Computational methods are significant determinants of the associations and definitions of insulin resistance using the homeostasis model assessment in women of reproductive age.

BACKGROUND: Insulin resistance (IR) plays an important role in the pathogenesis of polycystic ovary syndrome (PCOS), but identification of insulin-resistant individuals is difficult. The homeostasis model assessment (HOMA), a surrogate marker of IR, is available in 2 computational models: HOMA1-IR (formula) and HOMA2-IR (computer program), which differ in incorporated physiological assumptions. This study evaluates the associations of the 2 models as markers of IR, the metabolic syndrome (MS), and PCOS. METHODS: Anthropometric, hormonal, and biochemical parameters were measured in 92 PCOS women and 110 controls. HOMA1 and HOMA2 were used to assess IR. Regression analyses were used to find the associations of the 2 models with different variables, MS, and PCOS. RESULTS: The cutoff levels for definition of IR were HOMA1-IR ≥2.9 and HOMA2-IR ≥1.7. Mean HOMA1-IR (2.79) and HOMA2-IR (1.42) differed substantially. The difference (HOMA1-IR - HOMA2-IR) was significantly correlated with insulin, fasting plasma glucose, triglycerides, HDL cholesterol, waist circumference, leptin, and adiponectin (all P < 0.05). HOMA1-IR and HOMA2-IR were significantly associated with MS (odds ratio 5.7 and 4.2, respectively) and PCOS (odds ratio 3.7 and 3.5, respectively). CONCLUSIONS: HOMA computational methods significantly affect the associations and cutoff values used for definition of IR. The correlations of the difference in the computational methods corroborate differences in captured physiological mechanisms. As precise identification of IR in PCOS patients is of practical importance, practitioners and researchers should be aware of these differences in the HOMA computational methods.

Specific isoforms of leucine-rich alpha2-glycoprotein detected in the proliferative endometrium of women undergoing assisted reproduction are associated with spontaneous pregnancy.

OBJECTIVE: To examine differences in specific protein expression from the surface of the human endometrium with respect to eventual pregnancy in infertile women. DESIGN: Laboratory study. SETTING: University hospital. PATIENT(S): Thirty-one women presenting for investigation into infertility at an assisted reproductive unit. INTERVENTION(S): Endometrial flushings were collected during the proliferative phase of the menstrual cycle and subjected to electrophoretic separation on the basis of isoelectric point and molecular weight. Computerized analysis of the resulting spots was performed, and the proteins were identified using tandem mass spectrometry. MAIN OUTCOME MEASURE(S): The expression of individual isoforms of leucine-rich alpha2-glycoprotein (LRG) was compared in nonpregnant patients (n = 25), those who became pregnant as a result of treatment (n = 3), and those who had treatment-independent pregnancies (n = 3). RESULT(S): A statistically significant difference was found in expression of two LRG isoforms, which were higher in the women who subsequently became pregnant independent of treatment. CONCLUSION(S): Several indirect lines of evidence suggest a role for LRG in implantation/decidualization. [1] LRG is implicated in transforming growth factor beta signal transduction. [2] Similar sequences have been identified in murine uterine tissues. [3] LRG may be involved in the infiltration of decidua by uterine natural killer cells, given that the murine homolog of LRG supports lymphocyte infiltration into secondary lymphoid tissues. [4] Human uterine natural killer cells differentiate into granular forms during early pregnancy, and LRG is known to support neutrophil granulocytic differentiation in humans.