BMC Endocrine Disorders最新文献

Background: Polycystic ovary syndrome (PCOS) is a prevalent endocrine and metabolic disorder characterized by hyperandrogenism, insulin resistance, and reproductive dysfunction. Accumulating evidence indicates that gut microbiota and their metabolites, particularly short-chain fatty acids (SCFAs), contribute to PCOS pathogenesis. However, subtype-specific alterations, especially in Traditional Chinese Medicine (TCM)-defined phlegm-dampness PCOS, remain insufficiently explored.

Objective: This study aimed to comprehensively compare gut microbial composition, SCFA concentrations, and their associations with anthropometric, clinical, and biochemical indicators in women with phlegm-dampness PCOS, non-phlegm-dampness PCOS, and healthy controls.

Methods: In this cross-sectional analysis, 54 women were recruited and stratified into phlegm-dampness PCOS (n = 17), non-phlegm-dampness PCOS (n = 18), and healthy control (n = 19) groups. Anthropometric measurements, reproductive and metabolic indices, and serum hormones were assessed. Fecal SCFAs were quantified via gas chromatography, and gut microbial profiles were characterized using 16 S rRNA gene sequencing. Bioinformatic and statistical analyses included diversity indices, taxonomic abundance, principal component and clustering analyses, and correlation networks linking microbiota, SCFAs, and host phenotypes.

Results: Phlegm-dampness PCOS exhibited significantly reduced α-diversity compared with controls (p < 0.05) and distinct microbial profiles across multiple taxonomic levels. Key alterations included enrichment of Blautia wexlerae and depletion of Faecalibacterium and Alistipes. Fecal butyrate and propionate levels were markedly reduced in phlegm-dampness PCOS versus controls (p < 0.01). Correlation analyses revealed Blautia wexlerae was positively associated with BMI, waist circumference, hirsutism, and acanthosis nigricans, while Alistipes shahii correlated with serum testosterone and HOMA-IR. Distinct correlation networks highlighted microbiota-metabolite-host interactions specific to phlegm-dampness PCOS. Compared with healthy controls, the non-phlegm PCOS group (Group B) exhibited intermediate values for microbial diversity and SCFAs; however, most Group B vs. control differences were not significant after adjustment for BMI and age with FDR correction.

Conclusion: Women with phlegm-dampness PCOS demonstrate more profound gut dysbiosis, SCFA depletion, and distinct microbiota-clinical correlations than non-phlegm-dampness PCOS and healthy controls. These findings underscore the biological relevance of TCM-based subtype stratification and suggest that precision microbiota-targeted interventions may enhance therapeutic outcomes in PCOS.

Clinical trial number: NA.

Objective: Elevated prolactin levels are considered a potential parameter associated with increased cardiovascular risk. The aim of our study is to investigate the possible role of Endocan levels in the cardiovascular risk associated with hyperprolactinemia by comparing patients with hyperprolactinemia to a healthy control group.

Methods: The study included 39 patients with hyperprolactinemia of various etiologies and 39 healthy controls. In both groups, cardiovascular risk-related parameters-including height, body weight, BMI, waist circumference, CRP, and lipid levels-were evaluated and recorded. Endocan levels were measured using the ELISA method.

Results: The groups were comparable in age, sex, height, body weight, BMI, and waist circumference. No significant differences were found between the patient and control groups in terms of height, body weight, BMI, waist circumference, WBC count, fasting glucose, insulin levels, HOMA-IR, HbA1c, lipid profile, CRP, and 25(OH) vitamin D levels. However, serum Endocan levels were significantly higher in the hyperprolactinemic group (p = 0.028). In this group, Endocan levels showed a significant positive correlation with waist circumference, body weight, and BMI, and a negative correlation with WBC count.

Conclusion: One of the key findings of our study is the elevated Endocan levels in patients with mildly increased prolactin levels (45.90 ± 2.72 ng/mL), indicating a higher cardiovascular risk. This may reflect the association between elevated prolactin and endothelial dysfunction. Further prospective studies with larger sample sizes and longer follow-up are needed to better evaluate Endocan levels in patients with hyperprolactinemia.

Clinical trial number: No applicable.

Purpose: Netrin-1 is a urinary protein that may help in the diagnosis of diabetic nephropathy. The objectives of this study were to assess urinary netrin-1 levels in patients with type 2 diabetic nephropathy and to determine its correlation with renal function among them.

Methodology: This cross-sectional analytical study was conducted at a tertiary care teaching hospital in south India for 18 months. Study subjects were divided into four groups: non-diabetics, diabetics with normal to mildly increased albuminuria, moderately increased albuminuria, and severely increased albuminuria. Urinary albumin was quantified by nephelometry for all study subjects. The ELISA technique estimated urinary netrin-1 levels in all groups.

Results: Urinary netrin-1 levels were higher in diabetic subjects with normal to mildly increased and severely increased albuminuria than in the control group. Correlation analysis showed that there was a positive correlation of urinary netrin-1 with urinary albumin-creatinine ratio (UACR) and no correlation with estimated glomerular filtration rate (eGFR). Urinary netrin-1 showed a sensitivity of 88.3% and specificity of 75% at a cut-off value of 889.74 pg/mg creatinine for diagnosing diabetic nephropathy.

Conclusion: Urinary netrin-1 levels were elevated in diabetic subjects with moderately and severely increased albuminuria as compared to non-diabetic subjects. It showed a positive correlation with the urinary albumin-creatinine ratio and no correlation with eGFR in diabetic subjects.

Background: Glycated albumin (GA) is a useful marker for short-term glycemic control, but its levels may be influenced by body composition. Therefore, we aimed to investigate the impact of increasing body mass index (BMI) on GA levels in healthy individuals.

Methods: This cross-sectional study included healthy individuals with normal and elevated BMI. Individuals with diabetes mellitus, pregnancy, acute infection, a history of cardiovascular events, malignancy, chronic liver disease, nephrotic syndrome, thyroid dysfunction, anemia, morbid obesity (BMI ≥ 40 kg/m²), or any other condition known to affect GA levels were excluded. Anthropometric and biochemical measurements were obtained and compared between normal and elevated BMI groups. Statistical analyses were performed using Statistical Package for the Social Sciences (SPSS) version 22.0.

Results: A total of 52 individuals with elevated BMI and 49 with normal BMI were included in the analysis. Individuals with elevated BMI had significantly lower levels of GA (42.8 ± 7.2 vs. 51.3 ± 6.0, p < 0.001), while levels of C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) were markedly higher (0.6 ± 0.4 vs. 0.4 ± 0.2, p < 0.001 and 13.5 ± 12.3 vs. 8.3 ± 7.5, p = 0.002; respectively). BMI showed a moderate inverse association with GA (r=-0.583, p < 0.001). Moreover, BMI was positively associated with CRP (r = 0.366, p < 0.001) and ESR (r = 0.299, p = 0.002). In addition, GA levels exhibited negative correlations with CRP (r=-0.401, p < 0.001) and ESR (r=-0.384, p < 0.001). Multivariate regression analysis confirmed that BMI was independently associated with GA levels (B=-2.727, 95% CI:-5.077 to -0.377, p = 0.024).

Conclusion: Our results suggest a potential inverse association between BMI and GA levels.

Clinical trial number: Not applicable.

Background: The aim of this study was to investigate the association between estimated glucose disposal rate (eGDR) and the risk of future diabetes development in middle-aged and elderly adults, and to construct a diabetes prediction model.

Methods: The present study comprised a total of 8,072 participants, with 6,965 drawn from the China Health and Retirement Longitudinal Study (CHARLS) cohort and 1,107 from the English Longitudinal Study of Aging (ELSA) cohort. The correlation between eGDR and the onset of diabetes was analysed by means of a logistic regression model, and subgroup analyses and restricted cubic spline (RCS) curve analyses were performed to verify the non-linear relationship. A predictive model was constructed based on multivariable variables, and model efficacy was assessed by subject operating characteristic curves (AUC) and calibration curves.

Results: The prevalence of diabetes mellitus was 5.87% in the CHARLS cohort and 9.94% in the ELSA cohort. It was found that eGDR was significantly lower in both cohorts of diabetic patients (P < 0.001). Furthermore, an association was observed between eGDR reduction and an increased risk of developing diabetes. The multivariable-adjusted odds ratios (OR) for Q2-Q4 in the CHARLS cohort were 0.66 (0.51-0.84), 0.36 (0.25-0.51), and 0.31 (0.20-0.47), respectively, using the eGDR quartiles (Q1 as the reference); and for the ELSA cohort, the values were 0.40 (0.23-0.70), 0.30 (0.15-0.62), and 0.06 (0.01-0.28), respectively. RCS analyses revealed no evidence of nonlinear association between eGDR and diabetes, after adjusting for confounders. A column-line graphical model, incorporating variables of heart disease, stroke, BMI, lipids, glucose and eGDR, yielded AUCs of 0.75 (0.72-0.77) and 0.85 (0.82-0.89) in the CHARLS and ELSA cohorts, respectively. Calibration curves demonstrated adequate model fit, while decision curves indicated a substantial net benefit.

Conclusion: Reduced eGDR is an independent risk factor for the development of diabetes mellitus in middle-aged and elderly adults, and is linearly and negatively correlated with the risk of diabetes mellitus.

Background: Diabetes mellitus (DM) is a significant global public health concern, with prediabetes serving as a critical stage between normoglycemia and DM. Without intervention, individuals with prediabetes face an increased risk of developing DM, underscoring the need for effective preventive measures. The Hemoglobin Glycation Index (HGI)-which measures the discrepancy between actual and predicted glycated hemoglobin (HbA1c) levels-has shown promise in predicting the onset of both microvascular and macrovascular complications associated with DM. However, its potential role in assessing the risk of developing DM or prediabetes remains to be fully established. This study aims to investigate the predictive capacity of HGI for both DM and prediabetes.

Method: This retrospective cohort study utilized data from the China Health and Retirement Longitudinal Study (CHARLS), involving participants aged 45 years and older who were assessed in 2011 and followed up in 2015. Univariate and multivariate logistic regression models were employed to analyze the relationship between HGI and the incidence of prediabetes and DM. Dose-response analyses were conducted using restricted cubic splines, and subgroup analyses were performed based on various demographic and health-related factors.

Results: Among 3,963 participants, 187 individuals (4.72%) developed prediabetes within four years, and 107 individuals (2.70%) developed DM. HGI was independently associated with an increased risk of developing both DM and prediabetes, with adjusted odds ratios of 1.61 (95% confidence interval [CI]: 1.19-2.16, p = 0.001) and 2.03 (95% CI: 1.40-2.94, p < 0.001), respectively. A linear relationship was observed between HGI and both DM and prediabetes. An interaction effect was identified between age and HGI; specifically, the association between higher HGI and incident DM was more pronounced in individuals aged 45 to 60 years. Among this age group, the OR was 3.93 (95% CI: 2.19-7.05, p < 0.001).

Conclusion: HGI is identified as an independent risk factor for both DM and prediabetes, demonstrating its utility in predicting the likelihood of their development, particularly within the population aged 45 to 60. These findings highlight the potential of HGI as a valuable biomarker for the early identification of DM risk, thereby facilitating the formulation of targeted intervention strategies.

Trial registration: Not applicable.