Abstract
Background
Despite advancements in ST-segment elevation myocardial infarction (STEMI) management, residual risks of major adverse cardiovascular events (MACE) persist. Apelin, a cardioprotective peptide with anti-inflammatory properties, and total cholesterol (TC), a key atherogenic factor, may synergistically influence outcomes. This study evaluated the prognostic value of the Apelin/TC ratio for long-term MACEs in STEMI patients undergoing primary percutaneous coronary intervention (PCI).
Methods
A secondary analysis of 464 STEMI patients from a Chinese cohort was conducted. Patients were stratified by median Apelin/TC ratio (≥ 14 vs. < 14). Demographic, clinical, and laboratory data were analyzed. Cox regression models assessed associations between the Apelin/TC ratio and MACEs over 30 months. Receiver operator characteristic curve (ROC) determined predictive performance.
Results
The cohort’s median Apelin/TC ratio was 14. Patients with a ratio < 14 (n = 225) exhibited higher MACEs incidence (25.43% overall; p < 0.001) versus the high-ratio group (n = 239). Multivariable Cox models confirmed the Apelin/TC ratio as an independent predictor of MACEs (per 1 standard deviation increase: hazard ratios (HR) 0.437, 95% confidence intervals (CI) 0.305–0.627; categorical: HR 0.479, 95% CI 0.319–0.720, both p < 0.001). Survival curves demonstrated significant divergence (log-rank p < 0.001). ROC analysis revealed moderate predictive capacity (Area Under The Curve 0.64, 95% CI 0.58–0.69).
Conclusions
A lower Apelin/TC ratio at admission independently predicted long-term MACEs in STEMI patients post-PCI, reflecting interplay between lipid burden and Apelin’s cardioprotective effects. This ratio may enhance risk stratification by capturing dual metabolic and inflammatory pathways. Further validation is warranted to establish its clinical utility in guiding targeted therapies.
Supplementary Information
The online version contains supplementary material available at 10.1186/s12872-025-04949-5.
Keywords: Apelin/TC ratio, ST-elevation myocardial infarction, Prognostic, Major adverse cardiovascular events
Introduction
Cardiovascular diseases are the leading cause of death globally [1], with acute coronary syndromes (ACS) representing one of the most severe forms [2]. ST-segment elevation myocardial infarction (STEMI), a critical manifestation of ACS, is characterized by complete or near-complete coronary artery occlusion, leading to myocardial ischemic necrosis [2]. Over the past two decades, substantial advancements in early revascularization strategies and secondary prevention measures have significantly reduced mortality rates among patients with STEMI [3, 4]. These improvements include the widespread adoption of timely reperfusion therapies and rigorous adherence to evidence-based guidelines for secondary prevention, such as anticoagulation, antiplatelet therapy, and angiotensin-converting enzyme inhibitors [2, 3]. However, despite these advancements, a significant subset of STEMI patients continues to exhibit elevated risks of adverse cardiovascular outcomes, both in the short and long term [5, 6].
Traditional biomarkers such as troponin and B-type natriuretic peptide have been instrumental in diagnosis and prognosis [7, 8]. However, these single markers often provide an incomplete picture of the disease’s complexity. Over the past several decades, accumulating experimental and clinical evidence has underscored the critical role of inflammation in driving adverse cardiovascular outcomes among patients with STEMI [9]. This body of research highlights how inflammatory pathways contribute to plaque instability, thrombogenesis, and post-infarction remodeling, thereby serving as a key factor in mediating both acute and chronic complications following STEMI [9]. Recent studies further suggest that residual inflammatory risk persists even in patients receiving optimal reperfusion therapy and guideline-directed medical therapy [10], emphasizing the need for targeted anti-inflammatory strategies to mitigate long-term cardiovascular risk in this population.
Apelin, an endogenous peptide with antioxidant and anti-inflammatory properties, plays a significant role in cardiovascular protection [11–14]. It has been shown to reduce ischemia–reperfusion injury and stabilize vulnerable plaques, thereby lowering the risk of adverse cardiovascular events [11–14]. Conversely, total cholesterol (TC), primarily transported by low-density lipoprotein-cholesterol (LDL), is a key contributor to atherosclerosis. Elevated TC levels promote lipid accumulation in arterial walls, fostering plaque formation and increasing cardiovascular risk [15, 16]. The Apelin-to-total cholesterol ratio (Apelin/TC ratio) emerges as a novel composite biomarker that integrates the protective effects of Apelin with the atherogenic potential of TC. This ratio may provide a more holistic assessment of cardiovascular risk by capturing the interplay between lipid metabolism, inflammation, and oxidative stress. A recent meta-analysis has demonstrated that Apelin/TC ratio could be offered as diagnostic markers for cardiovascular diseases [17].
To date, limited clinical data exist on the prognostic value of Apelin/TC ratio in the STEMI population. This study investigated the relationship between the Apelin/TC ratio and long-term major adverse cardiovascular events (MACE) in STEMI patients, aiming to evaluate its potential as a risk stratification tool. By analyzing this composite biomarker, we sought to offer clinicians a new approach to identify high-risk patients early, thereby enhancing treatment strategies and improving patient outcomes.
Materials and methods
Study design and population
This study constituted a secondary analysis of longitudinal data originating from First People’s Hospital of Taizhou in China [18]. The original dataset, openly accessible via the Dryad repository (https://datadryad.org) and provided by Yang et al. [19], was utilized in compliance with the platform’s terms of service, which permit reuse for secondary research without infringing on authors’ rights. The primary research enrolled 464 STEMI patients consecutively and non-selectively between January 2010 and October 2014. Diagnostic criteria included characteristic clinical symptoms (e.g., chest pain persisting beyond 30 min), electrocardiographic abnormalities (ST-segment elevation in two or more adjacent leads and/or depression), and significant elevation of serum cardiac biomarkers such as myocardial enzymes and troponin. All patients underwent successful primary percutaneous coronary intervention (PCI) within 12 h of symptom onset. Comprehensive details regarding the study design, exclusion criteria, and treatment protocols have been previously published [18]. Informed consent was obtained from all participants. As the dataset was anonymized and aligned with Dryad’s ethical guidelines, additional institutional ethics approval was not required for this analysis.
Data collection
Upon hospital admission, demographic and clinical data were recorded for each patient, including age, sex, systolic blood pressure, heart rate, prior history of myocardial infarction, hypertension, diabetes mellitus, Killip grade, and presence of anterior wall myocardial infarction. Laboratory assessments following hospitalization encompassed blood biomarkers such as Apelin-12, hemoglobin, white blood cell (WBC) count, neutrophil percentage, platelet count, creatinine, albumin, blood urea nitrogen, uric acid, fasting blood glucose (FBG), high-density lipoprotein cholesterol (HDL-C), TC, triglycerides (TG), LDL, D-dimer, peak cardiac troponin I (cTnI), and creatine kinase-MB (CK-MB). Electrocardiographic and echocardiographic parameters—including pathological Q-waves, left atrial diameter, and left ventricular end-diastolic diameter (LVEDD)—were documented within five days post-PCI. Interventional cardiologists assessed procedural details such as the number of stents implanted, culprit vessel identification, and Gensini score calculation during revascularization.
Apelin-12 detection via ELISA methodology
Serum samples were obtained through centrifugation (2500 × g, 10 min) within 1 h of collection and cryopreserved at − 80 °C. Apelin-12 levels were quantified using a commercially supplied enzyme-linked immunosorbent assay (ELISA) kit (Phoenix Pharmaceuticals, USA) according to manufacturer specifications [18]. Briefly, 50 μL of standards, serum samples, or controls were loaded per well, followed by 25 μL of primary antibody and 25 μL of biotinylated peptide, with incubation at 20–23 °C for 2 h. Post-washing (4 × 350 μL assay buffer), 100 μL of streptavidin–horseradish peroxidase conjugate was added, followed by a 1-h incubation. After repeated washing, 100 μL of 3,3',5,5'-tetramethylbenzidine substrate was introduced and incubated for 1 h before terminating the reaction with 100 μL of 2 N HCl. The assay demonstrated a sensitivity threshold of 0.1 mg/L, with intra- and inter-assay coefficients of variation at 1.26% and 5.4%, respectively. All measurements were conducted in triplicate to ensure reproducibility.
Definitions
The Apelin/TC ratio was derived by multiplying the ratio of Apelin-12 concentration (ng/mL) to TC (mmol/L) by 100. MACE served as the primary clinical endpoint, defined as a composite of recurrent target vessel myocardial infarction, clinically indicated target lesion revascularization, congestive heart failure, cardiogenic shock, or cardiac death. Post-procedural clinical outcomes were monitored for all participants over a 30-month follow-up period following PCI.
Statistical analysis
Patients were categorized into two groups using the median value of the Apelin/TC ratio as a cutoff: a high Apelin/TC ratio group (≥ 14) and a low Apelin/TC ratio group (< 14). For continuous variables, mean ± standard deviation (SD) was used to describe normally distributed data, while median values with interquartile ranges (25th and 75th percentiles) were reported for non-normally distributed data. Categorical variables were presented as counts and percentages. Comparisons of continuous variables were performed using Student’s t-test for normally distributed data and the Mann–Whitney U test for non-normally distributed data. Categorical variables were compared using the chi-square test.
To evaluate the relationship between the Apelin/TC ratio and MACEs, three Cox proportional-hazards regression models were constructed: (1) an unadjusted model with no covariates; (2) a minimally adjusted model accounting for demographic factors (age and sex); and (3) a fully adjusted multivariable model that included all clinically relevant covariates identified through univariate analysis (p < 0.2 threshold) in addition to the demographic variables from Model 2. Results were reported as hazard ratios (HR) with 95% confidence intervals (CI). The cumulative incidence of MACEs in the low and high Apelin/TC ratio groups was estimated using Kaplan–Meier survival curves and compared with the log-rank test. Restricted cubic splines (RCS) were used to assess whether there was a linear or nonlinear correlation between Apelin/TC ratio and MACEs. The predictive ability of the Apelin/TC ratio for MACEs was assessed using receiver operating characteristic (ROC) curve analysis, with the area under the curve (AUC) indicating diagnostic performance. Sensitivity and specificity were plotted as sensitivity versus 1-specificity, and the optimal cutoff value was determined using the Youden Index.
All statistical analyses were conducted using R version 3.4.4, and a p-value threshold of < 0.05 was used to determine statistical significance.
Results
Baseline characteristics of the study population
This study enrolled 464 consecutive STEMI patients undergoing primary PCI, with their baseline clinical characteristics comprehensively outlined in Table 1. Upon admission, the median Apelin/TC ratio was determined to be 14 (range: 1–162). Using this median cutoff, the cohort was stratified into high Apelin/TC ratio (≥ 14, n = 239) and low Apelin/TC ratio (< 14, n = 225) groups for comparative analysis. As demonstrated in Table 1, significant differences were observed between the two groups in gender (p = 0.004), LVEDD (p = 0.023), creatinine (p < 0.001), Uric acid (p < 0.001), TC (p < 0.001), HDL (p < 0.001), LDL (p = 0.002), and Apelin-12 (p < 0.001).
Table 1.
Baseline characteristics of the study population included in the study
| Variables | Total (n = 464) | Apelin/TC ratio | p | |
|---|---|---|---|---|
| Low, < 14, N = 239 | High, ≥ 14, N = 225 | |||
| Age (years) | 63.00 ± 11.92 | 62.28 ± 11.72 | 63.77 ± 12.12 | 0.177 |
| Gender, n (%) | 0.004 | |||
| Males | 355 (76.51) | 196 (82.01) | 159 (70.67) | |
| Females | 109 (23.49) | 43 (17.99) | 66 (29.33) | |
| Hypotension history, n (%) | 0.925 | |||
| No | 199 (42.89) | 102 (42.68) | 97 (43.11) | |
| Yes | 265 (57.11) | 137 (57.32) | 128 (56.89) | |
| Diabetes history, n (%) | 0. 347 | |||
| No | 314 (67.67) | 157 (65.69) | 157 (69.78) | |
| Yes | 150 (32.33) | 82 (34.31) | 68 (30.22) | |
| Myocardial infarction history, n (%) | 0.702 | |||
| No | 409 (88.15) | 212 (88.70) | 197 (87.56) | |
| Yes | 55 (11.85) | 27 (11.30) | 28 (12.44) | |
| Pathological Q wave, n (%) | 0.254 | |||
| No | 241 (51.94) | 118 (49.37) | 123 (54.67) | |
| Yes | 223 (48.06) | 121 (50.63) | 102 (45.33) | |
| AWMI, n (%) | 0.708 | |||
| No | 233 (50.22) | 118 (49.37) | 115 (51.11) | |
| Yes | 231 (49.78) | 121 (50.63) | 110 (48.89) | |
| Culprit vessels, n (%) | 0.093 | |||
| LAD | 233 (50.22) | 130 (54.39) | 103 (45.78) | |
| LCX | 72 (15.52) | 38 (15.90) | 34 (15.11) | |
| RCA | 159 (34.27) | 71 (29.71) | 88 (39.11) | |
| LVEDD (mm) | 50.00 (45.00, 56.00) | 51.00 (46.00, 56.00) | 49.00 (44.00, 55.00) | 0.023 |
| Left atrial diameter (mm) | 38.00 (33.00, 42.00) | 38.00 (34.00, 42.00) | 38.00 (33.00, 41.00) | 0.258 |
| GENSINI score | 74.00 (42.00, 101.00) | 79.00 (46.00, 101.00) | 67.00 (37.00, 101.00) | 0.176 |
| Stent number n (%) | 0.618 | |||
| 1 | 302 (65.09) | 160 (66.95) | 142 (63.11) | |
| 2 | 148 (31.90) | 73 (30.54) | 75 (33.33) | |
| 3 | 14 (3.02) | 6 (2.51) | 8 (3.56) | |
| SBP (mmHg) | 131.00 (109.00, 153.00) | 131.00 (110.00, 157.00) | 133.00 (109.00, 149.00) | 0.690 |
| Heart rate (beats/min) | 76.00 (64.00, 89.00) | 76.00 (65.00, 87.00) | 75.00 (64.00, 90.00) | 0.754 |
| Killip’s grade, n (%) | 0.171 | |||
| I | 352 (75.86) | 175 (73.22) | 177 (78.67) | |
| ≥ II | 112 (24.14) | 64 (26.78) | 48 (21.33) | |
| FBG (mmol/l) | 7.11 (5.79, 9.71) | 7.52 (5.84, 9.97) | 6.92 (5.71, 9.32) | 0.080 |
| Neutrophils (%) | 77.55 (66.23, 85.10) | 77.60 (65.85, 85.25) | 76.40 (67.05, 85.05) | 0.842 |
| WBC (× 109/L) | 9.96 (7.16, 12.96) | 10.14 (6.96, 13.10) | 9.36 (7.26, 11.96) | 0.204 |
| Platelet (× 109/L) | 231.50 (183.00, 272.00) | 233.00 (182.00, 273.50) | 222.00 (184.50, 272.00) | 0.590 |
| Urea nitrogen (mmol/L) | 6.74 ± 2.07 | 6.61 ± 2.09 | 6.87 ± 2.05 | 0.176 |
| Creatinine (μmol/L) | 75.00 (62.00, 85.70) | 68.10 (56.00, 80.00) | 80.00 (68.50, 88.00) | < 0.001 |
| Uric acid (μmol/L) | 335.05 (282.20, 390.00) | 332.00 (270.00, 390.00) | 340.00 (290.00, 390.00) | < 0.001 |
| Hemoglobin (g/L) | 143.00 (131.00, 158.00) | 144.00 (132.00, 157.00) | 142.00 (131.00, 158.00) | 0.535 |
| Albumin (g/L) | 38.00 (35.00, 41.00) | 38.00 (35.00, 41.00) | 38.00 (35.00, 40.50) | 0.562 |
| TC (mmol/L) | 5.64 ± 1.13 | 6.10 ± 1.02 | 5.16 ± 1.04 | < 0.001 |
| TG (mmol/L) | 0.96 (0.55, 1.53) | 1.10 (0.54, 1.59) | 0.88 (0.56, 1.47) | 0.062 |
| HDL (mmol/L) | 1.20 ± 0.27 | 1.24 ± 0.27 | 1.16 ± 0.27 | < 0.001 |
| LDL (mmol/L) | 3.00 (2.48, 3.60) | 3.10 (2.59, 3.78) | 2.88 (2.39, 3.49) | 0.002 |
| Apelin-12 | 0.83 ± 0.34 | 0.61 ± 0.16 | 1.06 ± 0.32 | < 0.001 |
| Peak cTnI (ng/m L) | 13.55 (4.21, 28.80) | 15.50 (6.09, 30.00) | 12.80 (2.72, 27.50) | 0.062 |
| Peak CK-MB (U/L) | 106.00 (44.00, 194.25) | 110.00 (56.50, 197.00) | 104.00 (35.00, 191.00) | 0.128 |
| D-Dimer (mg/L) | 0.90 (0.20, 1.70) | 0.90 (0.30, 1.60) | 0.90 (0.20, 1.80) | 0.545 |
| MACE, n (%) | < 0.001 | |||
| No | 346 (74.57) | 162 (67.78) | 184 (81.78) | |
| Yes | 118 (25.43) | 77 (32.22) | 41 (18.22) | |
Abbreviations: Apelin/TC ratio serum Apelin-12 to total cholesterol ratio, SBP systolic blood pressure, AWMI Anterior wall myocardial infarction, LVEDD left ventricular and diastolic diameter, WBC white blood cells, FBG fasting blood glucose, TC total cholesterol, TG triglyceride, HDL high-density lipoprotein, LDL low-density lipoprotein-cholesterol, cTnI cardiac troponin I, CK-MB creatine kinase MB, LAD left anterior descending coronary artery, LCX left circumflex coronary artery, RCA right coronary artery, MACE major adverse cardiovascular events
Incidence of MACEs
A total of 118 (25.43%) patients developed MACEs during follow-up. Additionally, the high Apelin/TC ratio group had a lower incidence of MACEs compared to the low Apelin/TC ratio group (p < 0.001). Figure 1 shows the survival curves for incident MACEs stratified by Apelin/TC ratio. Patients with lower Apelin/TC ratio had poorer disease-free survival compared to the higher Apelin/TC ratio (log-rank test p < 0.001).
Fig. 1.
Kaplan–Meier curves stratified by Apelin/TC ratio. The curves showed different incidence of MACEs of STEMI patients with different Apelin/TC ratio
Cox regression analysis
In univariate analysis, age (HR = 1.04, 95% CI: 1.02—1.05), pathological Q wave (HR = 1.71, 95% CI: 1.19—2.48), AWMI (HR = 1.71, 95% CI: 1.18—2.47), LVEDD (HR = 1.05, 95% CI: 1.02—1.08), left atrial diameter (HR = 1.04, 95% CI: 1.01—1.08), heart rate(HR = 1.01, 95% CI: 1.01—1.02), hemoglobin(HR = 0.98, 95% CI: 0.97—0.99), HDL(HR = 2.21, 95% CI: 1.13—4.32), TC(HR = 1.21, 95% CI: 1.05—1.40), Apelin-12 (HR = 0.212, 95% CI: 0.11—0.43) and Apelin/TC ratio (per 1 SD) (HR = 0.44, 95% CI: 0.30—0.63) were found be significantly associated with MACEs (Table s1).
Three cox proportional hazard models were established to assess the relationship between the Apelin/TC ratio and MACEs (Table 2). In the crude model, Apelin/TC ratio (per 1 SD increase) was negatively associated with MACEs (HR 0.435, 95% CI 0.302–0.626). After correcting for other confounding factors, this trend was still significant (in Model 2, HR 0.383, 95% CI 0.265–0.553; in Model 3, HR 0.437, 95% CI 0.305–0.627). A similar result occurred when Apelin/TC ratio was a categorical variable (in Model 1, HR 0.511, 95% CI 0.350–0.746; in Model 2, HR 0.455, 95% CI 0.310–0.668; in Model 3, HR 0.479, 95% CI 0.319–0.720). Based on the favorable results observed, we proceeded to evaluate the nature of the relationship between the Apelin/TC ratio and the occurrence of MACEs by employing multivariate-adjusted RCS. As demonstrated in Fig. 2, the analysis revealed a significant linear correlation between the Apelin/TC ratio and MACEs (P for non-linearity = 0.617).
Table 2.
Cox regression analysis for the relationship between Apelin/TC ratio and MACEs
| Apelin/TC ratio | Model 1 | Model 2 | Model 3 | ||||
|---|---|---|---|---|---|---|---|
| HR (95%CI) | p-value | HR (95%CI) | p-value | HR (95%CI) | p-value | ||
| As a categorical variable | Per 1 SD | 0.435(0.302–0.626) | < 0.001 | 0.383(0.265–0.553) | < 0.001 | 0.437(0.305–0.627) | < 0.001 |
| As a categorical variable | Low group | Ref | Ref | Ref | |||
| High group | 0.511(0.350–0.746) | 0.001 | 0.455(0.310–0.668) | < 0.001 | 0.479(0.319–0.720) | < 0.001 | |
Note: Model 1was crude model with no variables adjusted
Model 2 adjusted for age, gender
Model 3 adjusted for age, gender, myocardial infarction history, pathological Q wave, anterior wall myocardial infarction, systolic blood pressure, heart rate, left ventricular diastolic diameter, left atrial diameter, Gensini score, white blood cells, platelets, high-density lipoprotein, and peak cardiac troponin I
Fig. 2.
The relationship between the Apelin/TC ratio and MACEs in patients with STEMI. Hazard ratios are indicated by solid lines and 95% CIs by shaded areas
Predictive performance assessment
The ROC method was employed for assessing the Apelin/TC ratio in predicting the occurrence of MACE in STEMI patients (Fig. 3). The area under the ROC curve for predicting MACE was 0.64 (95% CI: 0.58–0.69) for the Apelin/TC ratio, compared to 0.62 (95% CI: 0.56–0.68) for Apelin-12 alone and 0.59 (95% CI: 0.53–0.65) for TC alone. At the optimal cutoff value of 12.07 (maximizing the Youden Index), sensitivity reached 67.6%, specificity was 55.1%, and the Youden Index was 0.227.
Fig. 3.
Receiver operating characteristic curves for Apelin/TC ratio, Apelin-12 alone, and TC alone for predicting the incidence of MACEs in patients with STEMI
Discussion
The present secondary analysis of a STEMI cohort undergoing primary PCI revealed that a lower Apelin/TC ratio at admission was independently associated with an increased risk of MACEs during follow-up, even after adjusting for established clinical and biochemical risk factors. This finding underscored the potential prognostic utility of the Apelin/TC ratio in risk stratification for STEMI patients, offering a novel perspective on the interplay between lipid metabolism and cardiovascular outcomes.
The median Apelin/TC ratio of 14 in our cohort effectively stratified patients into distinct prognostic groups. Notably, the high Apelin/TC ratio group exhibited a significantly lower incidence of MACEs compared to the low-ratio group (p < 0.001), a finding further corroborated by Kaplan–Meier survival analysis (log-rank p < 0.001). This aligns with emerging evidence suggesting that lipid-related biomarkers, particularly those reflecting dynamic interactions between lipid fractions and inflammatory or metabolic pathways, may refine risk prediction in acute coronary syndromes [20–23]. For instance, ratios such as neutrophil/HDL or HDL/apolipoprotein A-1 have shown prognostic value by encapsulating both atherogenic burden and inflammatory activity [21, 23]. The Apelin/TC ratio, as a composite marker, could theoretically integrate the protective effects of Apelin with the atherogenic burden represented by TC [12–16, 24, 25]. This dual-pathway metric may thus capture broader pathophysiological mechanisms underlying post-STEMI outcomes, extending beyond conventional single-marker approaches. This hypothesis is supported by the robust negative association observed in multivariable Cox models, where the Apelin/TC ratio remained a significant predictor of MACEs across incremental adjustments for confounders. Notably, the consistency of results when analyzing the ratio as both a continuous and categorical variable strengthens its clinical applicability.
The AUC values for the Apelin/TC ratio, Apelin alone, and TC alone were 0.64, 0.62, and 0.59, respectively. These results indicate that the Apelin/TC ratio has a slightly higher predictive capacity compared to Apelin alone and TC alone. Although all AUC values suggest moderate predictive performance, the Apelin/TC ratio demonstrates a modest improvement in predictive ability. The potential superiority of the Apelin/TC ratio can be attributed to its ability to integrate the protective effects of Apelin with the atherogenic potential of TC. This composite biomarker captures the interplay between lipid metabolism and cardiovascular protection, providing a more comprehensive assessment of cardiovascular risk. The slight improvement in AUC for the Apelin/TC ratio suggests that it may offer a more nuanced understanding of the risk profile compared to Apelin or TC alone. The optimal cutoff of 12.07, derived from the Youden Index, may serve as a pragmatic threshold for risk stratification in clinical settings, though external validation is warranted. Future research should focus on validating the Apelin/TC ratio in external cohorts and investigating its incremental value when combined with traditional risk factors and other emerging biomarkers. Such efforts will help clarify the clinical role of the Apelin/TC ratio and inform its integration into existing risk assessment frameworks.
Biological plausibility for these findings may lie in Apelin’s proposed role in mitigating ischemia–reperfusion injury and stabilizing vulnerable plaques [11–14]. Apelin-12, a protein with antioxidant and anti-inflammatory properties, has been shown to reduce oxidative stress and inflammation in vascular tissues, which are key contributors to ischemia–reperfusion injury [12, 24, 26]. Additionally, Apelin’s role in stabilizing vulnerable plaques could be attributed to its ability to enhance the integrity of the fibrous cap and reduce plaque vulnerability [14], thereby lowering the risk of plaque rupture and subsequent thrombotic events. On the other hand, elevated TC reflects residual atherogenic risk. TC, primarily carried by LDL, is a major contributor to the development and progression of atherosclerosis. High levels of TC can lead to lipid accumulation in the arterial wall, promoting plaque formation and increasing the risk of cardiovascular events [15, 16]. Even when LDL levels are adequately controlled, residual risk may persist due to other lipoprotein particles or non-lipoprotein-related factors [27], which could be captured by the Apelin/TC ratio. As a regulating peptide of cardiovascular, gastrointestinal, hypothalamus-hypophysis, and immune systems, Apelin appears to regulate lipid metabolism and adiposity since it increases uncoupling protein 1 (Ucp1) mRNA levels (a marker of peripheral energy expenditure) in brown adipose tissue and Uco3 mRNA levels (a regulator of fatty acid export) in skeletal muscle [25, 28]. A low Apelin/TC ratio could thus signal an imbalance between protective mechanisms and ongoing lipid-driven damage. This ratio may serve as a marker that integrates both the protective effects of Apelin and the atherogenic potential of TC, providing a more comprehensive assessment of cardiovascular risk. When Apelin levels are low relative to TC, it may indicate that the protective mechanisms are overwhelmed by the pro-atherogenic processes, leading to an increased susceptibility to adverse cardiovascular outcomes.
Beyond establishing the Apelin/TC ratio as an independent prognostic marker, our findings prompt consideration of its potential translational utility. While requiring validation in prospective cohorts, this ratio could refine risk stratification post-STEMI by identifying patients with high residual risk despite revascularization and guideline-directed therapy. Specifically, individuals with a low Apelin/TC ratio might benefit from intensified surveillance (e.g., enhanced follow-up, advanced cardiac imaging), prioritized cardiac rehabilitation, or earlier enrollment in trials of novel cardioprotective agents. Therapeutically, our results generate hypotheses for targeted interventions: (1) Augmenting apelin signaling via emerging apelin receptor agonists in low-ratio patients, leveraging its vasoprotective and antioxidant effects; (2) Personalized metabolic management—including aggressive lipid control (e.g., PCSK9 inhibitors) or lifestyle/dietary protocols—aimed at correcting the dysmetabolic state reflected by the ratio; and (3) Optimization of guideline-directed medical therapy adherence and dosing. Importantly, these strategies remain hypothetical; our observational design precludes causal inference, and interventional studies must confirm whether ratio-guided management improves outcomes. Future steps include standardizing apelin assays, validating cutoffs across populations, and demonstrating clinical utility in trials.
This study has several limitations. First, as a single-center retrospective study, unmeasured biases (e.g., treatment variations, unaccounted comorbidities) may persist despite multivariable adjustments. Second, the observational design precludes causal inferences—whether Apelin/TC ratio directly modulates outcomes or serves as a surrogate for unmeasured pathways remains unclear. Third, the modest AUC underscores the need to evaluate this ratio within multimodal prediction models. Finally, generalizability to non-STEMI populations or those managed conservatively requires further investigation.
Conclusion
In STEMI patients undergoing primary PCI, a lower Apelin/TC ratio at admission independently predicted adverse cardiovascular outcomes. This ratio may serve as a pragmatic biomarker for risk stratification, integrating lipid and non-lipid pathways. Future prospective studies should validate its prognostic utility and explore its mechanistic links to atherosclerosis progression.
Supplementary Information
Acknowledgements
We would like to thank Yang Lingchang and its collaborators who prepared the publicly available data.
Clinical trial number
Not applicable.
Abbreviations
- ACS
Acute coronary syndromes
- STEMI
ST-segment elevation myocardial infarction
- TC
Total cholesterol
- LDL
Low-density lipoprotein-cholesterol
- Apelin/TC ratio
Apelin-to-total cholesterol ratio
- MACE
Major adverse cardiovascular events
- PCI
Percutaneous coronary intervention
- WBC
White blood cell count
- FBG
Fasting blood glucose
- HDL-C
High-density lipoprotein cholesterol
- TG
Triglycerides
- cTnI
Cardiac troponin I
- CK-MB
Creatine kinase-MB
- LVEDD
Left ventricular end-diastolic diameter
- SD
Standard deviation
- HR
Hazard ratios
- RCS
Restricted cubic splines
- ROC
Receiver operating characteristic
- AUC
Area under the curve
Authors’ contributions
Xiaoqin Lin: Conceptualization, Methodology, Software, Data curation, Writing- Original draft preparation. Junjie Huang: Visualization, Investigation. Hanxiao Lin: Software, Validation. Peiqi Chen: Supervision, Writing- Reviewing and Editing. All authors have read and agreed to the published version of the manuscript.
Funding
None.
Data availability
The data that support the findings of this study are openly available in Dryad at https://doi.org/10.5061/dryad.pf56m.
Declarations
Ethics approval and consent to participate
Informed consent was obtained from all participants. As the dataset was anonymized and aligned with Dryad’s ethical guidelines, additional institutional ethics approval was not required for this analysis.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
Footnotes
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Data Availability Statement
The data that support the findings of this study are openly available in Dryad at https://doi.org/10.5061/dryad.pf56m.