The correlation of retinol-binding protein-4 and lipoprotein combine index with the prevalence and diagnosis of acute coronary syndrome

The association between healthy eating index-2015 with anthropometric, cardiometabolic and hepatic indices among patients with non-alcoholic fatty liver disease

BACKGROUND

Obesity, cardiovascular diseases, and metabolic disorders are common problems among participants with non-alcoholic fatty liver disease (NAFLD). However, the association between these problems and the healthy eating index-2015 (HEI-2015) remains unknown. Although the HEI-2015 originated from American dietary guidelines, its comprehensive evaluation of diet quality provides valuable insights for various populations, including Iranians. Therefore, the objective of this study was to investigate the association between anthropometric, hepatic, and cardio-metabolic indices with HEI-2015 scores in participants with NAFLD.

METHODS

We conducted a cross-sectional analysis of data from the Hoveyzeh Cohort Study, which included adults aged 35 to 70 years between 2016 and 2018. A total of 664 participant with NAFLD (452 females and 212 males) were included in the analysis. The HEI-2015 was assessed using the Food Frequency Questionnaire (FFQ). Various indices, including the body shape index (ABSI), atherogenic index of plasma (AIP), visceral adiposity index (VAI), lipid accumulation product (LAP), cardiometabolic index (CMI), lipoprotein combine index (LCI), AST/ALT ratio, ALD/NAFLD index, and hepatic steatosis index (HSI), were calculated.

RESULTS

No significant differences were observed in anthropometric, cardio-metabolic, and hepatic indices across the quartiles of HEI-2015. However, among participants with NAFLD, men had significantly higher AIP and LCI levels, while women had significantly higher BMI, ABSI, VAI, LAP, and CMI levels. Additionally, women with NAFLD exhibited higher AST/ALT and HSI levels but lower ALD/NAFLD levels compared to men with NAFLD. Linear regression analysis among men with NAFLD revealed a significant negative correlation between HEI-2015 score and HSI in both the unadjusted model (β=-0.131, SE = 0.058, p = 0.024) and the adjusted model for energy intake (β=-0.129, SE = 0.058, p = 0.028).

CONCLUSION

The present study demonstrated a correlation between lower HEI-2015 scores and an increased risk of steatosis in men with NAFLD. Moreover, our findings highlighted gender-related differences in NAFLD and cardio-metabolic disorders.

Using a k-means clustering to identify novel phenotypes of acute ischemic stroke and development of its Clinlabomics models

Objective

Acute ischemic stroke (AIS) is a heterogeneous condition. To stratify the heterogeneity, identify novel phenotypes, and develop Clinlabomics models of phenotypes that can conduct more personalized treatments for AIS.

Methods

In a retrospective analysis, consecutive AIS and non-AIS inpatients were enrolled. An unsupervised k-means clustering algorithm was used to classify AIS patients into distinct novel phenotypes. Besides, the intergroup comparisons across the phenotypes were performed in clinical and laboratory data. Next, the least absolute shrinkage and selection operator (LASSO) algorithm was used to select essential variables. In addition, Clinlabomics predictive models of phenotypes were established by a support vector machines (SVM) classifier. We used the area under curve (AUC), accuracy, sensitivity, and specificity to evaluate the performance of the models.

Results

Of the three derived phenotypes in 909 AIS patients [median age 64 (IQR: 17) years, 69% male], in phenotype 1 (N = 401), patients were relatively young and obese and had significantly elevated levels of lipids. Phenotype 2 (N = 463) was associated with abnormal ion levels. Phenotype 3 (N = 45) was characterized by the highest level of inflammation, accompanied by mild multiple-organ dysfunction. The external validation cohort prospectively collected 507 AIS patients [median age 60 (IQR: 18) years, 70% male]. Phenotype characteristics were similar in the validation cohort. After LASSO analysis, Clinlabomics models of phenotype 1 and 2 were constructed by the SVM algorithm, yielding high AUC (0.977, 95% CI: 0.961-0.993 and 0.984, 95% CI: 0.971-0.997), accuracy (0.936, 95% CI: 0.922-0.956 and 0.952, 95% CI: 0.938-0.972), sensitivity (0.984, 95% CI: 0.968-0.998 and 0.958, 95% CI: 0.939-0.984), and specificity (0.892, 95% CI: 0.874-0.926 and 0.945, 95% CI: 0.923-0.969).

Conclusion

In this study, three novel phenotypes that reflected the abnormal variables of AIS patients were identified, and the Clinlabomics models of phenotypes were established, which are conducive to individualized treatments.

Nonlinear relationship between untraditional lipid parameters and the risk of prediabetes: a large retrospective study based on Chinese adults

BACKGROUND

Abnormal lipid metabolism poses a risk for prediabetes. However, research on lipid parameters used to predict the risk of prediabetes is scarce, and the significance of traditional and untraditional lipid parameters remains unexplored in prediabetes. This study aimed to comprehensively evaluate the association between 12 lipid parameters and prediabetes and their diagnostic value.

METHODS

This cross-sectional study included data from 100,309 Chinese adults with normal baseline blood glucose levels. New onset of prediabetes was the outcome of concern. Untraditional lipid parameters were derived from traditional lipid parameters. Multivariate logistic regression and smooth curve fitting were used to examine the nonlinear relationship between lipid parameters and prediabetes. A two-piecewise linear regression model was used to identify the critical points of lipid parameters influencing the risk of prediabetes. The areas under the receiver operating characteristic curve estimated the predictive value of the lipid parameters.

RESULTS

A total of 12,352 participants (12.31%) were newly diagnosed with prediabetes. Following adjustments for confounding covariables, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol were negatively correlated with prediabetes risk. Conversely, total cholesterol, triglyceride (TG), lipoprotein combine index (LCI), atherogenic index of plasma (AIP), non-HDL-C, atherogenic coefficient, Castelli's index-I, remnant cholesterol (RC), and RC/HDL-C ratio displayed positive correlations. In younger adults, females, individuals with a family history of diabetes, and non-obese individuals, LCI, TG, and AIP exhibited higher predictive values for the onset of prediabetes compared to other lipid profiles.

CONCLUSION

Nonlinear associations were observed between untraditional lipid parameters and the risk of prediabetes. The predictive value of untraditional lipid parameters for prediabetes surpassed that of traditional lipid parameters, with LCI emerging as the most effective predictor for prediabetes.

Use of Atherogenic Indices as Assessment Methods of Clinical Atherosclerotic Diseases

BACKGROUND

Central illustration : Use of Atherogenic Indices as Assessment Methods of Clinical Atherosclerotic Diseases.

BACKGROUND

The search for clinically useful methods to assess atherosclerotic diseases (ASCVD) with good accuracy, low cost, non-invasiveness, and easy handling has been stimulated for years. Thus, the atherogenic indices evaluated in this study may fit this growing demand.

OBJECTIVES

To assess the potential of atherogenic indices to evaluate patients with clinical atherosclerosis.

METHODS

Single-center cross-sectional study, through which the Castelli I and II indices, the atherogenic index of plasma (AIP), the lipoprotein combine index, and the variation in the peripheral perfusion index between 90 and 120 seconds after an endothelium-dependent (ΔPI90-120) vasodilator stimulus were evaluated in the prediction of atherosclerosis. Statistical significance was set at p < 0.05.

RESULTS

The sample consisted of 298 individuals with an average age of 63.0±16.1 years, of which 57.4% were women. Paired comparisons of the ROC curve analysis of the indices that reached the area under the curve (AUC) > 0.6 show that ΔPI90-120 and AIP were superior to other indices, and no differences were observed between them (difference between AUC = 0.056; 95%CI -0.003-0.115). Furthermore, both the ΔPI90-120 [odds ratio (OR) 9.58; 95%CI 4.71-19.46)] and AIP (OR 5.35; 95%CI 2.30-12.45) were independent predictors of clinical atherosclerosis.

CONCLUSIONS

The AIP and ΔPI90-120 represented better accuracy in discriminating clinical ASCVD. Moreover, they were independent predictors of clinical ASCVD, evidencing a promising possibility for developing preventive and control strategies for cardiovascular diseases. Therefore, they are markers for multicenter studies from the point of view of practicality, low cost, and external validity.

The atherogenic index of plasma (AIP) is a predictor for the severity of coronary artery disease

Objective

Dyslipidemia is a key risk factor for coronary artery disease (CAD). This study aimed to investigate the correlation between the atherogenic index of plasma (AIP) and the severity of CAD.

Methods

2,491 patients were enrolled in this study and analyzed retrospectively, including 665 non-CAD patients as the control group and 1,826 CAD patients. The CAD patients were classified into three subgroups according to tertiles of SYNTAX score (SS). Non-high-density lipoprotein cholesterol (Non-HDL-C) was defined as serum total cholesterol (TC) minus serum high-density lipoprotein cholesterol (Non-HDL-C), atherogenic index (AI) was defined as the ratio of non-HDL-C to HDL-C; AIP was defined as the logarithm of the ratio of the concentration of triglyceride (TG) to HDL-C; lipoprotein combine index (LCI) was defined as the ratio of TC∗TG∗ low-density lipoprotein cholesterol (LDL)to HDL-C; Castelli Risk Index I (CRI I) was defined as the ratio of TC to HDL-C; Castelli Risk Index II (CRI II) was defined as the ratio of LDL-C to HDL-C.

Results

The levels of AIP (P < 0.001), AI (P < 0.001), and LCI (P = 0.013) were higher in the CAD group compared with the non-CAD group. The Spearman correlation analysis showed that AIP (r = 0.075, P < 0.001), AI (r = 0.132, P < 0.001), and LCI (r = 0.072, P = 0.001) were positively correlated with SS. The multivariate logistic regression model showed CRI I (OR: 1.11, 95% CI: 1.03-1.19, P = 0.005), CRI II (OR: 1.26, 95% CI: 1.15-1.39, P < 0.001), AI (OR: 1.28, 95% CI: 1.17-1.40, P < 0.001), AIP (OR: 2.06, 95% CI: 1.38-3.07, P < 0.001), and LCI (OR: 1.01, 95% CI: 1.01-1.02, P < 0.001) were independent predictors of severity of CAD After adjusting various confounders.

Conclusion

CRI I, CRI II, AIP, AI, and LCI were independent predictors of the severity of CAD, which could be used as a biomarker for the evaluation of the severity of CAD.

Metabolic Deregulations in Patients with Polycystic Ovary Syndrome

Polycystic ovary syndrome (PCOS) contributes to endocrine and metabolic complications for women worldwide. The aim of this study was to establish the usefulness of new anthropometric indices and atherogenic indices in the evaluation of metabolic disorders, in particular, glucose and insulin abnormalities in the profiles of women with polycystic ovary syndrome (PCOS). In the study, a total of 49 women with PCOS aged between 18 and 39 years were recruited. All patients were tested for fasting glucose and insulin, lipid parameters, oral-glucose administration, and biochemical parameters. All of them underwent anthropometric measurements, such as BMI (body mass index), WHR (waist-to-hip ratio), WHtR (waist-to-height ratio), BAI (body adiposity index), VAI (visceral adiposity index), LAP (lipid accumulation product), BRI (body roundness index), ABSI (A body shape index), AIP (atherogenic risk of plasma), AC (atherogenic coefficient), Castelli risk index-I, Castelli risk index-II and (LCI) lipoprotein combine index, TG/HDL-C ratio, METS-IR (The metabolic score of insulin resistance), triglyceride glucose index (TyG index), triglyceride glucose-body mass index (TyG-BMI index) and triglyceride glucose-waist circumference index (TyG-WC index) were calculated. The analyzed anthropometric measurements/indices and atherogenic indices demonstrated significant correlations in PCOS women. T A strong relationship was found between fasting glucose, fasting insulin, glucose after 60 min, HOMA-IR index in the patients with PCOS. There was no significant relationship between HbA1c and other analyzed parameters and indices. Most of the analyzed anthropometric and atherogenic indices may be useful tools in evaluating metabolic disorders, and, in particular, glucose and insulin abnormalities in PCOS women.

The predictive value of nontraditional lipid parameters for intracranial and extracranial atherosclerotic stenosis: a hospital-based observational study in China

BACKGROUND

Ischemic strokes are primarily caused by intracranial and extracranial atherosclerotic stenosis. Nontraditional lipid parameters broaden traditional lipid profiles, better reflect the metabolism and interaction between different lipid components, and optimize the predictive ability of lipid profiles for atherosclerotic diseases. This research was carried out to investigate the predictive value of nontraditional lipid parameters for intracranial or extracranial atherosclerotic stenosis.

METHODS

The investigation collected data from inpatients who underwent cervical vascular ultrasonography, carotid CTA, cerebral artery CTA or MRA, and brain MRI or CT from December 2014 to December 2021. The nontraditional lipid parameters were calculated by collecting traditional lipid parameters. To evaluate the predictive power of nontraditional lipid parameters, logistic regression and receiver operating characteristic curve (ROC) analyses were performed.

RESULTS

Based on the inclusion and exclusion criteria, 545 patients were included. According to the imaging results, inpatients were divided into two groups, including no intracranial or extracranial atherosclerotic stenosis (n = 250) and intracranial or extracranial atherosclerotic stenosis (AS, n = 295). Among them, AS was further divided into three subgroups: intracranial atherosclerotic stenosis (ICAS), extracranial atherosclerotic stenosis (ECAS) and combined intracranial and extracranial atherosclerotic stenosis (IECAS). Logistic regression analysis showed that nontraditional lipid parameters, including the atherogenic index of plasma (AIP), TG/HDL-C, remnant cholesterol (RC), nonhigh-density lipoprotein cholesterol (non-HDL-C), lipoprotein combine index (LCI), atherogenic coefficient (AC), Castelli's index-I (CRI-I) and Castelli's index-II (CRI-II), were significantly correlated with intracranial or extracranial atherosclerotic stenosis (P < 0.05). Compared with other nontraditional lipid parameters, regardless of adjusting for potential confounding factors, AIP had a greater OR value in ICAS (OR = 4.226, 95% CI: 1.681-10.625), ECAS (OR = 2.993, 95% CI: 1.119-8.003) and IECAS (OR = 4.502, 95% CI: 1.613-12.561). ROC curve analysis revealed that nontraditional lipid parameters had good predictive power for intracranial or extracranial atherosclerotic stenosis.

CONCLUSIONS

This Chinese hospital-based study demonstrates that nontraditional lipid parameters (AIP, LCI, RC, CRI-II, AC, CRI-I and non-HDL-C) are effective predictors of intracranial and extracranial atherosclerotic stenosis, of which AIP may be a significant risk factor for predicting atherosclerotic arterial stenosis in the intracranial or extracranial regions.

A Prognostic Model for In-Hospital Mortality in Critically Ill Patients with Pneumonia

Purpose

To determine the utility of a novel serum biomarker for the outcome prediction of critically ill patients with pneumonia.

Patients and Methods

A retrospective analysis of critically ill patients was performed at an emergency department. The expression and prediction value of parameters were assessed. Binary logistic regression analysis was utilized to determine the indicators associated with in-hospital mortality of pneumonia patients. The Last Absolute Shrinkage and Selection Operator was used to further determine the independent predictors, which were validated by multiple logistic regression. The receiver operator characteristic curve was performed to assess their prediction values. A prognostic nomogram model was finally established for the outcome prediction for critically ill patients with pneumonia.

Results

Retinol-binding protein (RBP) was significantly reduced in non-survived and pneumonia patients. CURB-65 score, levels of RBP, and blood urea nitrogen (BUN) were associated with in-hospital mortality of critically ill patients with pneumonia. Their combination was determined to be an ideal prognostic predictor (area under the curve of 0.762) and further developed into a nomogram prediction model (c-index 0.764).

Conclusion

RBP is a novel in-hospital mortality predictor, which well supplements the CURB-65 score for critical pneumonia patients.

Prognostic significance of multiple triglycerides-derived metabolic indices in patients with acute coronary syndrome

BACKGROUND

Triglyceride (TG) and its related metabolic indices, all recognized as surrogates of insulin resistance, have been demonstrated to be relevant to clinical prognosis. However, the relative value of these TG-related indices for predicting cardiovascular events among patients with acute coronary syndrome (ACS) has not been examined.

METHODS

The TG, the triglyceride-glucose (TyG) index, the atherogenic index of plasma, TG to high-density lipoprotein cholesterol ratio, and the lipoprotein combine index were assessed in 1694 ACS patients undergoing percutaneous coronary intervention. The primary endpoint was major adverse cardiovascular event (MACE), which was the composite of all-cause mortality, stroke, myocardial infarction, or unplanned repeat revascularization.

RESULTS

During a median follow-up of 31 months, 345 patients (20.4%) had MACE. The risk of the MACE was increased with higher TG and the four TG-derived metabolic indices [TG-adjusted hazard ratio (HR) = 1.002, 95% CI: 1.001-1.003; TyG index-adjusted HR = 1.736, 95% CI: 1.398-2.156; atherogenic index of plasma-adjusted HR = 2.513, 95% CI: 1.562-4.043; TG to high-density lipoprotein cholesterol ratio-adjusted HR = 1.148, 95% CI: 1.048-1.258; and lipoprotein combine index-adjusted HR = 1.009, 95% CI: 1.004-1.014; P < 0.001 for all indices]. TG and all the four indices significantly improved the predictive ability for MACE in addition to the baseline model. Among them, TyG index showed the best ability for predicting MACE compared with the other three indices from all the three measurements ( P < 0.05 for all comparison).

CONCLUSIONS

TG and TG-derived metabolic indices were all strongly associated with MACE among ACS patients undergoing percutaneous coronary intervention. Among all the indices, TyG index showed the best ability to predict the risk of MACE.

Association Between Circulating Retinol-Binding Protein 4 and Adverse Cardiovascular Events in Stable Coronary Artery Disease

Background

The predictive role of retinol-binding protein 4 (RBP4) in the adverse prognosis of patients with stable coronary artery disease (CAD) has not been well-defined. We thus conducted this cohort study to investigate the association between circulating RBP4 level and major adverse cardiovascular events (MACEs) in Chinese patients with stable CAD.

Methods

Patients with stable CAD and serum RBP4 concentration measurement at admission between July 2012 and January 2015 were included. The primary outcome in this study was incident MACEs, which included acute coronary syndrome, heart failure, stroke, peripheral vascular disease, and cardiovascular death. Cox proportional hazards regression was adopted to investigate the association between RBP4 and the incidence of MACEs.

Results

A total of 840 patients with stable CAD were analyzed. The mean age of patients was 61.2 ± 15.9 years, and 56.1% of them were men. After a median follow-up of 2.3 years, 129 MACEs were observed. Compared to participants exposed to the first quartile of serum RBP4 level, those in the second, the third, and the fourth quartiles had associated hazard ratios (HRs) of 2.38 [95% confidence interval (CI): 1.33-4.26], 2.35 (95% CI: 1.31-4.21), and 2.27 (95% CI: 1.28-4.04) after adjusted for confounders, respectively. Every 5 μg/ml increment in serum RBP4 concentration was associated with an adjusted HR of 1.13 (95% CI: 1.05-1.22) for the occurrence of MACEs. Subgroup analyses suggested no significant modifying effects of baseline characteristics for the association between RBP4 and MACEs in patients with stable CAD.

Conclusion

Our finding suggested that the higher circulating RBP4 level was significantly associated with an increased risk of MACEs in patients with stable CAD.

The Association of Triglyceride Glucose index for Coronary Artery Disease in Postmenopausal Women

This study aimed to explore the association between the triglyceride glucose (TyG) index and coronary artery disease (CAD) in postmenopausal women. This study enrolled 869 postmenopausal women and classified them into two groups: CAD group (n  =  538) and control group (n  =  331). The TyG index was significantly higher in patients with CAD than in controls (P < 0.05).Receiver operator characteristic curves showed that the TyG index was more discriminative for CAD than for control group, and after adjusting for the traditional clinical prognostic factors, including age (>60 years), diabetes, ischemic stroke, systolic blood pressure (≥140), and ejection fraction (<50%), we found that the TyG index could be an independent risk factor for CAD (P < 0.05). The risk of increased TyG index was greater in the <50 years subgroup than in the >50 years subgroup (P < 0.05). The TyG index may be a valuable clinical predictor of CAD risk in postmenopausal women.

Low Levels of Serum Fetuin-A and Retinol-Binding Protein 4 Correlate with Lipoprotein Subfractions in Morbid Obese and Lean Non-Diabetic Subjects

Background: Fetuin-A and retinol-binding protein 4 (RBP4) are secreted as both hepatokine and adipokine. These are involved in insulin resistance, obesity-related dyslipidemia, and atherosclerosis. To date, correlations of circulating fetuin-A and RBP4 with lipoprotein subfractions as well as high-density lipoprotein (HDL)-linked proteins have not been entirely investigated in morbid obese and lean non-diabetic subjects. Methods: One-hundred obese non-diabetic patients (body mass index, BMI: 42.5 ± 8.1 kg/m²) along with 32 gender and age-matched normal weight controls (BMI: 24.5 ± 2.5 kg/m²) were enrolled in our study. Serum fetuin-A and RBP4 were measured by ELISA. Lipoprotein subfractions were distributed by Lipoprint gelelectrophoresis. Results: Serum fetuin-A and RBP4 were unexpectedly lower in obese patients (p < 0.01 and p < 0.01, respectively) compared to controls and correlated with each other (r = 0.37; p < 0.001). Fetuin-A had positive correlations with HDL-C (r = 0.22; p = 0.02), apolipoprotein AI (apoAI) (r = 0.33; p < 0.001), very-low density lipoprotein (VLDL) subfraction (r = 0.18; p = 0.05), and large HDL subfraction levels (r = 0.3; p = 0.001) but did not show correlation with carbohydrate parameters in all subjects. RBP4 correlated positively with HDL-C (r = 0.2; p = 0.025), apoAI (r = 0.23; p = 0.01), VLDL subfraction (r = 0.37; p < 0.001), intermediate HDL subfraction (r = 0.23; p = 0.01), and small HDL subfraction (r = 0.21; p = 0.02) concentrations, as well as C-peptide levels in overall participants. Backward stepwise multiple regression analysis showed that serum fetuin-A concentration is best predicted by RBP4 and large HDL subfraction. In model 2, VLDL subfraction was the independent predictor of serum RBP4 level. Conclusions: Our data may indicate a potential role of fetuin-A and RBP4 in impaired lipoprotein metabolism associated with obesity.

Circulating retinol binding protein 4 levels in coronary artery disease: a systematic review and meta-analysis

BACKGROUND

Retinol binding protein 4 (RBP4) has been proposed to play a role in the pathophysiology of coronary artery disease (CAD), but previous findings on the association of RBP4 levels with CAD are inconsistent.

METHODS

A meta-analysis based on observational studies was conducted to evaluate the association between circulating RBP4 levels and CAD. Databases including PubMed, Web of Science, Embase, Google Scholar and ClinicalTrials.gov database were searched for eligible studies published up to 12 July 2021. Standard mean differences (SMDs) with 95% confidence intervals (CIs) were calculated using the inverse variance heterogeneity (IVhet) and random-effects model for data with moderate and high heterogeneity (I² > 30%) and data with low heterogeneity were analysed using a fixed-effects model (I² ≤ 30%). Moreover, a bias-adjusted quality-effects model was generated, and the prediction interval was also calculated under the random-effects model.

RESULTS

Two nested case-control studies, one cohort study and twelve case-control studies with a total of 7111 participants were included. Circulating RBP4 levels in patients with CAD were comparable to those in the controls under the IVhet model (SMD: 0.25, 95% CI: - 0.29-0.79, I²: 96.00%). The quality-effects model produced consistent results. However, the association turned to be significant under the random-effect model (SMD: 0.46, 95% CI: 0.17-0.75, I²: 96.00%), whereas the 95% predictive interval (PI) included null values (95% PI: - 0.82-1.74). Subgroup analyses illustrated a positive relationship between CAD and RBP4 levels in patients with complications (SMD: 1.34, 95% CI: 0.38-2.29, I²: 96.00%). The meta-regression analysis revealed that the mean BMI of patients (P = 0.03) and complication status (P = 0.01) influenced the variation in SMD.

CONCLUSIONS

There was low-quality evidence that patients with CAD exhibited similar circulating RBP4 levels compared with controls, and high inter-study heterogeneity was also observed. Thus, RBP4 might not be a potential risk factor for CAD. Comparisons among different subtypes of RBP4 with larger sample size are needed in the future.