Surrogate Indices Of Insulin Resistance Research Articles

Association of Triglyceride Glucose-Derived Indexes with Recurrent Events Following Atherosclerotic Cardiovascular Disease.

Triglyceride glucose (TyG) and TyG-body mass index (TyG-BMI) are reliable surrogate indexes of insulin resistance and used for risk stratification and outcome prediction in patients with atherosclerotic cardiovascular disease (ASCVD). Here, we inserted estimated average glucose (eAG) into the TyG (TyAG) and TyG-BMI (TyAG-BMI) as derived parameters and explored their clinical significance in cardiovascular risk prediction. This was a population-based cohort study of 9,944 Chinese patients with ASCVD. The baseline admission fasting glucose and A1C-derived eAG values were recorded. Cardiovascular events (CVEs) that occurred during an average of 38.5 months of follow-up were recorded. We stratified the patients into four groups by quartiles of the parameters. Baseline data and outcomes were analyzed. Distribution of the TyAG and TyAG-BMI indexes shifted slightly toward higher values (the right side) compared with TyG and TyG-BMI, respectively. The baseline levels of cardiovascular risk factors and coronary severity increased with quartile of TyG, TyAG, TyG-BMI, and TyAG-BMI (all P<0.001). The multivariate-adjusted hazard ratios for CVEs when the highest and lowest quartiles were compared from low to high were 1.02 (95% confidence interval [CI], 0.77 to 1.36; TyG), 1.29 (95% CI, 0.97 to 1.73; TyAG), 1.59 (95% CI, 1.01 to 2.58; TyG-BMI), and 1.91 (95% CI, 1.16 to 3.15; TyAG-BMI). The latter two showed statistical significance. This study suggests that TyAG and TyAG-BMI exhibit more information than TyG and TyG-BMI in disease progression among patients with ASCVD. The TyAG-BMI index provided better predictive performance for CVEs than other parameters.

Surrogate indices of insulin resistance using the Matsuda index as reference in adult men-a computational approach.

Overweight and obesity, high blood pressure, hyperglycemia, hyperlipidemia, and insulin resistance (IR) are strongly associated with non-communicable diseases (NCDs), including type 2 diabetes, cardiovascular disease, stroke, and cancer. Different surrogate indices of IR are derived and validated with the euglycemic-hyperinsulinemic clamp (EHC) test. Thus, using a computational approach to predict IR with Matsuda index as reference, this study aimed to determine the optimal cutoff value and diagnosis accuracy for surrogate indices in non-diabetic young adult men. A cross-sectional descriptive study was carried out with 93 young men (ages 18-31). Serum levels of glucose and insulin were analyzed in the fasting state and during an oral glucose tolerance test (OGTT). Additionally, clinical, biochemical, hormonal, and anthropometric characteristics and body composition (DEXA) were determined. The computational approach to evaluate the IR diagnostic accuracy and cutoff value using difference parameters was examined, as well as other statistical tools to make the output robust. The highest sensitivity and specificity at the optimal cutoff value, respectively, were established for the Homeostasis model assessment of insulin resistance index (HOMA-IR) (0.91; 0.98; 3.40), the Quantitative insulin sensitivity check index (QUICKI) (0.98; 0.96; 0.33), the triglyceride-glucose (TyG)-waist circumference index (TyG-WC) (1.00; 1.00; 427.77), the TyG-body mass index (TyG-BMI) (1.00; 1.00; 132.44), TyG-waist-to-height ratio (TyG-WHtR) (0.98; 1.00; 2.48), waist-to-height ratio (WHtR) (1.00; 1.00; 0.53), waist circumference (WC) (1.00; 1.00; 92.63), body mass index (BMI) (1.00; 1.00; 28.69), total body fat percentage (TFM) (%) (1.00; 1.00; 31.07), android fat (AF) (%) (1.00; 0.98; 40.33), lipid accumulation product (LAP) (0.84; 1.00; 45.49), leptin (0.91; 1.00; 16.08), leptin/adiponectin ratio (LAR) (0.84; 1.00; 1.17), and fasting insulin (0.91; 0.98; 16.01). The computational approach was used to determine the diagnosis accuracy and the optimal cutoff value for IR to be used in preventive healthcare.

High Mannose Correlates With Surrogate Indexes of Insulin Resistance and Is Associated With an Increased Risk of Cardiovascular Events Independently of Glycemic Status and Traditional Risk Factors.

To explore the associations among mannose, indexes of insulin resistance (IR) and secretion, and long-term cardiovascular outcomes. Fasting mannose was assayed in 1,403 participants, one-half of which had a first myocardial infarction (MI) with either normal glucose tolerance (n = 1,045) or newly detected dysglycemia (i.e., impaired glucose tolerance or type 2 diabetes; n = 358). Regression models were used to explore mannose associations with surrogate indexes of IR/insulin secretion. Multivariate Cox models were used to investigate the independent association between high (higher quartile) versus low (lower three quartiles) mannose and major adverse cardiac events (MACE) (n = 163) during the 10-year follow-up. Mannose was independently associated with IR indexes (all P ≤ 0.001). High versus low mannose was independently associated with MACE (hazard ratio 1.54, 95% CI 1.07-2.20) in the overall population. Mannose might represent a new biomarker able to track early, potentially detrimental glucometabolic alterations independently of glycemic state.

High mannose correlates with surrogate indexes of insulin resistance and predicts cardiovascular events independently of glycaemic status and traditional risk factors

Abstract Background Plasma mannose, an emerging marker of insulin resistance (IR), is independently associated with coronary artery disease and cardiovascular (CV) events, not only in patients with altered glycaemic status, but also among those with normal glucose tolerance (NGT) [1, 2]. Whether mannose is a predictor of future CV events is not known. Purpose To investigate the association of mannose with surrogate indexes of IR as well as with long-term prognosis in patients with and without dysglycaemia. Methods Fasting plasma mannose was measured by high-performance liquid chromatography coupled to tandem mass spectrometry (HPLC-MS-MS) in 696 cases with a first myocardial infarction (MI) and 707 controls matched for age, gender and living area from the PAROKRANK study [3]. Subjects free of known diabetes were further categorized as having either NGT (n=1045) or newly detected dysglycaemia (i.e., impaired glucose tolerance or type 2 diabetes; n=358) according to the results of an oral glucose tolerance test (OGTT). Surrogate indexes of IR and insulin secretion were calculated using glucose, insulin and C-peptide levels measured at 0, 30 and 120 minutes during the OGTT. The relationship between plasma mannose and different indexes was explored by fitting univariate and multivariate linear regression models. Kaplan-Meier functions were used to estimate crude survival across mannose quartiles. Unadjusted and adjusted Cox proportional hazards models were used to investigate the prognostic capacity of mannose, categorized as high (top quartile) vs low (lowest three quartiles), in relation to major adverse cardiac events (MACE) defined as CV death, MI and stroke during 10 years of follow-up. Secondary outcomes were single components of MACE and all-cause mortality. Results Mannose levels were associated with indexes of IR independently of BMI and other covariates in both the NGT and dysglycaemia subgroups. There was no difference in crude MACE-free survival between subjects with high and low mannose (log-rank p=0.10; Figure 1). However, high mannose remained as the only predictor of MACE in the overall population (Hazard ratio (HR): 1.58 (1.10-2.27); p=0.014) after multiple adjustments (Figure 2). This association was independent of the presence of dysglycaemia (interaction p between mannose category and dysglycaemia group=0.94) and IR expressed as HOMA-IR. High mannose also predicted MI, independently of the presence of a first MI (HR: 1.62 (1.00-2.62); p=0.050), while there was no significant association with the other secondary outcomes. Conclusions In a case-control setting of first MI, high mannose was the only significant predictor of future CV events, independently of traditional CV risk factors including a previous MI, glycaemic state and IR. Our findings expand the knowledge indicating that mannose might be used as a clinical tool for CV risk stratification.

The single point insulin sensitivity estimator (SPISE) index as a predictor of metabolic syndrome in Korean adults

PurposeRecently, the single-point insulin sensitivity estimator (SPISE) has been developed as a simple surrogate of insulin resistance based on BMI, triglycerides (TG), and HDL-C. However, no studies have focused on the predictive power of the SPISE index for identifying metabolic syndrome (MetSyn) in Korean adults. Here, this study aimed to estimate the predictive power of the SPISE index for determining MetSyn and to compare its predictive power with other insulin sensitivity/resistance indices in South Korean adults. MethodsA total of 7837 participants from the 2019 and 2020 Korean National Health and Nutrition Examination Surveys were analyzed in the present study. MetSyn was defined by the AHA/NCEP criteria. In addition, HOMA-IR, inverse insulin, TG/HDL, TyG index (triglyceride-glucose index), and SPISE index were calculated based on the previous literature. ResultsPredictive power of the SPISE index for determining MetSyn (ROC-AUC [95 % CI] = 0.90 [0.90–0.91], sensitivity = 83.4 %, specificity = 82.2 %, cut-off point = 6.14, p < .001) was higher than that of HOMA-IR (ROC-AUC: 0.81), inverse insulin (ROC-AUC: 0.76), TG/HDL-C (ROC-AUC: 0.87), and TyG index (ROC-AUC: 0.88), the P value for ROC-AUC comparison < .001. ConclusionSPISE index has demonstrated superior predictive value for diagnosing MetSyn regardless of sex and is strongly correlated with blood pressure compared with other surrogate indices of insulin resistance, attesting to its utility as a reliable indicator of insulin resistance and MetSyn in Korean adults.

Comparison of longitudinal changes in four surrogate insulin resistance indexes for incident T2DM in middle-aged and elderly Chinese.

Previous studies suggested a significant relationship between four surrogate indexes of insulin resistance and subsequent type 2 diabetes mellitus (T2DM). But the association of longitudinal changes (denoted as -D) in CVAI (Chinese visceral adiposity index), LAP (lipid accumulation product), TyG (triglyceride-glucose), and TG/HDL-C (triglyceride/ high-density lipoprotein cholesterol) indexes with the risk of T2DM remained uncertain. We aimed to compare the changes in those four surrogate indexes for predicting T2DM in middle-aged and elderly Chinese. We extracted data from the China Health and Retirement Longitudinal Study (CHARLS). Multivariate logistic regression models were used to estimate odds ratio (OR) with 95% confidence interval (CI) of incident T2DM with four surrogate indexes. The restricted cubic spline analysis was used to examine potential non-linear correlation and visualize the dose-response relationship between four indexes and T2DM. The receiver operator characteristic curve was used to compare the performance of the four indexes to predict T2DM. We enrolled 4,596 participants in total, including 504 (10.97%) with T2DM. Analysis results showed that four surrogate indexes were associated with T2DM, and the multivariate-adjusted ORs (95% CIs) of T2DM were 1.08 (1.00-1.16), 1.47 (1.32-1.63), 1.12 (1.00-1.25), and 2.45 (2.12-2.83) for each IQR (interquartile range) increment in CVAI-D, LAP-D, TG/HDLC-D, and TyG-D, respectively. Restricted cubic spline regression showed a non-linear correlation between four surrogate indexes and the risk of T2DM (p for non-linear < 0.001). From the ROC (receiver operating characteristic) curve, TyG-D had the highest AUC (area under curve), and its AUC values were significantly different from other three indexes both in male and female (all P < 0.001). Compared with other indexes, TyG-D was a better predictor in the clinical setting for identifying middle-aged and elderly Chinese with T2DM. Monitoring long-term changes in TyG might help in the early identification of individuals at high risk of T2DM.

Usefulness of four surrogate indexes of insulin resistance in middle-aged population in Hefei, China

Objective Previous study have shown that lipid accumulation product (LAP), visceral adiposity index (VAI), triglyceride/high-density lipoprotein cholesterol ratio (TG/HDL-C) and triglycerides/glucose index (TyG index) could be simple clinical indicators of insulin resistance (IR) based on anthropometric and/or biochemical parameters. However, the rational and preferred surrogate marker of IR in different population has yet to be validated. The aim of this study was evaluating the practicability of the LAP, VAI, TG/HDL-C, and TyG in predicting IR in middle-aged Chinese population. Methods A cross-sectional study was conducted in 569 Chinese participants (mean age was 48.5; man 67.7%), and each participant completed a questionnaire survey, anthropometric measurement, and biochemical testing. One-way ANOVAs, Chi-squared test, Pearson’s correlation, and multiple logistic regression were used to evaluate the association between VAI, LAP, TG/HDL-C, and TyG with IR. To correctly discriminate individuals with insulin resistance, a receiver operating characteristic (ROC) analysis was conducted for each evaluated variable and the overall diagnostic accuracy was quantified using the area under the ROC curve (AUC). The AUC of evaluated variables were compared using a nonparametric approach. The optimal cut-off points were determined by the Youden’s index, and the corresponding sensitivity and specificity were provided. Results Significant positive correlation was identified between HOMA-IR with TG/HDL-C (r = 0.306), VAI (r = 0.217), LAP (r = 0.381), and TyG (r = 0.371), respectively (all p < .001). After adjustment for potential confounders of IR, compared with the lowest tertiles, odds ratio (95% CI) having IR in the highest tertiles of TG/HDL-C, VAI, LAP and TyG were 6.07 (2.89–12.71), 10.89 (4.37–27.13), 4.68 (2.00–10.92), and 12.20 (5.04–29.56). The area under ROC curves to predict HOMA-diagnosed IR was 0.773 for TG/HDL-C, 0.767 for VAI, 0.806 for LAP, and 0.800 for TyG, respectively. Among those, LAP showed the greatest value of AUC [0.806 (0.763–0.850)] and highest specificity (0.804). Conclusion Compared with other indicators, the LAP and TyG are simple, relatively accurate, clinically available surrogate markers of insulin resistance in middle-aged population in Hefei, China. Among 4 evaluated parameters, the LAP have the highest specificity and the TyG have the highest sensitivity. Key Messages LAP and TyG could be used as simple and alternative methods to identify the individuals at risk for insulin resistance. LAP and TyG have relatively high predictive ability in diagnosis of IR compared with VAI and TG/HDL-C. No significant difference is observed between LAP and TyG in the ability of predicting insulin resistance.

Usefulness of four surrogate indexes of insulin resistance in middle-aged population in Hefei, China

Usefulness of four surrogate indexes of insulin resistance in middle-aged population in Hefei, China

Comparison of measures of insulin sensitivity in early-lactation dairy goats

This experiment aimed to investigate the correlations between surrogate indices of insulin resistance (IR)—namely, the homeostasis model of IR, the quantitative insulin sensitivity check index, and the revised quantitative insulin sensitivity check index—and measures of IR obtained from an intravenous glucose tolerance test (IVGTT) performed in early-lactation dairy goats. Saanen goats (n = 26) with varying levels of milk production (1.7–4.8 kg/d) were selected and underwent an IVGTT on 43 ± 0.7 d postpartum (mean ± standard deviation). Data from the IVGTT were fitted in the minimal model to calculate parameters of glucose–insulin dynamics such as insulin sensitivity index and acute insulin response to glucose. Surrogate indices were computed using the average of the IVGTT basal samples. Correlation analysis revealed no relationship between surrogate indices of IR and measures of IR derived from the IVGTT (e.g., insulin sensitivity index, glucose clearance rate, glucose area under the curve). Therefore, our results suggest that surrogate indices of IR are not suitable for assessing the insulin sensitivity of peripheral tissue in early-lactation goats.

Surrogate Indexes of Insulin Resistance in Dairy Goats: Transitional Variation in Subclinical Hyperketonemia.

Background: Dairy goats are highly susceptible to subclinical hyperketonemia (SCHK) during the transition period. This study aimed to compare the variation in metabolic parameters and surrogate indexes of insulin resistance (sIR) between goats with SCHK and clinically healthy (HEAL) goats during the transition period. Methods: Twenty Guanzhong dairy goats were assorted to HEAL (n = 10) and SCHK (n = 10) groups according to the blood β-hydroxybutyrate (BHBA) concentrations. The blood samples were taken from the jugular vein of each goat at −3, −2, −1, 0 (partum), +1, +2, and +3 weeks relative to kidding to analyses GLU and INS. The sIR was calculated from blood metabolic parameters. Results: Compared with the HEAL goats, the insulin concentrations were significantly higher in SCHK goats during the first three weeks postpartum. The QUICKI, revised QUICKI (RQUICKI), and RQUICKIBHBA were significantly lower in goats with SCHK at 1 week postpartum, while the homeostasis model assessment-IR (HOMA-IR) was significantly higher. Conclusion: Goats with SCHK made more efforts through elevated insulin levels at early lactation than HEAL goats, thereby maintaining the normal glucose concentrations.

Circulating HMGB1 Levels Are Associated With Glucose Clamp-Derived Measures of Insulin Resistance in Women With PCOS

Context: High mobility group box 1 (HMGB1) is a nuclear constitutive and highly conserved mammalian protein which shows several important physiologic functions, playing a crucial role in local and systemic inflammation. It also seems to be implicated in the development of metabolic syndrome, whereas some in vitro and animal models and recent preliminary human studies suggested its potential role in polycystic ovary syndrome (PCOS) pathophysiology. In particular, some data suggested a potential role of HMGB1 in follicular maturation block. Moreover, increased blood and follicular fluid HMGB1 concentrations have been reported in PCOS women, showing a direct correlation with surrogate indexes of insulin-resistance (IR) (i.e. HOMA-IR).Objective: The purpose of the present study was to investigate the relationships between serum HMGB1 levels and clinical, endocrine and metabolic parameters of PCOS patients.Design and patients: Sixty women with PCOS, 30 with IR and 30 with normal insulin sensitivity (IS), and 30 healthy controls were included in the study. In these subjects, body fat was quantified by bioelectrical impedance; plasma HMGB1 levels were measured using a specific ELISA method (Tecan, Mannedorf, Switzerland); and serum androgens were measured by liquid chromatography/mass spectrometry and equilibrium dialysis. In PCOS women, IR was measured using the gold standard hyperinsulinemic-euglycemic clamp technique, combined with indirect calorimetry.Results: HMGB1 levels did not differ between PCOS women and healthy controls (4.11 ± 3.22 vs 3.77 ± 2.50 ng/mL, respectively; p=0.61). Moreover, HMGB1 levels did not differ between PCOS phenotype subgroups. However, PCOS IR women showed higher levels of this protein as compared with PCOS IS (5.00 ± 3.53 vs 3.16 ± 2.59 ng/mL, respectively; p=0.017). In women with PCOS, HMGB1 levels were associated with several metabolic parameters, including IR measured by glucose utilization during the clamp (rho -0.37, p=0.005). This correlation was preserved after adjusting for potential confounding parameters, such as age, fat mass and serum free testosterone. HMGB1 levels did not change during glucose-clamp induced acute hyperinsulinemia, either in the whole cohort of patients or in IR and IS subgroups analyzed separately. Both in the whole population under study and in PCOS women, HMGB1 levels did not correlate with anthropometric parameters, hormonal features and ovarian morphology.Conclusions: In women with PCOS, HMGB1 blood levels show an independent association with insulin resistance. However, no associations with other typical features of the syndrome were found. Further research is needed in order to establish whether this protein may play a role in the pathogenesis of PCOS.

One Year of Dapaglifozin Add-On Therapy Ameliorates Surrogate Indexes of Insulin Resistance and Adiposity in Patients with Type 2 Diabetes Mellitus.

IntroductionThis study investigates the effects of dapagliflozin on the visceral adiposity index (VAI), lipid accumulation product (LAP), product of triglycerides and glucose (TyG) and triglycerides to HDL-cholesterol ratio (TG/HDL-C) in patients with type 2 diabetes mellitus (T2D).MethodsIn this real-life study, dapaglifozin was added to metformin alone (group 1, no. 42) or insulin plus metformin (group 2, no. 58) in 100 T2D patients.ResultsIn group 1, after 6 months of dapaglifozin addition, a significant decrease in BMI (p < 0.001), waist circumference (WC) (p < 0.001), systolic blood pressure (SBP) (p = 0.009), diastolic blood pressure (DBP) (p = 0.012), mean fasting blood glucose (FBG), post-breakfast glucose (PBG), post-lunch glucose (PLG) and post-dinner glucose (PDG) (all p < 0.001), HbA1c (p < 0.001), VAI (p = 0.020), LAP (p = 0.028), Tyg (p < 0.001), TG/HDL-C (p = 0.020) and glutamate pyruvate transaminase (GPT) (p < 0.001) was observed compared to baseline. After 12 months a significant decrease in BMI (p < 0.001), WC (p = 0.006), SBP (p = 0.023), DBP (p = 0.005), mean FPG, PBG, PLG and PDG (all p < 0.001), HbA1c (p < 0.001), total cholesterol (p = 0.038), triglycerides (p = 0.026), VAI (p = 0.013), GPT (p < 0.001), LAP index (p = 0.024), Tyg index (p < 0.001) and TG/HDL-c ratio (p = 0.016) was observed compared to baseline. In group 2, after 6 months of dapaglifozin addition, a significant decrease in BMI (p < 0.001), WC (p < 0.001), SBP (p = 0.015), DBP (p = 0.007), mean FPG, PBG, PLG and PDG (all p < 0.001), HbA1c (p < 0.001), VAI (p = 0.040), LAP (p = 0.047), Tyg (p < 0.001), TG/HDL-C (p = 0.048) and GPT (p < 0.001) was observed compared to baseline. By contrast, after 12 months a significant decrease in BMI (p < 0.001), WC (p < 0.001), SBP (p = 0.001), DBP (p = 0.002), mean FPG, PBG, PLG and PDG (all p < 0.001), HbA1c (p < 0.001), GPT (p < 0.001) and Tyg index (p = 0.003) was observed compared to baseline.ConclusionsDapagliflozin treatment significantly reduced surrogate indexes of insulin resistance and adiposity in patients with T2D.

Cut-off values of surrogate indices of insulin resistance as risk predictors for metabolic syndrome

Abstract Background The metabolic syndrome (MS) based on insulin resistance (IR) is a cluster of conditions indicating an increased risk of cardiometabolic diseases. This study aimed to define valid cut-off values for surrogate measures for IR to predicting the risk for the development of MS in the Hungarian general (HG) and Roma (HR) populations. Methods This study included 397 HG and 368 HR subjects aged 20-64 years from a complex health survey in 2018/2019. Four surrogate measures, namely the homeostasis model assessment-IR (HOMA-IR), McAuley index (McA), TG to HDL-cholesterol ratio (TG/HDL-C) and TG and glucose index (TyG) were calculated for all participants. The cut-off values were determined as the value with the highest Youden index (YI) on the basis of results obtained by receiver operating characteristic (ROC) curve analysis for the development of MS on separate and combined populations. Results Since no significant difference could be detected between the results obtained on separate populations, cut-off values defined on the combined one are proposed to use for risk prediction. The area under the ROC curve was 0.753 (95%CI: 0.718-0.787) for HOMA-IR, 0.827 (95%CI: 0.797-0.856) for McA, 0.843 (95%CI: 0.814-0.872) for TG/HDL-C ratio and 0.862 (95%CI: 0.835-0.889) for TyG. The cut-off value was 2.32 (sensitivity (sens.) 70.9%; specificity (spec.) 69.0%; YI: 0.399) for HOMA-IR, 5.989 (sens. 69.7%; spec. 82.7%; YI: 0.524) for McA, 1.274 (sens. 73.4; spec. 84.3%; YI: 0.574) for TG/HDL-C ratio and 4.694 (sens. 77.2%; spec. 84.3%; YI: 0.615) for TyG. Concerning the fact, that the TyG has the best indicative power for predicting IR to the estimation of MS risk in both populations the IR/MS prevalence was defined by using TyG and found to be as high as 42.3% and 40.5% in the HG and HR populations, respectively. Conclusions Based on our results the TyG index could be a useful supplementary method for identifying individuals at risk for MS. Key messages The optimal cut-off points’ four surrogate indices of insulin resistance for the prediction of metabolic syndrome did not differ significantly between the Hungarian general and Roma populations. The triglyceride and glucose index proved to be the strongest predictor for the risk of metabolic syndrome in the Hungarian general and Roma populations.

The triglyceride/glucose ratio is a reliable index of fasting insulin resistance: Observations from hyperinsulinaemic-euglycaemic clamp studies in young, normoglycaemic males from southern India

Background & aimsNon-obese Asians have a high propensity to develop insulin resistance. Therefore, screening such individuals for insulin resistance using simple surrogate indices is important. In this study, we aimed to validate the triglyceride-glucose (Tg/glu) ratio against the M value of hyperinsulinaemic-euglycaemic clamp (HEC) procedure and other surrogate indices of insulin resistance in normoglycaemic Indian males from Southern India. MethodsA cohort of 105 normoglycaemic males (mean BMI: 19.2 ± 2.6 kg/m2) underwent HEC procedure. Surrogate indices of insulin resistance viz. the triglyceride-glucose (Tg/Glu) ratio, the triglyceride-glucose index, the McAuley’s index, the HOMA-IR, the QUICKI, the fasting glucose to insulin ratio (FG-IR), and the fasting C- peptide index were calculated and correlated with the M value. The cut-off value for the Tg/Glu ratio was obtained using the Receiver Operator Characteristics (ROC) with Area under curve (AUC) analysis at 95% confidence interval (CI). The P value < 0.05 was considered statistically significant. ResultsThe Tg/Glu ratio demonstrated significantly higher AUC (0.81), when compared to the Tg × glu index (0.63), 20/fasting C peptide × fasting plasma glucose index (0.55), HOMA-IR (0.47), QUICKI (0.26), FGIR (0.12) and McAuley’s index (0.18). For the Tg/Glu ratio, a cut-off value ≥ 1.19 had high sensitivity (80%) and specificity (79%) values (PPV: 16%; NPV: 98.8%) respectively. ConclusionThe Tg/Glu ratio can be used as a reliable surrogate index to screen for risk of insulin resistance in lean, normoglycaemic males from Southern India.

SAT-624 Predictive Ability of Lipoprotein Insulin Resistance (LPIR) Score in South Asians: A Comparison of Surrogate Indices of Insulin Sensitivity/Resistance

South Asians (SA) are at higher risk for developing insulin resistance (IR) and type 2 diabetes. Consequently, identifying IR in this population is important. Lack of standardization and harmonization of insulin assays limit the clinical use of insulin-based surrogate indexes of insulin resistance. The lipoprotein insulin resistance (LPIR) score, a metabolomic marker, reflects the lipoprotein abnormalities observed in insulin-resistant states. The reliability of the LPIR score to predict IR in South Asians is currently unknown. In this study, we aimed to evaluate the predictive accuracy of LPIR compared to other fasting-based surrogate indices in SA.In a cross-sectional study of 59 non-diabetic SA subjects (age 36 ± 8 years, BMI 26.5 ± 5.2 kg/m2), we used calibration model analysis to assess the ability of the LPIR score and other simple surrogate indices [homeostasis model assessment (HOMA-IR), quantitative insulin sensitivity check index (QUICKI) and Adipose tissue insulin sensitivity (Adipo-SI)] to predict insulin sensitivity derived from the reference frequently sampled intravenous glucose tolerance test (FSIVGTT) and Minimal Model analysis (SiMM). LPIR scores were calculated using six lipoprotein particle concentrations and sizes measured by nuclear magnetic resonance (NMR) spectroscopy. Further, quantitative predictive accuracy and index comparisons were determined by root mean squared error (RMSE) of prediction and leave-one-out cross-validation-type RMSE of prediction (CVPE). Receiver operating characteristic (ROC) curve analysis was performed to determine how well LPIR distinguished insulin resistant individuals, categorized as an SiMM < 3.As determined by calibration model analysis, Adipo-SI, HOMA-IR, and QUICKI showed moderate correlations with for SiMM (Adipo-SI: r = 0.66; HOMA-IR: r = 0.60; QUICKI: r = 0.57, p = <0.0001). No significant differences were noted among CVPE or RMSE from any of the routinely used surrogate indices when compared with LPIR. The ROC area under the curve was 0.76 (95% CI 0.64–0.87) suggesting that LPIR performed well in identifying insulin resistant subjects. The optimal cut-off in IR individuals was LPIR >46 (sensitivity: 75.9 %, specificity: 70.0%). We conclude that NMR-derived LPIR may be an appropriate index to assess insulin resistance in South Asians.

Surrogate indexes of insulin resistance and risk of metabolic syndrome in non-Hispanic White, non-Hispanic Black and Mexican American

AimTo compare the strength of associations between surrogate indexes of insulin resistance (sIR) and risk of metabolic syndrome (MetS) in non-Hispanic White (NHW), non-Hispanic Black (NHB) and Mexican American (MA) adults. MethodsThe 2013–2016 US National Health and Nutrition Examination Survey data (n = 3435) were used for this study. The associations between sIR that includes Triglyceride/HDL cholesterol ratio (TG/HDL-C), triglyceride glucose (TG) index, visceral adiposity index (VAI), lipid accumulation product (LAP), TG-body mass index (TG-BMI), and TG-waist circumference (TG-WC) and risk for MetS were determined using the prevalence odds ratio (OR) from the logistic regression analyses. Pseudo-R-squared tests were used to estimate the proportion of variance in MetS accounted for by each sIR. Akaike Information Criterion and Bayesian Information Criterion from the multinomial logistic regression analysis were used to compare models that included each sIR and its components separately as predictors of MetS. Areas under curves (AUC) from the receiver-operating characteristic (ROC) were used to detect their diagnostic capabilities. ResultsCompared with other sIR, TG-WC (AUC = 0.899; 95% CI: 0.884–0.913 in NHW) and (AUC = 0.893; 95% CI:0.871–0.915 in NHB), and LAP (AUC = 877; 95% CI: 0.861–0.894 in MA) exhibited the highest diagnostic and predictive accuracy for MetS. Compared with other sIR, TG-WC (OR = 22.8; 95% CI:16.6–31.0 in NHW) and (OR = 22.7; 95% CI:13.1–39.3 in NHB), and LAP (OR = 10.6; 95%:6.6–17.0 in MA) were most significantly associated with increased odds of MetS, adjusting for eGFR, age, marital status, CHD, CHF, income, education, physical activity, alcohol use, smoking and use of cholesterol-lowering medication. ConclusionsTG-WC in NHW and NHB, and LAP in MA are more powerful than other proxies of IR in predicting MetS. TG-WC and LAP can serve as adjunctive tools for screening for MetS in NHW, NHB, and MA.

Relationships of surrogate indexes of insulin resistance with insulin sensitivity assessed by euglycemic hyperinsulinemic clamp and subclinical vascular damage

IntroductionInsulin resistance plays a crucial role in the pathogenesis of type 2 diabetes and cardiovascular disease. The triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio, visceral adiposity index (VAI), lipid accumulation...

Fasting triglycerides and glucose index is more suitable for the identification of metabolically unhealthy individuals in the Chinese adult population: A nationwide study.

Aims/IntroductionMetabolic unhealth can be defined by the components of metabolic syndrome, which is closely connected to insulin resistance. We aimed to determine a simple index to identify metabolic unhealth in the Chinese adult population.Materials and MethodsA total of 30,291 individuals were screened from the China National Diabetes and Metabolic Disorders Study carried out from June 2007 to May 2008. Metabolic unhealth was defined using components of metabolic syndrome, except waist circumference. We compared the three surrogate indices of insulin resistance: the product of fasting triglycerides and glucose (TyG), triglycerides divided by high‐density lipoprotein cholesterol and the metabolic score for insulin resistance for the evaluation of metabolic status.ResultsAll indices had high sensitivity and specificity for the identification of metabolic unhealth, especially the TyG index with an area under the curve of 0.863 for men and 0.867 for women. Participants were divided into subgroups for further analysis. The TyG index also showed high diagnostic values, especially for younger individuals and men with normal waist circumference. Sex‐specific cut‐offs for three indices were also used to define metabolic unhealth. The TyG index showed the highest agreement with κ values of 0.603 and 0.605 for men and women between the components of metabolic syndrome and three indices.ConclusionsWe propose that the TyG index, just read in one blood laboratory test report, is simpler and more suitable for the identification of metabolically unhealthy individuals as well as who have high risk of cardiometabolic diseases of the Chinese adult population.

Abstract 2268: Serum insulin and glucose, indices of insulin resistance, and risk of lung cancer

Abstract Background: Although insulin is crucial in human growth and development, it also harbors antiapoptotic properties and acts as a growth factor by stimulating mitosis through the Akt pathway, which could lead to tumor growth and promotion. Insulin has been positively associated with several cancer sites, but no studies to date have examined fasting serum insulin concentrations and risk of lung cancer. Methods: The Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study was a randomized, double-blind intervention trial conducted among 29,133 male smokers in southwest Finland. Participants were randomly assigned to one of four groups in a 2x2 factorial design (α-tocopherol alone, β-carotene alone, both supplements, or placebo). 196 lung cancer cases and 395 subcohort members were sampled from the larger cohort. Fasting serum collected at enrollment (5-12 years prior to diagnosis) was analyzed for insulin using a double-antibody immunochemiluminometric assay, and for glucose using a hexokinase assay. Cox proportional hazards models were used to estimate the hazard ratio (HR) and 95% confidence intervals (CI) of lung cancer risk by quartiles of insulin, glucose, and surrogate indices of insulin resistance (insulin:glucose molar ratio and homeostasis model assessment of insulin resistance [HOMA-IR]). Multivariable models adjusted for age, BMI, family history of lung cancer, and pack-years of smoking. Results: Insulin was positively associated with risk of lung cancer (Q4 vs. Q1 HR: 2.10, 95% CI: 1.12, 3.94). A similar association was seen with HOMA-IR (Q4 vs. Q1 HR: 1.83, 95% CI: 0.99, 3.38). We observed no statistically significant associations with glucose or the insulin:glucose molar ratio (P-trend=0.55 and P-trend = 0.27, respectively). Insulin and HOMA-IR were associated with lung cancer risk regardless of stage, although the findings were stronger for the lower stage cancers (Q4 vs. Q1 insulin, stage I-II HR=2.85, 95% CI: 1.14, 7.15, P-trend=0.01; stage III-IV HR=0.94, 95% CI: 0.93 - 4.06, P-trend=0.23; HOMA-IR stage I-II HR=2.25, 95% CI 0.89-5.69, P-trend=0.02, stage III-IV HR=1.78, 95% CI=0.87 - 3.61, P-trend=0.34). Findings were similar across histologic subtypes of lung cancer. Conclusion: Higher fasting serum insulin and insulin resistance appear to be associated with an increased risk of lung cancer. In addition, elevated insulin concentrations may be more strongly associated with lower stage lung malignancies, suggesting a role for insulin in stimulating the growth of early pulmonary cancers. Citation Format: Ilona Argirion, Stephanie J. Weinstein, Satu Männistö, Demetrius Albanes, Alison M. Mondul. Serum insulin and glucose, indices of insulin resistance, and risk of lung cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 2268. doi:10.1158/1538-7445.AM2017-2268

Comparison of Surrogate Markers as Measures of Uncomplicated Insulin Resistance in Korean Adults.

BackgroundMetabolic syndrome (MS) is known to increase the risk of various cardiometabolic diseases and in-sulin resistance (IR) has known to have central role in the development of MS. Many surrogate indices of IR have been proposed and the detection of MS might be a suitable model for assessing the accuracy of surrogate indices. The aims of our study are to invest the most appropriate index by assessment of the diagnostic capacity of IR among each surrogate index and identifying cut-off values for discriminating uncomplicated MS in Korean adults.MethodsA cross-sectional study was performed, assessing 294 Korean adults, 85 of whom were diagnosed with uncomplicated MS. The sensitivities and specificities of five surrogate IR indices were compared to discriminate MS from healthy subjects; these included fasting serum insulin, homeostasis model assessment–insulin resistance index, quantitative insulin sensitivity check index, McAuley index, and Disse index. Correlations between each index value were assessed using Pearson's and Spearman's correlation methods.ResultsThe McAuley index showed the highest area under the curve (0.85), specificity (86.12%), accuracy (82.31%), positive predictive value (68.13%), and negative predictive value (88.67%) to distinguish MS, with a cut-off point of 5.3 defined. Correlation coefficients of the five indices showed that the McAuley index had the strongest correlation with IR.ConclusionThe McAuley index showed the best accuracy in the detection of MS as a surrogate marker of IR. To establish more effective and accurate standards of measuring IR, comprehensive and multi-scaled studies are required.