Abstract 89: Comparison of novel marker of insulin resistance with homeostasis model assessment of insulin resistance and its correlation in metabolic syndrome in south Indian population

Background: The clustering of risk factors of cardiovascular disease (CVD) in individuals hasbeen defined as Metabolic Syndrome (MetS) and helps us to identify populations at risk for future CVD. The prevalence of MetS in Indian population has been shown to be one in three persons, which may be higher if we consider urban populations alone. The major forerunner of all the components of MetS is Insulin resistance, which is measured by a hyperinsulinemic euglycemic clamp. However, this method is cumbersome and an easier, albeit less accurate method of measurement is Homeostasis Model Assessment of Insulin Resistance (HOMA-IR). HOMA-IR, however, requires the measurement of Plasma Insulin levels, which may be inaccurate due to poor standardization and is also not widely available. Thus, we attempted to study the performance of lipid based biochemical markers of insulin resistance for the diagnosis of MetS. In this study, we analyzed three lipid based indices, Triglyceride Glucose index (TyG index), Triglyceride: High Density Lipoprotein (TG:HDL) ratio and Lipid Accumulation Product (LAP). There exists a lack of Indian data on these surrogate Indian insulin resistance markers. Aim of the Study: To compare the efficacy of novel biomarkers of Insulin resistance with HOMA-IR in the diagnosis of MetS in South Indian population. To estimate a population specific cutoff for these biomarkers for our population. Methods: This was a cross sectional study and included apparently healthy population presenting to our hospital for routine Master Health Checkup medical assessment and apparently healthy population residing in Kallindhiri, a village near Madurai. The height, weight, waist circumference, hip circumference and blood pressure were measured for all the patients. A fasting serum sample was collected for the measurement of fasting lipid profile, fasting plasma glucose and fasting serum insulin levels. Based on the data collected, Body Mass Index (BMI), Waist hip ratio, Waist height ratio, HOMA-IR, TyG index, TG:HDL ratio and LAP were calculated. The diagnostic efficacy of these indices was compared against the presence of MetS based on the NCEP ATP III criteria. Receiver Operating Characteristic Curve was performed to discriminatedecision levels (cut-offs) of serum markers in early diagnosis of MetS. The results were considered significant with p value less than 0.05. Results: We included a total of 192 patients in our study, consisting of 36% (n = 70) males and 63% (n = 122) females. All the baseline characteristics except height, weight and HDL cholesterol were comparable between the male and female groups. The calculated value of HOMA-IR, TyG index, TG:HDL ratio and LAP showed an increasing trend with increasing levels of BMI. The mean value of HOMA IR in patients without MetS was 0.99 +/- 0.781, whereas in the patients with MetS was 2.32+/-1.27 (p value-<0.001). The mean value of TyG index in patients without MetS was 4.51+/-0.18, whereas the mean value in patients with MetS was 4.83 +/- 0.203 (p value-<0.001). The mean value of TG:HDL ratio in female patients without MetS was 2.01 +/- 0.522, whereas the mean value in patients with MetS was 4.69 +/- 2.62 (p value-<0.001). The mean value of TG:HDL ratio in male patients without MetS was 2.11+/- 0.59, whereas the mean value in patients with MetS was 5.06 +/- 2.31 (p value-<0.001). The mean value of Lipid Accumulation Product in male patients without MetS was 24.30+/- 21.24, whereas the mean value in patients with MetS was 59.34 +/- 22.72 (p value-<0.001). The mean value of Lipid accumulation Product ratio in female patients without MetS was 27.34+/- 15.69, whereas the mean value in patients with MetS was 63.78 +/- 20.27 (p value-<0.001). Based on the Receiver Operating characteristics (ROC) curve plotted for the data, a population specific cutoff for these indices was computed. The Area Under Curve (AUC) was highest for LAP (0.917). The AUC for TG: HDL ratio was 0.886, TyG index was 0.885 and HOMA-IR was 0.829. Based on the ROC curves our proposed cutoff for South Indian population for HOMA-IR was 1.23, with a sensitivity of 78.9% and specificity of 80%. The cutoff for TyG index in our population was 4.65, with sensitivity of 80.7% and specificity of 81%. The population specific cutoff for TG: HDL ratio computed by us was 3.44 in males and 2.6 in females. The male specific cutoff exhibited a sensitivity of 79.2% and specificity of 78% and the female specific cutoff showed a sensitivity of 81.8% and specificity of 82%. %. The population specific cutoff for LAP computed by us was 38.8 in males and 44.2 in females. The male specific cutoff exhibited a sensitivity of 83.3% and specificity of 85% and the female specific cutoff showed a sensitivity of 84.8% and specificity of 85%. Conclusion: The cutoffs for the novel indices of insulin resistance which have been previously studied in Caucasian populations cannot be applied to Indian populations due to distinct ethnic characteristics. The diagnostic accuracy of these novel biomarkers of Insulin Resistance are better than the biochemical gold standard of HOMA-IR based on the ROC curves. In our study, we found the ideal cutoff for HOMA-IR in our population to be 1.23. We propose a cutoff of 4.65 for TyG index, 3.44 for TG:HDL ratio in males and 2.6 in females, and a LAP cutoff of 38.8 in males and 44.2 in females for the early diagnosis of MetS, and we advocate to bring these indices for screening in routine clinical settings.