Potentially modifiable blood triglyceride levels by the control of conventional risk factors

Use machine learning models to identify and assess risk factors for coronary artery disease

Accurate prediction of coronary artery disease (CAD) is crucial for enabling early clinical diagnosis and tailoring personalized treatment options. This study attempts to construct a machine learning (ML) model for predicting CAD risk and further elucidate the complex nonlinear interactions between the disease and its risk factors. Employing the Z-Alizadeh Sani dataset, which includes records of 303 patients, univariate analysis and the Boruta algorithm were applied for feature selection, and nine different ML techniques were subsequently deployed to produce predictive models. To elucidate the intricate pathogenesis of CAD, this study harnessed the analytical capabilities of Shapley values, alongside the use of generalized additive models for curve fitting, to probe into the nonlinear interactions between the disease and its associated risk factors. Furthermore, we implemented a piecewise linear regression model to precisely pinpoint inflection points within these complex nonlinear dynamics. The findings of this investigation reveal that logistic regression (LR) stands out as the preeminent predictive model, demonstrating remarkable efficacy, it achieved an Area Under the Receiver Operating Characteristic curve (AUROC) of 0.981 (95% CI: 0.952-1), and an Area Under the Precision-Recall Curve (AUPRC) of 0.993. The utilization of the 14 most pivotal features in constructing a dynamic nomogram. Analysis of the Shapley smoothing curves uncovered distinctive "S"-shaped and "C"-shaped relationships linking age and triglycerides to CAD, respectively. In summary, machine learning models could provide valuable insights for the early diagnosis of CAD. The SHAP method may provide a personalized risk assessment of the relationship between CAD and its risk factors.

Effect of sacubitril/valsartan on lipid metabolism in patients with chronic kidney disease combined with chronic heart failure: a retrospective study

BACKGROUND AND OBJECTIVE

Dyslipidemia is significantly more common in those with concurrent chronic kidney disease (CKD) and chronic heart failure (CHF). Sacubitril/valsartan has showcased its influence on both cardiac and renal functions, extending its influence to the modulation of lipid metabolism pathways. This study aimed to examine how sacubitril/valsartan affects lipid metabolism within the context of CKD and CHF.

METHODS

This study adopted a retrospective design, focusing on a single center and involving participants who were subjected to treatment with sacubitril/valsartan and valsartan. The investigation assessed the treatment duration, with a particular emphasis on recording blood lipid indicators, including triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A (ApoA), and apolipoprotein B (ApoB). Furthermore, cardiac and renal functions, blood pressure, potassium levels, and other factors influencing the blood lipids were analyzed in both groups at identical time points.

RESULTS

After 16 weeks of observation, the sacubitril/valsartan group exhibited lower TG levels compared to the valsartan group. Noteworthy was the fact that individuals undergoing sacubitril/valsartan treatment experienced an average reduction of 0.84 mmol/L in TG levels, in stark contrast to the valsartan group, which registered a decline of 0.27 mmol/L (P < 0.001). The sacubitril/valsartan group exhibited elevated levels of HDL-C and ApoA in comparison to the valsartan group (PHDL-C = 0.023, PApoA = 0.030). While TC, LDL-C, and ApoB decreased compared to baseline, the differences between groups were not statistical significance. Regarding cardiac indicators, there was an observed enhancement in the left ventricular ejection fraction (LVEF) within the sacubitril/valsartan group when compared to the baseline, and it was noticeably higher than that of the valsartan group. Spearman correlation analysis and multiple linear regression analysis revealed that medication, body mass index(BMI), and hemoglobin A1c (HbA1c) had a direct influencing effect on TG levels.

CONCLUSION

Sacubitril/valsartan demonstrated improvements in lipid metabolism and cardiac indicators in patients with CKD and CHF. Specifically, it presented promising benefits in reducing TG levels. In addition, both BMI and HbA1c emerged as influential factors contributing to alterations in TG levels, independent of the administration of sacubitril/valsartan.

Polygenic Risk of Hypertriglyceridemia Is Modified by BMI

Background: Genetic risk scores (GRSs) have partially improved the understanding of the etiology of moderate hypertriglyceridemia (HTG), which until recently was mainly assessed by secondary predisposing causes. The main objective of this study was to assess whether this variability is due to the interaction between clinical variables and GRS. Methods: We analyzed 276 patients with suspected polygenic HTG. An unweighted GRS was developed with the following variants: c.724C > G (ZPR1 gene), c.56C > G (APOA5 gene), c.1337T > C (GCKR gene), g.19986711A > G (LPL gene), c.107 + 1647T > C (BAZ1B gene) and g.125478730A > T (TRIB gene). Interactions between the GRS and clinical variables (body mass index (BMI), diabetes mellitus, diet, physical activity, alcohol consumption, age and gender) were evaluated. Results: The GRS was associated with triglyceride (TG) concentrations. There was a significant interaction between BMI and GRS, with the intensity of the relationship between the number of alleles and the TG concentration being greater in individuals with a higher BMI. Conclusions: GRS is associated with plasma TG concentrations and is markedly influenced by BMI. This finding could improve the stratification of patients with a high genetic risk for HTG who could benefit from more intensive healthcare interventions.

Perceived green space quality, child biomarkers and health-related outcomes: A longitudinal study

Accumulating exposure to quality green space over time is posited to influence child health, yet longitudinal studies are scarce. This study aimed to examine the associations between trajectories of perceived green space quality and child health-related outcomes. We used data from 1874 childrenin the B-cohort of the Longitudinal Study of Australian Children who participated in the Child Health Checkpoint module at 11-12 years. Data on caregiver perceived green space quality measured biennially was assessed using discrete trajectory mixture models to group children by contrasting distributions in green space quality over time. Examination of associations between trajectory groups of perceived green space quality and child biomarkers (i.e., albumin-to-creatinine ratio, total, cholesterol, total triglycerides, and glucose), physical health and behavioural assessments (i.e., anthropometric measurements, blood pressure, sedentary behaviour, physical activity, sleep, aerobic work capacity, and general wellbeing), and health care use were assessed using multilevel models, adjusted for sociodemographic variables. Four perceived green space quality trajectories were identified: "decreasing quality from high to moderate"; "increasing quality from low to high"; "consistently high quality"; "consistently low quality". Compared with consistently low levels of quality green space, adjusted models indicated consistently high-quality green space was associated with lower total triglycerides (β -0.13; 95%CI -0.25, -0.01). Lower odds of hospital admission was observed among children who accumulated quality green space over time (OR 0.45; 95%CI 0.23, 0.87). These associations were observed in boys only in sex-stratified analyses. Moreover, boys accumulating quality green space through time tended to have lower diastolic blood pressure (β -2.76; 95%CI -5.17, -0.35) and girls who experienced loss in quality green space tended to have a higher percentage of body fat (β 2.81; 95%CI 0.43, 5.20). Accumulating quality green space over time is important for various aspects of child health, with contrasting benefits by sex.

The correlation of atherosclerosis and triglyceride glucose index: a secondary analysis of a national cross-sectional study of Japanese

BACKGROUND

Few studies examined the relationship between triglyceride/glucose index (TyG index) and atherosclerosis in Japanese adults. Therefore, this study evaluated their relationship, as measured based on the brachial-ankle pulse wave velocity (baPWV) in Japanese adults.

METHODS

A total of 912 participants was selected from the NAGALA (NAFLD in Gifu Area, Longitudinal Analysis) study conducted from 2004 to 2012. The relationship between the TyG index and baPWV was estimated through a logistic model. Subgroup analyses by sex, age, body mass index (BMI), total cholesterol, low-density lipoprotein cholesterol, estimated glomerular filtration rate (eGFR), and fatty liver was performed. The formula for TyG index was ln (½fasting triglyceride level [mg/dL] × fasting plasma glucose level [mg/dL]).

RESULTS

A linear relationship between TyG and baPWV was discovered after adjusting for underlying confounders. An increased risk of baPWV was observed after adjusting for sex, age, BMI, systolic blood pressure, diastolic blood pressure, high-density lipoprotein cholesterol, fatty liver, eGFR, and TyG as a continuous variable (adjusted odds ratio [adj OR], 1.57; 95% confidence interval [95% CI], 1.14-2.18). Compared with the TyG index in the first tertile, the probabilities of subjects in the third tertile that developed to baPWV were 1.78-fold higher (adj OR 1.78, 95% CI 1.08-2.95: P for trend 0.024). Moreover, stable associations were observed between the TyG index and baPWV in different variables through subgroup analyses.

CONCLUSIONS

The highest tertile (above 8.57) of the TyG index was positively and linearly related to subclinical atherosclerosis in Japanese adults and may be valuable as a predicted marker.

Novel associations of SNPs MYLIP rs3757354 and ABCA1 2230806 gene with early-onset-preeclampsia: A case-control candidate genetic study

OBJECTIVE

To investigate the association between MYLIP rs3757354 and ABCA1 2230806 single nucleotide polymorphisms in women with preeclampsia in China.

STUDY DESIGN

The case-control study involved 205 patients with preeclampsia and 145 controls. All women with preeclampsia were divided into two groups: 78 patients with early-onset preeclampsia and 127 with late-onset preeclampsia.

MAIN OUTCOME MEASURE

MYLIP rs3757354 and ABCA1 rs2230806 SNPs were analyzed through multiplex PCR for targeted next-generation sequencing technology. A secondary outcome was lipid profile changes and liver function in women with PE.

RESULTS

Maternal age (OR: 1.073, 95% CI = 1.006-1.145), BMI (OR: 1.118, 95% CI = 1.040-1.201), TG/HDL-C (OR: 1.536, 95% CI = 1.080-2.183), and TT genotype of SNP rs3757354 (OR: 3.238, 95% CI = 1.313-7.990) were associated with EOPE risk. Our study found that patients with TT genotype of ABCA1 rs2230806 had more severe hepatic dysfunction and higher HDL levels in the EOPE group compared with CC/CT genotype. There was no association between rs2230806 and the risk of PE.

CONCLUSION

The polymorphisms of rs3757354 are associated with the risk of EOPE in Chinese pregnant women. The TT genotype in ABCA1 rs2230806 is a strong predictive risk for elevated aminotransferase levels in pregnant women with EOPE.