The clinical value of serum long non-coding RNA human leukocyte antigen complex group 11/microRNA-532-3p in the diagnosis and prognosis of patients with acute myocardial infarction undergoing percutaneous coronary intervention

Abstract

Background

Acute myocardial infarction (AMI) is a cardiovascular disease with the highest morbidity and mortality rate in the world. Several studies have suggested that abnormal regulation of non-coding RNAs (ncRNAs) may play a vital role in the occurrence and progress of AMI.

Objective

The purpose of this study was to investigate the clinical values of human leukocyte antigen complex group 11 (HCG11) or miR-532-3p in the diagnosis and prognosis of patients with AMI after percutaneous coronary intervention (PCI).

Methods

The clinical data of 100 AMI patients who underwent PCI were analyzed retrospectively. According to whether major adverse cardiovascular events (MACE) occurred after PCI, they were divided into MACE group (n = 38) and non-MACE group (n = 62). Basic clinical data and serum HCG11 and miR-532-3p levels were analyzed. Multivariate Cox regression analysis was performed to evaluate the risk factors for MACE, and the receiver operator characteristic (ROC) curve was constructed to assess the clinical predictive value of HCG11 and miR-532-3p for MACE.

Results

Compared with the control group, the serum HCG11 level and miR-532-3p in AMI patients were significantly increased or decreased, and the serum levels of HCG11 and miR-532-3p in the MACE group were significantly increased and decreased, compared with those in non-MACE group. Multivariate Cox regression showed that HCG11 and miR-532-3p were risk factors for MACE occurrence. ROC curve investigated that HCG11 combined with miR-532-3p has accurate predictive value for MACE.

Conclusion

This study showed that serum HCG11 and miR-532-3p have certain predictive value for MACE after PCI in patients with AMI.

Highlights

The serum levels of HCG11 and miR-532-3p in patients with AMI were significantly higher and lower than those in control group, respectively.

Compared with the MACE group, the levels of HCG11 and miR-532-3p in the non-MACE group showed an increasing and decreasing trend.

Multivariate regression analysis showed that high expression of HCG11 and low expression of miR-532-3p were risk factors for MACE.

Introduction

Acute myocardial infarction (AMI) refers to the closure of a coronary artery, in which blood flow is interrupted, resulting in partial myocardial necrosis due to severe and persistent ischemia [1]. Despite advances in medical technology and increased health awareness and protection, AMI remains a life-threatening emergency. Although remarkable progress has been made in new technologies, strategies and instruments such as percutaneous coronary intervention (PCI), coronary artery bypass grafting (CABG) and other drug treatments or revascularization, they can only save ischemic myocardium, but cannot promote the regeneration or repair of necrotic myocardium [2]. Therefore, after treatment, most patients still die from ventricular remodeling and heart failure. Presently, PCI is the first choice of treatment for patients with AMI [3]. However, after PCI, complications such as recurrent angina pectoris, revascularization operation, heart failure and severe arrhythmia may still occur. Looking for indicators that can predict the poor prognosis of patients with AMI after PCI will help to take preventive measures in advance and improve the prognosis of patients.

Long non-coding RNA (lncRNA) is a kind of RNA molecules with a length of more than 200 nucleotides, and it does not have protein coding ability [4]. At present, thousands of lncRNAs have been found in different species, which play a role in controlling gene expression and the growth and differentiation of other cells. Human leukocyte antigen complex group 11 (HCG11) has a wide range of biological functions, and plays a vital role in regulating the proliferation of vascular endothelial cells (VECs) and tumor cells [5, 6]. Some studies displayed that lncRNA HCG11 is highly expressed in unstable atherosclerotic plaques, and the increase of unstable and vulnerable plaques will aggravate the development of atherosclerosis [7]. Another study reported that HCG11 was enriched in the carotid artery stenosis cohort, and independently predicted the occurrence of cerebral ischemic events [8]. Given this evidence, this study evaluated the expression of HCG11 in patients with AMI. In terms of mechanism, it is usually reported that lncRNA, as competitive endogenous RNAs, absorbs microRNAs (miRNAs) through molecular sponge, thus exerting its regulatory role [9]. MiRNAs are short non-coding RNAs, with a length of 19–25 nucleotides, most of which are located in introns of protein-coding genes [10]. Circulating miRNAs are stably expressed in mammalian blood, which makes miRNAs an ideal biomarker for disease diagnosis and prognosis. MiR-532-3p, a member of the miR-532 family, is bound up with the occurrence of ovarian cancer and non-small cell lung cancer [11, 12]. Current research revealed that low levels of miR-532-3p are associated with ischemia/reperfusion (I/R) injury [13]. Huang et al. reported a reduction in miR-532-3p content in human vulnerable plaques and Apoe-/-mouse plaques [14]. However, the clinical value of HCG11 and miR-532-3p in AMI is still unclear.

The purpose of this study was to explore the expression levels of HCG11 and miR-532-3p in patients with AMI, and to estimate the predictive value of HCG11 or miR-532-3p or their combination in patients after PCI, so as to find valuable biomarkers for the prognosis assessment of patients with AMI.

Materials and methods

Study subjects and serum samples

From 2020 to 2021, 100 eligible patients with AMI and 98 control subjects without AMI were included continuously. All subjects gave written informed consent in accordance with the Declaration of Helsinki. This study was approved by the Hospital Ethics Committee of the Affiliated Hospital of Gansu Medical College, and the revised edition in 2013 was implemented according to the Helsinki Declaration of 1975. All patients with AMI were diagnosed for the first time and underwent PCI for the first time. (1) Inclusion criteria: the patient’s medical records are complete, including complete clinical data and follow-up data. These patients are all over 18 years old and were diagnosed with AMI for the first time. The diagnosis evidence of AMI can be the detection of cardiac troponin increase, and at least one of the following symptoms: symptoms of acute myocardial ischemia, ischemic electrocardiogram (ECG) changes, and pathological Q-wave development. (2) Exclusion criteria: patients with a history of heart failure, cardiomyopathy, atrial fibrillation, definite malignant tumors and recent surgical history. In addition, 98 medically qualified volunteers with age and gender matching were recruited from the physical examination center of the hospital as the control group. Subjects in the control group were assessed to be free of myocardial ischemic disease by clinical signs and symptoms, laboratory examination, electrocardiogram, and myocardial perfusion imaging. Two tubes of venous blood were collected immediately after admission, one tube was used for the detection of myocardial injury markers, and the other tube was used for serum isolation.

Data collection

Baseline data were collected for all subjects using the hospital information system. Gender, age, body mass index (BMI), history of hypertension and history of diabetes were included. At the same time, perfect blood drawing indexes including total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-C), low density lipoprotein cholesterol (LDL-C), blood glucose, neutrophil-lymphocyte ratio (NLR), creatine kinase isoenzyme (CK-MB) and cardiac troponin I (cTnI) were collected within 24 h of admission. The Global Registry of Active Coronary Event score, or GRACE score, is a score used to assess the risk of major adverse cardiovascular events (MACE) in patients with acute coronary syndromes [15]. GRACE score of each patient was recorded and collated by two physicians who were unaware of the laboratory test results and grouping.

Reverse transcription-quantitative polymerase chain reaction (RT-qPCR)

250µL serum sample was taken, and 750µL Trizol regent (Catalog No.: 15596-026, Invitrogen, USA) was added, mixed, and left for 5 min. Total RNA was extracted with chloroform, isopropyl alcohol and 75% ethanol. The concentration and purity of total RNA were measured by spectrophotometer. The ideal OD260/OD280 value should be between 1.8 and 2.0. Next, according to the instructions of cDNA Synthesis kit (Catalog No.: 11483188001, Sigma, USA), the reverse transcription system was configured to synthesize cDNA. SYBR Green Master Mix (Catalog No.: 4368702, Thermo Fisher Scientific, USA) was used for RT-qPCR analysis. GAPDH and U6 were selected as the reference genes of HCG11 and miR-532-3p. The 2^−∆∆Ct method was applied for the relative expression of HCG11 and miR-532-3p. The sequence of primers needed for the experiment is as follows: HCG11: f: 5′- TAACGACAACGGACAAAGGC-3′, r: 5′- TCTTCCGACAGCAAGGTCTG-3′; miR-532-3p: f: 5’- CGTTTCCAACTGTATG-3’, r: 5’-CAACGGCGGATGGCC-3’; U6: f: 5’-ATGATGGCACTGTACTGGGCC-3’, r: 5’-GATTGGCAGCGATTATACACC-3’; GAPDH: f: 5’-CGGAGCGATCAGAAGACCT-3’, r: 5’-GTTGCTCATAGTACGGGAAC-3’.

Follow-up analysis after PCI

The follow-up time was 1 year after PCI. Establish the communication file of the patients, and conduct bedside follow-up for the inpatient after inquiring the patient’s hospitalization data through the inpatient system; patients discharged from hospital were followed up mainly by outpatient follow-up or telephone follow-up. MACE were recorded during follow-up, including all-cause death, nonfatal myocardial infarction, nonfatal stroke, target vessel and nontarget vessel revascularization. All-cause death included cardiogenic death and non-cardiogenic death. Cardiogenic death included death caused by myocardial infarction, cardiogenic shock and cardiac arrest. Non-cardiac deaths include those caused by pulmonary heart disease, respiratory arrest, and multiple organ dysfunction syndrome. Nonfatal myocardial infarction was defined as hospitalization for cardiogenic chest pain or angina with positive cardiac biomarkers. A non-fatal stroke is defined as a typical neurological deficit that occurs suddenly or rapidly, lasts more than 24 h, and is attributed to a cerebrovascular event. Members of the research team followed up the patients with AMI at 30 days, 3 months, 5 months, 7 months, 9 months and 12 months respectively, and all MACE were examined and verified by the hospital. Patients were classified into MACE (n = 38) and non-MACE (n = 62) groups based on MACE status.

Cell culture and treatment

H9c2 cells were used as tool cells to evaluate the targeted binding of HCG11 and miR-532-3p. The H9c2 cell line was purchased from the cell bank, Chinese Academy of Sciences. The cells were cultured in the DMEM medium containing 10% serum in an incubator containing 5% CO₂, and the fresh medium was replaced every other day. When the cells grew to 80-90%, the passage was carried out in a ratio of 1:2.

Luciferase reporter gene

A dual-luciferase reporting system was used to detect the interaction between HCG11 and miR-532-3p. Appropriate amounts of cells were inoculated into 12-well plates and cultivated overnight. HCG11 wild type (WT) plasmid and HCG11 mutant (MUT) plasmid were constructed according to the targeted binding sequence of miR-532-3p. Based on the Lipofectamine 3000 transfection reagent specification, WT-HCG11 + miR-532-3p mimic, WT-HCG11 + miR-532-3p inhibitor, WT-HCG11 + mimic-NC, and WT-HCG11 + inhibitor-NC were diluted using Opti-MEM, respectively. They were then mixed with Lipofectamine 3000 diluted with Opti-MEM. Add 50µL of the above solution into each well, mix well, and continue to culture in the incubator for 24 h. Finally, dual-luciferase reporter gene assay kit (Promega, USA) was used to detect luciferase activity in each group.

Bioinformatics analysis

The downstream target genes of miR-532-3p were predicted using StarBase, TargetScan and miRWalk databases. StarBase predicted 1853 target genes of miR-532-3p, TargetScan predicted 337 target genes, and miRWalk predicted 14,060 target genes. Subsequently, Venn diagram was drawn by online databases, and target genes in the intersection of three databases were selected for subsequent analysis. The 118 target genes in the intersection were imported into the Bioinformatics online website for further analysis. Gene Ontology (GO) functional annotation includes three parts: cell components (CC), biological process (BP), and molecular functions (MF). The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed on target genes, and the signal pathways with significant differences were found.

Data analysis

Data analysis was carried out using SPSS 22.0 software. The normality of the data was evaluated with Kolmogorov-Smirnov test. Data that conform to normal distribution are expressed as mean ± standard deviation (SD). Independent sample t test was used for comparison between the two groups, and one-way analysis of variance (ANOVA) was used for comparison of multiple groups. Logistic regression analysis was used to evaluate the possible risk factors for AMI. Pearson method was used to evaluate the correlation between serum HCG11 and miR-532-3p level in patients with AMI. The predictive value of serum HCG11 and miR-532-3p was evaluated by receiver operating characteristic (ROC) curve. Multivariate Cox regression analysis was used to analyze the independent factors affecting the occurrence of MACE in patients with AMI after PCI. P < 0.05 were considered to be statistically significant.

Results

Comparison of baseline data between AMI group and control group

The basic information, clinical indicators and medication information of patients with AMI and control populations are summarized in Table 1. There were no statistically significant differences in age, sex, and body mass index (BMI) between the two groups (P > 0.05), which indicates that the two groups are matched and comparable. In addition, we observed that hypertension, triglycerides (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), glucose levels upon admission (GLU) and neutrophil-lymphocyte ratio (NLR) in the AMI group were significantly higher than those in the control group (P < 0.05). Additionally, significantly increased CK-MB and cTnI levels were observed in the AMI group, indicating myocardial injury.

Table 1 Comparison of clinical basic data of subjects

Verification of the expression level and interaction relationship between HCG11 and miR-532-3p

Through the detection of serum samples of all subjects, RT-qPCR results showed that compared with the control group, the expression level of HCG11 in AMI group was significantly higher, while the expression level of miR-532-3p was significantly lower (Fig. 1A-B, P < 0.001). Pearson correlation coefficient method was used to evaluate the correlation between miR-532-3p and HCG11. The results showed that the expression level of serum miR-532-3p was negatively correlated with the expression of HCG11, and the r value was − 0.8269 (Fig. 1C, P < 0.001). Subsequently, miR-532-3p targeting HCG11 was predicted with ENCORI database. Furthermore, luciferase reports were carried out to verify the targeting relationship between miR-532-3p and HCG11. The results showed that transfection with miR-532-3p mimics decreased luciferase activity in WT group, while transfection with miR-532-3p inhibitors increased the luciferase activity. The above situation was not observed in the MUT group, suggesting that miR-532-3p has the function of targeting HCG11-3’-UTR and regulating its expression (Fig. 1D, P < 0.001).

Fig. 1

Expression of HCG11 and miR-532-3p and verification of their targeting relationship. A. qRT-PCR detected that the expression level of HCG11 was increased in patients with AMI. B. The expression level of miR-532-3p was significantly decreased in AMI group. C. Pearson correlation coefficient analysis showed that the expression level of miR-532-3p was negatively correlated with HCG11. D. The ENCORI (StarbaseV2.0) database showed the targeting sites of HCG11 and miR-532-3p, and the targeting relationship between them was verified by luciferase reporter gene. ^***P < 0.001 versus control group

Diagnostic value analysis of HCG11/miR-532-5p for AMI occurrence

Logistic regression analysis was used to investigate the effect of each index on the occurrence of AMI. As shown in Table 2, HCG11 (OR = 6.881, 95% CI = 3.415–13.865, P < 0.001) and miR-532-3p (OR = 0.377, 95% CI = 0.188–0.753, P = 0.006) were significantly correlated with the occurrence of AMI.

Table 2 Impact of factors on the occurrence of AMI

Relationship between HCG11, mir-532-3p and the occurrence of MACE after PCI in patients with AMI

Patients with AMI treated with PCI were followed up for one year, and according to the occurrence of MACE, the patients were divided into non-MACE group and MACE group. In the poor prognosis group, 38 patients developed MACE, and in the good prognosis group, 62 patients did not. After analyzing the gene expression levels of the two groups, it was found that compared with the group with good prognosis, the serum level of HCG11 in the poor prognosis group was significantly increased, while the level of miR-532-3p was decreased (Fig. 2A-B, P < 0.001). The comparison of baseline data between the two groups was shown in Table 3. It was observed that the cases of hypertension and diabetes in the poor prognosis group was higher than those in the good prognosis group (P < 0.05). Compared with good prognosis group, the levels of TG, GLU, NLR and Grace score were enhanced in the poor prognosis group (P < 0.01). In addition, differences in HDL-C between the two groups were also observed, with the level of HDL-C in the poor prognosis group being lower than that in the good prognosis group (P < 0.05).

Fig. 2

The expression difference of HCG11 and miR-532-3p in different prognostic groups of AMI patients after PCI. A. The expression of HCG11 was increased in the poor prognosis group. B. miR-532-3p was significantly down-regulated in the group with poor prognosis. ^***P < 0.001 versus control group

Table 3 Comparison of baseline data between the two groups

Further, to investigate the prognostic factors of AMI patients after PCI, multivariate Cox regression was performed. The results showed that HCG11 (HR = 5.972, 95%CI = 2.045–17.439) and miR-532-3p (HR = 0.335, 95%CI = 0.157–0.714) were identified as risk factors for the occurrence of MACE after PCI (Fig. 3A-B, P < 0.05).

Fig. 3

Analysis and evaluation of prognostic factors. A. Forest plot of multivariate Cox regression analysis. B. Multivariate Cox regression analysis was used to assess the risk factors affecting prognosis. ROC curves for the prediction of 1-year MACE. C. Serum HCG11 levels were used to construct the ROC curve. D. Serum miR-532-3p levels were used to construct the ROC curve. E. Combined ROC curves of serum HCG11 and miR-532-3p

Prognostic value analysis of HCG11/miR-532-3p for MACE of AMI patients after PCI

Subsequently, ROC curves were constructed to evaluate the prognostic value of HCG11 and miR-532-3p in patients with AMI. Figure 3C showed that HCG11 was used as a predictor to predict the occurrence of poor prognosis. The AUC value of this curve was 0.896, and the sensitivity and specificity are 81.6% and 88.7%, respectively. In Fig. 3D, the AUC value of the miR-532-3p curve was 0.858, with the sensitivity of 86.8% and specificity of 77.4%. Figure 3E revealed the combined diagnostic curve of HCG11 and miR-532-3p. The AUC value of the curve was 0.958, and the sensitivity and specificity were 84.2% and 95.2%, respectively. All the above three ROC curves show the accurate diagnostic value of poor prognosis. However, from the AUC values of the three curves, HCG11 combined with miR-532-3p showed the best diagnostic value for poor prognosis.

Bioinformatics analysis of mir-532-5p target gene

A Venn diagram was performed to draw the target genes predicted by StarBase, TargetScan and miRWalk, and there were 118 target genes at the intersection of the three databases (see Fig. 4A; Table 4). GO enrichment analysis of target genes was conducted from the perspectives of biological processes (BP), cellular components (CC) and molecular functions (MF). The results showed that these target genes are involved in the regulation of many biological processes, such as the positive regulation of cell catabolism, the regulation of mRNA metabolism and the signal transduction of Ras protein. As far as cell components are concerned, these target genes are enriched in ribonucleoprotein granule, nuclear spots and cytoplasmic ribonucleoprotein granule. In addition, the main molecular functions of these target genes are to regulate nuclear input signal receptor activity, nucleocytoplasmic carrier activity, RNA polymerase activity, adrenergic receptor binding and protein phosphatase activator activity (see Fig. 4B-D). KEGG pathway analysis showed that the target genes of miR-532-3p were mainly enriched in the PI3K-Akt signaling pathway and Ras signaling pathway, as well as in the pathways of cytoplasmic transport and endocytosis (see Fig. 4E).

Fig. 4

Bioinformatics analysis of miR-532-5p target genes. A. Venn diagram was constructed for all target genes predicted by StarBase, TargetScan, and miRWalk databases. B. Module on biological processes in Gene Ontology [18] analysis. C. Module on cellular component in GO analysis. D. Module on molecular function in GO analysis. E. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis

Table 4 Venn diagram-the name of the mir-532-3p target gene in the intersection of three databases

Discussion

In the present study, the abnormal expression profile of HCG11 and miR-532-3p was determined after AMI. Further, through logistic regression analysis, it was preliminarily concluded that the risk factors for AMI included HCG11 and miR-532-3p. Within one year after PCI, 38 patients developed MACE, while the remaining 62 patients did not. Multivariate Cox regression analysis proved that HCG11 and miR-532-3p were independent prognostic factors for MACE after PCI. Besides, the key biological processes and signal pathways involved in miR-532-3p were identified and analyzed through GO and KEGG pathway enrichment analysis.

PCI is the most effective method to protect the vitality of ischemic myocardium and limit the infarct size. Although early treatment can provide patients with a good chance of prognosis, a large number of patients will still have MACE after PCI. In this study, through the analysis of the clinical data, the proportion of patients with hypertension or diabetes in the MACE group was significantly higher than that in the non-MACE group. At the same time, there were significant differences in TG, HDL-C, GLU, NLR and GRACE score between the MACE group and the non-MACE group. Studies have found that AMI patients with a history of diabetes have a higher probability of MACE after PCI, which is the result of the combined action of lipid-energy metabolism, oxidative stress and insulin resistance-based inflammatory response [16]. Elevated blood pressure on admission is also a risk factor for poor prognosis of AMI. As shown by Kosaoka et al., hypertension can cause vascular endothelium damage, promote platelet aggregation and release of vasoactive substances, thereby aggravating the degree of vascular stenosis [17]. Therefore, it is more difficult for AMI patients with underlying diseases to perform PCI and more likely to have postoperative complications such as MACE. The GRACE score of the poor prognosis group was significantly higher than that of the good prognosis group. The developers of GRACE and some later researchers tested the score through statistical models, and proved that this score has good predictive value for the short-term and long-term prognosis of patients with AMI [18, 19]. In addition, in the multivariate regression analysis of this study, these mentioned factors are not risk factors for MACE, which may be related to the small sample size.

Recent studies showed that lncRNAs are important regulators of atherosclerosis and play a crucial role in the occurrence and development of AS. In order to gain a more comprehensive understanding of the role of lncRNAs in AMI and to provide a new direction for the development of novel biomarkers for disease prognosis, we conducted this study. Early studies found that in patients with acute STEMI, lncRNA LIPCAR increased significantly within 4 h after the onset of symptoms, and in patients with AMI, lncRNA MIAT is significantly elevated within 3 h after the onset of ischemic symptoms [20, 21]. Therefore, abnormal expression of lncRNA may be of great significance in AMI. This study found that the increased expression of HCG11 in serum samples after the onset of AMI is one of the risk factors for the occurrence of AMI. The role of HCG11 in human cancer has been reported many times in past studies. For example, Liu et al. found that HCG11 expression increased in breast cancer, which influenced the prognosis of patients [22]. Xu et al. reported that HCG11 level was upregulated in liver cancer and promoted cancer progression by activating the MAPK signal pathway [23]. Recently, HCG11 has been found to play a key role in cerebral ischemia reperfusion (CI/R) injury by downregulating p53 expression through competitive binding to miR-381-5p, thereby promoting CI/R injury [24]. In addition, the results of this study showed that the expression of serum miR-532-3p in the MACE group showed a downward trend compared with that in the non-MACE group. The cardioprotective effect of miR-532-3p in cardiovascular disease has been widely reported. Liu et al. demonstrated that the overexpression of miR-532-3p can alleviate the apoptosis of HCAECs and promote cell proliferation by inhibiting MAPK1 in coronary heart disease (CHD) [25]. Further luciferase reporter gene assay showed that HCG11 could target miR-532-3p and negatively regulate the expression of miR-532-3p.

Furthermore, target gene prediction, GO functional enrichment analysis and KEGG pathway enrichment analysis of miR-532-3p were carried out through bioinformatics analysis. The results showed that the intersection target genes of miR-532-3p predicted by TargetScan, Starbase and miRWalk databases were mainly enriched in ribonucleoprotein particles, which were mainly involved in the positive regulation of cellular catabolism and other biological processes. These target genes are enriched in the PI3K-Akt signaling pathway and Ras signaling pathway. The relationship between these signaling pathways and AMI or atherosclerosis has been mentioned in many studies. Zhang et al. reported that inhibiting the activity of PI3K-Akt signal pathway can reduce myocardial fibrosis after AMI [26]. Wang et al. proved that activation of the Ras signaling pathway can promote the progress of atherosclerosis [27]. Therefore, PI3K-Akt and Ras signal pathway are the most important approaches for future mechanism research.

However, there are some limitations in this study, as follows: (1) This study is a retrospective study with a small sample size, which may lead to bias in the analysis process. (2) We only measured the indicators at admission, that is, in the acute phase, and did not follow up to verify whether these indicators changed over a longer period after PCI. (3) AMI patients, such as STEMI and NSTEMI, were not classified in this paper. (4) There may be other indicators not included in the study that are also risk factors for MACE after PCI. Therefore, in future studies, we not only need to conduct multi-center, large-sample studies to prove the current experimental results, but also need to include more research indicators to analyze the risk factors affecting MACE as comprehensively as possible, so as to make the research results more accurate.

Combined with the results of previous studies and current studies, we believe that HCG11 and miR-532-3p may be a simple and practical tool to evaluate the prognosis of AMI patients within 1 year after PCI, which can provide some help for clinicians’ decision making. Of course, studies on HCG11 and miR-532-3p are still limited to small samples and single-center studies, and whether they can continue to be extended to patients with all types of myocardial infarction is still unclear, and more large-scale experiments are still needed to be verified. In a word, in this study, we confirmed that HCG11 and miR-532-3p are risk factors for MACE in patients with AMI after PCI within 1 year. The combined prediction of MACE by HCG11 and miR-532-3p was more accurate than that by separate determination.