Introduction

Coronary atherosclerotic heart disease, a highly prevalent cardiovascular disorder, is characterized by the accumulation of atherosclerotic plaques within the coronary arteries, leading to progressive narrowing or obstruction of the vessel lumen and resulting in myocardial ischemia, hypoxia, and potentially necrosis1. Associated risk factors include inflammatory processes, hypertension, insulin resistance, disorders of lipid and glucose metabolism, cigarette smoking, and vascular endothelial dysfunction2,3,4. Cardiovascular adverse events constitute the principal cause of mortality among patients with coronary artery disease5. Thus, novel and straightforward screening biomarkers are urgently needed to evaluate early-stage CAD severity and prognosis.

CTRP9, a member of the adiponectin superfamily, is predominantly secreted by epicardial adipose tissue, as well as by the liver, skeletal muscle, and various other organs tissues6,7. CTRP9 has attracted increasing attention due to its significant role in antioxidative stress, anti-atherosclerosis, immune inflammation regulation, energy and glycolipid metabolism, and vascular endothelial function8. Notably, CTRP9 exhibits cardioprotective effects and has emerged as a novel factor for cardiovascular protection in development of CAD9,10. Hence, CTRP9 shows promise as a novel biomarker for predicting CAD progression and prognosis.

This study aims to explore and analyze the correlation between plasma CTRP9 levels and the complexity as well as the prognosis of CAD. This provides valuable evidence to support the early diagnosis, risk stratification, and prediction of adverse events during the progression of CAD.

Methods

Target population

Between February 2022 and July 2022, a total of 436 consecutive patients with suspected stable CAD who underwent coronary angiography were screened at the First Affiliated Hospital of Anhui Medical University. Based on clinical presentation, laboratory findings, medical history, coronary angiographic results, and predefined inclusion and exclusion criteria, 134 patients were excluded from the study. The detailed exclusion process is illustrated in Fig. 1. In accordance with the specified exclusion and inclusion criteria, a total of 302 patients were enrolled in this study. Inclusion criteria for cases involved meeting the diagnostic criteria set forth by the United States College of Cardiology Heart Association in 2020; Secure informed consent from the study participants and obtain approval from the medical ethics committee. Exclusion criteria: patients with severe organic heart diseases such as congestive heart failure, valvular heart disease, myocarditis, etc.; patients underwent CABG or PCI; patients with severe hepatic or renal dysfunction; patients older than 80 or younger than 18 years of age; patients with incomplete clinical data. (Fig. 1)

Fig. 1
Fig. 1
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Flow chart of study participants. Patients with coronary atherosclerotic heart disease (CAD) who were enrolled in the study were categorized into two groups based on their severity of coronary artery disease. CAD: Coronary atherosclerotic heart disease. CAG: Coronary arteriography. PCI: Percutaneous artery intervention. CABG: Coronary artery bypass grafting. SYNTAX: Synergy between percutaneous coronary intervention with taxus and cardiac surgery. MACEs: Major adverse cardiovascular events.

Data collection

Fasting venous blood was collected the day after admission and the levels of fasting blood glucose (FBG), creatine kinase-MB (CK-MB), lactate dehydrogenase (LDH), estimated glomerular filtration rate (eGFR), serum creatinine (Scr), uric acid (UA), fibrinogen (FIB), D-dimer (D-D), total cholesterol (TC), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), lipoprotein-a (Lp (a)), apolipoprotein A1 (ApoA1), and apolipoprotein B (ApoB), were measured using the standard laboratory analyzer. Age, gender, body mass index (BMI), history of hypertension, Type 2 diabetes mellitus (T2DM), smoking and drinking, were obtained through the clinical electronic medical record system. Simpson ultrasonography was utilized to acquire data on ejection fraction (EF) and left ventricular end-diastolic diameter (LVDD). Prior to CAG, fasting venous blood was obtained from the study subjects. After centrifugation, the supernatant was extracted for testing. It was then divided into two parts, sub-packaged in EP tubes, and subsequently stored at -80℃. ELISA was employed for the detection of plasma CTRP9 levels. The ELISA kit was provided by Shanghai Aibo Biotechnology Company and utilized in strict adherence to the reagent’s guidelines.

Coronary angiography

Coronary angiography and percutaneous coronary intervention were conducted in accordance with the prevailing guidelines11. The SYNTAX scores evaluate the severity of coronary artery lesions by integrating factors such as the location of coronary lesions, the degree of calcification, the degree of stenosis, and the presence or absence of collateral circulation. According to the score, coronary lesions were divided into three grades: (1) mild lesions: ≤22 points; (2) Moderate lesions: 23–32 points; (3) Severe lesions: ≥33 points12. In view of the relatively small number of patients in the severe disease group (n = 34), together with the imbalance in subgroup sample sizes, the need to preserve the robustness of statistical analyses, and the clinical relevance of coronary lesion complexity, the moderate and severe SYNTAX score categories were subsequently combined into a single cohort (SYNTAX ≥ 23) for all subsequent analyses in this study. Based on the SYNTAX scores, patients were categorized into two groups: mild lesions group (scores ≤ 22) and moderate-severe lesions group (scores ≥ 23). The cardiac catheterization procedures were performed by two experienced interventional cardiologists.

Endpoint event assessment

A clinical follow-up study was conducted on all research subjects, with the primary endpoint being the occurrence of MACEs, including cardiac death, non-fatal myocardial infarction, coronary revascularization, readmission for heart failure and non-fatal stroke13. The median follow-up duration for these events was 21 months (median, 21 months; interquartile range, 4–21months).

Data analysis

Statistical analyses were conducted using SPSS version 26.0. Prior to analysis, the normality of all continuous variables was assessed using the Kolmogorov–Smirnov test. Continuous variables conforming to a normal distribution were expressed as mean ± standard deviation (SD), whereas non-normally distributed variables were presented as median with interquartile range (IQR). Comparisons between two groups were performed using independent-samples t-tests for normally distributed variables and Mann–Whitney U tests for non-normally distributed variables. Comparisons between two groups were conducted using independent-samples t-tests for normally distributed variables (with variance homogeneity confirmed by Levene’s test) and Mann–Whitney U tests for non-normally distributed variables. Correlations between continuous variables were assessed using Spearman rank correlation due to the non-normal distribution of several key variables. A logistic regression model was employed to investigate whether the study indications were risk factors for the severity of CAD. ROC curves were generated to illustrate the diagnostic performance of plasma CTRP9 levels for MACEs and mid/high SYNTAX scores. MACE-free survival curves, based on plasma CTRP9 levels, were constructed using Kaplan-Meier survival estimates. Survival rate disparities were evaluated using the log-rank test. Prognostic risk factors were analyzed through univariate and multivariate analyses using the Cox regression model. All tests were two-tailed, and P < 0.05 was considered statistically significant.

Results

Baseline information

Table 1 displays the general information of the target population. No statistically significant differences were observed between the two groups in the following variables: sex, BMI, drinking, smoking, ApoA1, ApoB, eGFR, Scr, CRP, LVDD and medication history (P > 0.05). However, significant disparities were observed in age, T2DM, plasma CTRP9 level, TC, TG, HDL-C, LDL-C, Lp (a), FBG, CK-MB, UA, LDH, FIB, D-D, EF, vessel involvement and SYNTAX scores (P < 0.05).

Table 1 General information of enrolled patients.
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Correlation between plasma CTRP9 level and other variables

In Table 2, an analysis is presented regarding the association between plasma CTRP9 levels and other variables in patients. The results indicate that plasma CTRP9 levels are positively related to HDL-C but inversely related to TG, TC, LDL-C, UA, FBG, and SYNTAX scores. Figure 2 shows that with the increase of CTRP9, the SYNTAX scores gradually decrease, indicating a reduction in the degree of coronary stenosis.

Table 2 The correlation between CTRP9 and risk factors for CAD.
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Fig. 2
Fig. 2
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Correlation between plasma CTRP9 levels and the SYNTAX scores.

Logistic regression analysis of risk factors for moderate-severe lesions

Figure 3 illustrates the results of the association between CTRP9 and the degree of coronary stenosis, taking into account various confounding factors through adjustment. Univariate logistic regression analysis identified age, T2DM, UA, FIB, D-D, FBG, LDL-C, TC, TG, and Lp-a as potential risk factors, while CTRP9, HDL-C, and LVEF were recognized as protective factors. In multivariate logistic regression analysis, CTRP9 consistently manifests itself as an independent protective factor, even after accounting for various confounding factors (Fig. 3, OR: 0.987, 95% CI: 0.980–0.993, P < 0.001).

Fig. 3
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Logistic regression analysis of risk factors for moderate-severe lesions. OR: Odds ratio. CI: Confidence interval. #: There were no statistically significant variables in the univariate analysis.

Diagnostic value of plasma CTRP9 level in ROC curve for moderate-severe lesions

The diagnostic value of plasma CTRP9 levels for identifying moderate-severe coronary artery lesions was evaluated using receiver operating characteristic (ROC) curve analysis. The optimal cut-off value of CTRP9 was determined using the Youden index and identified as 266.95 ng/mL, yielding an AUC of 0.911 (95% CI: 0.876–0.946, sensitivity: 86.90%, specificity: 80.90%, P < 0.001). (Fig. 4)

Fig. 4
Fig. 4
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Diagnostic value of plasma CTRP9 level in ROC curve for moderate-severe lesions. AUC: Area under the curve. CI: Confidence interval.

Univariate and multivariate Cox regression model in MACEs

The incidence of MACEs was determined through a follow-up survey in different sub-groups. Throughout the median follow-up duration of 21 months (median: 21 months; range: 4–21 months), a total of 97 cases of MACEs, constituting 32.12%, were documented. This comprised 3 instances of cardiac death, 37 occurrences of non-fatal acute myocardial infarction (AMI), 21 incidents of coronary revascularization, 27 cases of heart failure, and 9 occurrences of ischemic stroke. Variables with potential clinical relevance and those showing significance in univariate analyses were entered into the multivariate Cox proportional hazards model using a forward selection approach. In the multiple Cox regression model, CTRP9 was identified as an independent predictor of MACEs, maintaining statistical significance even after adjustment for potential confounders. Lower plasma CTRP9 levels were independently associated with an increased risk of MACEs. Notably, the HR reflects the effect of a per-unit (per ng/mL) decrease in CTRP9 concentration, indicating that for each 1 ng/mL reduction in CTRP9, the risk of MACEs increases by approximately 0.4%. (Table 3).

Table 3 Univariate and Multivariate Cox regression analysis of MACEs.
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Kaplan–Meier survival curves

Based on the cut-off value of CTRP9 derived from the ROC analysis, patients were stratified into different groups, and those with lower plasma CTRP9 levels exhibited a significantly higher risk of MACEs. Furthermore, when CTRP9 was entered into the Cox proportional hazards model as a continuous variable, lower plasma CTRP9 levels were independently associated with an increased risk of MACEs. Notably, the hazard ratio reflects the effect of a per-unit (per ng/mL) decrease in CTRP9 concentration. (Fig. 5, P < 0.001).

Fig. 5
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Kaplan–Meier survival curves.

Discussion

CTRP9 is a protein, the closest paralog of adiponectin, and is predominantly expressed in adipose tissue. It exerts a wide range of metabolic functions across multiple organ systems, including adipose tissue, liver, cardiac myocytes, hypothalamus, and skeletal muscle14,15. Previous studies have confirmed that CTRP9 has a protective effect in diabetes, CAD, lung diseases, and other fields9,16. With the advancement of research, CTRP9 has attracted considerable attention in the cardiovascular field due to its beneficial effects in cardiovascular protection17.

This study demonstrated the correlation between CTRP9 levels and the complexity of coronary artery lesions, while also highlighting its prognostic value in assessing adverse cardiovascular risks in patients with CAD. Plasma CTRP9 levels exhibited a significant decrease in patients with moderate-severe vascular disease compared to those with mild lesions. Lower CTRP9 levels were associated with higher SYNTAX scores, indicating increased complexity of coronary artery lesions. Even when accounting for multiple confounding factors, CTRP9 retained its status as an independent protective factor for coronary artery lesions. The explanation for the negative correlation between CTRP9 levels and coronary artery stenosis that we have found may be attributed to the fact that CTRP9 can increase the stability of the plaques. To further investigate the clinical significance of CTRP9, ROC curve analysis was performed to evaluate its diagnostic performance. The optimal cut-off value was determined to be 266.95 ng/mL based on the Youden index. Since reduced CTRP9 levels correlate with coronary lesion complexity, this optimal cut-off value provides a practical means of identifying patients predisposed to advanced coronary atherosclerosis.

Such patients could benefit from closer clinical monitoring and more intensive therapeutic interventions, thereby enabling earlier risk stratification and more targeted management in clinical practice.

Dysregulated lipid metabolism and oxidative stress can impair endothelial function and accelerate the progression of atherosclerotic plaques, ultimately leading to coronary lumen narrowing. Previous studies have demonstrated that CTRP9 exerts multiple vasoprotective effects during the development and progression of atherosclerosis2,18. Li et al. reported that, in apolipoprotein E–deficient mice, overexpression of CTRP9 enhanced carotid plaque stability by reducing the levels of pro-inflammatory cytokines, including tumor necrosis factor-α (TNF-α) and monocyte chemoattractant protein-9 (MCP-9)19. In addition, CTRP9 suppresses inflammation-related signaling pathways such as nuclear factor-k-gene binding (NF-κB), leading to decreased expression of adhesion molecules, including vascular cell adhesion molecule 1 (VCAM-1) and intercellular cell adhesion molecule 1 (ICAM-1), and promotes endothelium-dependent vasodilation through activation of the AMP-activated protein kinase (AMPK) pathway. CTRP9 also reduces reactive oxygen species production and attenuates high-glucose-induced oxidative stress20,21,22. These studies provide evidence that CTRP9 may contribute to inhibiting the release of inflammatory cytokines and adhesion molecules, thereby preserving the integrity and function of blood vessels and mitigating the progression of atherosclerosis.

CTRP9 has been shown to play a significant role in enhancing insulin sensitivity and regulating lipid metabolism16. This study further investigated the relationship between CTRP9 and blood lipids lipid profiles and glycemic parameters in patients. Plasma CTRP9 levels revealed a significant negative correlation with LDL-C, FBG, and TG, while a positive correlation was observed with HDL-C. These relationships were also partially reflected in a study of Huang et al.23. These findings suggest that plasma CTRP9 levels may serve as a valuable biomarker for evaluating glucose and lipid metabolism, as well as the severity of atherosclerosis. Gao et al. demonstrated that CTRP9 was exclusively associated with well-developed coronary collateral circulation in non-diabetic participants, but not in diabetic participants24. These findings suggest that CTRP9 has the potential to promote vascular revascularization in the event of ischemic events. In a study of 416 patients with T2DM, plasma CTRP9 concentrations were found to be significantly correlated with atherosclerosis25. Previous experiments have indicated that circulating CTRP9 was associated with coronary stiffness, and the plasma CTRP9 levels in patients with CAD were reduced26. Lei S et al. found that CTRP9 enhanced cholesterol efflux by reducing foam cell apoptosis27. CTRP9 plays a crucial role in attenuating cardiac dysfunction associated with high-fat diet-induced metabolic stress28. Based on these studies, we hypothesized that differences in CTRP9 expression levels may be related to its compensatory response to insulin resistance and inflammatory environments in different study subjects, such as CAD and T2DM.

The protective effect of CTRP9 on CAD has been reported, but its relationship with the prognosis of CAD remains unclear. The incidence of MACEs is commonly used as a major outcome indicator to evaluate the effectiveness of interventions in clinical trials29. In this study, lower plasma CTRP9 concentrations were associated with a higher risk of MACEs compared with higher levels. From a statistical perspective, CTRP9 was analyzed as a continuous variable in the Cox regression model; therefore, the observed HR reflects the incremental change in risk associated with each 1 ng/mL decrease in plasma CTRP9 levels. CTRP9 is an anti-inflammatory protein that improves endothelial function, and a reduction in its levels represents a state of chronic adverse biological exposure. Consequently, although the hazard ratio per unit decrease appears numerically small, the wide range of CTRP9 levels observed in clinical practice suggests that cumulative decreases across multiple units may have substantial clinical significance. These results indicate that CTRP9 may serve as a reliable biomarker for predicting the prognosis of CAD. Emerging research indicates that CTRP9 has the capacity to confer cardioprotective benefits through promoting the secretion of angiogenic factors in endothelial cells, inhibiting intimal hyperplasia, and reducing myocardial fibrosis30,31. Numerous other studies have indicated that the administering a specific concentration of CTRP9 to wild-type mice prior to ischemia-reperfusion reduces the myocardial infarction area32,33. Li et al. revealed a significant reduction in circulating CTRP9 levels among patients with myocardial infarction, irrespective of the stage of the infarction. These findings may indicate that CTRP9 is a unique predictor of myocardial infarction. Further experiments indicated that administration of certain concentrations of CTRP9 to mice modeled with myocardial infarction could improve left ventricular systolic function34. This is also consistent with our experimental results, which revealed that further multivariate Cox regression analysis indicated that CTRP9 and EF retained their independent predictive capacity for MACEs in CAD, even after adjusting for confounding factors. Liu et al. demonstrated that CTRP9 has the potential to ameliorate fibrosis, atrial inflammation, and susceptibility to atrial fibrillation in rats following myocardial infarction35. CTRP9 could attenuate cardiac remodeling after myocardial infarction and the reduction of CTRP9 level was directly proportional to the morbidity, mortality, and severity of heart failure36. These consequences also suggested that CTRP9 exerted a unique protective role in cardiac prognosis.

Based on current evidence, plasma CTRP9 levels may have clinical value for risk stratification in patients with coronary artery disease. Lower CTRP9 concentrations are associated with more complex coronary lesions and an increased risk of long-term major adverse cardiovascular events, independent of confounders. Given its inverse relationship with adverse metabolic profiles and atherosclerosis severity, CTRP9 may complement traditional risk markers to identify high-risk CAD patients. Combined with prior evidence of its anti-inflammatory, anti-atherosclerotic, and cardioprotective effects, CTRP9 represents a promising biomarker for improving prognostic evaluation in CAD. Therefore, future clinical strategies for managing CAD should extensively investigate the functions of CTRP9, emphasizing the necessity for additional research to fully understand the clinical implications of CTRP9 within the CAD context.

Limitation

Nonetheless, several inherent limitations of this study should be recognized. First, the observational and single-center design may introduce potential bias, and the findings may not be generalizable to other populations. Second, the study lacks external validation, which could further strengthen the robustness of the results. Third, the relatively short follow-up duration may limit the ability to capture long-term clinical outcomes comprehensively. Additionally, the modest sample size may reduce the statistical power of certain analyses. Finally, while this study provides valuable clinical associations, the underlying mechanisms through which CTRP9 regulates the progression of coronary artery disease remain to be fully elucidated. Comprehensive experimental studies, including animal models, are warranted to investigate these mechanisms in detail.

Conclusion

In general, plasma CTRP9 levels were found to be low in the moderate-severe group, and these reductions in CTRP9 levels may aid in identifying individuals at an increased risk of MACEs. It can be preliminarily inferred that CTRP9 serves as a significant risk factor for assessing the degree of coronary artery stenosis and predicting the prognosis of patients with CAD. In the future, it is expected to guide the treatment of patients with CAD.