Abstract
Aim: Acute coronary syndrome (ACS), a leading cause of morbidity and mortality worldwide, is among the most serious cardiovascular diseases. Circadian rhythms are present in almost all organisms. In clinical practice, we have found that ACS is closely related to these circadian rhythms. However, the relationship between circadian rhythms and plaque instability in ACS patients is incompletely understood. The aim of this study is to provide new insights into the relationship between circadian rhythms and plaque instability in ACS patients. Methods: We enrolled patients with ACS and individuals with normal coronary artery function in this study. The Athens Insomnia Scale (AIS), Pittsburgh Sleep Quality Index (PSQI), International Physical Activity Questionnaire (IPAQ) and Healthy Diet Score (HDS) were used to evaluate circadian rhythms. Furthermore, quantitative real-time polymerase chain reaction (qRT-PCR) was used to assess the mRNA expression levels of muscle aryl hydrocarbon receptor nuclear translocator-like protein 1 (Bmal1), circadian locomotor output cycles kaput (Clock), Cryptochrome1 (Cry1), Period2 (Per2), nuclear receptor subfamily 1, group D, member 1 (Rev-erbα), and matrix metalloproteinases MMP2 and MMP9. Results: AIS scores and PSQI scores were significantly higher in patients with ST segment elevation myocardial infarction (STEMI), non-ST segment elevation myocardial infarction (NSTEMI), and unstable angina pectoris (UA) than in the normal controls (NCs) (P < 0.05). The IPAQ scores of the NCs and patients with UA were significantly higher than in patients with STEMI and NSTEMI (P < 0.05). Notably higher HDS scores were recorded for the NCs compared to those of patients with UA, NSTEMI, and STEMI (P < 0.05). Consistent with these findings, compared with the NCs, the lowest levels of Bmal1, Clock, Cry1, Per2 and Rev-erbα mRNAs were detected in patients with STEMI, followed by patients with NSTEMI and then patients with UA (P < 0.05). Furthermore, the levels of MMP2 and MMP9 mRNA were significantly higher in the patients with STEMI, NSTEMI, and UA than those in the NCs (P < 0.05). In addition, we found that the levels of MMP mRNA negatively correlated with the levels of clock genes mRNAs (P < 0.05, respectively). Conclusions: Based on our data, the circadian rhythms and clock genes are correlatively with the occurrence of ACS, and the expression levels of clock genes are negatively correlated with plaque stability in ACS patients.
Keywords: Acute coronary syndrome (ACS), circadian rhythms, plaque stability
Introduction
Acute coronary syndrome (ACS) is a serious clinical syndrome that includes unstable angina pectoris (UA), ST segment elevation myocardial infarction (STEMI), and non-ST segment elevation myocardial infarction (NSTEMI). It is caused by partial or complete occlusion of the coronary arteries due to sudden rupture of atherosclerotic plaques and subsequent coronary thrombosis [1]. Myocardial infarct and unstable angina tend to occur between the early morning and noon [2]. Epidemiological research has consistently shown the circadian rhythmicity of the time of ACS onset [2]. Therefore, we speculated that this phenomenon may be related to circadian rhythms; however, the mechanism underlying the phenomenon remains unclear.
All organisms, including bacteria, plants and mammals, have intrinsic 24-h rhythms that adapt to changes in the surrounding environment. In humans, the central pacemaker of the circadian rhythm is the suprachiasmatic nucleus (SCN) of the hypothalamus, which orchestrates the 24-h cycles present in most cells of the body that are of particular relevance to behavioral and physiological functions, including sleep/wake cycles, feeding behavior, and rhythmic activity [3]. The core genes of the circadian clock include Clock and Bmal1, and the regulatory genes include Crys, Pers and Rev-erbs, which play important roles in regulating physiologic activities. Many animal experiments and clinical studies have shown that abnormal circadian rhythms may lead to atherosclerosis [4], obesity [5], diabetes mellitus [6], hyperlipidemia [7], endothelial cell dysfunction [8] and abnormal immune response [9]. These conditions are closely related to the occurrence of ACS.
The aim of our study was to investigate interactions between abnormal circadian rhythms and plaque instability in acute coronary syndrome patients. We hypothesized that abnormal circadian rhythms and clock genes contribute to the development of ACS.
Materials and methods
Patient population
This study analyzed the relationship between abnormal circadian rhythms and ACS. In our study, 218 patients were recruited from the Central People’s Hospital in Yichang, Hubei Province, China. Their ages ranged from 29 to 85 years (mean age: 60.06 ± 11.15 years). Subjects were provided with detailed oral and written information about the research project and provided written consent prior to participation. The Ethics Committee of the Central People’s Hospital of Yichang approved the study. Patients were classified into four groups: group 1: normal control group (NC); group 2: UA group; group 3: acute STEMI group; and group 4: acute NSTEMI group. The diagnostic criteria were derived from the American Heart Association (AHA), the American College of Cardiology (ACC), and European Society of Cardiology (ESC) [10,11].
Inclusion and exclusion criteria
NC group: patients were diagnosed by coronary angiography, and no vascular diseases were observed.
UA group: 1) negative serum troponin level; 2) clinical manifestation of chest pain; and 3) the electrocardiogram (ECG) showed transient ST segment depression and/or a flat or inverted T-wave flat and rare ST segment elevation.
Acute STEMI group: 1) typical ischemic clinical manifestation of chest pain lasting ≥ 20 min; 2) ST segment elevation (≥ 1 mm) in ≥ 1 electrocardiogram leads; 3) a cardiac troponin (T or I), or a creatine kinase-myoglobin (CKMB) level greater than the institutional upper limit of normal; and 4) a coronary angiography revealed stenosis in the coronary artery.
Acute NSTEMI group: 1) typical clinical manifestation of chest pain during the 24 h prior to receiving medical treatment; 2) changes observed on ECG indicative of myocardial ischemia: ST segment depression (≥ 1 mm) and/or T-wave inversion; 3) a cardiac troponin (T or I) or a CKMB level greater than the institutional upper limit of normal; and 4) coronary angiography revealed stenosis in the coronary artery.
The exclusion criteria were as follows: 1) cardiovascular events for < 1 year, such as a stroke or myocardial infarction; 2) low-density lipoprotein (LDL)-cholesterol level ≥ 4.3 mmol/L; 3) presence of malignant diseases; 4) renal failure; 5) liver diseases; 6) various chronic and acute infections; 7) connective tissue diseases; 8) received treatment with anti-inflammatory drugs and/or immunosuppressive agents; 9) pregnant or lactating patients; and 10) subjects who were participating in another clinical trial or refused to sign the informed consent form.
Circadian rhythm assessments
The circadian rhythms of humans mainly manifest as sleep/wake cycles, feeding behavior and rhythmic activity. Therefore, we evaluated circadian rhythms among the enrolled patients in terms of sleep, diet and exercise. The Athens Insomnia Scale (AIS) shown in Table S1 in the Supplementary Appendix and the Pittsburgh Sleep Quality Index (PSQI) shown in Table S2 in the Supplementary Appendix were used to assess sleep quality during the last month. The International Physical Activity Questionnaire (IPAQ) shown in Table S3 in the Supplementary Appendix was used to assess the amount of physical activity in the last 7 days, and the sum of the MET (metabolic equivalent of task) min/week was calculated for each participant. In the IPAQ, 3.3 METs correspond to 1 minute of walking, 4.0 METs correspond to 1 minute of moderate activity and 8.0 METs correspond to 1 minute of vigorous activity. The Healthy Diet Score (HDS) shown in Table S4 in the Supplementary Appendix was used to assess daily energy intake during the last month.
Blood sample collection
We collected 8-10 mL of peripheral blood from all participants after an overnight fast. Blood samples were treated with ethylene diamine tetraacetic acid (EDTA) and examined within 4 h. The anti-coagulated blood was used for quantitative real-time polymerase chain reaction (qRT-PCR).
Isolation of peripheral blood mononuclear cells (PBMCs)
PBMCs were isolated from 5 mL of ethylene diamine tetraacetic acid-treated venous blood samples by Ficoll-Hypaque gradient centrifugation (1,600 rpm at room temperature for 19 min). After the centrifugation, the cells from the interface were collected and washed twice in Roswell Park Memorial Institute (RPMI) 1640 medium (Invitrogen, Auckland, NZ, USA).
qRT-PCR
Levels of the Bmal1, Clock, Per2, Cry1, Rev-erbα, Mmp2 and Mmp9 mRNAs were determined by qRT-PCR. Total RNA was extracted from peripheral blood mononuclear cells (PBMCs) using the RNAsimple Total RNA Kit (Lot DP419, TIANGEN Biotech, China) and reverse transcribed into cDNAs using the Revert Aid First Strand cDNA Synthesis Kit (Lot 00422877, Thermo Scientific, USA), according to the manufacturer’s instructions. Levels of the Bmal1, Clock, Per2, Cry1, Rev-erbα, Mmp2 and Mmp9 mRNAs were quantified using the SYBRP® Premix Ex TaqTM II (Lot RR820A, Takara, Japan) on an Agilent Strata Gene Mx3005P system (Agilent, American); Gapdh expression served as a control. Amplification was performed in a 20-µL reaction for 40 cycles of 15 s at 95°C and 30 s at 60°C after an initial denaturation step (72°C, 30 s). The following primer sequences were used: GAPDH forward: AGGTCCACCACTGACACGTT; GAPDH reverse: GCCTCAAGATCATCAGCAAT; Bmal1 forward: GAGCAGCTCTCCTCCTCTGA; Bmal1 reverse: CGTCGTGCTCCAGAACATAA; Clock forward: AGAGCACCTTCCCTCAGTCA; Clock reverse: GCACGTGTGCTACTGTGGTT; Per2 forward: ACTCAGCGAAGTGTCGGACAC; Per2 reverse: TTCGATCCTGTGATTCAAGGG; Cry1 forward: AGTTGCTCTCAAGGGAGTGG; Cry1 reverse: GACTAGGACGTTTCCCACCA; Rev-erbα forward: CTGGGAGGATTTCTCCATGA; Rev-erbα reverse: GCCTTAAGCAGGGTGACTTG; MMP2 forward: ACCTGAAGCTGGAGAACCAA; MMP2 reverse: TATCGAAGGCAGTGGAGAGG; MMP9 forward: CGACGTCTTCCAGTACCGAG; and MMP9 reverse: TTGTATCCGGCAAACTGGCT. Samples were analyzed in triplicate. The relative expression levels of mRNAs were determined using the 2-ΔΔt method.
Blood biochemistry measurements
Levels of total cholesterol (TC), triglycerides (TG), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), fasting plasma glucose (FPG), serum creatinine, C-reactive protein (CRP), alanine aminotransferase (ALT), aspartate transaminase (AST), creatine kinase (CK), CKMB, lactate dehydrogenase (LDH), and α-hydroxybutyrate dehydrogenase (α-HBDH) were measured using enzymatic methods in the clinical chemistry laboratory of the Central People’s Hospital in Yichang.
Statistical analysis
Data analyses were performed using the SPSS statistical software (version 18.0). Data for continuous variables are presented as means ± standard deviations (SD). Group comparisons were performed using a one-way ANOVA followed by Tukey’s test. Associations were evaluated using Pearson’s correlation coefficient. For discrete variables, differences were expressed as counts and percentages and were analyzed with a χ2 test (or Fisher’s exact test). A two-tailed P < 0.05 was considered significant.
Results
Participants’ characteristics
The clinical characteristics of the participants included in this study are presented in Table 1. Two hundred eighteen participants completed the study: 34 participants in the normal control group, 67 participants in the UA group, 89 participants in the acute STEMI group and 28 participants in the acute NSTEMI group. None of the following parameters differed among the four groups: age, BMI, smoking, drinking, diabetes mellitus, hyperlipidemia, hypertension, serum creatinine, and lipid profiles, including LDL-c, TG, and TC levels. Compared to NCs and patients with UA, patients with STEMI and NSTEMI were more likely to display significantly higher FPG, CRP, ALT and AST levels (P < 0.05), but the levels of these measures were not significantly different between the NCs and the patients with UA (P > 0.05) or between the patients with STEMI and NSTEMI (P > 0.05). Markedly higher levels of myocardial enzymes (CK, CKMB, LDH and α-HBDH) were observed in the STEMI group than those in the NC, NSTEMI and UA groups (P < 0.05). Compared to the NC and UA groups, higher levels of myocardial enzymes were detected in the NSTEMI group, but the difference was not significant (P > 0.05).
Table 1.
Clinical characteristics of the four groups
| Characteristics | NC (n = 34) | UA (n = 67) | STEMI (n = 89) | NSTEMI (n = 28) |
|---|---|---|---|---|
| Age, mean ± SD years | 54.12 ± 14.32 | 61.12 ± 9.44 | 60.42 ± 10.31 | 63.57 ± 11.08 |
| BMI (Kg/m2) | 24.25 ± 7.78 | 24.17 ± 3.02 | 24.10 ± 2.68 | 24.38 |
| FPG (mmol/L) | 5.21 ± 1.24 | 5.25 ± 1.50 | 6.62 ± 2.12a,b | 6.77 ± 2.20a,b |
| Current Smoker, n (%) | 11 (32.4) | 26 (38.3) | 41 (46.1) | 10 (35.7) |
| Current drinker, n (%) | 8 (23.5) | 19 (28.4) | 30 (33.7) | 7 (25.0) |
| Diabetes Mellitus, n (%) | 4 (11.8) | 11 (16.4) | 21 (23.6) | 6 (21.4) |
| Hyperlipidemia, n (%) | 5 (14.7) | 7 (10.4) | 10 (11.2) | 3 (10.7) |
| Hypertension, n (%) | 6 (17.6) | 10 (14.9) | 18 (20.2) | 5 (17.9) |
| CRP (mg/L) | 2.91 ± 1.48 | 5.73 ± 5.05 | 17.34 ± 13.52a,b | 16.62 ± 14.93a,b |
| ALT (U/L) | 25.61 ± 12.27 | 25.95 ± 19.33 | 51.20 ± 38.04a,b | 30.25 ± 14.65c |
| AST (U/L) | 23.94 ± 6.79 | 25.68 ± 11.33 | 210.88 ± 162.87a,b | 92.71 ± 86.83a,b,c |
| SCR (umol/L) | 65.22 ± 14.70 | 71.27 ± 21.74 | 72.46 ± 25.12 | 74.63 ± 14.99 |
| TC (mmol/L) | 4.47 ± 0.97 | 4.25 ± 0.79 | 4.38 ± 1.07 | 4.29 ± 1.35 |
| TG (mmol/L) | 1.68 ± 0.74 | 1.52 ± 1.11 | 1.34 ± 0.62 | 1.47 ± 0.72 |
| HDL (mmol/L) | 1.40 ± 0.30 | 1.36 ± 0.37 | 1.25 ± 0.28 | 1.15 ± 0.29a,b |
| LDL (mmol/L) | 2.65 ± 0.79 | 2.43 ± 0.68 | 2.65 ± 0.91 | 2.60 ± 0.81 |
| CK (IU/L) | 101.07 ± 55.43 | 116.00 ± 102.45 | 1914.50 ± 2212.71a,b | 836.00 ± 875.39c |
| CKMB (IU/L) | 14.77 ± 13.02 | 15.13 ± 9.02 | 166.51 ± 183.81a,b | 80.89 ± 82.47c |
| LDH (IU/L) | 217.97 ± 52.03 | 231.58 ± 65.57 | 676.45 ± 469.05a,b | 382.04 ± 171.80c |
| α-HBDH (IU/L) | 157.17 ± 30.17 | 166.93 ± 49.54 | 585.39 ± 445.09a,b | 306.56 ± 157.73c |
Data are presented as mean ± SD or number (percentage). NC: normal control group; UA: unstable angina pectoris group; STEMI: acute ST segment elevation myocardial infarction group; NSTEMI: acute non-ST segment elevation myocardial infarction group. SCR: serum creatinine; TC: total cholesterol; TG: triglyceride; HDL-C: high-density lipoprotein cholesterol; LDL-C: low density lipoprotein cholesterol; CRP: C-reactive protein; ALT: Alanine aminotransferase; AST: Aspartate transaminase; CK: Creatinekinase; CKMB: Creatine kinase-MB; LDH: lactate dehydrogenase; α-HBDH: α-hydroxybutyrate dehydrogenase.
P < 0.05 vs. NC.
P < 0.05 vs. UA.
P < 0.05 vs. STEMI.
Findings from angiography and percutaneous coronary interventions
All participants underwent coronary angiography. The findings from angiography and percutaneous coronary interventions are summarized in Table 2. Compared with the NCs, the most severe coronary lesions were observed in the patients with STEMI (P < 0.05), followed by the patients with NSTEMI (P < 0.05); the lowest lesion burden was observed in the patients with UA (P < 0.05). Figure 1A is an example of normal coronary angiography in NC group patients. Figure 1B is an example of abnormal coronary angiography in UA group patients. Figure 1C is an example of abnormal coronary angiography in acute STEMI group patients. Figure 1D is an example of abnormal coronary angiography in Acute NSTEMI group patients.
Table 2.
Results of coronary angiography in four groups
| NC (n = 34) | UA (n = 67) | STEMI (n = 89) | NSTEMI (n = 28) | χ2 | P | |
|---|---|---|---|---|---|---|
| No vessel disease, n (%) | 34 (100.0) | 13 (19.4) | 2 (2.7) | 1 (4.5) | 162.58 | < 0.001 |
| 1 vessel disease, n (%) | 30 (43.1) | 19 (21.6) | 11 (40.9) | |||
| 2 vessel disease, n (%) | 8 (12.5) | 29 (32.4) | 8 (27.3) | |||
| 3 vessel disease, n (%) | 16 (25.0) | 39 (43.3) | 8 (27.3) |
Data given as n (%), mean ± SD. NC: normal control group; UA: unstable angina pectoris group; STEMI: acute ST segment elevation myocardial infarction group; NSTEMI: acute non-ST segment elevation myocardial infarction group.
Figure 1.
Examples of results of coronary angiography in four groups of patients. A. No obvious stenosis by the coronary arteriography in an NC group patient. B. 80% stenosis in the proximal segment of LAD and 30% stenosis in the proximal segment of RCA in a UA group patient. C. 90% stenosis in the mid LAD, 95% stenosis in LCA, and 99% stenosis in RCA in an acute STEMI group patient. D. 85% stenosis in the mid of LAD, 90% stenosis in the mid of LCA and 80% stenosis in the proximal segment of RCA in an acute NSTEMI group patient.
Circadian rhythm assessments
All the participants completed the AIS, PSQI, IPAQ, and HDC to assess circadian rhythms. As shown in the results of the sleep quality evaluation presented in Table 3, significantly higher AIS scores were recorded for the patients with STEMI (9.02 ± 4.27), NSTEMI (8.61 ± 5.03), and UA (5.60 ± 4.30) compared to those of the NCs (2.24 ± 3.64) (P < 0.05). Similarly, the highest PSQI scores were observed for the STEMI group (9.85 ± 4.53) followed by the NSTEMI (8.82 ± 4.97), UA (7.60 ± 4.55), and NC (4.41 ± 3.55) groups, respectively (P < 0.05). Regarding the results of activity evaluation, the IPAQ scores of the NC and UA groups were significantly higher than those in the STEMI and NSTEMI groups (P < 0.05). However, the differences between the STEMI and NSTEMI groups were not statistically significant (P > 0.05). Based on the results of the daily energy intake evaluation, notably higher HDS scores were recorded for the NCs than for the patients with UA, NSTEMI, and STEMI (NC, 39.41 ± 4.68; UA, 36.51 ± 3.84; NSTEMI, 34.63 ± 4.97; STEMI, 31.58 ± 3.88; P < 0.05).
Table 3.
Assessments of circadian rhythm in four groups
| NC (n = 34) | UA (n = 67) | STEMI (n = 89) | NSTEMI (n = 28) | |
|---|---|---|---|---|
| Score of AIS | 2.24 ± 3.64 | 5.60 ± 4.30a | 9.02 ± 4.27a,b | 8.61 ± 5.03a,b |
| Score of PSQI | 4.41 ± 3.55 | 7.60 ± 4.55a | 9.85 ± 4.53a,b | 8.82 ± 4.97a,b |
| Score of IPAQ | 4018.19 ± 2046.80 | 3335.50 ± 2005.76 | 1912.55 ± 1769.62a,b | 2096.67 ± 1751.25a,b |
| Healthy diet score | 39.41 ± 4.68 | 36.51 ± 3.84a | 31.58 ± 3.88a,b | 34.63 ± 4.97a,b,c |
Data are presented as mean ± SD. AIS: Athens Insomnia Scale; PSQI: Pittsburgh sleep quality index; IPAQ: International physical activity questionnaire. NC: normal control group; UA: unstable angina pectoris group; STEMI: acute ST segment elevation myocardial infarction group; NSTEMI: acute non-ST segment elevation myocardial infarction group.
P < 0.05 vs. NC.
P < 0.05 vs. UA.
P < 0.05 vs. STEMI.
Levels of the clock gene mRNAs in PBMCs
The core of the molecular clock is the heterodimeric transcription factor heterodimer Clock/Bmal1. The genes regulating the molecular clock include Crys, Pers and Rev-erbs. In this study, we measured the levels of the Bmal1, Clock, Cry1, Per2, and Rev-erbα mRNAs in PBMCs from all participants. As shown in Figure 2, compared with NCs, the lowest levels of all clock gene mRNAs were observed in the patients with STEMI (P < 0.05), followed by the patients with NSTEMI (P < 0.05) and finally the patients with UA (P < 0.05).
Figure 2.
The expressions of Bmal1, Clock, Cry1, Per2 and Rev-erbα mRNA in PBMC were identified by real-time PCR. NC: normal control group; UA: unstable angina pectoris group; STEMI: acute ST segment elevation myocardial infarction group; NSTEMI: acute non-ST segment elevation myocardial infarction group. A. The relative expression of Bmal1 mRNA in four groups; B. The relative expression of Clock mRNA in four groups; C. The relative expression of Cry1 mRNA in four groups; D. The relative expression of Per2 mRNA in four groups; E. The relative expression of Rev-erbα mRNA in four groups. Data are shown as mean ± SEM. *P < 0.05 vs. NC. #P < 0.05 vs. UA. ΔP < 0.05 vs. STEMI.
Expression of Mmp mRNAs in PBMCs
In our study, we measured the levels of MMP2 and MMP9 mRNAs in PBMCs from all participants. As shown in Figure 3, statistically significant differences in MMP2 and MMP9 mRNA expression levels were observed among the four groups. Significantly increased mRNA levels of MMP2 and MMP9 were detected in the STEMI, NSTEMI and UA groups compared with those in the NC group (P < 0.05). Patients with STEMI and NSTEMI displayed significantly higher mRNA levels of MMP2 and MMP9 compared to the patients with UA (P < 0.05), but compared with the patients with NSTEMI, the expression levels of MMP2 and MMP9 mRNAs were higher in the patients with STEMI (P < 0.05).
Figure 3.
The expressions of MMP2 and MMP9 mRNA in PBMC were identified by real-time PCR. NC: normal control group; UA: unstable angina pectoris group; STEMI: acute ST segment elevation myocardial infarction group; NSTEMI: acute non-ST segment elevation myocardial infarction group. The expressions of MMP2 and MMP9 mRNA in PBMC were identified by real-time PCR. A. The relative expression of MMP2 mRNA in four groups; B. The relative expression of MMP9 mRNA in four groups. Data are shown as mean ± SEM. *P < 0.05 vs. NC. #P < 0.05 vs. UA. ΔP < 0.05 vs. STEMI.
Correlation between clock genes and MMPs
As shown in Figure 4, the level of MMP2 mRNA showed negative correlation with the levels of the Bmal1, Clock, Cry1, Per2 and Rev-erbα mRNAs among STEMI, NSTEMI, and UA groups (r = -0.7282, P < 0.0001; r = -0.6430, P < 0.0001; r = -0.6607, P < 0.0001; r = -0.6379, P < 0.0001; r = -0.5090, P < 0.0001; respectively). Consistently, as shown in Figure 5, the level of MMP9 mRNA showed negative correlation with the levels of the Bmal1, Clock, Cry1, Per2, and Rev-erbα mRNAs among STEMI, NSTEMI and UA groups (r = -0.7507, P < 0.0001; r = -0.6732, P < 0.0001; r = -0.6640, P < 0.0001; r = -0.6972, P < 0.0001; r = -0.7166, P < 0.0001; respectively).
Figure 4.
The correlations between the expressions of clock genes and the expression of MMP2. A. The correlation between the expression of Bmal1 and the expression of MMP2. B. The correlation between the expression of Clock and the expression of MMP2. C. The correlation between the expression of Cry1 and the expression of MMP2. D. The correlation between the expression of Per2 and the expression of MMP2. E. The correlation between the expression of Rev-erbα and the expression of MMP2. Pearson’s correlation coefficient (normal distributed data) was used to assess interrelationships; P < 0.01 is considered statistically significant. (r, correlation coefficient; P values are shown).
Figure 5.
The correlations between the expressions of clock genes and the expression of MMP9. A. The correlation between the expression of Bmal1 and the expression of MMP9. B. The correlation between the expression of Clock and the expression of MMP9. C. The correlation between the expression of Cry1 and the expression of MMP9. D. The correlation between the expression of Per2 and the expression of MMP9. E. The correlation between the expression of Rev-erbα and the expression of MMP9. Pearson’s correlation coefficient (normal distributed data) was used to assess interrelationships; P < 0.01 is considered statistically significant. (r, correlation coefficient; P values are shown).
Discussion
To the best of our knowledge, this study is the first to investigate the relationship between abnormal circadian rhythms and ACS, including UA, STEMI and NSTEMI. Our data indicated that abnormal circadian rhythms could promote the occurrence of ACS. In addition, patients with ACS exhibited significantly decreased levels of Bmal1, Clock, Cry1, Per2 and Rev-erbα mRNAs in PBMCs. Furthermore, patients with ACS also showed notably increased levels of MMP2 and MMP9 mRNAs compared to NCs. Therefore, the levels of clock genes were negatively correlated with the severity of coronary artery lesions. In contrast, the levels of MMP mRNAs were positively correlated with the severity of plaque instability. Based on these results, the expression levels of Bmal1, Clock, Cry1, Per2 and Rev-erbα may diminish the process of atherosclerosis and correlate with the severity of atherosclerosis. More importantly, the levels of MMP mRNAs negatively correlated with the levels of clock genes mRNAs. These results suggest that the clock genes may diminish the plaque instability of plaque by disturbing the levels of MMPs. These findings may contribute to improving our understanding of and ability to monitor ACS, simultaneously suggesting possible therapeutic methods to prevent the occurrence of ACS.
Circadian rhythms are present in most cells of the body and play important roles in biological processes. Disrupted circadian rhythms can lead to the development of cardiovascular diseases [4,12], tumors [13], immune system diseases [14] and hematological diseases [15], among other conditions. ACS is mainly caused by abluminal remodeling, plaque erosion or thrombus formation upon rupture. Dyssomnia, changes in physical activity and disordered dietary habits can disrupt normal circadian rhythms and the expression levels of clock genes. Knutsson et al. found that insomniacs and shift workers had a higher risk of acute myocardial infarction [16]. In addition, disrupted circadian rhythms were a novel risk factor for insulin resistance and Type 2 diabetes [17,18] and increased the levels of circulating inflammatory cytokine [19,20]. Based on our clinical data, we found that the incidence of ACS was increased among individuals exhibiting dyssomnia, changes in physical activity and disordered dietary habits. In addition, we found that the levels of FPG and CRP were higher in ACS patients. Therefore, we suspected that the circadian rhythm could affect the occurrence of ACS by regulating glucose metabolism and inflammatory responses. The severity of these conditions was positively correlated with the severity of coronary artery lesions.
The core genes Bmal1 and Clock play major roles in maintaining the homeostasis of circadian rhythms. In our study, markedly decreased levels of Bmal1 and Clock mRNAs were observed in the patients with UA, NSTEMI and STEMI. Pan et al. [4] found that in animal experiments, compared with Apoe-/- mice, Bmal1-/-Apoe-/- mice show increased hyperlipidemia and atherosclerosis, but Bmal1 overexpression in Bmal1-/-Apoe-/- mice reduces hyperlipidemia and atherosclerosis. According to a study by Pan et al. [21], Ldlr-/-Apoe-/- mice with a global Clock mutation develop more lesions in the aortic arches and aortic roots. Moreover, downregulated expression of Bmal1 or Clock not only induces hyperglycemia, hypertriglyceridemia and hypercholesterolemia [22-24] but also increases the expression of inflammatory cytokines [25]. Bmal1 knockout endothelial cells exhibit reduced nitric oxide production and increased superoxide levels [8,26]. Furthermore, based on the results of the present study, high expression levels of Cry1, Per2 and Rev-Erbα protected individuals from developing ACS. Previous peer studies have reported that Cry1 overexpression in a mouse model of atherosclerosis significantly decreases the expression of proinflammatory factors and the concentrations of LDL-c [27]. Furthermore, Cry1 overexpression ameliorates the development of atherosclerosis by regulating the TLR/NF-κB pathway [27]. Similarly, Per2-/- mice display aortic endothelial dysfunction involving reduced nitric oxide production and increased levels of cyclooxygenase-1-derived vasoconstrictors [28]. However, in those mice, the difference in Per2 expression did not affect metabolic risk factors [28]. Rev-erbα silencing has been shown to elevate plasma lipid levels [29]. Furthermore, Rev-erbα overexpression inhibits the expression of inflammatory factors [30]. In summary, abnormal circadian rhythms can affect the occurrence of ACS by changing the expression levels of clock genes. Although the underlying mechanism remains unclear, we presume that the clock genes may reduce the incidence of ACS by maintaining normal vascular endothelial function, limiting the inflammatory response, and decreasing plasma lipid levels. These conclusions warrant further investigation in the future.
MMPs, which are highly concentrated in foam cell-rich regions, participate in the creation of plaques and remodeling of the vascular wall. MMPs play important roles in the development of atherosclerosis. Previous studies have shown that elevated MMP concentrations may contribute to plaque rupture [31]. Furthermore, enhanced MMP activity leads to activation of the pro-inflammatory factor IL-1β [32]. One important finding in the present study was that the increased levels of MMP2 and MMP9 mRNAs observed in patients with ACS correlated with the severity of plaque instability. Interestingly, increased expression levels of clock genes in macrophages downregulate MMP levels [33]. In our study, we found that the levels of MMP2 and MMP9 mRNAs negatively correlated with the levels of Bmal1, Clock, Cry1, Per2, and Rev-Erbα mRNAs. Moreover, compared to other clock genes, the levels of Bmal1 had the highest correlation. Therefore, we suspected that clock genes could increase the stability of atherosclerotic plaques by reducing the expression levels of MMPs. However, the mechanism by which clock genes affect MMPs expressions in patients with ACS remains unclear and warrants further investigation.
In conclusion, abnormal circadian rhythms and clock genes contributed to the development of ACS, and the expression levels of clock genes were negatively correlated with the severity of coronary artery lesions. Meanwhile, the expression levels of MMPs were higher in the patients with ACS. Moreover, the levels of MMP mRNAs negatively correlated with the levels of clock genes mRNAs. Therefore, we hypothesized that abnormal circadian rhythms and clock genes can increase the instability of atherosclerotic plaques by disturbing the levels of MMPs. Our findings can be regarded as preliminary due to a rather small sample and need replication in a large cohort of ACS patients. It must be noted, though, that because the patients with ACS had all been treated with various psychopharmacological drugs during a number of years, we cannot exclude that the here observed alterations are due to long term epigenetic drug effects on the levels of glucose and lipid in the ACS patients. Because of the limitation of conditions, we could not collect blood samples at different time intervals to observe changes of the expressions of circadian rhythm genes. There are some limitations such as the mechanism by which clock genes moderated glucose metabolism and inflammatory responses and MMPs. Unfortunately, the results do not explain the mechanism underlying the relationships between circadian rhythms and clock genes and the stability of atherosclerotic plaques in patients with ACS. We will continue to investigate this mechanism in subsequent experiments. Furthermore, the regulation of circadian rhythms and clock genes may be targets for therapeutic intervention in patients with ACS.
Acknowledgements
This work was supported by the National Natural Science Foundation of China (Grant No. 81770456; 81400794; 81500230).
Disclosure of conflict of interest
None.
Supporting Information
References
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