Home Investigation into miRNA profile in patient groups with and without ST elevation
Article Open Access

Investigation into miRNA profile in patient groups with and without ST elevation

  • Onur Bobusoglu ORCID logo , Senay Balci ORCID logo , Ahmet Gundes ORCID logo , Ahmet Camsari ORCID logo and Lulufer Tamer ORCID logo EMAIL logo
Published/Copyright: March 31, 2023
Download Article (PDF)
Turkish Journal of Biochemistry
From the journal Turkish Journal of Biochemistry Volume 48 Issue 2

Abstract

Objectives

Because acute myocardial infarction (AMI) may occur suddenly and cannot be predicted, it is critical to identify early diagnosis markers. In recent years, in addition to the developing diagnostic methods, other markers that may be related to the diagnosis of AMI are miRNA molecules. The specificity of miRNAs involved in the pathogenesis of atherosclerosis and regulation of cardiac functions has been shown. The present study aimed to investigate the changes in miRNA expression levels in MI patients with ST-elevation (STEMI) and without ST elevation (NSTEMI).

Methods

In this study, 25 patients with STEMI, 25 with NSTEMI, and 20 healthy participants were included. Expression analysis of miRNAs isolated from the plasma of individuals was performed using high-throughput real-time PCR.

Results

Compared with the control group, miR-221-3p and miR-30d-5p were downregulated, while miR-25-3p, miR-92a-3p, miR-34a-5p and miR-150 upregulated in the patient group with NSTEMI; miR-221-3p, miR-25-3p, miR-30d-5p and miR-92a-3p were downregulated while miR-208a-3p was upregulated in patients with STEMI (p>0.05).

Conclusions

In conclusion, miRNAs may be an early biomarker for diagnosing AMI; however, further and larger studies are needed.

Keywords: acute coronary syndrome; coronary artery; high-throughput RT-PCR; microRNA; NSTEMI; STEMI

Introduction

Acute coronary syndrome is the name given to all symptoms that may occur due to acute myocardial ischemia. The acute coronary syndrome arises because of partial or complete obstruction of coronary artery blood flow that arises from atherosclerotic plaque rupture and subsequent thrombosis. In clinical practice, unstable angina pectoris, non-ST elevation myocardial infarction, and ST-elevation myocardial infarction may appear [1].

The aim of acute coronary syndromes is to reduce the morbidity and mortality that may be present with early diagnosis and treatment. However, it continues to be the most critical cause of morbidity and mortality despite the developing diagnosis and treatments worldwide. Coronary heart diseases account for a third of all deaths. In recent years, miRNAs are a molecule thought to be associated with AMI diagnosis and the diagnostic methods used [2, 3]. miRNAs are single-stranded RNAs that do not encode a protein, approximately 18–24 nucleotides in length. Mature miRNAs bind to complete or nearly complete mRNA sequences and inhibit the expression of genes in their target by either inhibiting translation or triggering RNA degradation after transcription [4]. miRNAs are thought to regulate the expression of 30–90% of human genes by binding to target mRNAs [5]. Thus, various diseases may arise, especially cancer, cardiovascular diseases, muscular disorders and neurodegenerative diseases, related to the critical functions of proteins [6].

Since miRNAs have been shown to play a role in the pathogenesis of atherosclerosis and the regulation of cardiac functions, this study aims to determine the expression levels of miRNAs regarding expression changes in patients with STEMI and NSTEMI [7].

Materials and methods

The present study included 25 ST-segment elevations (Male: 20, Female: 5, mean age: 59.9 ± 11.0) and 25 non-ST elevations (Male: 22, Female: 3, mean age: 64.24 ± 11.1) patients that applied to the Department of Cardiology at University Hospital. Twenty completely healthy individuals without any systemic disease were included in the control group (Male: 14, Female: 6, mean age: 49.6 ± 7.3). The present research was approved by the Local Research Ethical Committee (decision date 28.08.2014; no: 2014/203) before conducting this study.

Plasma and RNA isolation

A total of 6–7 mL of peripheral blood samples were collected in 2% EDTA-containing tubes and centrifuged at 4,000 rpm for 15 min. The plasma was then transferred into a clean microcentrifuge tube and centrifuged at 13,000 for five min and then 200 mL of plasma was stored at −80 °C until RNA isolation. Total RNA containing miRNAs was isolated from plasma using the High Pure miRNA Isolation Kit (Roche Diagnostic GmbH, Mannheim, Germany) and stored at −80 °C.

cDNA synthesis reaction

cDNA synthesis of miRNA was performed using miScript Reverse Transcription Kit according to the manufacturer’s instructions (Qiagen, USA). Total RNA samples were thawed on ice cDNA master mix was prepared for 70 samples. Then, 3.5 μL of this master mix and 3.5 μL of total RNA samples were pipetted into each well of a 96-well PCR plate (Thermo Fisher Scientific, USA). PCR plates were covered with PCR plate film (MicroAmp Optical Adhesive Film, Thermo Fisher Scientific, USA), vortexed on a plate shaker for 10 s, and then centrifuged for 45 s at 600 g. The PCR plate was then incubated at 37 °C for 60 min and then at 95 °C for five min in the thermal cycler (Genepro, TC-E-3846, China). After the cDNA reaction was completed plate was centrifuged for one min to avoid loss of cDNA. Then, 28 μL of nuclease-free water was added to each well. Plates were again covered and vortexed on a plate shaker for 10 s and then centrifuged for 45 s at 600 g.

Pre-amplification reaction

We performed a pre-amplification reaction to increasing the quantity and quality of cDNA for miRNA reaction. Thus, miScript Microfluidics PreAMP Kit (Qiagen, USA) was used to pre-amplify cDNAs. First of all, a pre-amplification master mix was prepared for 70 samples. Then, 8 μL of pre-amplification master mix and 2 μL of diluted cDNA samples were dispensed into each well of a 96-well PCR plate (Thermo Fisher Scientific, USA). Plates were covered with PCR plate film (MicroAmp Optical Adhesive Film, Thermo Fisher Scientific, USA), vortexed on a plate shaker for 10 s and then centrifuged for 45 s at 600 g. The plate was then cycled in the thermal cycler (Genepro, TC-E-3846, China) under the following conditions: one cycle of the activation step for 15 min at 95 °C, followed by 12 cycles of denaturation for 30 s at 94 °C, and annealing/extension for three min at 60 °C and finally 4 °C for at least 600 s.

Exonuclease I reaction

The exonuclease I (Exol) reaction removes non-specific signalizations of single-stranded DNA molecules during the reaction. After the pre-amplification reaction was completed, the plate was centrifuged for one min. Then exol mix was prepared and 2 μL of this mix was added to each well of pre-amplified RNA samples. The plate was covered and vortexed on a plate shaker for 10 s and then centrifuged for one min at 500 g. After centrifugation, the plate was performed for Exol reaction in a thermal cycler (Genepro, TC-E-3846, China) as follows: 37 °C for 30 min; and 80 °C for 15 min. After the Exol reaction was completed, the plate was centrifuged for one min and 18 μL of nuclease-free water was added to each well. Plates were then covered with a plate film and vortexed for homogenization on a plate shaker for 10 s and then centrifuged for 45 s at 600 g.

miRNA analysis by high throughput real-time qPCR

miRNA assay preparation

miRNA analysis was performed using the high throughput real-time qPCR method using BioMark HD System (Fluidigm, San Francisco, USA). We profiled 11 candidate miRNAs (miR499a-5p, miR-1, miR-374a-5p, miR-25-3p, miR-34a-5p, miR-30d-5p, miR-92a-3p, hsa-miR-150, miR208a-3p, miR-221-3p and miR133a-3p), a negative control, a reverse transcription control, and a PCR positive control. miRNAs assay plate, which included 11 miRNAs and the qPCR master mix, was prepared according to the manufacturer’s instructions. After miRNA primers were prepared, they were ready to load into Dynamic Arrays directly.

qPCR mix preparation

Before preparation of the qPCR mix, the syringes which prefilled control line fluid were injected into the appropriate position of Dynamic Arrays 96.96 GE and then the Dynamic Array chip was placed into IFC Controller HX (Fluidigm, San Francisco, USA) for priming. During priming (about 20 min), the qPCR master mix was prepared. After priming and preparation of mix, 4 μL of qPCR master mix and 2 μL of diluted pre-amplified cDNA samples (which performed Exol reaction) were then added to each 96-well PCR plate. After covering with plate film, the plate vortexed on a plate shaker for 10 s and then centrifuged for 45 s at 600 g. After centrifugation, the samples were ready for transfer to Dynamic Arrays. Thus, 4.75 μL of the mixture prepared above was transferred into sample inlets of Dynamic Array. Similarly, 4.50 μL of miRNA assays were prepared before being transferred into assay inlets of Dynamic Array. For distributing the assays and samples into the reaction wells, 96.96 Dynamic Array was placed into the IFC Controller HXs to load the samples and assay into the appropriate PCR wells. After the loading process was finished, 96.96 Dynamic Array was placed into the BioMark for performing miRNA expression. To confirm that all wells were fulfilled with PCR mix and samples, a passive reference dye called ROX was used. miRNA expression analysis was performed using BioMark RT-PCR analysis software.

Statistical analysis

Categorical variables were summarized in numbers and percentages, while continuous variables were summarized regarding mean ± standard deviation. The chi-square test was used to examine the relationship between categorical variables. An independent sample t-test was used to compare the two groups regarding continuous variables. Global normalization was performed in miRNA analysis. p<0.05 was considered statistically significant.

Results

Twenty-five patients with ST-segment elevation and 25 non-ST-segment elevation patients, and 20 healthy individuals without any systemic disease who applied to Mersin University Hospital Cardiology Department with the diagnosis of acute myocardial infarction were included in this study. The demographic characteristics of the STEMI, NSTEMI and control groups included in this study are given in Table 1. The mean age of the STEMI group was 59.90 ± 11.0, the mean age of the NSTEMI group was 64.24 ± 11.1, and while the mean age of the control group was 49.60 ± 7.3. In all groups, the number of men was higher than women. None of the individuals in the control group had diabetes, heart disease, hypertension, hyperlipidemia, smoking or alcohol use. The patients in the STEMI group had 32% diabetes, 24% heart disease, 48% hypertension, and 20% hyperlipidemia. In the NSTEMI group of patients, 36% had diabetes and hypertension, 32% had heart disease, and 8% had hyperlipidemia. The percentage of smokers was higher in both groups than in alcohol use. In addition, smoking and alcohol use were higher in the STEMI group. No significant difference was found between the patients in NSTEMI and STEMI groups regarding gender, diabetes, hypertension, hyperlipidemia, heart disease, smoking and alcohol (p>0.05).

Table 1:

Demographic characteristics of STEMI, NSTEMI and control groups.

Control STEMI NSTEMI
Age 49.60 ± 7.3 58.90 ± 11.0 64.24 ± 11.1
n (%) n (%) n (%)
Sex Female 6 (30) 5 (20) 3 (12)
Male 14 (70) 20 (80) 22 (88)
Diabetes Yes 0 (0) 8 (32) 9 (36)
No 25 (100) 17 (68) 16 (64)
Heart disease Yes 0 (0) 6 (24) 8 (32)
No 25 (100) 19 (76) 17 (68)
Hypertension Yes 0 (0) 12 (48) 9 (36)
No 25 (100) 13 (52) 16 (64)
Hyperlipidemia Yes 0 (0) 5 (20) 2 (8)
No 25 (100) 20 (80) 23 (92)
Cigarette Yes 0 (0) 17 (68) 11 (44)
No 25 (100) 8 (32) 14 (56)
Alcohol Yes 0 (0) 7 (28) 2 (8)
No 25 (100) 18 (72) 23 (92)

Results of the miRNA expression levels of the STEMI, NSTEMI and control groups

Expression levels of miR499a-5p, miR-1, miR-374a-5p, miR-25-3p, miR-34a-5p, miR-30d-5p, miR-92a-3p, hsa-miR-150, miR208a-3p, miR-221-3p and miR133a-3p were investigated in STEMI, NSTEMI and control groups.

Results of the miRNA expression levels of the NSTEMI and control groups

The miRNA expression levels of the NSTEMI patient group and the control group included in the present study are given in Figure 1. In the NSTEMI patient group, miR-221-3p and miR-30d-5p were downregulated, while miR-25-3p, miR-34a-5p, miR-92a-3p and hsa-miR-150 were up-regulated. The difference in expression level was not statistically significant (p>0.05).

Figure 1: miRNA expression levels of the NSTEMI and control groups.
Figure 1:

miRNA expression levels of the NSTEMI and control groups.

Results of miRNA expression levels of STEMI and control groups

The STEMI patient group included in the present study and the control group’s miRNA expression levels are given in Figure 2. Compared with the control group, miR-221-3p, miR-25-3p, miR-30d-5p and miR-92a-3p were downregulated, while miR-208a-3p was upregulated in patients with STEMI. However, there was no significant difference in miRNA expression levels between the control group and patients with STEMI (p>0.05).

Figure 2: miRNA expression levels of STEMI and control groups.
Figure 2:

miRNA expression levels of STEMI and control groups.

Results of the miRNA expression levels of the STEMI and NSTEMI groups

The miRNA expression levels of the NSTEMI and STEMI patient groups included in the study are given in Figure 3.

Figure 3: miRNA expression levels of the STEMI and NSTEMI groups.
Figure 3:

miRNA expression levels of the STEMI and NSTEMI groups.

In NSTEMI patient group, miR-150, miR-221-3p, miR-25-3p, miR-30d-5p, miR-34a-5p, and miR-92a-3p were downregulated, it was not statistically significant.

Discussion

Mortality is extremely high in patients diagnosed with ACS, and approximately 1/3 of these patients die within the first hour. 2/3 of the deaths in hospitals are within the first 24 h. While hospital mortality is 10% in NSTEMI, it is 20% in STEMI. Only 30–50% of these patients can be diagnosed with AMI [8].Survivors after AMI face the risk of chronic debility due to heart failure, angina pectoris and functional limitations because of myocardial damage. Half of the unexpected out-of-hospital deaths are due to sudden cardiac death due to ACS. The first step in approaching acute coronary syndromes is to make the correct diagnosis quickly [8, 9]. After a fast and accurate diagnosis, the patients can receive treatment quickly, and they benefit from the treatment more. Many new cardiac biomarkers for diagnosing acute coronary syndrome patients have been studied clinically and miRNAs are one of them [10].

Circulating miRNAs are currently in the focus of interest as non-invasive biomarkers of cardiovascular pathologies, including CAD and ACS; STEMI and NSTEMI and unstable angina. However, the available data for some miRNAs appear to differ due to methodological differences [11].

Circulating miRNAs are resistant to ribonuclease, as well as being stable even under freezing or thawing and other harsh conditions, making them potent biomarker candidates [12]. A specific source of circulating microRNAs is difficult to determine without dividing the total pool of circulating microRNAs into fractions. However, it is considered that the most likely potential source for some miRNAs has been identified, as some are abundant in certain tissue-specific or circulating fractions. The group of miRNAs most abundant in skeletal or cardiac muscle, called myomiR, are miR-1-3p, miR-133a-3p, miR-133b, miR-208a/b-3p and miR-499a-5p. These miRNAs have been reported to have low plasma/serum levels in healthy individuals. Although their levels have been shown to increase after myocardial infarction, it has been determined that their levels increase after intense physical exercise [13, 14].

Many miRNAs are actively/passively released into circulation to modulate gene function. It binds to the 3′ untranslated regions of the target mRNA and leads to repression or disruption of translation of mRNAs [15, 16].

Studies in the relevant literature suggest that miRNAs may play a crucial role in cardiovascular diseases, plays a role in the early pathology of MI and promotes therapeutic cardiac remodeling [17, 18].

The first clinical study showing that the heart is the source of circulating miRNAs during myocardial damage is performed by De Rosa et al. In their study, skeletal muscle (miR-133a, miR-499 and miR-155), vascular (miR-126, miR-92a), leukocyte (miR-155) and platelet (miR-223) origin miRNAs were isolated, and miR-133a, miR-499 and miR208a levels were higher in troponin positive acute coronary syndromes than in stable coronary artery disease [19].

In the study conducted by Ward et al. in patients diagnosed with STEMI and NSTEMI, plasma miR 25-3p and 374b-5p, platelet miR 25-3p and 221-3p and peripheral blood mononuclear cell miR 25-3p, 221-3p expression levels were significantly higher in patients with STEMI than diagnosed with patients with NSTEMI. In the same study, plasma miR 30d-5p expression levels were lower in patients with STEMI than patients with NSTEMI, and plasma miR 483-5p expression levels were higher. These miRNAs were thought to be the ideal biomarkers [20].

In the study by Zhang et al., the findings showed that miR-150 was significantly higher in AMI, especially in patients diagnosed with NSTEMI. In a study by Boon et al., it has been shown that miR-34a causes aging in heart cells, and the therapy to target this miRNA accelerates the healing of myocytes after AMI and prevents fibrosis [21, 22].

In the study conducted by Wang et al., which examined the relationship between AMI and miRNA, the findings showed many miRNA levels, including miR-1, miR-133a, miR-133b and miR-208a specific to skeletal and cardiac muscle, increased in rats with AMI. Among them, miR-1, miR-133a and miR-133b were high in skeletal muscle damage. In other studies, it was emphasized that their cardio-specific properties were low. miR-208a has a high cardiac tissue specificity and can be easily detected in 90–100% of patients within the first four hours of the onset of symptoms. In the same study, it was emphasized that miR-208a had high sensitivity and specificity in diagnosing AMI and could be a new biomarker. Thus, miR-208 is called cardiomiR. It has even been reported that cTnI rises in the 3rd hour after AMI and peaks in 24–48 h, while miR-208 rises after 0 h and remains high for 24 h [23].

In our study, when the patient groups and the control group were compared, miR-1, miR-25-3p, miR-34a-5p, miR-30d-5p, miR-92a-3p, miR-150, miR-133a-3p, miR-208a- There was no statistically significant difference in the expression levels of 3p, miR-221-3p, miR499a-5p and miR374a-5p (p> 0.05). Because the majority of CAD patients are taking antiplatelet drugs and statins, different results are obtained in circulating plasma levels of some miRNAs [11]. It is thought to be a reason for the difference between studies. Moreover, we think that the reason for the difference in the literature is the difference in the sample (tissue, platelet, epithelial cell), sampling time, animal study, and the basic method of the study.

In conclusion, miRNAs are associated with physiological and pathological processes involved in developing CAD, such as endothelial dysfunction, inflammation, apoptosis, angiogenesis and atherosclerosis. Although it has been shown by profile scanning studies that miRNAs are associated with the diagnosis and prognosis of heart diseases, the diagnostic and prognostic power of miRNAs will be better understood by determining their correlations with clinical and laboratory parameters. In addition, to develop diagnostic and therapeutic approaches for coronary artery disease, the roles of miRNAs should be better explored, and the expression change should be understood. Therefore, studies should be conducted in different populations by considering the effect of pre-analytical and analytical conditions, the presence of comorbidities, and drug use.

Corresponding author: Prof. Dr. Lulufer Tamer, Department of Medical Biochemistry, Mersin University Faculty of Medicine, 33079, Mersin, Türkiye, Phone: +90 542 431 53 58, +90 324 361 06 84, E-mail:

Funding source: Mersin University Scientific Research Projects Unit

Award Identifier / Grant number: 2015-TP3-1190

  1. Research funding: This research project was partially supported Mersin University Scientific Research Projects Unit under grant number 2015-TP3-1190.

  2. Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  3. Competing interests: Authors state no conflict of interest.

  4. Informed consent: Informed consent was obtained from all individuals included in this study.

  5. Ethical approval: Ethical approval was obtained from the Ethics Committee of Mersin University (Decision No: 2014/203, Date: 28.08.2014).

References

1. Roe, MT, Ohman, EM, Pollack, CV, Peterson, ED, Brindis, RG, Harrington, RA, et al.. Changing the model of care for patients with acute coronary syndromes. Am Heart J 2003;146:605–12. https://doi.org/10.1016/s0002-8703(03)00388-0.Search in Google Scholar

2. Meder, B, Keller, A, Vogel, B, Haas, J, Sedaghat-Hamedani, F, Kayvanpour, E, et al.. MicroRNA signatures in total peripheral blood as novel biomarkers for acute myocardial infarction. Basic Res Cardiol 2011;106:13–23. https://doi.org/10.1007/s00395-010-0123-2.Search in Google Scholar PubMed

3. Ai, J, Zhang, R, Li, Y, Pu, J, Lu, Y, Jiao, J, et al.. Circulating microRNA-1 as a potential novel biomarker for acute myocardial infarction. Biochem Biophys Res Commun 2010;391:73–7. https://doi.org/10.1016/j.bbrc.2009.11.005.Search in Google Scholar PubMed

4. Voorhoeve, PM, Agami, R. Classifying microRNAs in cancer: the good, the bad and the ugly. Biochim Biophys Acta 1775:274–82. https://doi.org/10.1016/j.bbcan.2006.11.003.Search in Google Scholar PubMed

5. Friedman, RC, Farh, KK, Burge, CB, Bartel, DP. Most mammalian mRNAs are conserved targets of microRNAs. Genome Res;19:92–105. https://doi.org/10.1101/gr.082701.108.Search in Google Scholar PubMed PubMed Central

6. Small, EM, Olson, EN. Pervasive roles of microRNAs in cardiovascular biology. Nature 2011;469:336–42.10.1038/nature09783Search in Google Scholar PubMed PubMed Central

7. Fichtlscherer, S, De Rosa, S, Fox, H, Schwietz, T, Fischer, A, Liebetrau, C, et al.. Circulating microRNAs in patients with coronary artery disease. Circ Res 2010;107:677–84. https://doi.org/10.1161/circresaha.109.215566.Search in Google Scholar

8. Falk, E, Thuesen, L. Pathology of coronary microembolisation and No reflow. Heart 2003;89:983–5, https://doi.org/10.1136/heart.89.9.983,Search in Google Scholar PubMed PubMed Central

9. Bogaty, P, Hackett, D, Davies, G, Maseri, A. Vasoreactivity of the culprit lesion in unstable angina. Circulation 2000;101:841–3.Search in Google Scholar

10. Wang, GK, Zhu, JQ, Zhang, JT, Li, Q, Li, Y, He, J, et al.. Circulating microRNA: a novel potential biomarker for early diagnosis of acute myocardial infarction in humans. Eur Heart J 2010;31:659–66. https://doi.org/10.1093/eurheartj/ehq013.Search in Google Scholar PubMed

11. Zhelankin, AV, Stonogina, DA, Vasiliev, SV, Babalyan, KA, Sharova, EI, Doludin, YV, et al.. Circulating extracellular miRNA analysis in patients with stable CAD and acute coronary syndromes. Biomolecules 2021;11:962. https://doi.org/10.3390/biom11070962.Search in Google Scholar PubMed PubMed Central

12. Kroh, EM, Parkin, RK, Mitchell, P, Tewari, M. Analysis ofcirculating microRNA biomarkers in plasma and serum using quantitative reverse transcription-PCR (qRTPCR). Methods 2010;50:298–301. https://doi.org/10.1016/j.ymeth.2010.01.032.Search in Google Scholar PubMed PubMed Central

13. Kaur, A, Mackin, ST, Schlosser, K, Wong, FL, Elharram, M, Delles, C, et al.. Systematic review of MicroRNA biomarkers in acute coronary syndrome and stable coronary artery disease. Cardiovasc Res 2020;116:1113–24. https://doi.org/10.1093/cvr/cvz302.Search in Google Scholar PubMed

14. Siracusa, J, Koulmann, N, Banzet, S. Circulating MyomiRs: a new class of biomarkers to monitor skeletal muscle in physiology and medicine. J. Cachexia Sarcopenia Muscle 2018; 9, 20–7, https://doi.org/10.1002/jcsm.12227,Search in Google Scholar PubMed PubMed Central

15. Bartel, DP. MicroRNAs: target recognition and regulatory functions. Cell 2009;136:215–33. https://doi.org/10.1016/j.cell.2009.01.002.Search in Google Scholar PubMed PubMed Central

16. Pillai, RS, Bhattacharyya, SN, Filipowicz, W. Repression repression of protein synthesis by miRNAs: how many mechanisms? Trends Cell Biol 2007;17:118–26. https://doi.org/10.1016/j.tcb.2006.12.007.Search in Google Scholar PubMed

17. Xiao, Y, Zhao, J, Tuazon, JP, Borlongan, CV, Yu, G. MicroRNA-133a and myocardial infarction. Cell Transplant 2019;28:831–8. https://doi.org/10.1177/0963689719843806.Search in Google Scholar PubMed PubMed Central

18. Wang, J, Feng, Q, Liang, D, Shi, J. MiRNA-26a inhibits myocardial infarction-induced apoptosis by targeting PTEN via JAK/STAT pathways. Cells Dev 2021;165:203661. https://doi.org/10.1016/j.cdev.2021.203661.Search in Google Scholar PubMed

19. Schachinger, V, Britten, MB, Zeiher, AM. Prognostic impact of coronary vasodilatator dysfunction on adverse long-term outcome or coronary heart disease. Circulation 2000;101:1899–906. https://doi.org/10.1161/01.cir.101.16.1899.Search in Google Scholar PubMed

20. Buffon, A, Biasucci, LM, Liuzzo, G, D’Onofrio, G, Crea, F, Maseri, A. Widespread coronary inflammation in unstable angina. N Engl J Med 2002;347:5–12. https://doi.org/10.1056/nejmoa012295.Search in Google Scholar PubMed

21. Reimer, KA, Jennings, RB. The ‘wavefront phenomenon’ of myocardial ischemic cell death. II. Transmural progression of necrosis within the framework of ischemic bed size (myocardium at risk) and collateral flow. Lab Invest 1979;40:633–44.Search in Google Scholar

22. Stary, HC, Chandler, AB, Dinsmore, RE, Fuster, V, Glagov, S, Insull, W, et al.. A definition of advanced types of atherosclerotic lesions and a histological classification of atherosclerosis. Circulation 1995;92:1355–74. https://doi.org/10.1161/01.cir.92.5.1355.Search in Google Scholar PubMed

23. Monaco, C, Mathur, A, Martin, JF. What causes acute coronary syndromes? Applying Koch’s postulates. Atherosclerosis 2005;179:1–15. https://doi.org/10.1016/j.atherosclerosis.2004.10.022.Search in Google Scholar PubMed

Received: 2022-02-04
Accepted: 2022-11-21
Published Online: 2023-03-31

© 2023 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

  1. Frontmatter
  2. Review
  3. A dual role of proton pump inhibition on cancer: a critical review
  4. Opinion Paper
  5. The consumption of vegetable oils and their possible participation as a neuroprotector
  6. Research Articles
  7. Analysis of inappropriate repeated laboratory testing
  8. SNP based analysis depicts phenotypic variability in heme oxygenase-1 protein
  9. The D allele of angiotensin-converting enzyme gene insertion/deletion polymorphism is associated with the lung involvement in COVID-19
  10. The effect of survivin gene in breast cancer risk and prognosis
  11. Increase of Claudin-5, ICAM-1 and eNOS expressions in human brain endothelial cells by ammonium chloride
  12. The effect of different anti-inflammatory treatment strategies on process of atherosclerosis in ankylosing spondylitis patients
  13. Genetic dissection of the Mastl-Arpp19/Ensa-PP2A-B55δ pathway in mammalian cells
  14. Investigation into miRNA profile in patient groups with and without ST elevation
  15. Prognostic value of total thiol and D-dimer in patients hospitalized with COVID-19
  16. Case Report
  17. The effect of heterophilic antibody interference in thyroglobulin measurement on different immunoassay devices
https://doi.org/10.1515/tjb-2021-0282
Keywords for this article
acute coronary syndrome; coronary artery; high-throughput RT-PCR; microRNA; NSTEMI; STEMI
Creative Commons
BY 4.0

Articles in the same Issue

  1. Frontmatter
  2. Review
  3. A dual role of proton pump inhibition on cancer: a critical review
  4. Opinion Paper
  5. The consumption of vegetable oils and their possible participation as a neuroprotector
  6. Research Articles
  7. Analysis of inappropriate repeated laboratory testing
  8. SNP based analysis depicts phenotypic variability in heme oxygenase-1 protein
  9. The D allele of angiotensin-converting enzyme gene insertion/deletion polymorphism is associated with the lung involvement in COVID-19
  10. The effect of survivin gene in breast cancer risk and prognosis
  11. Increase of Claudin-5, ICAM-1 and eNOS expressions in human brain endothelial cells by ammonium chloride
  12. The effect of different anti-inflammatory treatment strategies on process of atherosclerosis in ankylosing spondylitis patients
  13. Genetic dissection of the Mastl-Arpp19/Ensa-PP2A-B55δ pathway in mammalian cells
  14. Investigation into miRNA profile in patient groups with and without ST elevation
  15. Prognostic value of total thiol and D-dimer in patients hospitalized with COVID-19
  16. Case Report
  17. The effect of heterophilic antibody interference in thyroglobulin measurement on different immunoassay devices
Sign up now to receive a 20% welcome discount
Institutional Access
How does access work?
Have an idea on how to improve our website?
Please write us.
© 2025 De Gruyter Brill
Downloaded on 28.9.2025 from https://www.degruyterbrill.com/document/doi/10.1515/tjb-2021-0282/html
Scroll to top button