Biochemical and Anthropometric Indices of Insulin Resistance in Obese and Overweight Children with Metabolic Dysfunction-Associated Fatty Liver Disease.

BACKGROUND The prevalence of metabolic (dysfunction)-associated fatty liver disease (MAFLD) increases together with the epidemic of childhood obesity. An important mechanism in the phenomenon appears to be insulin resistance (IR), the assessment of which in children is problematic. The homeostatic model assessment of IR (HOMA-IR), commonly used for this, is not standardized and appears not to correlate with IR in the pediatric population. Therefore, our study aimed to evaluate potential substitute indices of IR, including the triglyceride-glucose index (TyG), triglyceride to high-density lipoprotein cholesterol ratio (TG/HDL-C), modified TyG indices: TyG-waist circumference (TyG-WC) and TyG-body mass index (TyG-BMI) as surrogate markers of MAFLD in obese children suspected to have liver disease. MATERIAL AND METHODS The retrospective study included 264 obese children admitted to the Department to diagnose suspected liver disease. MAFLD was diagnosed according to the International Expert Consensus Statement. Anthropometric measurements and laboratory tests were made and the indices were calculated. Receiver operating characteristics analysis was performed to calculate the power of the indices. RESULTS MAFLD was diagnosed in 184 patients (70%). Obese children with MAFLD showed significantly higher activity of liver enzymes and concentration of total cholesterol, TG, WC, and waist-to-hip ratio compared to non-hepatopathic obese controls (n=80). The most important indices in identifying MAFLD were: TyG (AUC=0.641, p<0.001, cut-off =8.41, sensitivity=57.4%, specificity=68.8%), and TG/HDL-C (AUC=0.638, p<0.001, cut-off=2.5, sensitivity=48.6%, specificity=76.3%). TyG-BMI and HOMA-IR were not useful predictors. CONCLUSIONS TyG and TG/HDL-C can be considered as potential surrogate biomarkers in predicting MAFLD in obese children.

Nonlinear association between atherogenic index of plasma and type 2 diabetes mellitus in overweight and obesity patients: evidence from Chinese medical examination data.

BACKGROUND: The atherogenic index of plasma (AIP) is closely associated with the onset of diabetes, with obesity being a significant risk factor for type 2 diabetes mellitus (T2DM). However, the association between the AIP and T2DM in overweight and obese populations has been infrequently studied. Therefore, this study aimed to explore this association in overweight and obese individuals with T2DM. METHODS: This cross-sectional analysis utilized data from 40,633 participants with a body mass index (BMI) ≥ 24 kg/m2 who were screened from January 2018 to December 2023 at Henan Provincial People's Hospital. Participants were categorized into groups of overweight and obese individuals with and without diabetes according to the T2DM criteria. The AIP, our dependent variable, was calculated using the formula log10 [(TG mol/L)/HDL-C (mol/L)]. We investigated the association between the AIP and T2DM in overweight and obese individuals using multivariate logistic regression, subgroup analysis, generalized additive models, smoothed curve fitting, and threshold effect analysis. Additionally, mediation analysis evaluated the role of inflammatory cells in AIP-related T2DM. RESULTS: Overweight and obese patients with T2DM exhibited higher AIP levels than those without diabetes. After adjusting for confounders, our results indicated a significant association between the AIP and the risk of T2DM in overweight and obese individuals (odds ratio (OR) = 5.17, 95% confidence interval (CI) 4.69-5.69). Notably, participants with a high baseline AIP (Q4 group) had a significantly greater risk of T2DM than those in the Q1 group, with an OR of 3.18 (95% CI 2.94-3.45). Subgroup analysis revealed that the association between the AIP and T2DM decreased with increasing age (interaction P < 0.001). In overweight and obese populations, the association between AIP and T2DM risk displayed a J-shaped nonlinear pattern, with AIP > - 0.07 indicating a significant increase in T2DM risk. Various inflammatory cells, including neutrophils, leukocytes, and monocytes, mediated 4.66%, 4.16%, and 1.93% of the associations, respectively. CONCLUSION: In overweight and obese individuals, the AIP was independently associated with T2DM, exhibiting a nonlinear association. Additionally, the association between the AIP and T2DM decreased with advancing age. Multiple types of inflammatory cells mediate this association.

Increased high-density lipoprotein cholesterol in patients with type 2 diabetes and its correlates: a cross-sectional, matched case-control survey.

BACKGROUND: So far, high-density lipoprotein cholesterol (HDL-C) levels and mortality were shown to have a U-shaped relationship. Additionally, high HDL-C levels increase the risk of developing a variety of diseases. However, a paucity of data exists regarding the characteristics of people with high HDL-C levels. The aim of this study was to assess the demographics and characteristics of patients with high HDL-C levels and compare their features with normal and low HDL-C groups. METHODS: As a cross-sectional, matched case-control study, a total of 510 patients with type 2 diabetes (T2D) were enrolled in the study and categorized into three matched groups according to their HDL-C concentrations. The studied groups were matched by their age and gender. Restricted cubic spline (RCS) curves were designed to evaluate the relationship between height, blood pressure, triglyceride, and vitamin D concentrations with the probability of having high HDL-C levels. Furthermore, violin plots were conducted to illustrate the distribution of continuous variables within each group. RESULTS: This study showed that having high HDL-C (more than 70 mg/dL) compared to having low HDL-C (less than 40 mg/dL in men and 50 mg/dL in women) was significantly associated with height (OR 0.918, 95% CI 0.866-0.974), systolic blood pressure (SBP) (0.941, 0.910-0.972), vitamin D (0.970, 0.941-0.999), and triglyceride (0.992, 0.987-0.998) serum concentrations. Further analysis investigated that having high HDL-C levels compared to desired HDL-C levels (40 ≤ HDL-C levels < 70 in men and 50 ≤ HDL-C levels < 70 in women) was inversely associated with having SPB values greater than 130 mmHg. Besides, sufficient vitamin D levels (above 20 ng/ml) could 0.349 times decrease the odds of having high HDL-C versus normal HDL-C levels. CONCLUSION: Sufficient vitamin D levels, SPB values higher than 130 mmHg, as well as increased triglyceride levels, were inversely associated with having high HDL levels. However, higher height values were associated with a decreased likelihood of having high HDL.

High levels of high-density lipoprotein cholesterol may increase the risk of diabetic kidney disease in patients with type 2 diabetes.

Studies have indicated that low high-density lipoprotein cholesterol (HDL-C) level is an important risk factor for diabetic kidney disease (DKD) in patients with type 2 diabetes (T2D). However, whether higher HDL-C levels decrease the risk of developing DKD remains unclear. This study aimed to clarify the relationship between HDL-C levels and DKD risk in individuals with T2D in China. In total, 936 patients with T2D were divided into DKD and non-DKD groups. The association between HDL-C levels and DKD risk was evaluated using logistic regression analysis and restricted cubic spline curves adjusted for potential confounders. Threshold effect analysis of HDL-C for DKD risk was also performed. Higher HDL-C levels did not consistently decrease the DKD risk. Furthermore, a nonlinear association with threshold interval effects between HDL-C levels and the incidence of DKD was observed. Patients with HDL-C ≤ 0.94 mmol/L or HDL-C > 1.54 mmol/L had significantly higher DKD risk after adjusting for confounding factors. Interestingly, the association between high HDL-C levels and increased DKD risk was more significant in women. A U-shaped association between HDL-C levels and DKD risk was observed; therefore, low and high HDL-C levels may increase the DKD risk in patients with T2D.

Association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio and obstructive sleep apnea: a cross-sectional study from NHANES.

BACKGROUND: Obstructive Sleep Apnea (OSA) is a widespread sleep disturbance linked to metabolic and cardiovascular conditions. The Non-High-Density Lipoprotein Cholesterol to High-Density Lipoprotein Cholesterol Ratios (NHHR) has been proposed as being a potential biomarker to gauge cardiovascular risk. However, its relationship with OSA remains unclear. METHODS: This survey investigated the link NHHR to OSA in American citizens aged 20 and older using information collected via the National Health and Nutrition Examination Survey (NHANES) during the years 2017 to 2020. Logistic regression models with multivariable adjustments were employed to assess this relationship. Nonlinear associations were explored using smooth curve fitting, with a two-part linear regression model identifying a threshold effect. Subgroup analyses were conducted to evaluate population-specific differences. RESULTS: The survey encompassed 6763 participants, with an average age of 50.75 ± 17.32. The average NHHR stood at 2.74, accompanied by a standard deviation of 1.34, while the average frequency of OSA was 49.93%. Upon adjusting for covariates, each unit increase in NHHR may be associated with a 9% rise in OSA incidence. (95% confidence intervals 1.04-1.14; P < 0.0001). Notably, a U-shaped curve depicted the NHHR-OSA relationship, with an inflection point at 4.12. Subgroup analyses revealed consistent associations, with educational attainment and diabetes status modifying the NHHR-OSA relationship. CONCLUSION: The study highlights NHHR as a potential tool for OSA prediction, presenting avenues for advanced risk evaluation, tailored interventions, personalized treatment approaches, and preventive healthcare.

The Predictive Value of Atherogenic Index of Plasma, Non- High Density Lipoprotein Cholesterol (Non-HDL-C), Non-HDL-C/HDL-C, and Lipoprotein Combine Index for Stroke Incidence and Prognosis in Maintenance Hemodialysis Patients.

Purpose: The serum lipid level is strongly associated with atherosclerosis. However, research on the relationship between lipid-derived indices and acute ischemic stroke (AIS) occurrence in hemodialysis populations is limited. This study aimed to explore the predictive value of lipid-derived indices, including atherogenic index of plasma (AIP), Non- high density lipoprotein cholesterol (Non-HDL-C), Non-HDL-C/HDL-C, and lipoprotein combine index (LCI) in clinical practice for the occurrence and prognosis of AIS in hemodialysis patients. Methods: A total of 451 patients undergoing maintenance hemodialysis were screened and 350 were enrolled in this study. The lipid parameters exhibit a progressive increase across the tertiles, with values rising from Q1 through Q3. Enrolled patients were divided into three groups (Q1, Q2, and Q3) based on tertiles of AIP, Non-HDL-C, Non-HDL-C/HDL-C, and LCI values. Kaplan-Meier curves were performed to investigate the association between the AIP, Non-HDL-C, Non-HDL-C/HDL-C, LCI and AIS-free survival in hemodialysis patients. Chi-square analysis was used to explore the association between the AIP, Non-HDL-C, Non-HDL-C/HDL-C, LCI and AIS outcomes in hemodialysis patients. AIS outcomes were assessed using the modified Rankin Scale (mRS). Results: Kaplan-Meier analysis revealed that the AIS-free survival rates were significantly higher in the Q1 group compared to Q2 and Q3 groups for AIP, Non-HDL-C, Non-HDL-C/HDL-C, and LCI. Log rank tests showed statistically significant differences between the Q1 group and the Q2 and Q3 groups (p < 0.05 for all). The proportion of patients with a good outcome mRS was higher in the Q1 group compared to the Q2-Q3 groups (AIP: 0.818 vs 0.792; Non- HDL-C: 0.866 vs 0.767; Non- HDL-C/HDL-C: 0.867 vs 0.767; LCI: 0.938 vs 0.750). Conclusion: The four lipid-derived parameters are effective predictors of AIS in patients undergoing hemodialysis, and AIP has a strongest correlation with the risk of AIS. Hemodialysis patients with elevated levels of the four lipid-derived indices had a higher incidence of AIS and poorer functional outcomes compared to those with lower levels. Our conclusions may require confirmation by further research in the future.

The relationship between NLR, LDL-C/HDL-C, NHR and coronary artery disease.

OBJECTIVE: Chronic inflammation and dyslipidemia are key risk factors for atherosclerotic cardiovascular diseases. We retrospectively explored the association between the neutrophil to lymphocyte ratio (NLR), the ratio of low-density lipoprotein cholesterol (LDL-C) to high-density lipoprotein cholesterol (HDL-C), and the neutrophil to HDL-C ratio (NHR), and the severity of coronary lesions in patients with acute coronary syndrome (ACS). METHOD: In June 2023, we selected 1210 patients who were diagnosed with ACS based on chest pain from January 2017 to December 2022. Of these, 1100 patients with abnormal coronary angiography were categorized into the experimental group, and 110 patients with normal coronary angiography were classified as the control group. We collected routine blood tests, lipid profiles, and coronary angiography results at admission (before coronary angiography). Patients were then stratified into a control group (Gensini score = 0) and an experimental group (Gensini score = 0) based on the Gensini score. The experimental group was further divided into a low score group (Gensini score < 69) and a high score group (Gensini score ≥ 69). RESULT: 1. Statistically significant differences were observed between the control and experimental groups in terms of gender, age, body mass index (BMI), hypertension, diabetes, smoking history, and counts of neutrophils (NEU), lymphocytes (LYM), monocytes (MON), eosinophils (EOS), red cell distribution width (RDW), total cholesterol (TC), HDL-C, LDL-C, NLR, LDL-C/HDL-C, and NHR (P<0.05). Furthermore, differences in BMI, hypertension, diabetes, smoking history, NEU, LYM, MON, TC, triglyceride (TG), HDL-C, LDL-C, NLR, LDL-C/HDL-C, and NHR were significant between the low and high score groups (P<0.05). 2. NEU, LYM, MON, TC, HDL-C, LDL-C, NLR, LDL-C/HDL-C, and NHR showed significant correlations with the Gensini score (r>0.2, P<0.05), with NLR and LDL-C/HDL-C showing the strongest correlations (r = 0.822, P = 0.000). 3. The Receiver Operating Characteristic (ROC) curve indicated that the combination of NLR and LDL-C/HDL-C had superior sensitivity and specificity in predicting the severity of coronary lesions, with a significant difference (P<0.05). The sensitivity was 87.1%, the specificity was 90.9%, and the cut-off point was 2.04. 4. A predictive model was developed based on the ratio of NLR and LDL-C/HDL-C to the Gensini score. The final model score was calculated as 6.803 + 7.029NLR + 13.079LDL-C/HDL-C (R2 = 0.708). CONCLUSION: Compared to NLR, LDL-C/HDL-C, and NHR, the combined NLR and LDL-C/HDL-C ratio is a more accurate marker for assessing the severity of coronary artery disease in ACS patients. Its convenience and effectiveness make it a promising tool for early assessment, timely risk stratification, and appropriate clinical intervention, ultimately improving clinical outcomes for ACS patients.

[Associations between 4 lipid biomarkers and cardiometabolic multimorbidity development in middle aged and old adults in China].

Objective: To estimate the longitudinal association between serum lipid biomarkers and the development of cardiometabolic multimorbidity (CMM) in middle-aged and old adults (≥45) in China, while examining effect differences among degree of dyslipidemia aggregation and various dyslipidemia combination patterns. Methods: Based on data from the China Health and Retirement Longitudinal Study (2011-2018), logistic regression analysis was used to evaluate the associations of TC, LDL-C, HDL-C, TG (4 forms of dyslipidemias), degree and pattern of dyslipidemia combination with CMM. We also used restricted cubic splines to show the dose-response associations between 4 lipid biomarkers and CMM development. Results: Of the 6 522 participants included, 590 (9.05%) developed CMM. After adjusting for covariates, all 4 forms of dyslipidemias were positively associated with CMM development (high TC: OR=1.33, 95%CI: 1.03-1.71; high LDL-C: OR=1.35, 95%CI: 1.05-1.75; low HDL-C: OR=1.45, 95%CI: 1.19-1.77; high TG: OR=1.50, 95%CI: 1.20-1.88). The U-shaped dose-response relationship between LDL-C and CMM development was observed (P for non-linear =0.022). The odds of CMM increased with the increase of dyslipidemias forms, which was highest in those with ≥3 forms of dyslipidemias (OR=2.02, 95%CI: 1.33-3.06). In various dyslipidemia form combinations, the possibility of CMM development was highest in those with high TC, high LDL-C and low HDL-C (OR=3.54, 95%CI: 1.40-8.67). High TC and high LDL-C were significantly associated with CMM development in people without cardiometabolic diseases. Low HDL-C was positively associated with diabetes and CMM development in participants without cardiometabolic diseases, cardiovascular disease (CVD) followed by diabetes, and diabetes followed by CVD. High TG was positively associated with diabetes and CMM in participants without cardiometabolic diseases, and diabetes followed by CVD. Conclusions: A total of 4 forms of dyslipidemia were all independently associated with CMM development in middle-aged and old adults in China. The dose-response relationship between LDL-C level and CMM development was U-shaped. The aggregation of 4 forms of dyslipidemia were associated with the development of CMM. Low HDL-C and high TG were significantly associated with multiple patterns of cardiometabolic diseases development.

Very high high-density lipoprotein cholesterol may be associated with higher risk of cognitive impairment in older adults.

BACKGROUND: Previous studies have shown that high-density lipoprotein cholesterol (HDL-C) levels are positively associated with cognitive function across a range of concentrations. However, recent studies have suggested that very high HDL-C levels may lead to poorer outcomes. Therefore, we aimed to investigate the relationship between different concentrations of HDL-C and cognitive impairment risk. METHODS: We collected data from 3632 participants aged over 60 years from the U.S. National Health and Nutrition Examination Survey (NHANES) between 2011 and 2014 to assess the relationship between HDL-C and cognitive function. Cognitive function was evaluated with the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) test, the animal fluency test (AFT), and the digit symbol substitution test (DSST). We used restricted cubic spline models and logistic regression to examine the association between HDL-C and cognitive function. RESULTS: A U-shaped was observed between HDL-C and cognitive outcomes, individuals with higher risk in those with both low and very high HDL-C levels compared with those with midrange values. Very high HDL-C levels (≥ 2.50 mmol/L) were associated with increased risk of cognitive impairment (OR = 2.19; 95% CI, 1.12-4.28) compared with those with HDL-C levels in the range of 1.50 to 1.99 mmol/L in older adults after adjustment for confounding factors. Interaction test demonstrated that relationship between very high HDL-C and the risk of cognitive impairment was not changed in different sex and race group (P for interaction > 0.05). CONCLUSIONS: Very high HDL-C levels were associated with an increased risk of cognitive impairment. HDL-C may not be a protective factor for maintaining brain health in older adults at very high levels.

Correlations of Serum Lipid Parameters and Atherogenic Indices With Left Ventricular Diastolic Dysfunction Among Apparently Healthy Patients With Type 2 Diabetes Mellitus: A Multicenter In-Hospital Cross-Sectional Study.

Background: In adolescents with Type 1 diabetes, lipid ratios are predictors of left ventricular diastolic dysfunction (LVDD). However, whether this also applies to adults with Type 2 Diabetes Mellitus (T2DM) is unclear. This study is aimed at assessing the correlations of serum lipid parameters and atherogenic indices with LVDD in patients with T2DM. Methods: This cross-sectional study included 203 patients with T2DM aged 59.9 ± 13.6 years (111 males, sex ratio: 1 : 2 in favor of males) from eight randomly selected urban hospitals. Demographic information was collected, an anthropometric assessment was performed, and blood pressure was measured. Fasting blood samples were obtained to assess total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TGs), glucose, and glycated hemoglobin. The atherogenic index of plasma (AIP), Castelli Risk Index I (CRI-I), Castelli Risk Index II (CRI-II), atherogenic coefficient, and non-HDL-C were determined using specific formulas. Diastolic function was assessed using echocardiography as per the 2016 updated guidelines of the American Society of Echocardiography (ASE) and the European Association of Cardiovascular Imaging (EACVI). Results: Approximately 47.8% of the participants had LVDD. Compared with participants with normal diastolic function, those with LVDD were more likely to be older than 55 years (p < 0.001), tended to have obesity (p = 0.045), had a higher risk of developing dyslipidemia (p = 0.041), and higher AIP and CRI-II (p < 0.05) levels while having similar low HDL-C and hypertriglyceridemia frequencies. In the multivariate model adjusting for age, high AIP (adjusted odds ratio [aOR], 3.37; 95% confidence interval [CI], 1.22-5.34) and high CRI-II (aOR: 3.80; 95% CI: 2.25-6.35) were independent determinants of LVDD. Conclusions: These results highlight the importance of considering atherogenic indices, primarily AIP and CRI-II in the management of T2DM patients. High AIP and high CRI-II could serve as surrogate markers of LVDD, an early cardiovascular manifestation in patients with T2DM.

Anthropometry for predicting cardiometabolic disease risk factors in adolescents.

OBJECTIVE: Early screening prevents chronic diseases by identifying at-risk adolescents through anthropometric measurements, but predictive value in diverse groups is uncertain. METHODS: A cross-sectional analysis of 12- to 19-year-old individuals from the 2017-2018 National Health and Nutrition Examination Survey (NHANES) assessed the predictive ability of BMI percentile, total body fat percentage, waist circumference (WC), and waist-hip ratio (WHR) for four cardiometabolic risk factors across race and ethnicity groups using receiver operating characteristic curves. RESULTS: The unweighted sample (N = 1194; 51.2% male individuals; 23.7% Hispanic, 13.2% non-Hispanic Black [NHB], 51.1% non-Hispanic White [NHW], 12.0% other/multirace) had a weighted prevalence of elevated blood pressure of 2.7%, hyperglycemia of 36.8%, hypertriglyceridemia of 4.8%, and low high-density lipoprotein (HDL) cholesterol of 15%. WHR (area under the curve [AUC] = 0.77), WC (AUC = 0.77), and BMI percentile (AUC = 0.73) outperformed total body fat percentage (AUC = 0.56) in predicting elevated blood pressure (p < 0.001 for all). BMI percentile was more accurate than total body fat percentage in predicting hypertriglyceridemia (AUC = 0.70 vs. 0.59; p = 0.02) and low HDL cholesterol (AUC = 0.69 vs. 0.59; p < 0.001). Race and ethnicity-based predictions varied: NHW adolescents had the highest AUC (0.89; p < 0.01) for elevated blood pressure prediction compared with Hispanic and NHB adolescents (AUC = 0.77 for both). Total body fat percentage was more accurate in predicting low HDL cholesterol among Hispanic versus NHW adolescents (AUC = 0.73 vs. 0.58; p = 0.04). CONCLUSIONS: WHR, WC, and BMI percentile are better predictors of cardiometabolic risk factors in adolescents than total body fat percentage. Predictive abilities differed by race and ethnicity, highlighting the importance of tailored risk assessment strategies.

The predictive value of cumulative atherogenic index of plasma (AIP) for cardiovascular outcomes: a prospective community-based cohort study.

BACKGROUND: Atherogenic index of plasma (AIP) has been reported as a critical predictor on the risks and clinical outcomes of cardiovascular diseases (CVDs), and we aimed to explore the potential predictive value of cumulative AIP on major adverse cardiac events (MACE), stroke, myocardial infarction (MI) and cardiovascular mortality. METHODS: A large-scale community-based prospective cohort was established from December 2011 to April 2012 and followed up in May to July 2014. The endpoint outcomes were obtained before December 31, 2021. AIP was calculated as the logarithmically transformed ratio of triglyceride (TG) to high-density lipoprotein cholesterol (HDL-c) and cumulative AIP was the average value of AIP in 2012 and 2014. RESULTS: An overall of 3820 participants (36.1% male) with mean (SD) age of 59.1 (8.7) years, were enrolled. Within a median follow-up of 7.5 years, a total of 371 (9.7%) participants were documented with MACE, 293 (7.7%) participants developed stroke, 68 (1.8%) suffered from MI and 65 (1.7%) experienced cardiovascular mortality. Multivariable Cox regression analysis revealed significant associations between cumulative AIP and the risk of MACE, stroke and MI. Regarding MACE, individuals with one higher unit of cumulative AIP were associated with 75% increment on the incidence of going through MACE in fully adjusted model, while categorizing participants into four groups, individuals in the highest cumulative AIP quartile were significantly associated with increased incidence of MACE (HR = 1.76, 95%CI: 1.27-2.44, p < 0.001 in fully adjusted model), stroke (HR = 1.69, 95%CI: 1.17-2.45, p = 0.005) and MI (HR = 2.82, 95%CI: 1.18-6.72, p = 0.019). But not a significant association was observed between cumulative AIP and cardiovascular mortality. In subgroup analysis, the association of cumulative AIP and the incidence of stroke was more pronounced in the elderly (HR: 0.89 vs. 2.41 for the age groups < 65 years and ≥ 65 years, p for interaction = 0.018). CONCLUSIONS: A higher cumulative AIP was significantly associated with an increased risk of MACE, stroke and MI independent of traditional cardiovascular risk factors in a community-based population, and the association of cumulative AIP and stroke was particularly pronounced in the elderly population.

Efficacy of AI-Guided (GenAISTM) Dietary Supplement Prescriptions versus Traditional Methods for Lowering LDL Cholesterol: A Randomized Parallel-Group Pilot Study.

Emerging evidence suggests that personalized dietary supplement regimens can significantly influence lipid metabolism and cardiovascular risk. The efficacy of AI-guided dietary supplement prescriptions, compared with standard physician-guided prescriptions, remains underexplored. In a randomized, parallel-group pilot study, 70 patients aged 40-75 years with LDL-C levels between 70 and 190 mg/dL were enrolled. Participants were randomized to receive either AI-guided dietary supplement prescriptions or standard physician-guided prescriptions for 90 days. The primary endpoint was the percent change in LDL-C levels. Secondary endpoints included changes in total cholesterol, HDL-C, triglycerides, and hsCRP. Supplement adherence and side effects were monitored. Sixty-seven participants completed the study. The AI-guided group experienced a 25.3% reduction in LDL-C levels (95% CI: -28.7% to -21.9%), significantly greater than the 15.2% reduction in the physician-guided group (95% CI: -18.5% to -11.9%; p < 0.01). Total cholesterol decreased by 15.4% (95% CI: -19.1% to -11.7%) in the AI-guided group compared with 8.1% (95% CI: -11.5% to -4.7%) in the physician-guided group (p < 0.05). Triglycerides were reduced by 22.1% (95% CI: -27.2% to -17.0%) in the AI-guided group versus 12.3% (95% CI: -16.7% to -7.9%) in the physician-guided group (p < 0.01). HDL-C and hsCRP changes were not significantly different between groups. The AI-guided group received a broader variety of supplements, including plant sterols, omega-3 fatty acids, red yeast rice, coenzyme Q10, niacin, and fiber supplements. Side effects were minimal and comparable between groups. AI-guided dietary supplement prescriptions significantly reduce LDL-C and triglycerides more effectively than standard physician-guided prescriptions, highlighting the potential for AI-driven personalization in managing hypercholesterolemia.

Does Serum Uric Acid Mediate Relation between Healthy Lifestyle and Components of Metabolic Syndrome?

A healthy lifestyle is related to metabolic syndrome (MetS), but the mechanism is not fully understood. This study aimed to examine the association of components of MetS with lifestyle in a Chinese population and potential mediation role of serum uric acid (SUA) in the association between lifestyle behaviors and risk of components of MetS. Data were derived from a baseline survey of the Shaanxi urban cohort in the Regional Ethnic Cohort Study in northwest China. The relationship between components of MetS, healthy lifestyle score (HLS), and SUA was investigated by logistic or linear regression. A counterfactual-based mediation analysis was performed to ascertain whether and to what extent SUA mediated the total effect of HLS on components of MetS. Compared to those with 1 or less low-risk lifestyle factors, participants with 4-5 factors had 43.6% lower risk of impaired glucose tolerance (OR = 0.564; 95%CI: 0.408~0.778), 60.8% reduction in risk of high blood pressure (OR = 0.392; 95%CI: 0.321~0.478), 69.4% reduction in risk of hypertriglyceridemia (OR = 0.306; 95%CI: 0.252~0.372), and 47.3% lower risk of low levels of HDL cholesterol (OR = 0.527; 95%CI: 0.434~0.641). SUA mediated 2.95% (95%CI: 1.81~6.16%) of the total effect of HLS on impaired glucose tolerance, 14.68% (95%CI: 12.04~18.85%) on high blood pressure, 17.29% (95%CI: 15.01~20.5%) on hypertriglyceridemia, and 12.83% (95%CI: 10.22~17.48%) on low levels of HDL cholesterol. Increased HLS tends to reduce risk of components of MetS partly by decreasing the SUA level, which could be an important mechanism by which lifestyle influences MetS.

Biochemical and Anthropometric Outcomes in Paediatric Patients with Heterozygous Familial Hypercholesterolemia after COVID-19 Pandemic Lockdowns: An Exploratory Analysis.

The COVID-19 pandemic lockdowns affected the lifestyles of children and adolescents, leading to an increase in childhood obesity. Paediatric patients with familial hypercholesterolemia (FH) may be more susceptible to lockdown effects due to their increased cardiovascular risk. However, data are lacking. We investigated the effect of lockdowns on the metabolic profile of paediatric patients with FH. Blood lipids and anthropometry measured in September 2021-April 2022 were retrospectively compared with pre-pandemic values. Thirty participants were included (1-16 years; 57% female). From baseline to post-pandemic, median [P25, P75] blood LDL-C concentration was 125 [112, 150] mg/dL vs. 125 [100, 147] mg/dL (p = 0.894); HDL-C was 58 [52, 65] mg/dL vs. 56 [51, 61] mg/dL (p = 0.107); triglycerides were 64 [44, 86] mg/dL vs. 59 [42, 86] mg/dL (p = 0.178). The BMI z-score did not change significantly (0.19 [-0.58, 0.89] vs. 0.30 [-0.48, 1.10], p = 0.524). The lack of deterioration in metabolic profiles during lockdowns is positive, as some deterioration was expected. We speculate that patients and caregivers were successfully educated about healthy lifestyle and dietary habits. Our results should be interpreted with caution since the study sample was small and heterogeneous. Multicentre research is needed to better understand the impact of lockdowns on this population.

Association of platelet to high-density lipoprotein cholesterol ratio with hyperuricemia.

The platelet/high-density lipoprotein ratio (PHR) has been identified as a significant indicator of inflammation and a hypercoagulable state, demonstrating a strong link with the severity of nonalcoholic fatty liver disease (NAFLD) and metabolic syndrome (MetS). However, its correlation with hyperuricemia has not yet been documented. This study utilized a cross-sectional design, analyzing data collected from the National Health and Nutrition Examination Survey (NHANES) between 2007 and 2016 in the United States. The platelet/high-density lipoprotein ratio (PHR) was determined by dividing the number of platelets (PLT) by the level of high-density lipoprotein cholesterol (HDL-C). We employed multivariable logistic regression analyses, generalized additive models, and subgroup analyses to investigate the correlation between PHR and hyperuricemia. The study revealed a hyperuricemia prevalence of 18.56%. Analysis indicated a significant positive correlation between PHR and the risk of hyperuricemia (OR 1.11, 95% CI 1.08, 1.14). This correlation remained consistent across different subgroups including age, ethnicity, gender, and body mass index (BMI). Smooth curve fitting demonstrated a saturation effect between PHR and the risk of hyperuricemia. PHR is positively correlated with hyperuricemia and may serve as a novel biomarker for predicting the onset of this condition. Additionally, targeted interventions to improve PHR might help reduce the incidence of hyperuricemia.

Association between non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol ratio (NHHR) and kidney stone: evidence from NHANES 2007-2018.

BACKGROUND: As an innovative lipid parameter, NHHR (the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol) can serve as a valuable tool for assessing cardiovascular disease risk. Nevertheless, the relationship between NHHR and the risk of kidney stones remains unexplored. METHODS: A cross-sectional survey utilized data from the National Health and Population Survey (NHANES) database in the United States spanning from 2007 to 2018. Distinct statistical analyses were applied, including weighted logistic regression, stratified and interaction analysis and restricted cubic spline curve (RCS) models, to examine the correlation between NHHR and the incidence of kidney stones. RESULTS: This analysis encompassed 24,664 participants, with 9.63% reporting incidents of kidney stones. Following multivariate logistic regression and comprehensive adjustments, participants in NHHR quartile 4 (OR 1.34; 95% CI 1.12, 1.60, P < 0.01) exhibited a significantly increased risk of kidney stones compared to those in NHHR quartile 1 (Q1). The RCS result further illustrated a non-linear correlation between NHHR and the incidence of kidney stones. The result of subgroup analysis manifested that participants without diabetes had a higher risk of kidney stones when measured high NHHR levels compared those with diabetes (p for interaction < 0.05). CONCLUSION: Elevated NHHR levels were found to be associated with an increased risk of kidney stones. Based on these findings, NHHR appears to be a promising predictive indicator for the occurrence of kidney stones.

Low HDL-C/ApoA-I index is associated with cardiometabolic risk factors and coronary artery calcium: a sub-analysis of the genetics of atherosclerotic disease (GEA) study.

BACKGROUND: The high-density lipoprotein cholesterol to apolipoprotein A-I index (HDL-C/ApoA-I) may be practical and useful in clinical practice as a marker of atherosclerosis. This study aimed to investigate the association between the HDL-C/ApoA-I index with cardiometabolic risk factors and subclinical atherosclerosis. METHODS: In this cross-sectional sub-analysis of the GEA study, 1,363 individuals, women (51.3%) and men (48.7%) between 20 and 75 years old, without coronary heart disease or diabetes mellitus were included. We defined an adverse cardiometabolic profile as excess adipose tissue metrics, non-alcoholic liver fat measured by non-contrasted tomography, metabolic syndrome, dyslipidemias, and insulin resistance. The population was stratified by quartiles of the HDL-C/Apo-AI index, and its dose-relationship associations were analysed using Tobit regression, binomial, and multinomial logistic regression analysis. RESULTS: Body mass index, visceral and pericardial fat, metabolic syndrome, fatty liver, high blood pressure, and CAC were inversely associated with the HDL-C/ApoA-I index. The CAC > 0 prevalence was higher in quartile 1 (29.2%) than in the last quartile (22%) of HDL-C/ApoA-I index (p = 0.035). The probability of having CAC > 0 was higher when the HDL-C/ApoA-I index was less than 0.28 (p < 0.001). This association was independent of classical coronary risk factors, visceral and pericardial fat measurements. CONCLUSION: The HDL-C/ApoA-I index is inversely associated with an adverse cardiometabolic profile and CAC score, making it a potentially useful and practical biomarker of coronary atherosclerosis. Overall, these findings suggest that the HDL-C/ApoA-I index could be useful for evaluating the probability of having higher cardiometabolic risk factors and subclinical atherosclerosis in adults without CAD.

Metabolic score for insulin resistance (METS-IR) predicts all-cause and cardiovascular mortality in the general population: evidence from NHANES 2001-2018.

BACKGROUND: The prevalence of obesity-associated insulin resistance (IR) is increasing along with the increase in obesity rates. In this study, we compared the predictive utility of four alternative indexes of IR [triglyceride glucose index (TyG index), metabolic score for insulin resistance (METS-IR), the triglyceride/high-density lipoprotein cholesterol (TG/HDL-C) ratio and homeostatic model assessment of insulin resistance (HOMA-IR)] for all-cause mortality and cardiovascular mortality in the general population based on key variables screened by the Boruta algorithm. The aim was to find the best replacement index of IR. METHODS: In this study, 14,653 participants were screened from the National Health and Nutrition Examination Survey (2001-2018). And TyG index, METS-IR, TG/HDL-C and HOMA-IR were calculated separately for each participant according to the given formula. The predictive values of IR replacement indexes for all-cause mortality and cardiovascular mortality in the general population were assessed. RESULTS: Over a median follow-up period of 116 months, a total of 2085 (10.23%) all-cause deaths and 549 (2.61%) cardiovascular disease (CVD) related deaths were recorded. Multivariate Cox regression and restricted cubic splines analysis showed that among the four indexes, only METS-IR was significantly associated with both all-cause and CVD mortality, and both showed non-linear associations with an approximate "U-shape". Specifically, baseline METS-IR lower than the inflection point (41.33) was negatively associated with mortality [hazard ratio (HR) 0.972, 95% CI 0.950-0.997 for all-cause mortality]. In contrast, baseline METS-IR higher than the inflection point (41.33) was positively associated with mortality (HR 1.019, 95% CI 1.011-1.026 for all-cause mortality and HR 1.028, 95% CI 1.014-1.043 for CVD mortality). We further stratified the METS-IR and showed that significant associations between METS-IR levels and all-cause and cardiovascular mortality were predominantly present in the nonelderly population aged < 65 years. CONCLUSIONS: In conjunction with the results of the Boruta algorithm, METS-IR demonstrated a more significant association with all-cause and cardiovascular mortality in the U.S. population compared to the other three alternative IR indexes (TyG index, TG/HDL-C and HOMA-IR), particularly evident in individuals under 65 years old.

Association between the atherogenic index of plasma and coronary collateral circulation in patients with chronic total occlusion.

BACKGROUND: The atherogenic index of plasma (AIP) is considered an independent risk factor for coronary artery disease (CAD). The present study investigated whether AIP correlates with the formation of coronary collateral circulation (CCC) in CAD patients with chronic total occlusion (CTO). METHODS: This retrospective study included 1093 CAD patients with CTO confirmed by coronary angiography from January 2020 to December 2020 at Beijing Anzhen Hospital. Based on the Rentrop scoring system, the patients were divided into the good CCC group and the poor CCC group. AIP was calculated by log (triglyceride/high-density lipoprotein cholesterol). Meanwhile, the study population was further divided into four groups according to the quartiles of AIP. RESULTS: Patients in the poor CCC group exhibited significantly higher AIP compared to those in the good CCC group (0.31 ± 0.27 vs. 0.14 ± 0.24, p < 0.001). Multivariate logistic regression analysis revealed an independent association between AIP and poor CCC, regardless of whether AIP was treated as a continuous or categorical variable (p < 0.001), after adjusting for confounding factors. Besides, this association remained consistent across most subgroups. The incorporation of AIP into the baseline model significantly enhanced the accuracy of identifying poor CCC [area under the curve (AUC): baseline model, 0.661 vs. baseline model + AIP, 0.721, p for comparison < 0.001]. CONCLUSIONS: Elevated AIP is independently associated with an increased risk of poor CCC in CAD patients with CTO, and AIP may improve the ability to identify poor CCC in clinical practice.