Insulin resistance (IR) is a risk factor for cardiovascular diseases and type 2 diabetes. Associations between DNA methylation (DNAm) and IR have been less studied in African ancestry (AA) populations than those of European ancestry (EA). We aimed to identify associations between whole blood DNAm and IR in up to 1,811 AA and 964 EA participants from the Atherosclerosis Risk in Communities (ARIC) study. We quantified IR using three surrogate measures: the homeostasis model assessment of insulin resistance (HOMA-IR), the triglyceride-glucose index (TyG), and the triglyceride glucose-body mass index (TyG-BMI). We used ancestry-stratified linear regression models to conduct epigenome-wide association studies of IR, adjusting for batch effects and relevant covariates. Among 484,436 tested CpG sites, 39 were significantly associated with IR, of which 31% (10 in AA and two in EA) were associated with TyG-BMI and not previously reported for IR or related traits. These include a positive association at cg18335991-SEMA7A in AA. SEMA7A inhibits adipogenesis of preadipocytes and lipogenesis of mature adipocytes. DNAm levels at cg18335991 have been reported to be negatively associated with SEMA7A expression in blood. After additionally adjusting for smoking and drinking status, 15 of the 39 significant CpG sites remained significant or suggestive. Our study identified novel IR-associated CpG sites, contributing to a broader understanding of the epigenetic mechanisms underlying IR in diverse populations.

Current literature lacks evidence to characterize the relationship between the triglyceride glucose - body mass index (TyG-BMI) and depression. Therefore, this study aimed to elucidate the potential association between TyG-BMI and depression risk in a Chinese middle-aged and elderly population.

The study utilized data from the China Health and Retirement Longitudinal Study (CHARLS) conducted in 2011, which included 17,708 participants. We used multifactorial logistic regression modeling to investigate the relationship between TyG-BMI and depression in Chinese adults, using smoothed curve fitting to assess the nonlinear relationship between them. In addition, we performed sensitivity and subgroup analyses to verify the robustness of the results.

A total of 9328 participants were included in our study, After adjusting for all potential covariates, participants with higher levels of TyG-BMI had a lower risk of depression compared to Q1, the adjusted OR (95 % CI) values were Q2 (OR: 0.84, 95 % CI: 0.74-0.96, p = 0.009), Q3 (OR: 0.75, 95 % CI: 0.65-0.86, p < 0.001), and Q4 (OR: 0.67, 95 % CI: 0.57-0.79, p < 0.001). The association between TyG-BMI and depression exhibited an L-shaped curve (nonlinear, p = 0.004). When TyG-BMI <200, Increased TyG-BMI was associated with a significantly lower risk of depression (OR = 0.87 [95 %CI:0.82-0.93], p < 0.001). However, there was no association between TyG-BMI and depression when TyG-BMI ≥200 (OR = 0.96 [95 %CI:0.91-1.02], p = 0.22).

The connection between TyG-BMI and depression in Chinese adults is L-shaped, with an inflection point around 200.

Intestinal health issues affect approximately 20% of the global population, yet the relationship between insulin resistance (IR) and intestinal health remains poorly understood. This study evaluated the discriminative ability of five IR surrogate indices-homeostatic model assessment for insulin resistance (HOMA-IR), triglyceride-glucose index (TyG), TyG adjusted for body mass index (TyG-BMI), triglyceride-to-high-density lipoprotein cholesterol ratio (TG/HDL-C), and estimated glucose disposal rate (eGDR)-for chronic diarrhea and constipation in adults.

Using data from the 2005-2010 National Health and Nutrition Examination Survey (NHANES), we analyzed associations between five IR surrogate indices and chronic diarrhea/constipation in adults. Key variables were selected via the Boruta algorithm and incorporated into weighted multivariate logistic regression models. Restricted cubic spline (RCS) analysis, threshold effect analysis, and receiver operating characteristic (ROC) curves were employed to assess these associations.

Among 6,133 participants in this study, 7.5% had chronic diarrhea and 7.4% had chronic constipation. After adjusting for confounders, multivariate logistic regression revealed significant positive associations of HOMA-IR (OR: 1.02, 95% CI: 1.00-1.04), TyG (OR: 1.28, 95% CI: 1.05-1.55), and TyG-BMI (OR: 1.01, 95% CI: 1.00-1.01) with chronic diarrhea, while eGDR showed an inverse association (OR: 0.88, 95% CI: 0.80-0.96). No significant associations were observed between IR surrogate indices and chronic constipation. RCS and threshold effect analyses demonstrated a non-linear relationship between TG/HDL-C and chronic diarrhea: Each 1-unit increase in TG/HDL-C below the threshold of 7.33 elevated diarrhea risk by 11% (95% CI: 1.05-1.17). ROC analysis indicated that TyG-BMI (AUC: 0.656 vs. 0.644) and eGDR (AUC: 0.652 vs. 0.644) significantly improved the discriminative ability of the baseline model for chronic diarrhea, whereas HOMA-IR and TyG showed no statistically meaningful enhancements.

IR surrogate indices were significantly associated with chronic diarrhea but not chronic constipation, highlighting their potential as biomarkers for screening diarrhea in the general population.

Knee osteoarthritis (OA) is associated with high insulin resistance, particularly in individuals with metabolic syndrome and type 2 diabetes. In this cross-sectional study, we aimed to explore the relationship between insulin resistance indices and the prevalence of knee OA using data from 4,209 participants of the 2009-2010 Korea National Health and Nutrition Examination Survey. We used several insulin resistance indices in our analysis: Homeostatic Model Assessment for Insulin Resistance (HOMA-IR), triglyceride-glucose (TyG) index, TyG-body mass index (TyG_BMI), TyG-waist circumference (TyG_WC), and visceral adiposity index (VAI). Without adjusting for confounding variables, the TyG_index increased the risk of knee OA by 1.056. After adjusting for confounders, the risk increased significantly by 1.082. Similarly, the TyG_BMI, TyG_WC, and VAI showed significant associations with knee OA. However, the association between HOMA-IR and knee OA was not significant. BMI (with and without confounding variable adjustments) was significantly associated with knee OA, whereas no significant associations were found for hypertension, dyslipidemia, diabetes, or WC. These results suggest that insulin resistance indices, particularly TyG-related indices, are significantly associated with knee OA. This highlights the potential benefits of managing knee OA in the context of metabolic syndrome, which is often associated with increased insulin resistance.

Insulin resistance(IR) is a key mechanism underlying both obesity and metabolic syndrome, with significant implications for the onset and progression of female infertility. This study systematically examines the associations between seven insulin resistance indicators and the risk of infertility in U.S. women of reproductive age, while also evaluating the diagnostic value of these indicators in predicting infertility.

This cross-sectional study analyzed data from the 2013-2018 National Health and Nutrition Examination Survey (NHANES) to explore the relationship between seven insulin resistance indicators and infertility risk. The indicators included the Metabolic Score for Insulin Resistance (METS-IR), Triglyceride-Glucose Index (TyG), Triglyceride-Glucose-Waist Circumference (TyG-WC), Triglyceride-Glucose-Body Mass Index (TyG-BMI), Triglyceride-Glucose-Waist-to-Height Ratio (TyG-WHtR), Homeostasis Model Assessment of Insulin Resistance (HOMA-IR), and Triglyceride/High-Density Lipoprotein Ratio (TG/HDL). Receiver Operating Characteristic (ROC) curves were used to assess the diagnostic accuracy of each insulin resistance indicator in predicting infertility. Additionally, smooth curve fitting and threshold effect analysis were employed to further explore the relationship between insulin resistance indicators with high diagnostic efficacy and infertility.

This study included 1,100 women aged 20-45, of whom 140 (12.61%) were diagnosed with infertility. The results revealed significant positive correlations between METS-IR, TyG-BMI, TyG-WC, TyG-WHtR, and infertility risk. Specifically, as TyG-WC and TyG-WHtR levels increased, the risk of infertility rose linearly, while METS-IR and TyG-BMI exhibited a nonlinear positive association with infertility risk. No significant correlations were observed between TyG, HOMA-IR, TG/HDL, and infertility. Finally, ROC curve analysis indicated that METS-IR outperformed the other six insulin resistance indicators in predicting infertility risk.

METS-IR, TyG-BMI, TyG-WC, and TyG-WHtR are significantly associated with the risk of infertility in U.S. women of reproductive age, with METS-IR demonstrating the highest predictive power. These findings suggest that METS-IR may have substantial clinical utility in evaluating infertility risk.

Previous studies have mainly explored the effects of body mass index (BMI) and triglyceride-glucose index (TyG index) on cardiovascular disease (CVD) separately or by examining the composite parameter (TyG-BMI) formed by multiplying the two and its association with CVD. However, few studies have investigated the combined effect of BMI categories and the TyG index on CVD. This study aimed to determine the association of BMI categories combined with the TyG index in new-onset CVD. A total of 94,002 participants were included from the Kailuan study. Their BMI combined with the TyG index was categorized into six groups: Low-BMI/Low-TyG, Middle-BMI/Low-TyG, High-BMI/Low-TyG, Low-BMI/High-TyG, Middle-BMI/High-TyG, and High-BMI/High-TyG. A multifactorial Cox proportional hazards model was used to analyze the longitudinal association between BMI combined with the TyG index and new-onset CVD events. During a follow-up period of 15.95 ± 3.59 years, 9791 new CVD events were recorded. After adjusting for confounding factors such as sex, age, smoking, drinking, physical activity, systolic blood pressure, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, uric acid, high-sensitivity C-reactive protein, antihypertensive drugs, hypoglycemic drugs, and lipid-lowering drugs, Cox regression analysis showed that the risk of CVD events was 52% higher in the High-BMI/High-TyG group (HR: 1.52; 95% CI 1.42-1.64) compared to the Low-BMI/Low-TyG group. The combination of high BMI (≥ 28.0) and high TyG index (> 8.58) significantly increases individual CVD risk. This study suggests that the combination of BMI and the TyG index may better help identify individuals at risk of developing CVD.

The triglyceride-glucose body mass index (TyG-BMI) is acknowledged as a dependable surrogate biomarker for the evaluation of insulin resistance (IR). Current research indicates a significant correlation between TyG-BMI and the risk of subsequent cardiovascular events in individuals diagnosed with cardiovascular-kidney-metabolic syndrome (CKM) at stages 0-3. Nevertheless, the prognostic significance of TyG-BMI in patients with CKM stage 4 has not been extensively investigated, and there is a paucity of evidence available on this topic. The study utilized patient data from the Medical Information Mart for Intensive Care (MIMIC-IV) database, categorizing the data into quartiles based on the TyG-BMI index. The primary outcomes of interest were all-cause mortality at 180 days and at one year. To assess the relationship between the TyG-BMI index and these outcomes in patients diagnosed with stage 4 CKM, a Cox proportional hazards model was employed. Additionally, a restricted cubic splines(RCS) model was applied to further investigate the associations between the TyG-BMI index and the specified outcomes. A total of 1,885 patients participated in the study, with 62.49% of the cohort being male. The all-cause mortality rates were recorded at 30.50% at 180 days and 35.12% at one year. Analysis using a multivariate Cox proportional hazards model revealed that an increase in the TyG-BMI index was significantly correlated with a reduction in the risk of all-cause mortality at both the 180-day and one-year marks. Specifically, for each standard deviation increase in the TyG-BMI index, the risk of all-cause mortality decreased by 17% within 180 days (HR = 0.83, 95% CI: 0.76-0.91) and by 21% within one year (HR = 0.79, 95% CI: 0.71-0.87). Furthermore, regression analysis utilizing RCS indicated a linear decrease in all-cause mortality rates associated with increasing TyG-BMI index values over both the 180-day and one-year periods (P for nonlinearity = 0.171 and P for nonlinearity = 0.141, respectively). In patients diagnosed with stage 4 CKM syndrome, a reduced TyG-BMI index was found to be significantly correlated with a heightened risk of all-cause mortality within both 180 days and one year. Consequently, the TyG-BMI index may be utilized as an effective instrument for risk stratification and prognostic assessment in this patient population.

The triglyceride-glucose (TyG) index serves as an alternative index for assessing insulin resistance (IR). The relationship between the TyG index and its combined indicators and sarcopenia remains insufficiently explored.

To investigate the association between the TyG index and its combined parameters and sarcopenia.

This cross-sectional study encompassed 792 community-dwelling older adults from the Chongqing Aging and Sarcopenia Evaluation (CHASE) cohort. The multivariate logistic regression model was used to analyze the relationship between the TyG index and its combined parameters, which include the triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-calf girth (TyG-CG), triglyceride glucose-waist circumference (TyG-WC), and triglyceride glucose-waist-to-hip ratio (TyG-WHR). The receiver operator characteristic (ROC) curve was utilized to assess the diagnostic effect of each index. The integrated discrimination improvement index (IDI) and net reclassification improvement (NRI) were applied to compare the diagnostic efficacy among the indices.

The TyG index and its combined parameters demonstrated a significant correlation with the risk of sarcopenia (P < 0.05). The area under the ROC curve (AUC) for the TyG index in predicting the risk of sarcopenia was 0.623 (95% confidence interval: 0.570-0.675). Notably, composite parameters incorporating the TyG index showed enhanced predictive performance. Specifically, TyG-BMI showing the highest AUC of 0.892 (95% confidence interval: 0.860-0.924), indicating its strong predictive potential. Furthermore, the diagnostic efficacy of TyG-BMI was superior to that of all other indicators in both the IDI and NRI.

The TyG index demonstrates diagnostic potential for sarcopenia identification, with significantly enhanced accuracy when combined with other parameters. Among them, TyG-BMI is a robust sarcopenia risk predictor due to its superior predictive power.

Polycystic ovary syndrome (PCOS), a common and multifactorial endocrine disorder in reproductive-aged women, is strongly associated with insulin resistance (IR) and type 2 diabetes mellitus (T2DM), and also affects up to one in four women with type 1 diabetes mellitus (T1DM). The current study explored the potential of Plantago ovata (P. ovata) seed ethanol extract (POEE) to modulate oxidative stress (OS), inflammatory responses, metabolic profiles, and hormonal levels in rat Streptozotocin (STZ)-induced DM and Letrozole (LET)-induced PCOS. Phytochemical analysis measured total phenolic content (TPC) and total flavonoid content (TFC) using HPLC-DAD-ESI MS for compound identification. POEE's antioxidant activity was evaluated in vitro through DPPH, H2O2, FRAP, and NO scavenging assays. Rats received POEE, metformin, or Trolox (TX) for 10 days. PCOS confirmation was achieved via ultrasound and histopathology. Serum levels of OS markers (TOS, TAC, OSI, MDA, AOPP, 8-OHdG, NO, 3-NT, AGEs, and SH), inflammatory markers (NF-κB, IL-1β, IL-18, Gasdermin D, and IL-10), metabolic parameters (fasting blood glucose, lipid profile, and liver enzymes), and hormone levels (LH, FSH, estrogen, testosterone, and insulin) were assessed. Additionally, the Triglyceride-Glucose index (TyG) and HOMA-IR were calculated. POEE had a medium content of polyphenols and a good in vitro antioxidant effect. In vivo, POEE administration in diabetic rats led to a reduction in OS markers and an increase in antioxidant levels, alongside decreases in inflammatory cytokines, blood glucose levels, and transaminase activity and improvements in lipid profile. In the PCOS model, POEE treatment effectively reduced total OS and lowered levels of LH, FSH, and testosterone, while elevating estrogen concentrations and reducing insulin resistance. These therapeutic effects were dose-dependent, with higher doses producing more pronounced outcomes, comparable to those observed with metformin and TX treatment.

Respiratory failure (RF) lead to high mortality rates and extended hospital stays in intensive care unit (ICU). The Triglyceride-Glucose (TyG) index, a reliable surrogate marker for insulin resistance (IR), predicted adverse outcomes in various diseases. Combining weight-related indices like body mass index (BMI) with TyG to form the TyG-BMI enhanced the assessment of IR and its impact on patient outcomes. However, the association between TyG-BMI and outcomes in patients with RF remained underexplored. This study retrospectively analyzed data from the MIMIC-IV database, focusing on critically ill patients with RF. From an initial cohort of 19,429 patients, 2177 met the inclusion criteria and were divided into quartiles based on TyG-BMI values. Key clinical information was collected within the first 24 h of ICU admission, including demographics, lab results, vital signs, and scoring systems such as SAPS II and SOFA. Primary outcome was 28-day, secondary outcomes were 180-day and 1-year mortality. Data were analyzed using multivariable Cox regression models, Kaplan-Meier survival curves, and restricted cubic splines to assess the nonlinear relationship between TyG-BMI and mortality. The study found significant differences in baseline characteristics across TyG-BMI quartiles. Kaplan-Meier survival curves indicated a higher survival probability for patients in the lowest TyG-BMI quartile (Q1) compared to higher quartiles (Q2-Q4). Adjusted hazard ratios demonstrated a nonlinear association between higher TyG-BMI values and increased mortality risk at all three time points. The RCS-derived cut-off value of 269 for TyG-BMI was identified as a significant threshold, with higher TyG-BMI values correlating with lower mortality risks. Subgroup analyses reinforced these findings across different patient demographics and clinical profiles. Higher TyG-BMI was associated to lower short-term and long-term mortality, suggesting a potential protective effect. These findings highlighted the importance of the TyG-BMI as a robust prognostic marker, providing valuable insights for improving treatment strategies for patients with RF.

This meta-analysis aimed to evaluate the diagnostic performance of the triglyceride-glucose (TyG) index in predicting cancer occurrence.

A comprehensive literature search was conducted in Embase, Medline, Cochrane Library, and Google Scholar from inception to July 2024. Observational studies reporting the diagnostic efficacy of the TyG index in predicting cancer occurrence using ROC curve analysis were included. Pooled sensitivity, specificity, and area under the summary receiver operating characteristic (SROC) curve were calculated using a bivariate random-effects model.

Eleven studies with 46,658 participants were included. Patients with cancer had a significantly higher TyG index than those without cancer (mean difference: 0.34, 95% CI: 0.23-0.45). The pooled sensitivity and specificity of the TyG index for predicting cancer occurrence were 0.68 (95% CI: 0.62-0.74) and 0.65 (95% CI: 0.54-0.74), respectively. The area under the SROC curve was 0.72 (95% CI: 0.68-0.75), indicating good discriminatory ability. Subgroup analysis of female participants yielded similar results, with an AUC of 0.73 (95% CI: 0.69-0.77).

The TyG index demonstrates good discriminatory ability and may have potential as an adjunct screening tool to help identify individuals at a higher risk of developing cancer. However, this should be interpreted alongside other established risk factors, as many confounding factors (including cancer type, genetic predisposition, and other malignancy risk factors) must be considered. Further research is needed to establish optimal cut-off values, which likely vary across different cancer types, and to investigate their diagnostic accuracy in diverse populations.

https://www.crd.york.ac.uk/prospero/, identifier CRD42024573712.

The triglyceride‒glucose body mass index (TyG-BMI) has been recognized as a significant predictor of cardiovascular disease risk and plays a crucial role in assessing insulin resistance. However, the correlation between the TyG-BMI and clinical outcomes in patients with sepsis and acute heart failure (AHF) has not been sufficiently explored. This study aimed to investigate the associations between TyG-BMI and clinical outcomes in patients with sepsis and AHF.

We conducted a retrospective analysis of ICU-admitted patients via data from the MIMIC-IV database. Multivariable logistic regression, sensitivity analysis, and restricted cubic spline (RCS) models were used to assess the relationship between TyG-BMI and all-cause mortality. K‒M survival analysis and Boruta analysis were employed to evaluate the predictive value of the TyG-BMI. Subgroup analyses considered the effects of age, sex, ethnicity, and comorbidities.

Among the 1,729 patients, a higher TyG-BMI was associated with lower all-cause mortality at 90 and 180 days. Each standard deviation increase in the TyG-BMI was linked to 0.2% and 0.3% reductions in 90-day and 180-day all-cause mortality, respectively. Kaplan‒Meier analysis revealed significantly lower all-cause mortality in patients with higher TyG-BMIs (P < 0.0001). The RCS model revealed a nonlinear relationship between the TyG-BMI and mortality. Boruta analysis identified the TyG-BMI as an important clinical feature. Sensitivity analyses revealed that the association remained significant after patients with myocardial infarction, malignancies, or missing data were excluded. The subgroup analysis revealed that for the 90-day and 180-day mortality rates, significant interactions were found only in the subgroup of patients with kidney diseases (P < 0.05).

The TyG-BMI may have potential value in predicting mortality in ICU patients with sepsis and AHF, supporting early risk assessment and clinical intervention. This study provides critical insights into patient prognosis.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is closely associated with insulin resistance (IR). However, the prognostic value of different alternative IR surrogates in patients with MASLD remains unclear. This study aimed to evaluate the association between various IR indices and all-cause mortality and cardiovascular mortality in MASLD patients.

A total of 8,753 adults aged ≥ 20 years with MASLD from the National Health and Nutrition Examination Survey (NHANES, 2003-2018) were included, and their mortality data were obtained from the National Death Index (NDI). Insulin resistance surrogates [including the triglyceride-glucose (TyG) index, TyG-body mass index (TyG-BMI), TyG-waist circumference index, TyG-waist-to-height ratio index, and Homeostatic Model Assessment for IR] were stratified into quartiles. Cox proportional hazards models, receiver operating characteristic (ROC) curve analysis, restricted cubic spline (RCS), mediation analyses, and subgroup analyses were used to explore the associations between these indices and all-cause mortality as well as cardiovascular mortality in MASLD patients.

During a median follow-up of 98 months, 1,234 deaths were observed, including 409 cardiovascular disease (CVD)-related deaths. In the fully adjusted model, higher quartiles of TyG-related indices were significantly associated with an increased risk of all-cause mortality in MASLD patients. Furthermore, the TyG-BMI index was associated with both all-cause mortality and CVD mortality [all-cause mortality: HR (95% CI) 2.84 (1.73-4.67), P < 0.001; CVD mortality: HR (95% CI) 5.32 (2.26-12.49), P < 0.001]. The RCS analyses indicated a U-shaped relationship between TyG-BMI and mortality, with a threshold value of 270.49. Subgroup analyses demonstrated that TyG-related indices had stronger associations with mortality in elderly MASLD patients.

Our findings highlight the prognostic value of IR indices, particularly TyG-BMI index, in predicting all-cause mortality and CVD mortality in MASLD patients.

The triglyceride-glucose (TyG) index has been confirmed to be a predictor of cardiovascular diseases. The present study aimed to assess the predictive value of TyG index for left ventricular aneurysm (LVA) formation and prognosis in patients with acute ST-segment elevation myocardial infarction (STEMI) who underwent primary percutaneous coronary intervention (PCI).

This prospective study included 991 patients with acute STEMI who underwent primary PCI. Multivariable logistic regression and receiver operating characteristic (ROC) curve analysis were used to assess the predictive value of TyG index for LVA formation. Prognosis analysis was performed with cox proportional hazard regression.

The prevalence of LVA was 14.4%. A higher TyG index was associated with a greater incidence of LVA (23.1% vs. 11.8%, P< 0.001). The TyG index was also higher in the LVA group than in the non-LVA group (9.4 ± 0.9 vs. 9.0 ± 0.8, P<0.001). Multivariable logistic regression analysis revealed that the TyG index was independently associated with the risk of LVA [odds ratio (OR)= 2.4, 95% confidence interval (CI)= 1.51-3.82, P< 0.001]. The predictive value of the TyG index remained significant even after cross-validation by dividing the study population into a training set (OR= 2.32, 95% CI= 1.24-4.35, P= 0.009) and validation set (OR= 3.19, 95% CI= 1.42-7.19, P= 0.005). Higher TyG index was correlated with increased risk of cardiac death (HR= 2.17, P= 0.04). The maximal length and width of LVA were significantly increased in patients with TyG index ≥ 9.68 compared with < 9.68 (P< 0.001). The discriminant power of TyG index for LVA was 0.742, which was superior to both triglyceride (C statistic= 0.666) and fasting blood glucose (C statistic= 0.613). The combination of TyG index, left ventricular ejection fraction, gensini score, and left anterior descending artery as the culprit vessel could significantly improve the predictive ability (C statistic= 0.908).

A higher TyG index was an independent predictor for LVA formation and increased risk of cardiac death in patients with STEMI who underwent primary PCI.

Osteoporosis (OP) is a major metabolic bone disease with significant health and socioeconomic impacts. The triglyceride-glucose (TyG) index and its derivatives, which reflect insulin resistance (IR), may play a role in bone metabolism. However, the relationship between TyG indices and OP is unclear. This study aimed to explore the association between TyG indices and OP in a low-income rural Chinese population.

This cross-sectional study was conducted in rural Tianjin, China, in 2020. Participants aged 60 years or older were included. Data were collected through interviews, including sociodemographic and clinical information, and physical examinations. Bone mineral density (BMD) of the femoral neck was measured using dual-energy X-ray absorptiometry (DXA). Multivariate regression models and restricted cubic spline (RCS) curves were used to assess the relationships between TyG indices and OP.

A total of 437 individuals were included in the final analysis, with 38 diagnosed with osteoporosis (prevalence of 8.7%). After adjusting for all covariates, each 1-unit increase in triglyceride-glucose-body mass index (TyG-BMI) was associated with a 2% lower risk of osteoporosis, (OR: 0.98, 95% CI: 0.96-1.00, P=0.029), especially in women, individuals with hypertension, and non-diabetic populations. The OP risk of the fourth quartile (Q4) of the triglyceride-glucose-waist circumference (TyG-WC) index after correcting for all covariates is 5.58 times that of the first quartile (Q1)(OR: 5.58, 95% CI: 1.14-27.41, P=0.034). Linear regression showed a positive correlation between TyG-BMI and BMD, particularly in women, individuals under 70, and those with hypertension or non-hypertension, with the strongest correlation in the non-hypertensive group.

TyG-related indices are associated with OP, suggesting a potential role in the early prevention and management of osteoporosis in this population, ultimately improving public health outcomes.

This study investigates the association between changes in TyG-BMI and the risk of diabetes mellitus (DM) in middle-aged and elderly adults in China, as prior research has mainly focused on single baseline measurements.

Data were obtained from CHARLS, a nationwide prospective cohort study. TyG-BMI changes (2011-2015) were analyzed using K-means clustering. Cox proportional hazards regression models assessed the relationship between TyG-BMI changes, cumulative TyG-BMI, and DM risk, with sensitivity and subgroup analyses ensuring robustness.

Compared to individuals with consistently low TyG-BMI (class 1), hazard ratios (HRs) for DM were 1.474, 2.250, and 3.142 for participants with moderately sustained and slowly increasing TyG-BMI (class 2), slowly increasing high level of TyG-BMI (class 3), and the highest and increasing TyG-BMI levels (class 4), respectively. △TyG-BMI2015-2011 (per 10-unit) yielded HRs of 1.064 for class 2, 1.108 for class 3, and 1.079 for class 4. Cumulative TyG-BMI (per 10-unit) had an HR of 1.029.

TyG-BMI changes and sustained exposure to high TyG-BMI levels are independently linked to increased DM risk. Monitoring long-term fluctuations in TyG-BMI could be an important strategy for preventing DM, and effectively controlling high TyG-BMI through various interventions may significantly reduce DM risk.

To examine the impact of overactive bladder (OAB) on all-cause and cardiovascular mortality in women in a real-world setting, and to examine the association of TyG-related indices with OAB.

Data on 6580 women aged ≥20 years were collected from the National Health and Nutrition Examination Survey (NHANES) database. Kaplan-Meier curves and Cox survival analysis were used to evaluate the association between OAB and all-cause and cardiovascular mortality. Biomarkers for metabolic syndrome were assessed for their association with OAB, including triglyceride-glucose (TyG) and TyG-related indices. The association between TyG-related indices and OAB was evaluated using restricted cubic splines (RCS), receiver operating characteristic (ROC) curves and multivariate logistic regression, with propensity score matching (PSM) employed to balance confounders between OAB and non-OAB groups.

Kaplan-Meier curves showed that OAB was associated with a poorer prognosis, and multivariate Cox regression analyses indicated that OAB was an independent risk factor for both all-cause and cardiovascular mortality. RCS revealed a positive association between TyG-related indices and OAB. Both ROC curves and multivariate logistic regression analysis indicated that TyG-WHtR (TyG combined with waist-to-height ratio) was strongly associated with OAB, with a higher TyG-WHtR associated with an increased risk of OAB. The retrospective design and selection bias may be the potential limitations.

OAB is positively associated with all-cause and cardiovascular mortality in women. TyG-related indices are positively associated with OAB, with TyG-WHtR as the most effective index.

This study evaluated the associations of the triglyceride-glucose (TyG) index or its attendant parameters, known as reliable measures of insulin resistance, with asymptomatic intracranial arterial stenosis (aICAS), along with their value for distinguishing individuals with a notable aICAS burden.

This study enrolled 2000 participants (aged ≥ 40 years) based on the Rose asymptomatic IntraCranial Artery Stenosis study. Transcranial Doppler ultrasound combined with magnetic resonance angiography was utilized to confirm aICAS. Logistic regression was applied to assess the associations between TyG or TyG-related indices (TyG-body mass index, TyG-waist circumference [TyG-WC], TyG-waist-to-hip ratio [TyG-WHR], or TyG-waist-to-height ratio [TyG-WHtR]) and aICAS. The diagnostic potential of them was investigated using receiver operating characteristic (ROC) analysis.

Among the 2000 participants, 146 (7.3%) had a diagnosis of aICAS. TyG-WC, TyG-WHR, or TyG-WHtR were independently related to the prevalence of aICAS (TyG-WC: OR 1.26, 95%CI 1.03-1.54; TyG-WHR: OR 1.29, 95%CI 1.07-1.55; TyG-WHtR: OR 1.25, 95%CI 1.04-1.51). ROC analysis disclosed that TyG-WHtR had significant superior performance in identifying aICAS compared with other parameters (all P < 0.05). Subgroup analysis revealed that higher TyG-WHtR values showed a positive association with a heightened prevalence of aICAS observed in elderly participants aged ≥ 65 years (OR 1.69, 95%CI 1.20-2.38), and hypertensive patients (OR 1.30, 95%CI 1.06-1.59).

The association of TyG-WHtR with aICAS showed that TyG-WHtR might be a more effective indicator for identifying populations with early-stage aICAS.

Insulin resistance is one of the major pathophysiological features of type 2 diabetes mellitus. Studies have revealed the association between type 2 diabetes mellitus and low back pain. However, few studies explored the relationship between insulin resistance and low back pain directly. Therefore, this study selected HOMA-IR, TyG, TyG-BMI, TyG-WC, and TyG-WtHR as indicators of insulin resistance to comprehensively investigate the association between insulin resistance and low back pain.

The data for this cross-sectional study were from NHANES. Multivariate logistic regression was used to assess the association of insulin resistance with low back pain, and the stability of the results was evaluated by stratified analysis.

A total of 6,126 adult participants were included in the study, including 3,657 non-LBP participants and 2,469 LBP patients. All of these five indices showed significant association with low back pain after full adjustment for all covariates (Model 3), HOMA-IR [OR = 1.052, 95% CI (1.018, 1.087), p = 0.003], TyG [OR = 1.431, 95% CI (1.013, 2.021), p = 0.042], TyG-BMI [OR = 1.003, 95% CI (1.002, 1.005), p < 0.0001], TyG-WC [OR = 1.001, 95% CI (1.001, 1.002), p < 0.0001], TyG-WtHR [OR = 1.268, 95% CI (1.155, 1.393), p < 0.0001]. The relationship between insulin resistance and low back pain is stable in most stratified populations (p-interaction >0.05).

Insulin resistance is associated with an increased risk of low back pain. The HOMA-IR, TyG, TyG-WC, TyG-BMI, and TyG-WtHR all showed a stable correlation with low back pain. TyG-BMI, TyG-WC, and TyG-WtHR are more stable in their associations with low back pain than TyG alone.

The potential links between triglyceride-glucose (TyG) related indicators and breast cancer incidence after menopause have been less well studied, and the joint associations between genetic risk, TyG related indicators, and breast cancer are unknown.

Simple surrogate indicators of insulin resistance including TyG, TyG-waist circumference (TyG-WC), TyG-waist to height ratio (TyG-WHtR), TyG-waist to hip ratio (TyG-WHR), TyG-body mass index (TyG-BMI). Genetic susceptibility in breast cancer was estimated by categorizing polygenic risk scores (PRS). For estimating the associations, we used Cox proportional hazards regression modeling. Correlation shapes were evaluated using restricted cubic splines (RCS). Mediation analyses for assessing the role of sex hormone-binding globulin (SHBG), C-reactive protein (CRP), testosterone, and glycosylated hemoglobin (HbA1c) in mediating the associations were conducted.

The study included 83,873 UK biobank participants who were followed for a median of 13.8 years, with 3,561 new cases of postmenopausal breast cancer. Genetic risk and TyG related indicators were monotonically related to breast cancer, with additive but not multiplicative interactions between them. The highest quartiles of TyG, TyG-WC, TyG-WHtR, TyG-WHR, and TyG-BMI were significantly associated with increased breast cancer risk with hazard ratio (95% confidence interval) were 1.12 (1.01-1.25), 1.35 (1.23-1.49), 1.16 (1.05-1.28), 1.22(1.12-1.33), and 1.31 (1.19-1.44), respectively. TyG-WC was nonlinearly linked to breast cancer (P for nonlinear = 0.006). Individuals with high genetic risk and high TyG related indicators exhibited a substantially elevated breast cancer risk by 4- to 5-fold compared with reference group. The associations were mainly mediated by SHBG, CRP, and testosterone, with mediation proportions ranging from 10.24% to 68.29%.

TyG related factors are linked to incident postmenopausal breast cancer, and the combined effects with genetic risk significantly optimize risk stratification. High levels of TyG related indicators may amplify the influence of genetic factors on postmenopausal breast cancer.

Not applicable.

The triglyceride-glucose-body mass index (TyG-BMI), a marker for insulin resistance, is recognized for its predictive role in cardiovascular and metabolic diseases, including kidney disease. we explored the TyG-BMI index's association with postoperative kidney injury in coronary artery bypass grafting (CABG) patients, who are at an elevated risk for such complications, underscoring its potential as a predictor for acute kidney injury (AKI).

This single-center, retrospective study included 126 patients. Patients were divided into AKI and non-AKI groups postoperatively according to the KDIGO classification criteria. Univariate logistic regression was used to screen for variables with significant differences (P < 0.01), and multiple multivariate regression models were constructed to analyze independent risk factors in the multivariate regression model and to analyze the value of TyG-BMI in predicting AKI in diabetic patients after CABG.

Compared to the non-AKI group, the AKI group had statistically significant differences in preoperative fasting triglycerides, preoperative fasting glucose, preoperative and postoperative creatinine levels, ICU stay duration, and TyG-BMI levels (P < 0.05). Based on the results of univariate regression analysis, a multivariate logistic regression model A was constructed using all significant variables, and a multivariate logistic regression model 2 was constructed using significant variables other than TyG-BMI. ROC analysis showed that model 2 had better predictive performance than model 1 (AUC = 0.836 vs. 0.766). A positive correlation was observed between TyG-BMI and AKI occurrence (Spearman's correlation coefficient: R = 0.33, P = 0.00019).

Elevated TyG-BMI levels are closely associated with AKI in diabetic patients after CABG. TyG-BMI has potentially predictive value for AKI in diabetic patients after CABG and may play a crucial role in risk stratification in clinical practice.

This study aims to investigate the significance of insulin resistance (IR) markers in predicting 48-hour hemorrhagic transformation and 3-month poor prognosis in acute ischemic stroke (AIS) patients of intravenous thrombolysis (IVT), with or without type 2 diabetes mellitus (T2DM).

A total of 1352 patients with AIS treated with IVT between January 2019 and December 2023 were retrospectively reviewed. We analyzed the prognostic value of IR markers, including the triglyceride-glucose (TyG) index, triglyceride and body mass index (TYG-BMI), and the insulin resistance metabolic score (METS-IR), in AIS patients who received IVT with or without T2DM. The primary outcome was 48-hour hemorrhagic transformation and 3-month poor prognosis (modified Rankin Scale [mRS] ≥ 3).

Among 1181 enrolled patients, 328 were diagnosed with T2DM, representing 27.8% of the cohort. T2DM group showed a higher proportion of poor prognosis (23% vs.11%, p < 0.001), but no significant difference in hemorrhagic transformation between the two groups. TyG index, TyG-BMI, and METS-IR all demonstrated predictive value for 3-month poor prognosis, with the TyG index showing the highest predictive accuracy [area under the curve (AUC): 0.848]. The optimal cutoff point for predicting poor prognosis was 7.409, with sensitivity of 0.762 and specificity of 0.855 (p < 0.001). However, all three indexes were limited in their ability to predict hemorrhagic transformation.

Elevated TyG index is an independent risk factor for 3-month poor prognosis in AIS patients of IVT with or without type T2DM, with the TyG index showing the highest predictive value. These findings provide a new understanding that IR can be used as a therapeutic target for AIS patients of IVT.

The triglyceride-glucose (TyG) index and triglyceride-glucose/body mass index (TyG-BMI) have been shown to be associated with cardiovascular and cerebrovascular disorders and the risk of death. The aim of this study was to explore the relationships of the TyG index and TyG-BMI with all-cause mortality among Chinese centenarians.

Data from the China Hainan Centenarian Cohort Study (CHCCS) were analyzed. Eligible centenarians were divided into quartiles on the basis of their TyG and TyG-BMI indices. Kaplan‒Meier analysis was used to compare survival times across groups. The associations of the TyG index and TyG-BMI with all-cause mortality were investigated using restricted cubic splines (RCSs) and Cox proportional hazards regression models. Moreover, the concordance of the associations of the TyG index and TyG-BMI with all-cause mortality in different subgroups was further explored by subgroup analysis.

A total of 921 centenarian participants were included in this study. During a median follow-up of 29.70 months, 852 (92.5%) centenarians died. The results of the RCS analysis demonstrated that the TyG index and TyG-BMI were both linearly and negatively associated with all-cause mortality. Compared with that for the highest the TyG index and TyG-BMI quartile groups, higher risks of death were found for the lowest quartile groups (TyG Q1 vs. Q4, HR 1.27, 95% CI 1.03-1.56, P = 0.024; TyG-BMI Q1 vs. Q4, HR 1.60, 95% CI 1.30-1.96, P < 0.001). Centenarians with lower TyG index and TyG-BMI values had significantly greater mortality risks according to the Kaplan‒Meier analysis (log-rank P = 0.020, log-rank P < 0.001, respectively). Subgroup analysis demonstrated that blood pressure could influence the linear negative correlation between the TyG-BMI and all-cause mortality.

Both lower TyG and TyG-BMI indices were significantly associated with higher all-cause mortality in Chinese centenarians, whereas the TyG-BMI was superior to the TyG index in predicting the mortality risk of centenarians.

BackgroundThe triglyceride-glucose (TyG) index is considered a robust surrogate for insulin resistance (IR). The relationship between the trajectory patterns of the TyG index and subsequent brain structure changes is still unclear.ObjectiveThis study investigates the relationship between 10-year trajectories of TyG-related indices and brain structural integrity in a 10-year follow-up.MethodsThis prospective study included 898 participants (mean age 55.6 years, 34.4% males) from the community-based Shunyi Study. IR was assessed using the TyG index, TyG-body mass index (BMI) index, TyG-waist circumference index, and TyG-waist-to-height ratio (WHtR) index. The group-based trajectory model was employed to identify the 10-year trajectories. Structural brain measurements included structural changes of the whiter matter (white matter hyperintensities (WMHs), fractional anisotropy, and mean diffusivity) and gray matter (brain parenchymal fraction (BPF), cortical thickness, and hippocampal volume). General linear models were utilized to examine the association between the trajectory patterns of TyG-related indices and brain structure.ResultsThree distinct trajectories of TyG-related indices were identified from 2013 to 2023. The high-level trajectory groups of TyG-related indices exhibited a greater volume of WMHs and were more susceptible to disruptions in white matter microstructural integrity. This association was most significant for the TyG-BMI and TyG-WHtR trajectory groups. No significant correlations were found for BPF and cortical thickness among the different TyG-related indices trajectories.ConclusionsThe findings suggest that long-term IR primarily damages brain white matter rather than causing structural changes in gray matter.

This study compares the association of eight insulin resistance (IR)-related markers (triglyceride-glucose index (TyG), TyG-body mass index (TyG-BMI), TyG-waist circumference (TyG-WC), TyG-waist-to-height ratio (TyG-WHtR), triglycerides-to-high-density lipoprotein cholesterol ratio (TG/HDL), lipid accumulation product (LAP), visceral adiposity index (VAI), and estimated glucose disposal rate (eGDR)) with cardiovascular disease (CVD).

Spearman's coefficients were used for correlations between IR-related markers. Predictive capacities were evaluated using receiver operating characteristic (ROC) curve analysis, Akaike Information Criterion, and Bayesian Information Criterion were calculated. Multivariable-adjusted Cox regression models and restricted cubic spline (RCS) analysis were performed to explore associations between IR-related markers and CVD.

In Pearson correlation analysis, TyG-WC and TyG-WHtR had a correlation coefficient of 0.95, while TG/HDL ratio and VAI had a correlation coefficient of 0.97. Regarding predictive capacity across different glycemic states, eGDR showed the best performance among the 8 IR-related markers, particularly in predicting stroke. According to Cox regression analysis, with each unit increase in TyG, TyG-BMI, TyG-WC, and TyG-WHtR, the risk of heart disease increased by 24.1%, 0.4%, 0.1%, and 17.56%, respectively; and the risk of stroke increased by 69.3%, 0.6%, 0.2%, and 36.5%, respectively. Additionally, TG/HDL ratio, VAI, and LAP exhibited nonlinear associations with heart disease and stroke risk. For each unit increase in eGDR, the risks of heart disease and stroke decreased by 21% and 14.2%, respectively.

eGDR is the most effective marker for predicting CVD, especially stroke, across all glycemic states. Modified TyG indices provide better predictive value than TyG alone.

Objective: Various insulin resistance (IR) indices have been developed to assess cardiovascular (CVS) risk. We compared the association between ten IR indices and cardiac, renal, and vascular end-organ measures in a predominantly young (age 45.0 ± 18.3 years) South African Black population. Methods: We assessed the relationships between ten IR indices (homeostatic model assessment for IR [HOMA-IR], quantitative insulin sensitivity check index [QUICKI], metabolic score for IR [METS-IR], triglyceride-glucose index [TyG], TyG-body mass index [TyG-BMI], TyG-waist circumference [TyG-WC], TyG-waist-to-height ratio [TyG-WHtR], triglyceride to high-density cholesterol concentration [TyG-HDL], lipid accumulation product [LAP], visceral adiposity index [VAI]) and end-organ measures in 779 community participants of African ancestry. Results: HOMA-IR and QUICKI were the only IR indices consistently associated with end-organ measures (left ventricular [LV] mass index, p ≤ 0.005; LV relative wall thickness, p < 0.0001; early-to-late mitral velocity, p ≤ 0.01; E/e', p ≤ 0.002; e', p < 0.0001; pulse wave velocity, p = 0.036 (HOMA-IR only); glomerular filtration rate [GFR], p < 0.0001), independent of confounders. Furthermore, HOMA-IR was consistently higher, and QUICKI lower, in those with compared to those without end-organ damage (LV hypertrophy [p ≤ 0.03], concentric LV [p < 0.03], and reduced GFR [p ≤ 0.008]), independent of confounders. Importantly, the associations between HOMA-IR or QUICKI and end-organ measures were independent of additional CVS risk factors, including adiposity measures, and were replicated in the participants without diabetes mellitus (n = 669) and in the participants without high blood pressure (n = 505). Conclusions: In a predominantly young community of African ancestry, of ten recommended IR indices, only HOMA-IR and QUICKI were consistently associated with end-organ damage independent of CVS risk factors.

Background: Recent evidence has shown that insulin resistance (IR), a hallmark of nonalcoholic fatty liver disease, predicts bladder cancer (BC) presence. However, the best surrogate marker of IR in predicting BC is still unclear. This study examined the relationships among ten surrogate markers of IR and the presence of BC. Methods: Data from 209 patients admitted to two urology departments from September 2021 to October 2024 were retrospectively analyzed. Individuals (median age 70 years) were divided into two groups (123 and 86 patients, respectively) based on the presence/absence after cystoscopy/TURB of non-metastatic BC. Univariate logistic regression was used to determine the relationships between groups, and the following IR parameters: Triglyceride-Glucose (TyG) index, TyG-BMI, HOMA-IR HOMAB, MetS-IR, Single Point Insulin Sensitivity Estimator, Disposition Index, non-HDL/HDL, TG/HDL-C ratio and Lipoprotein Combine Index. Stepwise logistic regressions were carried out to evaluate the significant predictions and LASSO regression to confirm any significant variable(s). The predictive value of the index test for coexistent BC was evaluated using receiver operating characteristic (ROC) curves and the area under the ROC curve (AUC). Results: The univariate analysis revealed that the TyG index and MetS-IR were associated with the BC presence. Specifically, the associations of the TyG index and MetS-IR were more significant in participants =/> 65 years old. In multivariate analysis, the stepwise logistic regression, evaluating the most representative variables at univariate analysis, revealed a prediction of BC by only TyG index (OR 2.51, p = 0.012), confirmed by LASSO regression, with an OR of 3.13, p = 0.004). Assessing the diagnostic reliability of TyG, it showed an interesting predictive value for the existence of BC (AUC = 0.60; 95% CI, 0.51-0.68, cut-off 8.50). Additionally, a restricted cubic spline model to fit the dose-response relationship between the values of the index text (TyG) and the BC evidenced the presence of a non-linear association, with a high predictive value of the first knot, corresponding to its 10th percentile. The decision curve analysis confirmed that the model (TyG) has utility in supporting clinical decisions. Conclusions: Compared to other surrogate markers of IR, the TyG index is effective in identifying individuals at risk for BC. A TyG threshold of 8.5 was highly sensitive for detecting BC subjects and may be suitable as an auxiliary diagnostic criterion for BC in adults, mainly if less than 65 years old.

The aim of this study was to analyze the association between TyG-BMI and 365-day mortality in critically ill patients with CHD.

Patient data were extracted from the MIMIC-IV database. All patients were categorized into 3 groups based on TyG-BMI index: Low TyG-BMI index group, Medium TyG-BMI index group, and High TyG-BMI index group. Outcomes included primary and secondary outcomes, with the primary outcome being 365-day mortality and the secondary outcomes being hospital survival, intensive care unit (ICU) survival, and 28-day, 90-day, and 180-day mortality. The Kaplan-Meier survival curves were used to compare the outcomes of the three groups. The relationship between TyG-BMI index and 365-day mortality was assessed using multivariate Cox proportional risk regression models and restricted cubic spline curves (RCS).

889 critically ill patients with CHD were analyzed. Among them, 600 (67.50%) were male patients with a mean age of 68.37 years and 289 (32.50%) were female patients with a mean age of 73.91 years. Patients with a medium TyG-BMI index had the best 365-day prognostic outcome and the highest survival rate compared with patients in the Low and High TyG-BMI index groups [201 (67.68%) vs. 166 (56.08%), 188 (63.51%); P=0.013]. After fully adjusted modeling analysis, the hazard ratio (HR) for 365-day mortality was found to be 0.71 (95% CI 0.54-0.93, P=0.012) for the Medium TyG-BMI index group. Meanwhile, RCS analysis showed an L-shaped relationship between TyG-BMI index and 365-day mortality.

The TyG-BMI index is significantly associated with 365-day mortality in patients with severe CHD.

This study sought to examine the associations between cardiometabolic indices and the onset of metabolic dysfunction-associated steatotic liver disease (MASLD) as well as its progression to liver fibrosis.

This study comprised 25,366 subjects aged 18 years and older, free of MASLD at baseline, from the Dalian Health Management Cohort (DHMC). Cardiometabolic indices include cardiometabolic index (CMI), atherogenic index of plasma (AIP), triglyceride glucose (TyG), triglyceride glucose-body mass index (TyG-BMI), triglyceride glucose-waist circumference (TyG-WC) and triglyceride glucose-waist height ratio (TyG-WHtR). All participants were categorized into quartile groups based on cardiometabolic indices. Cox proportional hazards regression models and restricted cubic splines were employed to examine the relationship between cardiometabolic indices and the incidence of MASLD as well as its progression to liver fibrosis, and analyses were performed between different subgroups. Mediation analysis was employed to explore how obesity and inflammation serve as mediators in the connection between cardiometabolic indices and MASLD. To evaluate the predictive ability of cardiometabolic indices for the onset of MASLD, the time-dependent receiver operating characteristic (ROC) curve was utilized.

A total of 5378 (21.2%) individuals developed MASLD during the follow-up period of 82,445 person-years. Multivariates Cox regression analyses showed that participants in the highest quartile of cardiometabolic indices had greater risk of MASLD than those in the lowest quartile (CMI: HR = 6.11, 95% CI 5.45-6.86; AIP: HR = 4.58, 95% CI 4.11-5.10; TyG: HR = 3.55, 95% CI 3.21-3.92; TyG-BMI: HR = 13.55, 95% CI 11.80-15.57; TyG-WC: HR = 12.52, 95% CI 10.93-14.34; TyG-WHtR: HR = 11.37, 95% CI 9.96-12.98). TyG-BMI (HR = 1.36, 95% CI 1.18-1.57), but not other cardiometabolic indices, was associated with liver fibrosis. Mediation analysis indicated that BMI mediated 40.4%, 33.2%, 36.5%, - 10.4%, 37.4%, 48.5% of the associations between CMI, AIP, TyG, TyG-BMI, TyG-WC, TyG-WHtR and MASLD. Time-dependent ROC curves demonstrated that TyG-BMI had a superior predictive ability for MASLD onset compared to other indicators.

The risk of developing MASLD increases as the level of cardiometabolic indices increases. Obesity may serve as a mediating factor in the aforementioned association. TyG-BMI showed the strongest association with the onset of MASLD and its progression to liver fibrosis, proved to be outperformed other cardiometabolic indicators, and could be the best clinical non-invasive biomarker for early screening of MASLD and liver fibrosis.

There is limited research on the relationship between the triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio and outcomes in new-onset heart failure (HF). Therefore, this study aimed to explore the association between TG/HDL-C ratio and clinical outcomes in these patients.

A retrospective cohort of 614 adults with new-onset HF hospitalized at The First Affiliated Hospital of Nanchang University between July 2021 and December 2022 was analyzed. The primary endpoint was major adverse cardiovascular events (MACE), defined as cardiovascular (CV) death and HF rehospitalizations within 12 months after discharge. Kaplan-Meier (K-M) curves, restricted cubic spline (RCS) analysis, and Cox regression evaluated the association between TG/HDL-C ratio and MACE risk.

Patients were divided into four quartiles (Quartile 1, 2,3 and 4) based on their TG/HDL-C ratios. The mean age was 68.94 ± 14.34 years, with 59.12% male. The mean left ventricular ejection fraction (LVEF) was 46.59 ± 10.89%, with 45.11% having an LVEF ≤ 40%. During the 12-month follow-up, 156 patients experienced MACE, comprising 18 CV deaths and 138 HF rehospitalizations. The Quartile 4 group had the highest MACE risk incidence compared to other groups (P < 0.001). K-M analysis confirmed that the Quartile 4 group was associated with an increased cumulative incidence of MACE, HF rehospitalization, and CV death (all P < 0.001). RCS analysis revealed a positive nonlinear relationship between the TG/HDL-C ratio and MACE risk (P for nonlinear = 0.026), with a sharp risk increase above a ratio of 1.08. After adjustment, TG/HDL-C ratio was independently associated with MACE (HR: 1.44, 95% CI: 1.29-1.60). Compared to Quartile 1, adjusted HRs were significantly higher in Quartiles 2, 3, and 4 (all P < 0.005).

The TG/HDL-C ratio is independently associated with 12-month MACE risk in new-onset HF patients. It may serve as a simple, cost-effective marker to improve early risk stratification and guide closer monitoring and tailored management in this high-risk population.

Metabolic syndrome is associated with vitamin D3 deficiency. This work aims to examine the efficacy of vitamin D3 in inhibiting MetS-induced myopathy and to determine whether the beneficial effects of vitamin D3 are mediated by the inhibition of dipeptidyl peptidase-4 (DPP-4). An in silico study investigated the potential effectiveness of vitamin D3 on the inhibition of the DPP-4 enzyme. An in vitro assay of the DPP-4 inhibitory effect of vitamin D3 was performed. In vivo and over 12 weeks, both diet (with 3% salt) and drinking water (with 10% fructose) were utilized to induce MetS. In the seventh week, rats received either vitamin D3, vildagliptin, a combination of both, or vehicles. Serum lipids, adipokines, glycemic indices, and glucagon-like peptide-1 (GLP-1), muscular glucose transporter type-4 (GLUT-4) content, DPP-4, adenosine monophosphate kinase (AMPK) activities, and Sudan Black B-stained lipids were assessed. Muscular reactive oxygen species (ROS), caspase-3, and desmin immunostaining were used to determine myopathy. MetS-induced metabolic dysfunction was ameliorated by vitamin D3, which also reduced intramuscular glycogen and lipid accumulation. This is demonstrated by the attenuation of MetS-induced myopathy by vitamin D3, decreased oxidative stress, increased desmin immuno-expression, and caspase-3 activity. Our in silico data demonstrated that vitamin D3 is capable of inhibiting DPP-4, which is further supported by biochemical findings. Vitamin D3 increased serum GLP-1, muscular AMPK activity, and GLUT-4 content, whereas the levels of muscular ROS were decreased in MetS. Vildagliptin and its combination with vitamin D3 yielded comparable results. It is suggested that the DPP-4 inhibitory potential of vitamin D3 is responsible for the amelioration of MetS-induced metabolic changes and myopathy.

This study aimed to investigate the association between four insulin resistance (IR) surrogates and bone mineral density (BMD) and whether IR surrogates could be risk factors for osteoporosis (OP) in Chinese non-diabetic postmenopausal individuals.

Four non-insulin-based surrogates including triglyceride glucose (TyG), triglyceride glucose with body mass index (TyG-BMI), triglycerides (TG)/high-density lipoprotein cholesterol (HDL-C) and the metabolic score for insulin resistance (METS-IR) index were calculated. All individuals underwent dual-energy X-ray absorptiometry for measurement of BMD. Pearson correlation analysis was employed to evaluate the correlations between IR indices and BMD. Subsequently, logistic regression analysis was performed to investigate the relationship between these indices and OP while the receiver-operating characteristic curve was used to assess the predictive values for OP.

Both TyG-BMI and the METS-IR index were significantly positively associated with BMD. As TyG-BMI and the METS-IR index increased, the prevalence of OP decreased. After adjusting confounding factors, the fourth quartile of TyG-BMI and the METS-IR index showed significantly decreased odds ratio of 0.304 and 0.352, respectively, for OP with respect to its first quartile value. The area under the curve of TyG-BMI and the METS-IR index was 0.616 and 0.605, respectively.

IR surrogates TyG-BMI and the METS-IR index were positively associated with BMD and may be protective factors for OP in Chinese non-diabetic postmenopausal women.

Previous studies have suggested that the triglyceride glucose (TyG) index and body roundness index (BRI) are indicators of insulin resistance (IR) and are associated with the incidence of cardiovascular disease (CVD) among middle and old-aged adults. BRI is considered a more accurate indicator of the proportion of body fat and visceral fat than body mass index (BMI). However, it remains unclear whether the combined use of the TyG index and BRI, specifically the triglyceride glucose-body roundness index (TyG-BRI), is associated with the incidence of CVD among Chinese middle and old-aged adults.

Data were obtained from the China Health and Retirement Longitudinal Study (CHARLS). The TyG-BRI index was computed using baseline measurements of triglycerides, fasting blood glucose, waist circumference, and height. Cox proportional hazards regression and restricted cubic spline (RCS) regression analyses were applied to assess the association between the TyG-BRI index and incident CVD (defined as cardiac events or stroke).

A total of 8,113 Chinese adults participated in this study, with a median age of 58 years, including 56.3% males. The fully adjusted Cox regression analysis revealed that individuals in the highest quartile (Q4) of the TyG-BRI index had a 59.1% increased risk of developing incident CVD compared to those in the lowest quartile (HR, 1.591 [95% CI, 1.330-1.902]). The TyG-BRI index showed a significant linear association with CVD incidence (P for nonlinearity = 0.447, P < 0.001). This association persisted after conducting subgroup and sensitivity analyses.

This study introduced a novel TyG-BRI index, which integrated IR and body roundness as a comprehensive indicator, demonstrating its strong and independent association with increased CVD risk in a Chinese nationwide cohort. Our findings provide new insights into the interaction between metabolic dysfunction and cardiovascular risk, suggesting that the TyG-BRI index could serve as a practical tool for targeted preventive interventions.

Depression and cognitive impairments are prevalent among older adults, with evidence suggesting potential links to obesity and lipid metabolism disturbances. This study investigates the relationships between the triglyceride-glucose (TyG) index, body mass index (BMI), depression, and cognitive dysfunction in older adults, leveraging data from the NHANES survey and employing machine learning techniques.

We analysed 1352 participants aged 60-79 from the 2011-2014 NHANES dataset, who underwent cognitive function testing, depression assessments, and TyG index measurements. Multivariate linear regression and subgroup analyses were conducted to examine associations between the TyG index and depression/cognitive impairment. Machine learning models evaluated the importance of predictive factors for depression, while Mendelian randomization (MR) was employed to explore the causal relationship between BMI and depression/cognitive function.

The TyG index was negatively associated with cognitive function scores and positively associated with depression scores in adjusted models (p < 0.001). In fully adjusted subgroup analyses, among obese individuals (BMI ≥ 28), a 100-unit increase in the TyG index was linked to a 3.79-point decrease in depression scores. Machine learning models (Xgboost, AUC = 0.960) identified BMI, TyG-BMI, gender, and comorbidities (e.g., asthma, stroke, emphysema) as key determinants of depression. MR analyses revealed a negative association between BMI and depression risk [OR: 0.9934; 95 % CI (0.9901-0.9968), p = 0.0001] and cognitive dysfunction risk [OR: 0.8514; 95 % CI (0.7929-0.9143), p < 0.05]. No evidence of heterogeneity or pleiotropy was detected.

Depression and cognitive impairments were self-reported, potentially introducing bias. The observed associations may be influenced by unmeasured confounders, necessitating further research into the underlying mechanisms.

Our findings reveal associations between the TyG index and psychocognitive health in older adults. While these results highlight lipid metabolism as a potential factor in depression and cognitive dysfunction, further studies are needed to validate these findings and explore underlying mechanisms.

Triglyceride-glucose (TyG) related indices, including TyG, TyG-body mass index (TyG-BMI), and TyG-waist circumference (TyG-WC), have been identified as promising biomarkers for assessing insulin resistance (IR), a known risk factor for ischemic stroke. While previous research has highlighted the relevance of these indices in various metabolic disorders, their predictive utility for ischemic stroke across different glucose metabolic statuses has not been extensively explored.

This study utilized data from the UK Biobank, analyzing 392,733 participants free from ischemic stroke at baseline, categorized into normal glucose, prediabetes, and diabetes groups based on American Diabetes Association criteria. TyG-related indices were computed using baseline measures of fasting blood glucose and triglycerides. Participants were followed for a median of 14.68 years to assess the incidence of ischemic stroke. Cox proportional hazards models adjusted for demographic and clinical covariates were used to explore the associations between TyG indices and stroke risk.

Over the follow-up period, 8033 participants experienced an ischemic stroke. Higher TyG-related indices were associated with an increased stroke risk in all glucose metabolism groups, with the strongest associations observed in the prediabetes and normal glucose groups. The risk of stroke increased progressively across quartiles of TyG, TyG-BMI, and TyG-WC indices. The analysis revealed that each unit increase in the TyG index significantly elevated stroke risk in diabetic individuals, while TyG-BMI and TyG-WC indices showed significant predictive power in the prediabetes and normal glucose groups.

TyG-related indices, particularly TyG-BMI and TyG-WC, are effective in predicting the risk of ischemic stroke, especially among individuals with prediabetes and normal glucose levels. These findings underscore the utility of TyG indices as tools for early detection and preventive strategies in stroke risk management across various states of glucose metabolism.