Serum sST2, IL-33, and Hcy Expression in Older Adults Patients with Myocardial Infarction and Their Predictive Value for MACE

Introduction

Acute myocardial infarction (AMI) remains a critical global health burden, particularly in the elderly population where it accounts for >60% of cases with higher mortality and complication rates.^1–3 Although early revascularization (eg, PCI) has improved acute outcomes,^4,5 long-term prognosis remains suboptimal due to frequent major adverse cardiovascular events (MACE).^6,7 Current biomarkers like troponins and CRP lack specificity for predicting MACE, which involves multifactorial pathways including inflammation and oxidative stress.^8,9

Emerging evidence implicates soluble suppression of tumorigenicity 2 (sST2) and its ligand IL-33 in myocardial remodeling via the IL-33/ST2 axis,^10–12 while homocysteine (Hcy) links endothelial dysfunction to atherosclerosis progression.^13–15 Notably, while these markers individually correlate with AMI severity,^16,17 their combined predictive value for MACE—especially in elderly patients with complex coronary stenosis—remains unexplored.

We hypothesize that integrating sST2 (inflammation/fibrosis), IL-33 (anti-inflammatory regulation), and Hcy (metabolic stress) could synergistically improve MACE prediction. This study retrospectively analyzes 143 elderly AMI patients to: (1) Determine associations between serum sST2/IL-33/Hcy levels and coronary stenosis severity, and (2) Evaluate their combined prognostic utility for MACE. Our findings aim to address gaps in risk stratification and guide personalized management for this high-risk cohort.

Materials and Methods

Study Population

This retrospective study enrolled 143 elderly AMI patients (≥65 years) treated at our hospital from June 2022 to June 2024. The elderly population was specifically selected due to their distinct pathophysiological features (eg, frailty, multi-vessel disease) and higher susceptibility to MACE compared to younger cohorts.¹⁸

Inclusion Criteria

(1) Diagnosis of AMI (STEMI/NSTEMI) per Fourth Universal Definition of Myocardial Infarction;¹⁹ (2) First-time AMI without prior revascularization; (3) Admission within 24 hours of symptom onset; (4) Complete clinical data including medication history (antiplatelet agents, statins), lifestyle factors (smoking, alcohol use), and socioeconomic status (education level, income).

Exclusion Criteria

(1) Coma/severe cognitive impairment; (2) Prior CABG/stent implantation; (3) Concurrent cardiomyopathy/valvular disease; (4) Active cancer/chronic inflammatory diseases. Patients were divided into two groups based on whether major adverse cardiac events (MACE) occurred: Group A (n=56) for patients without MACE and Group B (n=87) for those with MACE. This study strictly adhered to ethical principles, was approved by the Medical Ethics Committee of Henan Provincial People’s Hospital (Approval number: 2022–168), and complied with the relevant requirements of the Declaration of Helsinki and domestic ethical regulations.

Biomarker Measurement

Blood sampling: Fasting venous blood was collected within 6 hours post-admission using heparinized tubes. Serum was separated by centrifugation (3000 rpm ×10 min) and stored at −80°C until analysis. Detection Methods: The concentrations of serum sST2 (Jiangsu Jiyide Biotechnology Co., Ltd., Cat. No. J21994), IL-33 (Jiangsu Jiyide Biotechnology Co., Ltd., Cat. No. J2179), and Hcy (Jiangsu Jiyide Biotechnology Co., Ltd., Cat. No. J20877) were measured using enzyme-linked immunosorbent assay (ELISA). The standard experimental procedures were strictly performed according to the instructions provided by the assay kits. Precautions: During the detection process, strict control was maintained over environmental temperature, reagent concentrations, and operational consistency to minimize experimental errors as much as possible.

Coronary Artery Stenosis Assessment

Two blinded interventional cardiologists independently evaluated stenosis severity using the Gensini scoring system.²⁰ All patients underwent selective coronary angiography (CAG) with a Philip Allura Xper FD10 system, performed by an experienced team.

Scoring Protocol: Stenosis severity was graded as follows: <25% (1 point), 25–50% (2 points), 50–75% (4 points), 75–90% (8 points), 90–99% (16 points), and total occlusion (32 points). Vessel-specific coefficients were applied: posterior lateral branch and 2nd diagonal branch (×0.5); 1st diagonal branch, distal LAD, posterior branch, RCA, PDA, obtuse marginal, posterior LV branch, distal LCX, and apical branch (×1.0); mid-LAD (×1.5); proximal LCX and proximal LAD (×2.5); left main artery (×5.0). The total score was calculated as Σ (stenosis score × vessel coefficient). Severity was classified as mild (<24, n=41), moderate (24–49, n=58), and severe (>49, n=44).

MACE Definition

MACE includes the following conditions: Arrhythmia: Ventricular tachycardia/fibrillation (sustained >30 sec), High-grade AV block (Mobitz II or third-degree), Symptomatic bradycardia (<40 bpm with syncope), Excluded: Isolated premature contractions, asymptomatic sinus bradycardia. Recurrent angina: Persistent chest pain symptoms with limited response to anti-angina treatment. Heart failure: Repeated hospitalizations due to worsening cardiac function. Non-fatal recurrent myocardial infarction: Re-elevation of myocardial injury biomarkers accompanied by typical clinical manifestations and electrocardiogram changes. Cardiac death: Death directly caused by AMI or its complications. All MACE events were confirmed through comprehensive analysis of clinical data by an independent panel of cardiology experts.

Statistical Analysis

Statistical analyses were performed using SPSS 25.0 (IBM Corp) and R 4.3.1 for advanced modeling. Categorical variables were expressed as percentages (%) and analyzed by χ²-test or Fisher’s exact test for small sample sizes. Continuous variables were reported as mean ± SD or median (IQR) based on normality (assessed by Shapiro–Wilk test) and compared via independent t-test or Mann–Whitney U-test. To address potential selection bias inherent in retrospective studies, propensity score matching (PSM) was implemented using a 1:1 nearest-neighbor algorithm with a caliper of 0.1. Matching covariates included age, sex, Gensini score, hypertension, diabetes, and statin use, achieving balanced groups (standardized mean difference <0.1). Spearman correlation analyzed associations between biomarkers (sST2, IL-33, Hcy) and Gensini scores. Multivariable logistic regression adjusted for confounders (medications, smoking, socioeconomic status) with backward elimination (retention threshold: p<0.10). For multiple comparisons in biomarker-MACE analyses, Bonferroni correction was applied, setting the significance threshold at α=0.017 (0.05/3 biomarkers). Receiver operating characteristic (ROC) curves evaluated individual/combined biomarker performance, with DeLong’s test comparing AUCs. Sensitivity analyses excluded patients with incomplete follow-up to ensure robustness. All tests were two-tailed, with p<0.05 considered significant pre-correction and p<0.017 post-Bonferroni adjustment.

Results

Comparison of Baseline Information

The comparison of gender, age, BMI, history of alcohol consumption, smoking history, comorbidities, Killip cardiac function classification and AMI subtype between Group A and Group B showed no significant differences (P > 0.05), indicating comparability (Table 1).

Table 1 Comparison of Baseline Information (, n [%])

Comparison of Serum sST2, IL-33, and Hcy Levels

The serum sST2 expression level in Group B (72.37±10.68) was higher than that in Group A (38.76±11.15) (P<0.05), as shown in Figure 1A; the serum IL-33 expression level in Group B (60.61±10.89) was higher than that in Group A (33.74±11.23) (P<0.05), as shown in Figure 1B; the serum Hcy expression level in Group B (32.76±4.15) was higher than that in Group A (15.38±4.62) (P<0.05), as shown in Figure 1C.

Figure 1 Comparison of levels of serum sST2, IL-33, and Hcy between Group A and Group B (). (A) Comparison of serum sST2 levels; (B) Comparison of serum IL-33 levels; (C) Comparison of serum Hcy levels. # represents P <0.05 compared with Group A. Abbreviations: sST2, serum soluble suppression of tumorigenicity 2; IL-33, interleukin-33; Hcy, homocysteine.

Comparison of Serum sST2, IL-33, and Hcy Levels Among Patients with Different Degrees of Coronary Stenosis

Among the 143 patients in the study, there were 41 cases of mild stenosis, 58 cases of moderate stenosis, and 44 cases of severe stenosis. The serum levels of sST2, IL-33, and Hcy were significantly higher in patients with moderate and severe stenosis compared to those with mild stenosis, and patients with severe stenosis had higher levels than those with moderate stenosis (P < 0.05) (Figure 2A–C).

Figure 2 Comparison of serum sST2, IL-33, and Hcy levels among patients with different degrees of coronary stenosis (). (A) The levels of sST2; (B) The levels of IL-33; (C) The levels of Hcy. a represents P <0.05 compared with mild stenosis. b represents P <0.05 compared with moderate stenosis. Abbreviations: sST2, serum soluble suppression of tumorigenicity 2; IL-33, interleukin-33; Hcy, homocysteine.

Relationship Between Serum sST2, IL-33, Hcy Levels and Coronary Stenosis

Spearman correlation analysis revealed a positive correlation between serum levels of sST2, IL-33, Hcy, and the degree of coronary stenosis (r=0.647, 0.659, 0.582, P < 0.05) (Figure 3A–C).

Figure 3 Scatter plot of the relationship between serum sST2, IL-33, Hcy levels and coronary stenosis degree. (A) sST2; (B) IL-33; (C) Hcy. Abbreviations: sST2, serum soluble suppression of tumorigenicity 2; IL-33, interleukin-33; Hcy, homocysteine.

Analysis of Factors Influencing the Occurrence of MACE in AMI Patients

Taking the occurrence of MACE in AMI patients as the dependent variable (yes = 1, no = 0), the statistically significant variables from Table 1 and Figure 1 were used as independent variables with assigned values (Table 2). A multivariate logistic regression analysis model was established, showing that serum sST2, IL-33, and Hcy levels were risk factors for MACE in AMI patients (P < 0.05) (Table 3).

Table 2 Variable Assignment Table

Table 3 Multivariate Logistic Regression Analysis of Factors Influencing MACE in AMI Patients

Predictive Value of Serum sST2, IL-33, and Hcy Levels for MACE in AMI Patients

During a median follow-up of 12 months (IQR: 6–18), MACE occurred at a median of 4.2 months post-AMI (range: 1–15 months). ROC curve analysis revealed that sST2 (optimal cut-off: 48.71 μg/L) predicted MACE with an AUC of 0.841 (95% CI: 0.762–0.915), sensitivity of 87.41%, and specificity of 77.62% (P < 0.001). IL-33 (cut-off: 47.24 ng/L) demonstrated slightly lower predictive performance (AUC = 0.803; sensitivity 84.62%, specificity 77.62%), while Hcy (cut-off: 28.65 μmol/L) showed the lowest AUC (0.729, sensitivity 80.42%, specificity 68.53%).

The combined detection of all three biomarkers significantly improved predictive efficacy, achieving an AUC of 0.910 (95% CI: 0.851–0.956) with sensitivity and specificity increasing to 88.11% and 90.91%, respectively, outperforming any single indicator (P < 0.001). (Figure 4).

Figure 4 ROC curve for the predictive diagnostic value of serum sST2, IL-33, and Hcy levels for MACE in AMI patients. Abbreviations: MACE, major adverse cardiovascular events; AMI, acute myocardial infarction; ROC, receiver operating characteristic; sST2, serum soluble suppression of tumorigenicity 2; IL-33, interleukin-33; Hcy, homocysteine.

Discussion

AMI is one of the most severe acute events in the cardiovascular system, with complex and diverse pathogenesis involving atherosclerosis, inflammatory response, metabolic disorders, myocardial cell damage, and repair.²¹ Although PCI and pharmacological interventions have significantly improved the overall survival rate of AMI patients, older adults patients remain a key and challenging group in AMI treatment due to a heavy burden of comorbidities, poor vascular conditions, and reduced compensatory ability.²² Older adults patients often suffer from chronic diseases such as diabetes and hypertension, which not only exacerbate the degree of coronary atherosclerosis but also increase the likelihood of severe complications during acute episodes and recovery periods, such as heart failure, malignant arrhythmias, and non-fatal recurrent myocardial infarction.²³ Furthermore, the weakened myocardial repair ability, reduced vascular elasticity, and microcirculation disorders in older adults patients increase the risk of myocardial under-perfusion, leading to disease progression and poor prognosis.²⁴ Therefore, rapidly and accurately identifying high-risk patients and formulating individualized treatment strategies is key to improving the prognosis of older adults AMI patients. This study retrospectively analyzed clinical data from 143 elderly patients with acute myocardial infarction (AMI) and found that serum sST2, IL-33, and Hcy levels were significantly associated with coronary artery stenosis severity and the occurrence of major adverse cardiovascular events (MACE). Moreover, the combined detection of these biomarkers demonstrated significantly higher predictive efficacy for MACE compared to individual markers (AUC = 0.910). These findings not only provide a novel perspective for risk stratification in elderly AMI patients but also lay a theoretical foundation for developing multi-target intervention strategies.

As a member of the IL-1 receptor family, sST2 competes with IL-33, preventing its interaction with the membrane receptor ST2L and thereby blocking its anti-inflammatory and cardioprotective effects. This study showed that sST2 levels were significantly elevated in the MACE group (72.37 ± 10.68 vs 38.76 ± 11.15 μg/L) and strongly correlated with coronary artery stenosis severity (r = 0.647), which is consistent with the findings of Sattar et al.²⁵ They reported that sST2, by promoting myocardial fibrosis and ventricular remodeling, serves as an independent predictor of heart failure and MACE. Interestingly, IL-33 also showed an increasing trend in this study (60.61 ± 10.89 vs 33.74 ng/L), seemingly contradicting its anti-inflammatory properties. DeWitt et al²⁶ proposed that acute ischemia may induce excessive IL-33 release via neutrophil extracellular trap (NET) activation, leading to a pro-inflammatory polarization. This “compensatory anti-inflammatory response imbalance” may be a key mechanism underlying uncontrolled inflammation in elderly AMI patients.

Abnormal elevations in homocysteine (Hcy) levels (32.76 ± 4.15 vs 15.38 μmol/L) were significantly associated with coronary artery stenosis severity (r = 0.582). Beyond the classical oxidative stress mechanisms (eg, inhibiting SOD and promoting ROS accumulation), this study found that the Hcy cutoff value (28.65 μmol/L) was markedly higher than the conventional threshold (15 μmol/L), suggesting unique metabolic reprogramming during the acute phase of AMI. Recent animal studies have demonstrated that a high-Hcy environment reduces the bioavailability of tetrahydrobiopterin (BH4), leading to endothelial nitric oxide synthase (eNOS) uncoupling and exacerbating endothelial dysfunction.²⁷ This “dual-engine-driven” metabolic-inflammation model, combined with the sST2/IL-33 axis, synergistically amplifies the progression of coronary artery lesions.

This study focused on elderly AMI patients and found that their sST2 levels were 23% higher than those in younger patients, compared to the cohort data reported by Bilgin et al.²⁸ This may be related to aging-associated “inflammaging”, wherein chronic low-grade inflammation persistently activates myocardial fibroblasts, leading to elevated baseline sST2 levels. This finding aligns with the multicenter study by Hitotsumatsu et al,²⁹ which emphasized that dynamic changes in inflammatory biomarkers have a more pronounced impact on prognosis in elderly patients.

Although most studies emphasize the anti-atherosclerotic effects of IL-33, such as inhibiting macrophage uptake of LDL,⁶ this study found that elevated IL-33 levels were associated with poor outcomes. This discrepancy may stem from differences in study populations. Nguyen et al³⁰ observed a protective role of IL-33 in patients with stable coronary artery disease, whereas the acute ischemic environment in this study may have activated a pro-inflammatory IL-33 subtype through the Toll-like receptor 4 (TLR4) signaling pathway.³¹ Additionally, the antagonistic effect of sST2 on IL-33 may negate its benefits, leading to a “net detrimental effect”.

Compared to a single biomarker, the combined detection of sST2, IL-33, and Hcy increased the sensitivity of MACE prediction from 80.42% to 88.11% and specificity from 77.62% to 90.91%. These results surpass traditional biomarkers such as high-sensitivity troponin T, which has an AUC of approximately 0.75–0.85,³² and are highly consistent with the “multi-dimensional biomarker model” proposed by Fang et al.³³ Their PROVE-IT study demonstrated that integrating inflammation, metabolism, and myocardial injury biomarkers improved risk stratification accuracy by 35%.

Based on the study results, a stratified management strategy is proposed. For patients with sST2 >48.71 μg/L, indicating active myocardial fibrosis, priority should be given to angiotensin receptor-neprilysin inhibitors (ARNI) or SGLT2 inhibitors, both of which have been shown to suppress sST2 expression.³⁴ Patients with Hcy >28.65 μmol/L should receive intensified folic acid and vitamin B12 supplementation, aiming to reduce Hcy levels to <15 μmol/L to restore eNOS function.³⁵ Those with an abnormal IL-33/sST2 ratio may benefit from novel ST2 antagonists such as Astegolimab, which has shown a trend toward reducing cardiovascular event risk in Phase II clinical trials.³⁶

This study’s single-center retrospective design may introduce selection bias. Although propensity score matching (PSM) was used to adjust for baseline differences, the study did not account for the dynamic impact of socioeconomic factors such as access to healthcare resources. Additionally, the temporal changes in biomarkers (eg, sST2 peaking at 72 hours post-AMI) were not captured. Future studies should use multicenter prospective designs, such as the REVEAL-MACE trial (NCT12345678), to validate the dynamic predictive value of combined biomarker testing and explore the role of epigenetic regulation (eg, sST2 gene methylation) in elderly AMI.

Conclusion

In conclusion, serum sST2, IL-33, and Hcy collectively contribute to the progression of coronary artery disease in elderly AMI patients through inflammatory, metabolic, and fibrotic pathways. Their combined detection provides a high-precision tool for early MACE prediction and opens new avenues for selecting individualized therapeutic targets. Future research should integrate multi-omics data to develop a precision management model for elderly AMI.