Background Insulin resistance is core cause of metabolic syndrome. Determining insulin resistance is one of the foremost requirements imperative to understanding the pathophysiology of disease. The gold standard “Euglycaemic clamp test” is cumbersome, long and non-feasible in routine clinical setups to diagnose metabolic syndrome. Various continuous and steady state insulin resistance indices are now available in literature. We plan to evaluate commonly utilized steady state insulin resistance indices directly and Homeostasis Model Assessment for Insulin Resistance (HOMAIR) with added triglyceride (HOMA-TG index). Methods The cross-sectional study was carried from Jan-2016 to Dec-2018 at PNS HAFEEZ and department of chemical pathology, AFIP with following objectives: (1) To evaluate steady state insulin resistance markers for diagnosing metabolic syndrome as per IDF defined criteria by ROC curve analysis, (2) to measure Kendal Concordance between various insulin resistance indices and (3) to correlate steady state insulin resistance markers with anthropometric and lipid indices. After several exclusions we selected 224 subjects based upon “non-probability convenience sampling” for inclusion in study. Clinical history, anthropometric measures were calculated and sampling was done for insulin, glucose and other biochemical parameters. Metabolic syndrome was diagnosed as per IDF criteria, while HbA1c was utilized to diagnose diabetes mellitus. Pearson correlation was used to correlate various steady state insulin resistance indices including HOMAIR, HOMA2 index, QUICKI, G/I ratio, HOMA-TG index and serum insulin. AUC was calculated by ROC analysis for all surrogate insulin measures in diagnosis of metabolic syndrome. Results “HOMA-TG index” has shown the highest AUC for diagnosing metabolic syndrome along with higher correlation with lipid markers and anthropometric indices in comparison to other steady-state insulin resistance markers. Furthermore, QUICKI and G/I ratio showed the lowest AUC for detection of metabolic syndrome. Conclusion “HOMA-TG index” has shown highest AUC for metabolic syndrome diagnosis. However, QUICKI and G/I ration showed the lowest AUC for detection of metabolic syndrome. It is hoped that the potential “HOMA-TG index” may provide better diagnostic efficiency for diagnosing metabolic syndrome.

Kisspeptin as a neuropeptide was established initially as regulator GnRH pulse frequency and intensity. Over time it was recognized that the interaction are mediated through a specific receptor GPR54, which has also been found throughout the hypothalamic-pituitary-gonadal (HPG) axis. Further insights into the mechanisms leading to triggering of kisspeptin were identified to be both negative and positive feedbacks from gonadal steroids along with various internal metabolic alterations and environmental triggers in the shape of diet and lifestyle. More so it was identified that these Kisspeptin/GPR54 receptor interaction was also influenced by endocannabinoid (eCB) system, GABA-ergic neuronal outputs (GABA) and other chemical agents. The most influencing neuronal inputs modifying the release of kisspeptin were identified as group of neurons termed “KNDy” in the ARC nuclei. Based upon these discoveries, scientist attempted to evaluate kisspeptin as diagnostic marker for various diseases including precocious puberty, puberty confirmation, hypogonadism, infertility and polycystic ovarian Continuous...