Association Between Follicle-Stimulating Hormone Receptor (FSHR) rs6166 and Estrogen Receptor 1 (ESR1) rs2234693 Polymorphisms and Polycystic Ovary Syndrome Risk, Phenotype, and Reproductive Outcomes in an Infertile Portuguese Population.

INTRODUCTION: Polycystic ovary syndrome (PCOS) is a common endocrine disorder often leading to anovulatory infertility. PCOS pathophysiology is still unclear and several potential genetic susceptibility factors have been proposed. The effect of polymorphisms in two genesrelated to follicular recruitment and development, the follicle-stimulating hormone receptor (FSHR) and the estrogen receptor 1 (ESR1), have been studied in different populations with contradictory results. AIMS: To evaluate the influence of FSHR rs6166 (c.2039A>G) and of ESR1 rs2234693 (Pvull c.453-397 T > C) polymorphisms on PCOS risk, phenotype, and response to controlled ovarian stimulation (COS). MATERIALS AND METHODS: Genotyping of the FSHR rs6166 and the ESR1 rs2234693 polymorphisms was performed in PCOS women and a control group undergoing in vitro fertilization (IVF). Demographic, clinical, and biochemical data, genotype frequency, and IVF outcomes were compared between groups. RESULTS: We evaluated 88 PCOS women and 80 controls. There was no significant difference in the genotype distribution of FSHR rs6166 polymorphism between PCOS women and controls (AA 31.8%/AS 48.9%/SS 19.3% in PCOS women vs AA 37.5%/AS 40.0%/SS 22.5% in controls; p = 0.522). The same was true for the ESR1 rs2234693 (CC 24.1%/CT 46.0%/TT 29.9% in PCOS women vs CC 18.8%/CT 48.8%/TT 32.5% in controls; p = 0.697). In PCOS women, we found higher follicle-stimulating hormone (FSH) levels on the third day of the menstrual cycle associated with the SS variant of the FSHR polymorphism (9.2 vs 6.2 ± 1.6 and 5.6 ± 1.6 mUI/mL; p = 0.011). We did not find other associations between the baseline hormonal parameters, antral follicle count, and response measures to COS with FSHR or ESR1 genotypes. We found, however, a need for higher cumulative doses of FSH for COS in patients with the SS variant of the FSHR rs6166 polymorphism (1860.5 ± 627.8 IU for SSvs 1498.1 ± 359.3 for AA and 1425.4 ± 474.8 for SA; p = 0.046 and p = 0.046). CONCLUSION: Our data suggest that in the population, FSHR rs6166and ESR1 rs2234693 polymorphisms do not influence the risk of developing PCOS nor do they influence the patient's phenotype and IVF success. However, the SS variant of the FSHR rs6166 polymorphism may be associated with FSH resistance requiring higher FSH doses for COS.

Hypoglycemia unawareness in type 1 diabetes patients using intermittent continuous glucose monitoring: Identification of risk factors and glycemic patterns.

BACKGROUND: Hypoglycemia unawareness designates failure to detect eminent hypoglycemia. Clarke's questionnaire is one of the most used systems to evaluate this problem. AIMS: To relate Clarke's questionnaire (QQ) results with continuous glucose monitoring data. METHODS: Application of the questionnaire in a sample of type 1 diabetes mellitus (T1DM) patients using intermittent continuous glucose monitoring (iCGM). RESULTS: 111 T1DM patients were evaluated, 56.8% female, mean age 35.0 ± 12.4 years and mean disease duration 18.8 ± 10.5 years. According to CQ, 13.5% had unawareness, 76.6% awareness and 9.9% indeterminate awareness to hypoglycemia. Those with unawareness had longer disease duration (25.1 ± 10.4 vs 18.2 ± 10.3 for awareness and 14.9 ± 9.9 for indeterminate awareness, p = 0.047), more time below range (10.3 ± 4.9% vs 6.3 ± 5.1 and 6.3 ± 4.8; p = 0.009) and higher mean duration of hypoglycemia (131.7 ± 38.6 vs 116.6 ± 49.6 and 131.7 ± 38.6; p = 0.008). In multivariate analysis, mean duration of hypoglycemia was an independent predictor of CQ results. In a receiver operating curve (AUC 0.746; p = 0.004) a mean duration of hypoglycemia ≥106.5 min showed 84.6% sensitivity/64.4% specificity for unawareness. CONCLUSIONS: Our sample had a significative prevalence of hypoglycemia unawareness which increased with longer diabetes duration. iCGM data can be indicative of this problem, with a mean hypoglycemia duration ≥106.5 min being suggestive, albeit unspecific.

Does the Same Hyperlactatemia Cut-Off in the Context of Acute Diseases Hold the Same Meaning in Diabetes Mellitus?

Background Hyperlactatemia is defined by a lactate concentration of >2 mmol/L, and a lactate concentration of above >4 mmol/L is commonly used to define severe hyperlactatemia. It is a common disorder in critically ill patients and is associated with adverse prognosis. Diabetes mellitus(DM) can also be associated with increased lactate levels at baseline. In this study, we aimed to document the development of severe hyperlactatemia in acute situations among patients with and without DM, to analyze potential contributors to lactate elevation and their impact on mortality, and to analyze whether lactate concentrations of >4 mmol/L have equal prognostic significance in patients with and without DM. Methodology A retrospective, cross-sectional study was performed among patients admitted to our internal medicine wards in the context of acute disease with lactate concentrations of ​​≥2 mmol/L. Data were collected regarding age, sex, highest lactate concentrations, cause of hyperlactatemia, DM, and mortality. Statistical analysis was performed using SPSS version 23. Results In total, 151 patients with lactate levels of ≥2 mmol/L were analyzed. The mean age of the patients was 78.2 ± 14.9 years, and 55% of the patients were female. Overall, 55.6% of the patients had DM, as well as higher lactatemia of 6.3 ± 3.4 mmol/L (vs 5.1 ± 3.2 in non-DM patients, p = 0.003), with the majority reaching values of >4 mmol/L (vs 34.8% in non-DM patients). When potential contributors to the development of severe hyperlactatemia (lactate >4 mmol/L) were analyzed in DM patients, metformin consumption concomitantly with factors potentiating its accumulation, sepsis/septic shock, ischemia, and neoplasia were the most frequently identified contributors. In non-DM patients, the three former factors were also the most frequently reported. The 30-day mortality rate was 25.82%, with deceased patients also displaying a higher lactatemia of 6.5 ± 3.2 mmol/L (vs. 5.5 ± 3.3 mmol/L in patients who survived) (p = 0.037). In multivariate analysis, lactate values of >4 mmol/L were an independent predictor of mortality in the entire sample and in the subgroup without DM, but not in DM patients. Conclusions In our sample, patients with DM had higher lactate levels than non-DM patients. Our analysis raises the possibility that the same lactate values may not have equal capacity to assess prognosis in acute situations in patients with and without DM. Large-scale studies are needed to optimize cut-off points for lactatemia in patients with high baseline values, such as DM patients.