Correlation between the serum FABP4, ANGPTL3, and ANGPTL4 levels and coronary artery disease.

BACKGROUND: Lipid metabolism related factors, such as angiopoietin-like protein 3 (ANGPTL3), angiopoietin-like 4 (ANGPTL4), fatty acid-binding protein 4 (FABP4) are newly discovered factors that can affect coronary artery disease (CAD). In this study, we aimed to investigate the relationship between CAD and these lipid metabolism factors. HYPOTHESIS: ANGPTL3, ANGPTL4, and FABP4 may provide a new method for the control of CAD risk factors and the prevention and treatment of CAD. METHODS: We enrolled 284 consecutive inpatients with suspected CAD and divided them into CAD and non-CAD groups based on the coronary angiography results. Serum ANGPTL3, ANGPTL4, FABP4, and tumor necrosis factor-α (TNF-α) levels were estimated using the enzyme-linked immunosorbent assay. Multivariate logistic regression was used to assess the risk factors for CAD. The receiver operating characteristic curve was used to determine the cutoff and diagnostic values. RESULTS: The serum TNF-α, FABP4, ANGPTL3, and ANGPTL4 values showed a significant difference between the CAD and non-CAD groups (p < .05). After adjusting for confounding factors, the FABP4, ANGPTL3, and ANGPTL4 levels were independently associated with CAD (p < .05). The ANGPTL3 expression level was an independent risk factor for CAD in patients with hypertension, but not in those without hypertension. The ANGPTL3 > 67.53 ng/mL, ANGPTL4 > 29.95 ng/mL, and FABP4 > 1421.25 ng/L combination had the highest diagnostic value for CAD. CONCLUSION: ANGPTL3, ANGPTL4, and FABP4 were identified as independent risk factors for CAD and have valuable clinical implications for the diagnosis and treatment of CAD.

Application of systemic inflammation indices and lipid metabolism-related factors in coronary artery disease.

OBJECTIVE: We aimed to investigate the relationship between coronary artery disease (CAD) and systemic inflammation indices and lipid metabolism-related factors and subsequently, discuss the clinical application of these factors in CAD. METHODS: We enrolled 284 consecutive inpatients with suspected CAD and divided them into a CAD group and a non-CAD group according to coronary angiography results. Serum levels of angiopoietin-like protein 3 (ANGPTL3), angiopoietin-like protein 4 (ANGPTL4), fatty acid-binding protein 4 (FABP4), and tumor necrosis factor-α (TNF-α) levels were assessed using the ELISA and the systemic inflammation indices were calculated. Multivariate logistic regression was used to assess the risk factors of CAD. The receiver operating characteristic curve was used to determine the cutoff and diagnostic values. RESULTS: The neutrophil-to-high density lipoprotein cholesterol ratio (5.04 vs. 3.47), neutrophil-to-lymphocyte ratio (3.25 vs. 2.45), monocyte-to-high density lipoprotein cholesterol ratio (MHR) (0.46 vs. 0.36), monocyte-to-lymphocyte ratio (0.31 vs. 0.26), systemic immune-inflammation index (SII) (696.00 vs. 544.82), serum TNF-α (398.15 ng/l vs. 350.65 ng/l), FABP4 (1644.00 ng/l vs. 1553.00 ng/l), ANGPTL3 (57.60 ng/ml vs. 52.85 ng/ml), and ANGPTL4 (37.35 ng/ml vs. 35.20 ng/ml) values showed a significant difference between the CAD and non-CAD groups ( P  < 0.05). After adjusting for confounding factors, the following values were obtained: ANGPTL3 > 67.53 ng/ml [odds ratio (OR) = 8.108, 95% confidence interval (CI) (1.022-65.620)]; ANGPTL4 > 29.95 ng/ml [OR = 5.599, 95% CI (1.809-17.334)]; MHR > 0.47 [OR = 4.872, 95% CI (1.715-13.835)]; SII > 589.12 [OR = 5.131, 95% CI (1.995-13.200)]. These factors were found to be independently associated with CAD ( P  < 0.05). Diabetes combined with MHR > 0.47, SII > 589.12, TNF-α >285.60 ng/l, ANGPTL3 > 67.53 ng/ml, and ANGPTL4 > 29.95 ng/l had the highest diagnostic value for CAD [area under the curve: 0.921, 95% CI, (0.881-0.960), Sensitivity: 88.9%, Specificity: 82.2%, P  < 0.001]. CONCLUSION: MHR > 0.47, SII > 589.12, TNF-α >285.60 ng/l, ANGPTL3 > 67.53 ng/ml, and ANGPTL4 > 29.95 ng/l were identified as independent CAD risk factors and have valuable clinical implications in the diagnosis and treatment of CAD.

Establishment of a Predictive Model for Poor Prognosis of Incomplete Revascularization in Patients with Coronary Heart Disease and Multivessel Disease.

OBJECTIVE: To establish a predictive model for poor prognosis after incomplete revascularization (ICR) in patients with multivessel coronary artery disease (MVD). METHODS: Clinical data of 757 patients with MVD and ICR after percutaneous coronary intervention (PCI) in the Affiliated Hospital of Chengde Medical University from January 2020 to August 2021 were retrospectively collected. The least absolute shrinkage and selection operator regression method was used to screen variables, and multivariate logistic regression was used to establish a predictive model. An independent cohort was used to validate the model. The C-statistic was used to verify and evaluate the discriminative ability of the model; the calibration curve was drawn, and the decision curve analysis (DCA) was performed to evaluate the calibration degree, the clinical net benefit, and the practicability of the model. RESULTS: The predictive factors included female, age, unconjugated bilirubin, uric acid, low-density lipoprotein, hyperglycemia, total occlusion, and severe tortuosity lesion on coronary angiography. The C-statistic of the training and validation sets were 0.628 and 0.745, respectively. The statistical value of the Hosmer-Lemeshow test for the calibration curve of the training and validation sets were 5.27(P = 0.873) and 6.27 (P = 0.792), respectively. DCA showed that the model was clinically applicable when the predicted probability value of major adverse cardiovascular events(MACEs) ranged from 0.07 to 0.68. CONCLUSIONS: We established a predictive model for poor prognosis after ICR in patients with MVD. The predictive and calibration ability and the clinical net benefit of the predictive model were good, indicating that it can be used as an effective tool for the early prediction of poor prognosis after ICR in patients with MVD.

Role of serum C1q/TNF-related protein family levels in patients with acute coronary syndrome.

Background: The C1q/TNF-related protein (CTRP) family affects inflammation regulation, energy metabolism, and insulin signaling. However, their role in acute coronary syndrome (ACS) development is unclear. In this cross-sectional study, we aimed to investigate the association between CTRP family and ACS. Methods: We enrolled 289 consecutive inpatients with suspected ACS. Serum CTRP family, tumor necrosis factor-α (TNF-α), and adiponectin (ADP) levels were assessed using enzyme-linked immunosorbent assay (ELISA). Multivariate logistic regression and subgroup analyses were used to assess risk factors for ACS. Spearman's tests were used to analyze correlations between CTRP family and continuous variables. Results: Serum CTRP family levels differed significantly between ACS and Control groups (p < 0.05). After adjusting for confounding factors, CTRP family were independently associated with ACS (p < 0.05). The association between serum CTRP family levels and ACS was stable in various subgroups according to sex, age, diabetes mellitus, and dyslipidemia status (p for interaction > 0.05). Increasing tertiles of serum CTRP1 levels, significantly increased ACS risks, which decreased gradually with increasing CTRP2, CTRP12, and CTRP13 tertiles (p for trend < 0.05). Additionally, serum CTRP1, CTRP2, CTRP13, and CTRP15 levels were weakly correlated with the severity of coronary artery stenosis. Conclusion: CTRP1 and CTRP5 were identified as independent ACS risk factors, whereas CTRP2, CTRP3, CTRP9, CTRP12, CTRP13, and CTRP15 were independent protective factors for ACS. CTRP family, especially CTRP1 and CTRP3 could be novel potential clinical biomarkers of ACS.

Association Between Novel Pro- and Anti- Inflammatory Adipocytokines in Patients with Acute Coronary Syndrome.

BACKGROUND AND AIMS: Novel pro- and anti-inflammatory adipocytokines affect inflammation, energy metabolism, and insulin signaling. However, their role in acute coronary syndrome (ACS) development is unclear. We evaluated the diagnostic and risk predictive value of such adipocytokines for ACS. METHODS: We enrolled 168 consecutive inpatients with suspected ACS and detected serum PLIN1, PLIN2, PLIN5, CTRP6, CTRP7, CTRP11, WISP1, FAM19A5, TNF-α, and adiponectin levels. Multivariate logistic regression analysis and Spearman's test were used to assess risk factors for ACS and correlations between serum adipocytokines and continuous variables, respectively. RESULTS: Serum levels of the adipocytokines differed between ACS and Non-ACS groups (p < 0.05). After adjusting for confounding factors, serum PLIN1, PLIN2, PLIN5, CTRP6, CTRP7, CTRP11, WISP1, and FAM19A5 levels were independently associated with ACS (p < 0.05). Increasing tertiles of serum PLIN1, PLIN2, CTRP7, CTRP11, and WISP1 levels increased the ACS risk, which decreased gradually with increasing PLIN5 and CTRP6 tertiles (p for trend <0.05). Serum PLIN1, PLIN5, CTRP6, CTRP7, CTRP11, WISP1, and FAM19A5 levels correlated with ACS severity. CONCLUSIONS: PLIN1, PLIN2, CTRP7, CTRP11, and WISP1 were identified as independent ACS risk factors, whereas PLIN5, CTRP6, and FAM19A5 were independent protective factors for ACS. These serum adipocytokines are novel potential clinical biomarkers of ACS.