Peridroplet mitochondria are associated with the severity of MASLD and the prevention of MASLD by diethyldithiocarbamate.

Mitochondria can contact lipid droplets (LDs) to form peridroplet mitochondria (PDM) which trap fatty acids in LDs by providing ATP for triglyceride synthesis, and prevent lipotoxicity. However, the role of PDM in metabolic dysfunction associated steatotic liver disease (MASLD) is not clear. Here, the features of PDM in dietary MASLD models with different severity in mice were explored. Electron microscope photographs show that LDs and mitochondria rarely come into contact with each other in normal liver. In mice fed with high-fat diet, PDM can be observed in the liver as early as the beginning of steatosis in hepatocytes. For the first time, we show that PDM in mouse liver varies with the severity of MASLD. PDM and cytosolic mitochondria (CM) were isolated from the liver tissue of MASLD and analyzed by quantitative proteomics. Compared with CM, PDM have enhanced mitochondrial respiration and ATP synthesis. Diethyldithiocarbamate (DDC) alleviates choline-deficient, L-amino acid-defined diet-induced MASLD, while increases PDM in the liver. Similarly, DDC promotes the contact of mitochondria-LDs in steatotic C3A cells in vitro. Meanwhile, DDC promotes triglyceride synthesis and improves mitochondrial dysfunction in MASLD. In addition, DDC upregulates perilipin 5 both in vivo and in vitro, which is considered as a key regulator in PDM formation. Knockout of Plin5 inhibits the contact of mitochondria-LDs induced by DDC in C3A cells. These results demonstrate that PDM might be associated with the progression of MASLD and the prevention of MASLD by DDC. The regulation of PDM might be a new pharmacological strategy for MASLD.

GPAT3 is a potential therapeutic target to overcome sorafenib resistance in hepatocellular carcinoma.

Background: Sorafenib is the standard treatment for advanced hepatocellular carcinoma (HCC), but acquired resistance during the treatment greatly limits its clinical efficiency. Lipid metabolic disorder plays an important role in hepatocarcinogenesis. However, whether and how lipid metabolic reprogramming regulates sorafenib resistance of HCC cells remains vague. Methods: Sorafenib resistant HCC cells were established by continuous induction. UHPLC-MS/MS, proteomics, and flow cytometry were used to assess the lipid metabolism. ChIP and western blot were used to reflect the interaction of signal transducer and activator of transcription 3 (STAT3) with glycerol-3-phosphate acyltransferase 3 (GPAT3). Gain- and loss-of function studies were applied to explore the mechanism driving sorafenib resistance of HCC. Flow cytometry and CCK8 in vitro, and tumor size in vivo were used to evaluate the sorafenib sensitivity of HCC cells. Results: Our metabolome data revealed a significant enrichment of triglycerides in sorafenib-resistant HCC cells. Further analysis using proteomics and genomics techniques demonstrated a significant increase in the expression of GPAT3 in the sorafenib-resistant groups, which was found to be dependent on the activation of STAT3. The restoration of GPAT3 resensitized HCC cells to sorafenib, while overexpression of GPAT3 led to insensitivity to sorafenib. Mechanistically, GPAT3 upregulation increased triglyceride synthesis, which in turn stimulated the NF-κB/Bcl2 signaling pathway, resulting in apoptosis tolerance upon sorafenib treatment. Furthermore, our in vitro and in vivo studies revealed that pan-GPAT inhibitors effectively reversed sorafenib resistance in HCC cells. Conclusions: Our data demonstrate that GPAT3 elevation in HCC cells reprograms triglyceride metabolism which contributes to acquired resistance to sorafenib, which suggests GPAT3 as a potential target for enhancing the sensitivity of HCC to sorafenib.

Developing and validating a predictive model of delivering large-for-gestational-age infants among women with gestational diabetes mellitus.

BACKGROUND: The birth of large-for-gestational-age (LGA) infants is associated with many short-term adverse pregnancy outcomes. It has been observed that the proportion of LGA infants born to pregnant women with gestational diabetes mellitus (GDM) is significantly higher than that born to healthy pregnant women. However, traditional methods for the diagnosis of LGA have limitations. Therefore, this study aims to establish a predictive model that can effectively identify women with GDM who are at risk of delivering LGA infants. AIM: To develop and validate a nomogram prediction model of delivering LGA infants among pregnant women with GDM, and provide strategies for the effective prevention and timely intervention of LGA. METHODS: The multivariable prediction model was developed by carrying out the following steps. First, the variables that were associated with LGA risk in pregnant women with GDM were screened by univariate analyses, for which the P value was < 0.10. Subsequently, Least Absolute Shrinkage and Selection Operator regression was fit using ten cross-validations, and the optimal combination factors were selected by choosing lambda 1se as the criterion. The final predictors were determined by multiple backward stepwise logistic regression analysis, in which only the independent variables were associated with LGA risk, with a P value < 0.05. Finally, a risk prediction model was established and subsequently evaluated by using area under the receiver operating characteristic curve, calibration curve and decision curve analyses. RESULTS: After using a multistep screening method, we establish a predictive model. Several risk factors for delivering an LGA infant were identified (P < 0.01), including weight gain during pregnancy, parity, triglyceride-glucose index, free tetraiodothyronine level, abdominal circumference, alanine transaminase-aspartate aminotransferase ratio and weight at 24 gestational weeks. The nomogram's prediction ability was supported by the area under the curve (0.703, 0.709, and 0.699 for the training cohort, validation cohort, and test cohort, respectively). The calibration curves of the three cohorts displayed good agreement. The decision curve showed that the use of the 10%-60% threshold for identifying pregnant women with GDM who are at risk of delivering an LGA infant would result in a positive net benefit. CONCLUSION: Our nomogram incorporated easily accessible risk factors, facilitating individualized prediction of pregnant women with GDM who are likely to deliver an LGA infant.

Second-trimester triglyceride-glucose index to predict adverse outcomes in women with gestational diabetes mellitus: A retrospective multicenter cohort study.

AIMS/INTRODUCTION: Women with gestational diabetes mellitus are at high risk for adverse maternal and neonatal outcomes. The study aimed to evaluate the performance of the triglyceride-glucose index in predicting the risk of developing adverse outcomes in women with gestational diabetes mellitus. MATERIALS AND METHODS: This retrospective multicenter cohort study included 8,808 pregnant women with gestational diabetes mellitus in two grade-A tertiary hospitals in China during 2018-2022. The triglyceride-glucose index was defined as ln [triglyceride (mg/dL) × fasting blood glucose (mg/dL)/2]. Significant adverse gestational diabetes mellitus outcomes were chosen by generalized linear models as the main outcomes. Multivariable logistic regression models evaluated their association with the triglyceride-glucose index. Areas under the receiver operating characteristic curves predicted adverse pregnancy outcomes. The prediction efficiency was validated in the sensitivity analysis dataset and validation cohort. RESULTS: The triglyceride-glucose index was associated with preeclampsia, severe preeclampsia, preterm birth, placenta accreta spectrum, and macrosomia before and after adjusting for confounding factors (P < 0.05). The predictive performance of the triglyceride-glucose index was relatively moderate. Incorporating the triglyceride-glucose index into the baseline clinical risk model improved the area under curves for the diagnosis of preeclampsia (0.749 [0.714-0.784] vs 0.766 [0.734-0.798], P = 0.033) and macrosomia (0.664 [0.644-0.685] vs 0.676 [0.656-0.697], P = 0.002). These predictive models exhibited good calibration and robustness. CONCLUSIONS: The triglyceride-glucose index is positively associated with preeclampsia, severe preeclampsia, preterm birth, placenta accreta spectrum, and macrosomia and is useful for the early prediction and prevention of adverse outcomes in women with gestational diabetes mellitus.

Comparison of triglyceride-glucose index and anthropometric obesity indices in predicting severe grades of hepatic steatosis in nonalcoholic fatty liver disease among non-diabetic obese individuals.

Background and Aim: The triglyceride glucose index (TyG) has been proposed as a promising indicator of both insulin resistance (IR) and non-alcoholic fatty liver disease (NAFLD). However, the efficacy of the TyG index in predicting NAFLD has not been adequately studied, particularly in obese individuals. Materials and Methods: We analyzed 190 morbidly obese individuals. The TyG index, anthropometric obesity indices, homeostatic model assessment (HOMA-IR), and biochemical parameters were compared. NAFLD was diagnosed by hepatic ultrasonography and classified into four grades (0, 1, 2, and 3). Individuals in grades 2 and 3 are considered to have severe steatosis, while those in grades 0 and 1 do not. Results: The area under the curve (AUC) values of the TyG index, body mass index, neck circumferences, waist-to-hip ratio, and HOMA-IR did not differ significantly in predicting severe steatosis (0.640, 0.742, 0.725, 0.620, and 0.624 respectively). However, the AUC values of waist circumference and alanine aminotransferase provided better predictions than the TyG index (0.782, 0.744, and 0.640 respectively). Conclusion: The TyG index is highly effective in predicting both the presence and severity of NAFLD. However, it did not outperform simple obesity indices in predicting NAFLD and its severity in obese patients.

Triglyceride-glucose index as a potential predictor of major adverse cardiovascular and cerebrovascular events in patients with coronary heart disease complicated with depression.

Background: Triglyceride-glucose (TyG) index is a surrogate marker of insulin resistance and metabolic abnormalities, which is closely related to the prognosis of a variety of diseases. Patients with both CHD and depression have a higher risk of major adverse cardiovascular and cerebrovascular events (MACCE) and worse outcome. TyG index may be able to predict the adverse prognosis of this special population. Methods: The retrospective cohort study involved 596 patients with both CHD and depression between June 2013 and December 2023. The primary outcome endpoint was the occurrence of MACCE, including all-cause death, stroke, MI and emergent coronary revascularization. The receiver operating characteristic (ROC) curve, Cox regression analysis, Kaplan-Meier survival analysis, and restricted cubic spline (RCS) analysis were used to assess the correlation between TyG index and MACCE risk of in patients with CHD complicated with depression. Results: With a median follow-up of 31 (15-62) months, MACCE occurred in 281(47.15%) patients. The area under the ROC curve of TyG index predicting the risk of MACCE was 0.765(0.726-0.804) (P<0.01). Patients in the high TyG index group(69.73%) had a significantly higher risk of developing MACCE than those in the low TyG index group(23.63%) (P<0.01). The multifactorial RCS model showed a nonlinear correlation (nonlinear P<0.01, overall P<0.01), with a critical value of 8.80 for the TyG index to predict the occurrence of MACCE. The TyG index was able to further improve the predictive accuracy of MACCE. Conclusions: TyG index is a potential predictor of the risk of MACCE in patients with CHD complicated with depression.

Association between the triglyceride glucose index and short-term mortality in septic patients with or without obesity: a retrospective cohort study.

BACKGROUND: Sepsis is a significant contributor to both intensive care unit (ICU) admissions and mortality among patients in ICU, with a rising prevalence of obesity. There is a lack of extensive research on the correlation between TyGI and findings in patients with sepsis, especially in obese patients. METHODS: This study used a retrospective cohort design and included patients with sepsis (≥18 years) from the Medical Information Mart for Intensive Care IV database. The association between TyGI and outcome was examined using multivariable logistic regression analysis. RESULTS: 8,840 patients with sepsis were included in the analysis. The in-ICU mortality rate was 9.7%. Non-survivors exhibited significantly greater TyGI levels than survivors [9.19(8.76-9.71) vs. 9.10(8.67-9.54), p < 0.001]. The adjusted multivariate regression model showed that elevated TyGI values were linked to a greater likelihood of death in ICU (odds ratio [OR] range 1.072-1.793, p < 0.001) and hospital (OR range 1.068-1.445, p = 0.005). Restricted Cubic Spline analysis revealed a nonlinear association between TyGI and in-ICU and in-hospital mortality risks within specified ranges. Subgroup analysis revealed interaction effects in the general obesity, abdominal obesity, and impaired fasting glucose subgroups (p = 0.014, 0.016, and < 0.001, respectively). CONCLUSION: TyGI was associated with an increased sepsis-related short-term mortality risk and adverse outcomes after ICU admission.

Comprehensive analysis of the association between triglyceride-glucose index and coronary artery disease severity across different glucose metabolism states: a large-scale cross-sectional study from an Asian cohort.

BACKGROUND: The triglyceride-glucose (TyG) index is associated with the development and prognosis of coronary artery disease (CAD). However, the impact of the TyG index on CAD severity across different glucose metabolism states exhibits significant disparities in previous research. METHODS: This cross-sectional study comprised 10,433 participants from a prospective cohort. Participants were categorized into four groups based on glucose metabolism state: normal glucose regulation (NGR), prediabetes (pre-DM), diabetes mellitus (DM) without insulin prescribed (Rx), and DM with insulin Rx. The TyG index was determined by the following formula: Ln [TG (mg/dL) × FPG (mg/dL) / 2], where TG is triglycerides and FPG is fasting plasm glucose. Statistical methods such as binary logistic regression, interaction analysis, restricted cubic spline (RCS), and receiver operating characteristic (ROC) were employed to analyze the relationship between the TyG index and CAD severity across the entire population and glucose metabolism subgroups. Mediation analysis was conducted to examine the mediating effects of glycated hemoglobin (HbA1c) on these relationships. Sensitivity analysis was performed to ensure the robustness of the findings. RESULTS: Multivariable logistic regression analysis revealed a significant positive association between the TyG index and multi-vessel CAD in the entire population (OR: 1.34; 95% CI: 1.22-1.47 per 1-unit increment). Subgroup analysis demonstrated consistent positive associations in the NGR, pre-DM, and DM non-insulin Rx groups, with the highest OR observed in the NGR group (OR: 1.67; 95% CI: 1.3-2.14 per 1-unit increment). No correlation was found in the DM with insulin Rx subgroup. RCS analyses indicated the distinct dose-response relationships across different glucose metabolism subgroups. Including the TyG index in the established model slightly improved the predictive accuracy, particularly in the NGR group. Mediation analyses showed varying mediating effects of HbA1c among different glucose metabolism subgroups. Sensitivity analysis confirmed the robustness of the aforementioned relationships in the new-onset CAD population and in individuals not using antilipidemic medications. CONCLUSIONS: The TyG index positively associated with CAD severity across all glucose metabolism states, except for individuals receiving insulin treatment. Moreover, it might serve as a supplementary noninvasive predictor of CAD severity in addition to established factors, especially in NGR patients.

Association of triglyceride glucose-body mass index with Alzheimer's disease pathology, cognition and brain structure in non-demented people.

The relationship between the triglyceride glucose-body mass index (TyG-BMI) index and Alzheimer's disease (AD) pathology, cognition, and brain structure remains unclear. This study aimed to investigate these associations, focusing on cerebrospinal fluid (CSF) biomarkers, cognitive measures, and brain imaging data. Eight hundred and fifty-five non-demented participants were included. Linear regression was used to explore associations between the TyG-BMI index and AD pathology, cognition, and brain structure. The association between the TyG-BMI index and AD risk was assessed using Kaplan-Meier and Cox proportional hazards models. Longitudinal relationships were assessed using linear mixed-effects models. Mediation analyses were conducted to examine AD pathology's potential mediating role between the TyG-BMI index and cognition as well as brain structure. In the linear regression analyses, higher TyG-BMI levels were associated with increased Aß42 and decreased Tau, pTau, Tau/Aß42, pTau/Aß42, and pTau/Tau. Positive correlations were observed with mini-mental state examination (MMSE), memory (MEM), executive function (EF), and the volumes of the hippocampus, entorhinal cortex, and middle temporal regions, while negative correlations were found with Alzheimer's Disease Assessment Scale (ADAS). Longitudinally, the TyG-BMI index was inversely associated with ADAS, and positively with MMSE, MEM, EF, hippocampus, entorhinal, and middle temporal. High TyG-BMI levels were correlated with lower AD risk (HR 0.996 [0.994, 0.999]). Mediation analyses revealed AD pathology mediated the association between TyG-BMI index and cognition as well as brain structure. Additionally, the TyG-BMI index could mediate cognitive changes by influencing brain structure. The TyG-BMI index is associated with AD pathology, cognition, and brain structure.

Elevated TyG index is associated with increased risk of vitamin D deficiency among elderly patients with type 2 diabetes.

Vitamin D deficiency (VDD) is associated with increased risk of type 2 diabetes mellitus (T2DM) and insulin resistance (IR). We aimed to investigate the association between the triglyceride-glucose (TyG) index that represents IR and VDD in elderly patients with T2DM. We enrolled 572 elderly participants with T2DM in this study. TyG index was calculated as ln [fasting triglyceride (TG, mg/dL) × fasting blood glucose (mg/dL)/2]. Serum 25-hydroxyvitamin D [25(OH)D] level below 50 nmol/L was defined as VDD. The association between the TyG index and the VDD risk was evaluated by multivariate logistic regression analysis. We observed a significant decreased 25(OH)D level with the increase of the TyG index in elderly diabetic patients, and a negative correlation between the TyG index and 25(OH)D level. The participants in the highest TyG quartile had a 2.40-fold higher risk of VDD than those in the lowest TyG index quartile [OR 2.40; 95% CI 1.47-3.92; P < 0.001]. The association persisted after adjustments for age, sex, smoking, obesity, insulin therapy, hypoglycemic agents' medication, and some biochemical parameters. TyG index may be involved in the pathophysiology of VDD, which could be a predictor for VDD in elderly diabetic patients.

Non-insulin-based insulin resistance indices predict early neurological deterioration in elderly and middle-aged acute ischemic stroke patients in Northeast China.

Insulin resistance (IR) has a strong association with acute ischemic stroke (AIS) occurrence and poor prognosis of afflicted patients. However, the relation between early neurological deterioration (END) risk and IR in elderly and middle-aged patients remains to be thoroughly studied. Here, we investigated the relationship between four indicators of IR and the risk of END in middle-aged patients patients with AIS. The study retrospectively analyzed 1696 elderly and middle-aged patients having AIS between January 2019 and June 2023. Within 7 days of admission, the patients were then stratified relying upon alternations in the National Institutes of Health Stroke Scale. Subsequently, we employed logistic regression analyses for assessing each index correlation with END on the basis of the tertiles of TyG index (TyGI), triglyceride to high-density lipoprotein ratio (TG/HDL), TyG-BMI, alongside IR metabolic score (METS-IR). These four indicators were significantly heightened in the END group (n = 680) in comparison to the non-END group (n = 1016). When grouping using tertiles, the four aforementioned indicators emerged as independent risk factors for END occurrence, whether or not adjusted for confounding factors. The results revealed a progressive elevation in END occurrence risk with the rise in the tertile of each indicator. Finally, we utilized receiver operating characteristic (ROC) curves for assessing the indicators' predictive power. TyG-BMI, TyGI, TG/HDL, and METS-IRs' area under the curve (AUC) were, respectively, 0.736 (95% CI: 0.712-0.761; P < 0.001), 0. 694 (95% CI: 0.668-0.721; P < 0.001), 0.684 (95% CI: 0.658-0.711; P < 0.001), and 0.722 (95% CI: 0.697-0.747; P < 0.001). IR is associated with END risk in middle-aged AIS patients. TyG-BMI, TyGI, TG/HDL, and METS-IR are independent risk factors of END in elderly and middle-aged AIS patients. Simultaneously, these four IR indicators have significant predictive power for END.

An Increasing Triglyceride-Glucose Index Is Associated with a Pro-Inflammatory and Pro-Oxidant Phenotype.

Background/Objectives: Insulin resistance is crucial in the pathogenesis of Metabolic Syndrome (MetS), type 2 diabetes mellitus (T2DM) and premature atherosclerotic cardiovascular disease (ASCVD). The triglyceride-glucose index (TyG index), a validated measure of insulin resistance, also predicts MetS, T2DM, the severity of albuminuria and ASCVD. There are scant data providing mechanistic insights into these sequalae. Accordingly, we investigated the relationship between the TyG index and biomarkers of inflammation, oxidative stress, free fatty acid (FFA) levels and adipokine dysregulation in a cohort comprising both controls and patients with nascent MetS. Methods: Participants (n = 102) included 59 patients with MetS and 43 controls. People with diabetes, ASCVD, smoking and macro-inflammation were excluded. Fasting blood was obtained for both plasma and monocyte isolation. Results: Receiver Operating Characteristic (ROC) curve analysis revealed that the TyG index was an excellent predictor of MetS with an area under the curve of 0.87, and it correlated with both hepatic and adipose tissue insulin resistance. Both serum RBP-4 levels and non-HDL cholesterol increased significantly over tertiles of the TyG index. Based on the TyG index tertiles and/or correlations, oxidized LDL, nitrotyrosine, C-reactive protein, endotoxin, chemerin, interleukin-6 levels and monocyte toll-like receptor (TLR)-4 and TLR-2 and their cellular signaling were significantly associated with the TyG index. Conclusions: Increased non-HDL-C and, most importantly, a pro-inflammatory and pro-oxidant state could be advanced as potential mechanisms explaining the increased risk for T2DM and ASCVD with an increasing TyG index.

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.

Association between the triglyceride glucose index and depression: a meta-analysis.

Background: Obesity and diabetes have been associated with depressive symptoms. The aim of this systematic review and meta-analysis was to evaluate the association between the triglyceride glucose index (TyG index) a novel indicator of insulin resistance (IR) and depression in the adult population. Methods: Relevant observational studies were acquired through comprehensive searches of the Medline, Web of Science, Embase, Wanfang, and China National Knowledge Internet databases. To account for heterogeneity, a random-effects model was employed to combine the findings. Additionally, multiple subgroup analyses were conducted to assess the impact of various study characteristics on the outcome. Results: The meta-analysis comprised eight datasets from six cross-sectional studies, encompassing a total of 28,973 adults. The pooled findings suggested that subjects with a high TyG index, compared to those with a low TyG index, were associated with a higher prevalence of depression (odds ratio [OR]: 1.41, 95% confidence interval (CI): 1.28-1.56, p<0.001; I2 = 19%). Sensitivity analyses, by omitting one dataset at a time, showed consistent results (OR: 1.39-1.45, p<0.05). Further subgroup analyses showed consistent results in participants aged <50 years old and in those aged ≥50 years old, in men and in women, in studies with different cutoff values for the TyG index, and in studies with different methods for the diagnosis of depression (for each subgroup difference, p>0.05). Conclusion: A high TyG index may be associated with a higher prevalence of depression in the adult population.

Evaluation of the ability of insulin resistance and lipid-related indices to predict the presence of NAFLD in obese adolescents.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD) has become an important health issue in adolescents. Although several parameters and indices have been investigated for the evaluation of NAFLD in adults, these indices are limited in adolescents. In this study, body mass index, waist circumference, triponderal mass index, HbA1c, homeostatic model assessment insulin resistance (HOMA-IR), triglyceride/high-density lipoprotein (Tg/HDL), the lipid accumulation product (LAP) index, the triglyceride-glucose (TyG) index and the aminotransferase (AT) index were examined together, and their diagnostic values in the clinical treatment of NAFLD were compared. MATERIALS AND METHODS: Seventynine adolescents (10-19 years old) with obesity who were admitted to a pediatric clinic between January and August 2022 and who were diagnosed with exogenous obesity without any comorbidities were included in the study. The presence of NAFLD was evaluated by liver magnetic resonance imaging. The laboratory findings were obtained retrospectively from system records. Parameters were compared between the NAFLD (+) and NAFLD (-) groups. Logistic regression analysis was used to determine the most effective factors for NAFLD treatment. Receiver operating characteristic (ROC) analysis was performed with significant indices. Sex, HOMA-IR, TyG and AT indices were evaluated together with multivariate analysis to design a diagnostic scale. RESULTS: HbA1c, HOMA-IR, AT indices and TyG indices were greater in the NAFLD (+) group (P = 0.012; P = 0.001; P = 0.012; P = 0.002, respectively). There was a positive correlation between liver fat percentage and HOMA-IR, the TyG index, the AT index, and Tg/HDL. According to the regression analysis, male sex and elevated HOMA-IR were determined to be significant risk factors for the presence of NAFLD. A probability scale with 4 parameters [sex, HOMA-IR, the TyG index, and alanine aminotransferase (ALT)] was designed with 82.5% specificity and 80% sensitivity. CONCLUSION: Evaluation of the HOMA-IR and TyG indices, especially in high-risk patients, will support the diagnosis of NAFLD via ultrasonography. A probability scale with ALT, HOMA-IR, TyG, and sex data with a diagnostic accuracy of 80% may aid in the diagnosis of NAFLD in adolescents with obesity.

U shape association between triglyceride glucose index and congestive heart failure in patients with diabetes and prediabetes.

BACKGROUND: While previous population studies have shown that higher triglyceride-glucose (TyG) index values are associated with an increased risk of congestive heart failure (CHF), the relationship between TyG and CHF in patients with abnormal glucose metabolism remains understudied. This study aimed to evaluate the association between TyG and CHF in individuals with diabetes and prediabetes. METHODS: The study population was derived from the National Health and Nutrition Examination Survey (NHANES) spanning from 1999 to 2018. The exposure variable, TyG, was calculated based on triglyceride and fasting blood glucose levels, while the outcome of interest was CHF. A multivariate logistic regression analysis was employed to assess the association between TyG and CHF. RESULTS: A total of 13,644 patients with diabetes and prediabetes were included in this study. The results from the fitting curve analysis demonstrated a non-linear U-shaped correlation between TyG and CHF. Additionally, linear logistic regression analysis showed that each additional unit of TyG was associated with a non-significant odds ratio (OR) of 1.03 (95%CI: 0.88-1.22, P = 0.697) for the prevalence of CHF. A two-piecewise logistic regression model was used to calculate the threshold effect of the TyG. The log likelihood ratio test (p < 0.05) indicated that the two-piecewise logistic regression model was superior to the single-line logistic regression model. The TyG tangent point was observed at 8.60, and on the left side of this point, there existed a negative correlation between TyG and CHF (OR: 0.54, 95%CI: 0.36-0.81). Conversely, on the right side of the inflection point, a significant 28% increase in the prevalence of CHF was observed per unit increment in TyG (OR: 1.28, 95%CI: 1.04-1.56). CONCLUSIONS: The findings from this study suggest a U-shaped correlation between TyG and CHF, indicating that both elevated and reduced levels of TyG are associated with an increased prevalence of CHF.

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.

Association between triglyceride glucose-body mass index and all-cause mortality in critically ill patients with acute myocardial infarction: retrospective analysis of the MIMIC-IV database.

Background: Insulin resistance (IR) is closely related to the development of cardiovascular diseases. Triglyceride-glucose-body mass index (TyG-BMI) has been proven to be a reliable surrogate of IR, but the relationship between TyG-BMI and acute myocardial infarction (AMI) is unknown. The present study aims to determine the effects of TyG-BMI on the clinical prognosis of critically ill patients with AMI. Methods: The data of AMI patients were extracted from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. All patients were divided into four groups according to the TyG-BMI quartile. Outcomes were defined as 30-, 90-, 180-, and 365-day all-cause mortality. Kaplan-Meier (K-M) curve was used to compare survival rate between groups. Meanwhile, Cox regression analysis and restricted cubic splines (RCS) were used to explore the relationship between TyG-BMI index and outcome events. Results: A total of 1,188 critically ill patients with AMI were included in this study. They were divided into four groups according to TyG-BMI quartiles, there were significant differences in 90-, 180-, and 365-day all-cause mortality while there was no difference in 30-day all-cause mortality. Interestingly, with the increase of TyG-BMI, the 90-, 180-, and 365-day survival rate increased first and then gradually decreased, but the survival rate after decreasing was still higher than that in the group with the lowest TyG-BMI. U-shaped relationships between TyG-BMI index and 90-, 180-, and 365-day all-cause mortality were identified using RCS curve and the inflection point was 311.1, 316.5, and 320.1, respectively, whereas the TyG-BMI index was not non-linearly associated with 30-day all-cause mortality. The results of Cox proportional hazard regression analysis are consistent with those of RCS analysis. Conclusion: U-shaped relationships are existed between the TyG-BMI index and 90-, 180-, and 365-day all-cause mortality in critically ill patients with AMI, but not 30-day all-cause mortality. The TyG-BMI index can be used as an effective index for early prevention of critically ill patients with AMI.

Macromolecular Interactions of Lipoprotein Lipase (LPL).

Lipoprotein lipase (LPL) is a critical enzyme in humans that provides fuel to peripheral tissues. LPL hydrolyzes triglycerides from the cores of lipoproteins that are circulating in plasma and interacts with receptors to mediate lipoprotein uptake, thus directing lipid distribution via catalytic and non-catalytic functions. Functional losses in LPL or any of its myriad of regulators alter lipid homeostasis and potentially affect the risk of developing cardiovascular disease-either increasing or decreasing the risk depending on the mutated protein. The extensive LPL regulatory network tunes LPL activity to allocate fatty acids according to the energetic needs of the organism and thus is nutritionally responsive and tissue dependent. Multiple pharmaceuticals in development manipulate or mimic these regulators, demonstrating their translational importance. Another facet of LPL biology is that the oligomeric state of the enzyme is also central to its regulation. Recent structural studies have solidified the idea that LPL is regulated not only by interactions with other binding partners but also by self-associations. Here, we review the complexities of the protein-protein and protein-lipid interactions that govern LPL structure and function.

The discriminative ability of the triglyceride-glucose index to identify metabolic syndrome among adults of the northern Sri Lankan population.

BACKGROUND: The triglyceride-glucose index (TyG index) is a simple surrogate marker for Insulin Resistance (IR). However, the relationship between the TyG index and Metabolic Syndrome (MetS) remains unknown in the Northern Sri Lankan population. METHODS: This was a descriptive, cross-sectional study of adults aged between 18 and 65 years living in Jaffna, Sri Lanka. This study aimed to verify the discriminative ability of the TyG index to identify MetS using the International Diabetes Federation (IDF-2006) criteria and to determine the gender-specific TyG index cut-off values for better prediction of MetS in Northern Sri Lankan adults. TyG index was calculated as Ln[Triglycerides (TG) (mg/dl) × Fasting plasma glucose (FPG) (mg/dl)/2]. RESULTS: A total of 540 individuals were included in this study, with a mean age of 42.18 (± 13.89) years for males and 43.80 (± 12.56) years for females. The mean value of the TyG index in the total study population was 8.54 (± 0.53). Individuals in the higher quartiles of the TyG index had a significantly increased risk of MetS compared with those in the lowest quartile (p < 0.01). TyG index showed a stronger association with MetS than the FPG and all the conventional lipid components and the unadjusted odds ratio was 5.47. The area under the curve (AUC) of ROC revealed values of 0.914 (95% confidence interval (CI): 0.884, 0.944) for females, 0.881 (95% CI: 0.830, 0.932) for males and 0.897 (95% CI: 0.870, 0.924) for the total study population. TyG index had a stronger discriminative ability to identify MetS as per IDF criteria in the study population with a cut-off value of 8.60. The mean level of the TyG index significantly increased with the increasing number of MetS components. CONCLUSIONS: The mean value of the TyG index increased as the number of MetS components in the study population increased. Individuals with a higher TyG index had a significantly increased risk of having MetS compared with the lowest quartile of the TyG index. TyG index had a good discriminative ability to diagnose MetS as per IDF criteria among the northern Sri Lankan population.