Abstract
This study measured serum high mobility group box 1 (HMGB1) levels in patients with acute myocardial infarction (AMI) and/or heart failure (HF) and evaluated their relationship with peripheral inflammatory biomarkers and cardiac biomarkers, which have not been reported before. Of the patients, 55 had AMI without HF (AMI−HF), 42 had AMI with HF (AMI+HF), and 60 had HF without AMI (HF−AMI) compared with 50 healthy controls. Blood samples were collected to assess serum HMGB1 levels and blood test‐related inflammatory biomarkers (e.g., erythrocyte sedimentation rate [ESR], hs‐CRP, uric acid, and white blood cell count) and cardiac biomarkers (e.g., MYO, cTnI, CKMB, CK, NT‐proBNP, LDH, aspartate aminotransferase [AST], and alanine aminotransferase [ALT]). Compared to healthy controls, three groups of patients, especially those with AMI+HF, had significantly higher levels of serum HMGB1. All tested inflammatory biomarkers (except uric acid) were significantly positively correlated with HMGB1 in patients with AMI patients but not in patients with non‐AMI. In addition, all tested cardiac biomarkers (except NT‐proBNP in AMI−HF) were significantly higher in patients with AMI than in control individuals. The levels of MYO, cTnI, CKMB, CK, AST, and ALT were not significantly changed in patients with HF−AMI compared to control individuals, but were still much lower than those in patients with AMI (except ALT). In all patients, the levels of NT‐proBNP, and cTnI were significantly correlated with HMGB1 levels. Except for MYO, LDH, AST, and ALT, all cardiac biomarkers in AMI−HF and AMI+HF showed a significant correlation with HMGB1. Among risk factors, hypertension, diabetes, previous heart disease, and reduced left ventricular ejection fraction showed a significant correlation with HMGB1 in all disease groups.
Study Highlights.
WHAT IS THE CURRENT KNOWLEDGE ON THE TOPIC?
An observational case–control study was conducted, including 157 patients and 50 healthy controls. Of the patients, 55 had acute myocardial infarction (AMI) without heart failure (HF; AMI−HF), 42 had AMI with HF (AMI+HF), and 60 had HF without AMI (HF−AMI). The high mobility group box 1 (HMGB1) is an active biochemical factor early started to increase in the blood of patients with AMI−HF and can be used as a biomarker of AMI−HF. HMGB1 is further increased in patients with AMI+HF, which may be used to distinguish AMI with or without HF. HMGB1 is positively correlated with major inflammatory indexes in the AMI−HF and AMI+HF groups, which may be an important biomarker of inflammation‐mediated myocardial injury.
WHAT QUESTION DID THIS STUDY ADDRESS?
This study has been conducted to evaluate the serum HMGB1 level in patients with AMI and HF and its relationship with major inflammatory markers and cardiac biomarkers.
WHAT DOES THIS STUDY ADD TO OUR KNOWLEDGE?
Elevated serum HMGB1 may serve as an early biomarker of AMI−HF. In addition, HMGB1 is further elevated in patients with AMI+HF rather than HF−AMI, which can be used to distinguish AMI from HF. In addition, serum HMGB1 is positively correlated with inflammatory biomarkers in patients with AMI, so it may be considered as a surrogate biomarker for AMI detection.
HOW MIGHT THIS CHANGE CLINICAL PHARMACOLOGY OR TRANSLATIONAL SCIENCE?
The reported results indicated that HMGB1 might be a good candidate for future diagnosis and treatment for AMI with or without HF.
INTRODUCTION
Myocardial infarction (MI) is the most serious coronary artery disease, causing millions of deaths worldwide. 1 , 2 , 3 In recent decades, lifestyle improvements and increased use of evidence‐based therapies have significantly reduced coronary heart disease mortality. 2 Nevertheless, MI still greatly impacts the health of greater than seven million individuals worldwide each year. In addition, MI has a significant economic burden; in 2010, more than 1.1 million patients were hospitalized at a cost of ~$450 billion, which is projected to increase to $1 trillion annually by 2030. 4 Therefore, there is an urgent need to reduce the risk of MI in the population. It is generally known that modifiable and non‐modifiable risk factors associated with MI include sex, age, family history, smoking, diabetes mellitus, hypertension, and obesity.
Heart failure (HF) is the final stage of various heart diseases. It has been suggested that specific inflammatory cytokines are involved in the occurrence and development of MI and HF. 5 , 6 One of the damage‐associated molecular pattern molecules responsible for inducing cytokine storm is high mobility group box 1 (HMGB1), which acts as a signal during tissue damage and triggers a sterile inflammatory response. 7 Under ischemic stress, dying cells secrete HMGB1 to activate macrophages through receptors for advanced glycation end products and Toll‐like receptors‐4 to induce an inflammatory response, leading to MI. 8 Furthermore, the non‐oxidizable HMGB1 can recruit inflammatory cells to damaged sites via the chemokine receptor type 4, thus causing the migration of cardiac fibroblasts and facilitating adverse cardiac remodeling after MI. 9 , 10
Numerous studies have reported that serum HMGB1 is elevated in different cardiovascular diseases (CVDs), including MI and HF. 11 , 12 , 13 Kohno et al. 14 found that in patients with ST‐elevation MI, circulating HMGB1 peaked at 12 h after admission and remained elevated for greater than 7 days. The observed peak HMGB1 levels were independently correlated with cardiac rupture, pump failure, in‐hospital cardiac death, and C‐reactive protein (CRP) levels. 14 A recent study also documented that serum HMGB1 levels were positively correlated with high sensitivity CRP (hs‐CRP) levels, 15 the latter being used as an independent predictor of coronary events. 16 Further, it has also been found that in patients with coronary artery disease, serum HMGB1 is positively correlated with cardiac troponin I (cTnI), 15 a diagnostic biomarker for acute myocardial infarction (AMI). These pieces of evidence indicate that HMGB1 plays a vital role to promote inflammation in the inflammatory process of coronary events and can be used to assess the severity and stratification of coronary artery disease, particularly in AMI.
In addition, a positive correlation has been observed between HMGB1 and several biomarkers of HF, such as N‐Pro‐hormone of brain natriuretic peptide (NT‐proBNP), white blood cell (WBC) count, creatinine level, and New York Heart Association (NYHA) classification. Therefore, HMGB1 has been recommended to predict all‐cause death and heart transplantation. 17
Because HMGB1 is involved in the inflammatory pathogenesis of CVDs, blocking HMGB1 appears to be a therapeutic strategy for these diseases. So far, some animal studies have achieved promising results in treating CVDs with intravenous administration of nuclear HMGB1 or inhibition of extracellular HMGB1. 18 , 19 Therefore, it is important to understand whether AMI and HF as major CVDs correlate with HMGB1 and whether these diseases and HMGB1 correlate with other cardiac biomarkers or risk factors. In this study, we measured serum HMGB1 levels in patients with AMI and/or HF and evaluated the predictive value of HMGB1 in these CVDs. We found that HMGB1 was significantly associated with AMI but not HF, and correlated with most of the cardiac biomarkers tested. Our results support HMGB1 as a candidate biomarker to identify and distinguish AMI with or without HF which needed further research to establish it.
METHODOLOGY
Selection of participants
This study was conducted at the Third Xiang‐Ya Hospital of Central South University, Changsha, Hunan, China. Four groups of subjects were recruited, including healthy individuals as controls, patients with AMI but not HF (AMI−HF), patients with HF but not AMI (HF−AMI), and patients with both AMI and HF (AMI+HF). Each group requires 40 participants according to the predesign.
The diagnosis of HF involves the presence of associated symptoms and objective evidence. 20 Breathlessness, fatigue, and ankle edema are typical symptoms. Elevated NT‐proBNP greater than 600 pg/mL is objective evidence. The diagnosis of MI was based on the following three criteria: (i) elevated cardiac troponins, (ii) echocardiogram (ECG): an ECG with ST elevation, ST depression, T‐wave inversion, and abnormal Q‐wave may be used, and (iii) symptoms: common ischemic chest pain. Patients who displayed elevated troponin levels along with symptoms or ECG changes were diagnosed with AMI, 21 whereas AMI+HF is defined as patients having AMI with HF. All patients were admitted to our Department of Cardiology between April 2020 and March 2021.
Controls came from healthy volunteers who visited our hospital's Health Management Centre for annual health check‐ups at the same time period. They had no heart disease or other chronic diseases and were physically and mentally healthy.
Those participants aged less than 40 and greater than 80 years with chronic inflammatory disease, viral or bacterial infection, mental illness, liver, and renal dysfunction, hemorrhage, and malignant or neurogenic diseases were excluded.
Data collection
Basic information (age, sex, marital status, and history of smoking, alcohol drinking, and heart disease), physical characteristics (body mass index [BMI], heart rate, and blood pressure), biochemical factors (Table S1), and heart diagnostic report (ECG and echocardiography including left ventricular ejection fraction [LVEF]) were collected from the Hospital Information System (HIS).
Sample collection and biochemical analysis
Peripheral venous blood (4 mL) was drawn from the antecubital vein on the second day of admission. After centrifugation at 1000× g for 20 min, serum samples were aliquoted and stored at −80°C. All samples were thawed only once. Serum HMGB1 was determined using a commercially available enzyme‐linked immunosorbent assay kit (Wuhan USCN Business Co.) according to the provided protocol. The HMGB1 levels were calculated by reading absorbance at 450 nm in a spectrophotometer.
Other biochemical parameters listed in Table S1 were analyzed in our hospital's clinical laboratory according to standard protocols.
Ethics statement
This study was reviewed and approved by the Medical Ethics Committee of the Third Xiangya Hospital of Central South University, and was carried out in strict accordance with the committee's ethical guidelines (Approval No. 2021‐S161). Informed consent was obtained from all participants. All data were collected anonymously from the HIS and all authors ensured the confidentiality of patient data.
Statistical analysis
Statistical analysis was performed using SPSS version 20 (SPSS Inc.) and GraphPad Prism 6 (GraphPad). Quantitative data were analyzed using two‐tailed Student's t‐test or one‐way analysis of variance with least significant difference post hoc tests to compare statistical differences between and among the groups. Categorical data are presented as numbers and percentages and compared using the Chi‐square test or Fisher's exact test. Multiple‐variable regression analysis was performed to evaluate the correlation of biochemical variables with serum HMGB1. Additionally, a general linear model regression analysis was performed on the categorical data to evaluate the correlation with serum HMGB1. A receiver operating characteristic curve (ROC) analysis was performed to compare the area under the curve (AUC) for the sensitivity and specificity of each variable in different disease groups. A p value less than 0.05 was considered statistically significant.
RESULTS
Baseline features of study subjects
A total of 207 participants were enrolled in this study, including 50 healthy controls, 60 patients with HF−AMI, 55 patients with AMI−HF, and 42 patients with AMI+HF. The baseline demographic and clinical characteristics of the four study groups are shown in Table 1. There were no statistically significant differences in sex, age, BMI, and marital status among the four study groups. Compared to the control group, all three patient groups had significantly higher percentages of risk factors including hypertension, previous heart problem, diabetes, smoking, and drinking. In addition, all three disease groups had significantly higher heart rates and significantly lower LVEF than the control group.
TABLE 1.
Baseline demographic and clinical characteristics of study subjects.
| Variable | Control | HF−AMI | AMI−HF | AMI+HF |
|---|---|---|---|---|
| No. of patients | 50 | 60 | 55 | 42 |
| Male, % | 67.2 | 67.8 | 73.3 | 72.4 |
| Age, years | 51.6 ± 6.6 | 57.5 ± 10.1 | 55.7 ± 10.6 | 56.6 ± 11.5 |
| BMI, kg/m2 | 23.5 ± 2.1 | 24.3 ± 3.7 | 25.1 ± 2.8 | 24.4 ± 3.6 |
| Married, % | 100 | 100 | 100 | 100 |
| Hypertension, % | 10.0 | 63.7a,c | 57.8a | 71.4a,c |
| Previous heart problem, % | 0 | 79.3a,c | 52.5a | 60.4a,b |
| Diabetes, % | 7.4 | 35.4a | 42.3a | 51.1a,b |
| Smoking, % | 31.3 | 61.7a | 64.5a | 65.3a |
| Drinking, % | 3.1 | 60.7a,c | 43.5a | 40.4a,b |
| Heart rate, bpm | 75.2 ± 5.6 | 127.5 ± 26.3a,c | 103.6 ± 12.3a | 121.9 ± 14.5a,c |
| LVEF, % | 67.7 ± 5.6 | 45.03 ± 14.6a,c | 54.9 ± 11.5a | 45.4 ± 13.1a,c |
Note: Data are presented as the mean ± standard deviation (SD) or n (%). a p <0.01 vs. control; b p <0.05 vs. HF−AMI; c p <0.05 vs. AMI−HF.
Abbreviations: AMI−HF, acute myocardial infarction without heart failure; AMI+HF, acute myocardial infarction with heart failure; BMI, body mass index; bpm, beats per minute; HF−AMI, heart failure without acute myocardial infarction; LVEF, left ventricular ejection fraction.
Elevated serum HMGB1 levels in patients
When compared to the control group, serum HMGB1 levels in all three disease groups were significantly elevated (p values < 0.0001; Figure 1). Among the three disease groups, the AMI+HF patient group had the highest serum HMGB1 levels (20.2 ± 5.8 ng/mL), followed by the AMI−HF group (16.5 ± 5.7 ng/mL) and the HF−AMI group (11.8 ± 2.8 ng/mL). More precisely, the serum HMGB1 levels were significantly increased from the HF−AMI group to the AMI−HF group (p < 0.0001) and then to the AMI+HF group (p = 0.013; Figure 1). In ROC analysis of HMGB1, the AUCs of the AMI+HF, AMI−HF, and HF−AMI groups were 0.888, 0.869, and 0.861, respectively, which were statistically significant compared to the control group (Figures S1–S3, Tables S2–S4). These data suggest that circulating HMGB1 levels rise in patients with AMI or HF and are further elevated in patients with both AMI and HF.
FIGURE 1.
Serum HMGB1 levels in different study subjects. Data are presented as the mean ± SD. *p < 0.05 and ****p < 0.0001. AMI, acute myocardial infarction; HF, heart failure.
Evaluation of peripheral inflammatory biomarkers
Further blood biochemical tests were performed to evaluate peripheral inflammatory biomarkers, including ESR, hs‐CRP, total white blood cell (TWBC) count, absolute neutrophil count (ANC), absolute monocyte count (AMC), absolute lymphocyte count (ALC), and uric acid (UA). The results showed that all inflammatory biomarkers tested in the three disease groups (except UA in the AMI−HF group) were significantly higher than those in the control group (all p values <0.01; Table S5). Among the disease groups, almost all peripheral inflammatory biomarkers (except for ALC and UA) were increased from the HF−AMI group to the AMI−HF group and then to the AMI+HF group, and the change trend was consistent with that of HMGB1.
In ROC analysis, all observed inflammatory biomarkers showed significant sensitivity and specificity for AMI+HF, AMI−HF, and HF−AMI, except ALC in AMI+HF, and TWBC in HF−AMI (Figures S1–S3, Table S2–S4). These results suggest HMGB1 may be considered as the elevated inflammatory markers in patients with AMI and HF, and may have the role of inflammation in the pathogenesis of CVDs, which needs to carry further research.
Evaluation of serum cardiac biomarkers
In addition, we evaluated serum cardiac biomarkers, as shown in Table S6. All tested cardiac biomarkers of the AMI−HF and AMI+HF patient groups (except NT‐proBNP in the AMI−HF group) were significantly increased compared to the control group (all p values <0.05). It was also found that the levels of NT‐proBNP, LDH, and ALT in the HF−AMI patient group were significantly increased compared to the control group (all p values <0.05).
Among the three disease groups, the serum levels of MYO, AST, CK, CKMB, cTnI, and LDH in the AMI+HF and AMI−HF groups were significantly higher than those in the HF−AMI group (all p values <0.05). There were no differences between the two AMI groups for cardiac biomarkers MYO, AST, CK, CKMB, and cTnI. For ALT, there was no difference among the three disease groups. Regarding NT‐proBNP, its serum levels in the two HF groups were significantly higher than those in the AMI−HF group (both p values <0.001).
In ROC analysis, all tested serum cardiac biomarkers showed significant sensitivity and specificity for AMI+HF, AMI−HF, and HF−AMI (Figures S1–S3, Tables S2–S4). These data confirm that serum cardiac biomarkers are generally elevated in patients with AMI, and LDH and ALT are also elevated in patients with HF.
Correlation between serum HMGB1 and inflammatory biomarkers
Multiple‐variable regression analysis showed that there was no significant correlation between HMGB1 and any tested inflammatory biomarkers in the control group. However, serum HMGB1 levels were significantly positively correlated with the levels of hs‐CRP, TWBC, and ANC in both AMI−HF and AMI+HF patient groups. On the other hand, among the inflammatory biomarkers tested, only UA was significantly positively correlated with HMGB1 in the HF−AMI and AMI+HF patient groups (Table 2). These data support the involvement of HMGB1 in AMI inflammation through correlation with hs‐CRP, TWBC, ANC, and UA in HF with/without AMI.
TABLE 2.
Multiple‐variable regression analysis of serum HMGB1 with inflammatory biomarkers.
| Variable | Correlation | Control | HF−AMI | AMI−HF | AMI+HF |
|---|---|---|---|---|---|
| ESR | β coefficients | 0.075 | 0.268 | 0.127 | 0.074 |
| p value | 0.617 | 0.231 | 0.129 | 0.284 | |
| hs‐CRP | β coefficients | −0.024 | 0.222 | 0.243 | 0.250 |
| p value | 0.886 | 0.315 | 0.016* | 0.001* | |
| TWBC | β coefficients | −0.690 | 0.172 | 0.421 | 0.390 |
| p value | 0.668 | 0.357 | 0.027* | 0.022* | |
| ANC | β coefficients | −0.125 | 0.146 | 0.275 | 0.375 |
| p value | 0.461 | 0.542 | 0.141 | 0.016* | |
| AMC | β coefficients | −0.012 | −0.300 | 0.091 | −0.066 |
| p value | 0.936 | 0.158 | 0.304 | 0.326 | |
| ALC | β coefficients | −0.229 | 0.040 | −0.020 | −0.099 |
| p value | 0.152 | 0.802 | 0.781 | 0.120 | |
| UA | β coefficients | −0.227 | 0.361 | 0.006 | −0.186 |
| p value | 0.150 | 0.038* | 0.103 | 0.004* |
Note: Model summary R 2 = 0.357 (control), 0.451 (HF−AMI), 0.875 (AMI−HF), 0.916 (AMI+HF).
Abbreviations: AMI−HF, acute myocardial infarction without heart failure; AMI+HF, acute myocardial infarction with heart failure; ALC, absolute lymphocyte count; AMC, absolute monocyte count; ANC, absolute neutrophil count; ESR, erythrocyte sedimentation rate; HF−AMI, heart failure without acute myocardial infarction; TWBC, total white blood cell; UA, uric acid.
p ≤ 0.05 considered as significant.
Correlation between serum HMGB1 and cardiac biomarkers
Multiple‐variable regression analysis showed that there was no correlation between HMGB1 and any tested cardiac biomarkers in the control group. However, NT‐proBNP, cTnI, CKMB, and CK showed a significant positive correlation with HMGB1 in both AMI−HF and AMI+HF patient groups. Although ALT was found to have a significant positive correlation with HMGB1 in the AMI−HF patient group, it was not significant in other patient groups. Interestingly, NT‐proBNP and cTnI were significantly correlated with HMGB1 in all disease groups (Table 3). These data indicate that HMGB1 may have a role in the pathogenesis of AMI and HF by correlating with NT‐proBNP, cTnI, CKMB, and CK.
TABLE 3.
Multiple‐variable regression analysis of serum HMGB1 with cardiac biomarkers.
| Variable | Correlation | Control | HF−AMI | AMI−HF | AMI+HF |
|---|---|---|---|---|---|
| MYO | β coefficients | 0.077 | −0.067 | −0.090 | −0.200 |
| p value | 0.637 | 0.580 | 0.265 | 0.147 | |
| NT‐ProBNP | β coefficients | 0.074 | 0.715 | 0.216 | 0.355 |
| p value | 0.637 | <0.001* | 0.028* | <0.001* | |
| CTnI | β coefficients | −0.078 | 0.213 | 0.393 | 0.248 |
| p value | 0.603 | 0.023* | 0.007* | 0.016* | |
| CKMB | β coefficients | 0.142 | −0.036 | 0.263 | 0.261 |
| p value | 0.371 | 0.729 | 0.026* | 0.023* | |
| CK | β coefficients | −0.082 | 0.038 | 0.294 | 0.520 |
| p value | 0.615 | 0.811 | 0.032* | 0.002* | |
| LDH | β coefficients | 0.026 | 0.034 | −0.043 | −0.071 |
| p value | 0.872 | 0.759 | 0.437 | 0.552 | |
| AST | β coefficients | −0.306 | −0.046 | −0.152 | −0.020 |
| p value | 0.073 | 0.807 | 0.116 | 0.887 | |
| ALT | β coefficients | 0.105 | −0.044 | 0.138 | 0.019 |
| p value | 0.511 | 0.778 | 0.023* | 0.826 |
Note: Model summary R 2 = 0.378 (control), 0.618 (HF−AMI), 0.919 (AMI−HF), 0.808 (AMI+HF).
Abbreviations: AMI−HF, acute myocardial infarction without heart failure; AMI+HF, acute myocardial infarction with heart failure; ALT, alanine aminotransferase; AST, aspartate aminotransferase; HF−AMI, heart failure without acute myocardial infarction.
p ≤ 0.05 considered as significant.
Relationship between serum HMGB1 and cardiovascular risk factors
HMGB1 was not associated with sex, age, BMI, marital status, smoking, and heart rate (Tables 4 and 5). However, hypertension, diabetes, and previous heart problem were all significantly associated with serum HMGB1 levels (all p values <0.05). Notably, alcohol drinking was found to be significantly correlated with HMGB1 only in patients with AMI+HF. In addition, LVEF had a significant negative correlation with HMGB1 in all three patient groups (all p values <0.05), but not in the control group (Table 5). These data indicate that serum HMGB1 is related to cardiovascular risk factors, such as hypertension, diabetes, drinking habit, and heart disease history, but is negatively related to LVEF.
TABLE 4.
General linear model regression analysis of categorical cardiovascular risk factors depending on serum HMGB1.
| Risk factor | Control | HF−AMI | AMI−HF | AMI+HF | ||||
|---|---|---|---|---|---|---|---|---|
| Value level | p value | Value level | p value | Value level | p value | Value level | p value | |
| Sex | Male (30) | 0.827 | Male (42) | 0.984 | Male (41) | 0.496 | Male (28) | 0.430 |
| Female (20) | Female (18) | Female (14) | Female (14) | |||||
| Marital | Yes (50) | ‐ | Yes (60) | ‐ | Yes (55) | ‐ | Yes (42) | ‐ |
| No (0) | No (0) | No (0) | No (0) | |||||
| Hypertension | Yes (50) | ‐ | Yes (30) | 0.038* | Yes (28) | 0.036* | Yes (18) | <0.001* |
| No (0) | No (30) | No (27) | No (24) | |||||
| Diabetes | Yes (50) | ‐ | Yes (20) | 0.039* | Yes (26) | 0.006* | Yes (22) | 0.014* |
| No (0) | No (40) | No (29) | No (20) | |||||
| Smoking | Yes (16) | 0.302 | Yes (39) | 0.859 | Yes (35) | 0.068 | Yes (26) | 0.960 |
| No (34) | No (21) | No (20) | No (16) | |||||
| Drinking | Yes (50) | ‐ | Yes (39) | 0.744 | Yes (27) | 0.066 | Yes (18) | 0.031* |
| No (0) | No (21) | No (28) | No (24) | |||||
| Previous heart problem | Yes (50) | ‐ | Yes (40) | 0.015* | Yes (27) | <0.001* | Yes (25) | <0.001* |
| No (0) | No (20) | No (28) | No (17) | |||||
Note: Model summary R 2 = 0.013 (control), 0.419 (HF−AMI), 0.674 (AMI−HF), 0.818 (AMI+HF).
Abbreviations: AMI−HF, acute myocardial infarction without heart failure; AMI+HF, acute myocardial infarction with heart failure; HF−AMI, heart failure without acute myocardial infarction.
p ≤ 0.05 considered as significant.
TABLE 5.
Multiple‐variable regression analysis of serum HMGB1 with cardiovascular risk factors.
| Variable | Correlation | Control | HF−AMI | AMI−HF | AMI+HF |
|---|---|---|---|---|---|
| Age | β coefficients | 0.066 | 0.173 | 0.103 | 0.256 |
| p value | 0.668 | 0.195 | 0.436 | 0.108 | |
| BMI | β coefficients | 0.178 | 0.012 | −0.083 | 0.233 |
| p value | 0.247 | 0.088 | 0.532 | 0.135 | |
| Heart rate | β coefficients | −0.057 | −0.054 | 0.036 | 0.106 |
| p value | 0.701 | 0.688 | 0.783 | 0.468 | |
| LVEF | β coefficients | 0.124 | −0.306 | −0.406 | −0.451 |
| p value | 0.401 | 0.033* | 0.004* | 0.005* |
Note: Model summary R 2 = 0.217 (control), 0.116 (HF−AMI), 0.184 (AMI−HF), 0.335 (AMI+HF).
Abbreviations: AMI−HF, acute myocardial infarction without heart failure; AMI+HF, acute myocardial infarction with heart failure; BMI, body mass index; HF−AMI, heart failure without acute myocardial infarction; LVEF, left ventricular ejection fraction.
p ≤ 0.05 considered as significant.
DISCUSSION
This study aimed to measure serum HMGB1 levels in patients with AMI and/or HF and evaluate their relationship with peripheral inflammatory biomarkers and cardiac biomarkers, which have not been reported previously. Our results indicate that three groups of patients, specifically those with AMI+HF, had significantly higher levels of serum HMGB1. All tested inflammatory biomarkers, except UA, were significantly positively correlated with HMGB1 in patients with AMI, but not in non‐AMI patients. Moreover, all tested cardiac biomarkers, except NT proBNP in AMI−HF, were significantly higher in patients with AMI than in control individuals. The levels of MYO, cTnI, CKMB, CK AST, and ALT in patients with HF−AMI did not change significantly compared to control individuals. However, they (except ALT) were significantly lower than those in patients with AMI. Further, the levels of NT‐proBNP, and cTnI were significantly correlated with HMGB1 levels in all types of patients. Except for MYO, LDH, AST, and ALT, all cardiac biomarkers tested in AMI−HF and AMI+HF showed a significant correlation with HMGB1. Among the risk factors, hypertension, diabetes, previous heart problem, and reduced LVEF had a significant correlation with HMGB1 in all disease groups.
Raucci et al. 12 reported that serum HMGB1 is elevated in different CVDs. In the pathogenesis of CVDs, extracellular or cytoplasmic HMGB1 can increase inflammation, induce myocardial ischemia, myocarditis, cardiomyopathies, hypertrophy, and cardiomyocyte apoptosis, stimulate cardiac fibroblast activity, and reduce contractility. Interestingly, our results revealed that serum HMGB1 in patients with AMI−HF was higher than that in patients with HF−AMI but lower than that in patients with AMI+HF, implying that HMGB1 is relatively closely associated with AMI and plays an important role in the early stage of AMI. Furthermore, serum HMGB1 continues to rise, reaching a peak in patients with end‐stage AMI+HF. This finding is supported by the report of Volz et al., 13 who observed that elevated serum HMGB1 enhances myocardial damage, further leading to the development of HF. Assuming that increased circulating HMGB1 promotes AMI and aggravates its severity, it is expected to develop into AMI‐mediated HF (AMI+HF). Therefore, HMGB1 may be a predictor of adverse outcomes in patients with AMI+HF.
Goyal and colleagues 22 have listed ESR, WBC count, monocyte count, neutrophil count, UA, and hs‐CRP as blood biomarkers for cardiac inflammation. Our study demonstrated that these inflammatory markers are significantly elevated in patients, particularly in patients with AMI. ESR is a well‐known marker for fibrinogen and immunoglobulin‐mediated erythrocyte accumulation during inflammation and is considered a diagnostic criterion for CVDs. 23 , 24 Erikssen et al. 23 reported that elevated ESR levels are associated with cardiovascular risk and mortality. Similarly, we have observed elevated ESR levels in patients with AMI and/or HF; the ESR levels of the three patient groups were generally AMI+HF greater than AMI−HF greater than HF−AMI. Because HF is the end‐stage of heart disease and the ESR level was the highest in patients with AMI+HF, it can be inferred that ESR begins to rise in patients with AMI−HF and reaches its peak after developing HF.
It has been reported that patients with CVD with and without any previous cardiac disease have elevated hs‐CRP. 25 , 26 Fascinatingly, our results confirmed the elevation of hs‐CRP in all patient groups. Similar to ESR, the rise in hs‐CRP levels in the disease groups was AMI+HF greater than AMI−HF greater than HF−AMI. The regression analysis showed that for ESR and hs‐CRP, the hs‐CRP was significantly positively correlated with HMGB1 in patients with AMI−HF and patients with AMI+HF but not in patients with HF−AMI. Thus, these findings indicate that HMGB1 is highly correlated with hs‐CRP through the inflammatory response in patients with AMI with or without HF. In fact, in addition to CVDs, the positive correlation between serum HMGB1 and CRP has also been reported in other diseases, including juvenile idiopathic arthritis. 27
As chronic inflammation is a culprit of CVDs, it is not surprising to observe patients with increased systemic inflammation markers, such as TWBC, ANC, AMC, and ALC. Consistent with the changes in ESR and hs‐CRP, the elevated levels of WBC count in three patient groups were AMI+HF greater than AMI−HF greater than HF−AMI. Furthermore, there were significant differences in WBC and ANC counts among the three patient groups and two markers had a significant positive correlation with HMGB1 in patients with AMI−HF and patients with AMI+HF. More importantly, TWBC and ANC did not correlate with HMGB1 in patients with HF−AMI. In contrast, AMC and ALC did not show any significant differences and correlations with HMGB1 in any of the study groups. Therefore, WBC and ANC rather than AMC and ALC are associated with HMGB1 to induce signs of inflammation in AMI with or without HF. Based on our findings and previous reports that increased WBC, monocytes, and neutrophils are linked to CVDs and inflammation, 28 , 29 , 30 it is speculated that high HMGB1 levels may be a biological factor influencing inflammation in AMI−HF and AMI+HF, with a positive association with TWBC and ANC, but not with AMC and ALC.
UA is the end product of purine synthesis and has been linked to hypertension and metabolic syndrome. 25 , 31 Although serum UA is widely used for gout diagnosis, cross‐sectional studies have been conducted to investigate the influence of increased serum UA on CVDs. Low‐grade inflammation has been associated with chronic conditions, including CVDs. 31 However, previous studies did not demonstrate an independent correlation between UA and CVDs, thus questioning its role in the inflammation and pathogenesis of CVDs. 31 Our study found that patients with HF−AMI had the highest levels of UA and there was a significant positive correlation between UA and HMGB1 in both HF−AMI and AMI+HF. Apart from its association with UA, HMGB1 has little association with inflammation, as none of the other major inflammatory parameters showed any significant association with it in patients with HF. Our findings are consistent with Zalawadiya and colleagues's observations that colchicine harbors the potential to reduce CVD risk in patients with gout. This risk reduction was attributed to the anti‐inflammatory effect of colchicine rather than its effect on serum UA, implying that UA has a limited inflammatory role in CVDs. 31 Thus, it appears that HMGB1‐mediated inflammation begins at the stage of AMI−HF and becomes progressively more severe. Therefore, HMGB might be considered a risk factor for HF, because we did not find such elevated HMGB1 and inflammatory indicators in patients with HF−AMI.
In the current study, the high degrees of MYO and AST in the three patient groups were in the order of AMI−HF greater than AMI+HF greater than HF−AMI. Gibler and colleagues 32 reported that heart attack and severe muscle damage release MYO into the bloodstream to reduce oxygen supply to the muscle, which is considered an early indicator of AMI. 32 Our findings support the previous study and found elevated MYO in patients with AMI independent of HF. However, this study did not find any significant correlation between HMGB1 and MYO in any of the study groups. Ozawa et al. 19 reported that HMGB1 could affect AST and increase its levels during cardiac ischemia–reperfusion injury in rats. However, we did not find any correlation between AST with HMGB1 in any of the study groups. These findings suggest that elevated levels of MYO and AST in disease groups are independent of HMGB1.
In addition, HMGB1, CK, and CK‐MB were significantly higher in patients with AMI−HF and patients with AMI+HF than in patients with HF−AMI and control individuals. Moreover, HMGB1 was strongly correlated with CK and CK‐MB in patients with AMI−HF and patients with AMI+HF, but not in patients with HF−AMI. These findings support Jin et al. 33 and Cao et al., 34 who found a significant correlation between HMGB1 with CK and CK‐MB in myocardial injury and mycoplasma pneumonia. cTnI is more specific and sensitive to myocardial injury and infarction. 35 We found a significant positive correlation of cTnI with HMGB1 in patients with AMI−HF and patients with AMI+HF. Moreover, cTnI in patients with HF−AMI was also significantly positively correlated with HMGB1, because a small number of patients with HF−AMI without MI had slightly higher cTnI levels (note: no significant difference was noticed in cTnI between the control and HF−AMI groups) and elevated HMGB1 levels. Our findings on cTnI support a previous report which found a strong association of cTnI with HMGB1 in patients with coronary artery disease. 15 These data suggest that elevated HMGB1 can serve as a predictive marker for AMI−HF, whereas simultaneous elevation of cTnI and HMGB1 in AMI−HF can be considered a risk factor for AMI‐mediated HF.
The highest levels of NT proBNP and decreased LVEF have been noticed in patients with AMI+HF, but there were no statistically significant differences in NT proBNP and LVEF between patients with AMI+HF and patients with HF−AMI, supporting previous reports by Salah and colleagues 36 on the involvement of NT‐proBNP and reduced ejection fraction in the prognosis of HF. Although patients with AMI−HF had higher HMGB1 and significantly lower NT‐proBNP than patients with HF−AMI, both AMI−HF and HF−AMI patient groups showed a significant correlation between NT‐proBNP and HMGB1. This is because few patients with AMI−HF with above normal levels of NT‐proBNP had elevated HMGB1, and that few patients with HF−AMI with above normal levels of HMGB1 had elevated NT‐proBNP. Additionally, HMGB1 and NT‐proBNP were highest in patients with AMI+HF, so there may be a strong positive correlation between NT‐proBNP and HMGB1, not only in patients with HF but also in patients with AMI. Moreover, because no significant difference in NT‐proBNP was found between patients with AMI−HF and healthy controls, HMGB1 may serve as a new marker to differentiate patients with AMI and patients with HF by determining HMGB1 and NT‐proBNP.
Compared to the control group, the LDH levels of the three patient groups were significantly elevated, and the LDH levels of the three patient groups were AMI+HF greater than AMI−HF greater than HF−AMI. LDH was the only parameter with significantly different values in all disease groups compared to the control group (Table S6). Although between‐group comparison of HMGB1 and LDH showed significant differences, the association of LDH with HMGB1 was not significant in any patient group (Table 3). Additionally, ALT was positively correlated with HMGB1 only in patients with AMI, but not in patients with HF−AMI and patients with AMI+HF. Although HMGB1 has been found to have a strong positive correlation with LDH and AST during the development of cardiac ischemia–reperfusion damage in rats, 19 we found that ALT was correlated with HMGB1 only in patients with AMI.
Among the cardiovascular risk factors, hypertension, diabetes, alcohol consumption, previous heart disease, and LVEF were significantly associated with elevated HMGB1 (Table 4). Therefore, these several cardiovascular risk factors are considered to be risk factors associated with HMGB1, whereas sex, age, smoking, BMI, marital status, and heart rate are not risk factors associated with HMGB1.
Our findings suggest that HMGB1 may be considered an active disease parameter that promotes CVDs, especially AMI and HF. This study revealed that elevated HMGB1 in patients with AMI+HF and patients with AMI−HF has a correlation with the inflammatory response in cardiomyocytes 12 , 14 as well as with elevated ESR, CRP, WBC, neutrophils, and monocytes. HMGB1 levels were higher in patients with AMI−HF than in healthy controls and patients with HF−AMI but lower than in patients with AMI+HF, and similar results were seen for NT‐proBNP, cTnI, CK‐MB, and CK. The cTnI and CK‐MB are two established biomarkers of myocardial injury 37 and showed a strong correlation with HMGB1 in this study. Therefore, this may suggest that HMGB1 may initially be elevated in AMI, but not in HF, and ultimately elevated in end‐stage AMI+HF. Besides, patients with AMI−HF had the highest MYO, AST, and CK, but there were no significant differences compared to patients with AMI+HF. Because HMGB1 was also higher in both patients with AMI−HF and patients with AMI+HF and positively correlated with NT‐proBNP, cTnI, CK‐MB, and CK, these parameters are considered biomarkers for AMI. 32 , 37 , 38 Taken together, it can be considered that HMGB1 levels increase in AMI and peak in end‐stage AMI+HF. In light of this, HMGB1 can be suggested as a biomarker of inflammation 39 to detect AMI and possibly to differentiate HF−AMI from AMI+HF and AMI−HF, although further studies are needed to verify our findings.
However, this study has limitations as the results were generated mainly based on basic clinical diagnostic reports, small sample size, and specific patient population. Moreover, this study only showed relevant inflammatory indicators, cardiac enzymes/proteins, and risk factors associated with elevated HMGB1, whereas the underlying mechanisms and pathophysiology are unclear. It is unclear how HMGB1 was mechanistically elevated in patients with AMI−HF and patients with AMI+HF. Therefore, further research is needed to determine the role of HMGB1 in AMI−HF and AMI+HF through genetic, pharmacological, and immunologic manipulation of HMGB1 activity in vitro and in vivo. We believe that HMGB1 will be a potential biomarker and a new therapeutic target for CVDs.
CONCLUSIONS
Our quantitative and qualitative analysis of patient data suggests that elevated circulating HMGB1 is most likely to be an active biomarker in patients with AMI−HF and AMI+HF, but not in patients with HF−AMI. Additionally, HMGB1 is an important biological and biochemical factor that has a significant correlation with AMI−HF and AMI+HF, but not HF−AMI. Furthermore, our study shows that HMGB1 correlates with cardiac biomarkers commonly used to detect MI and HF and with major inflammatory indicators and risk factors for CVDs. These findings will prompt further studies to evaluate HMGB1 as a biomarker for AMI−HF and AMI+HF to differentiate AMI with or without HF.
AUTHOR CONTRIBUTIONS
A.W. wrote the manuscript. X.Z., and X.T. designed the research. A.W. performed the research. A.W., and Q.Y. analyzed the data. X.Z., J.W., and Z.Z. contributed new reagents/analytical tools.
FUNDING INFORMATION
This work was supported by National Natural Science Foundation of Hunan (2020JJ4850 to X.T.)
CONFLICT OF INTEREST STATEMENT
All authors declared no competing interests for this work.
Supporting information
Data S1
Wahid A, Wen J, Yang Q, Zhang Z, Zhao X, Tang X. Serum HMGB1 is a biomarker for acute myocardial infarction with or without heart failure. Clin Transl Sci. 2023;16:2299‐2309. doi: 10.1111/cts.13630
Contributor Information
Xiexiong Zhao, Email: 208302021@csu.edu.cn.
Xiaohong Tang, Email: tangxh007007@163.com.
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Associated Data
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Supplementary Materials
Data S1