected from each patient at admission and all patients received 6-month follow-up care.

Results

According to bioinformatic analysis, TREM1 was an important DEG in patients with AMI. Compared with the normal group, TREM1 expression was markedly increased in the AMI group (p < 0.001). TREM1 expression was positively correlated with fasting plasma glucose (FPG), glycosylated hemoglobin (HbAC), and the number of lesion vessels, although it had no correlation with Gensini score. TREM1 expression in the triple-vessels group was significantly higher than that of the single-vessel group (p < 0.05). Multiple linear regression showed that UA and HbAC were two factors influencing TREM1 expression. The ROC curve showed that TREM1 had a diagnostic significance in AMI (p < 0.001), especially in AMI patients without diabetes. Cox regression showed increased TREM1 expression was closely associated with 6-month major adverse cardiac events (MACEs) (p < 0.001).

Conclusions

TREM1 is a potentially significant biomarker for the diagnosis of AMI and may be closely associated with the severity of coronary lesions and diabetes. TREM1 may also be helpful in predicting the 6-month MACEs after AMI.

SUBMITTER: Ji Z 

PROVIDER: S-EPMC8231339 | biostudies-literature |

REPOSITORIES: biostudies-literature

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