Hyperandrogenemia is Common in Asymptomatic Women and is Associated with Increased Metabolic Risk

Mechanisms of probiotic modulation of ovarian sex hormone production and metabolism: a review

Sex hormones play a pivotal role in the growth and development of the skeletal, neurological, and reproductive systems. In women, the dysregulation of sex hormones can result in various health complications such as acne, hirsutism, and irregular menstruation. One of the most prevalent diseases associated with excess androgens is polycystic ovary syndrome with a hyperandrogenic phenotype. Probiotics have shown the potential to enhance the secretion of ovarian sex hormones. However, the underlying mechanism of action remains unclear. Furthermore, comprehensive reviews detailing how probiotics modulate ovarian sex hormones are scarce. This review seeks to shed light on the potential mechanisms through which probiotics influence the production of ovarian sex hormones. The role of probiotics across various biological axes, including the gut-ovarian, gut-brain-ovarian, gut-liver-ovarian, gut-pancreas-ovarian, and gut-fat-ovarian axes, with a focus on the direct impact of probiotics on the ovaries via the gut and their effects on brain gonadotropins is discussed. It is also proposed herein that probiotics can significantly influence the onset, progression, and complications of ovarian sex hormone abnormalities. In addition, this review provides a theoretical basis for the therapeutic application of probiotics in managing sex hormone-related health conditions.

Association of size for gestational age and dehydroepiandrosterone sulfate with cardiometabolic risk in central precocious puberty girls

Objective

The aim of this study was to assess whether size for gestational age and dehydroepiandrosterone sulfate (DHEAS) are associated with cardiometabolic risk in central precocious puberty (CPP) girls.

Methods

The retrospective study included 443 patients with newly diagnosed CPP. Subjects were categorized by birth weight for gestational age (appropriate [AGA], small [SGA], and large [LGA] for gestational age) and serum DHEAS concentration (high [≥75th percentile] and normal [<75th percentile] DHEAS). Cardiometabolic parameters were examined. Composite cardiometabolic risk (CMR) score was calculated based on BMI, blood pressure, glucose, insulin, triglyceride, and HDL cholesterol. Non-obesity CMR score was computed, omitting the value from BMI. Logistic regression models, general linear models, and partial correlation analyses were used to evaluate associations. Propensity score matching was performed for sensitivity analyses.

Results

Overall, 309 patients (69.8%) were born AGA, 80 (18.1%) were born SGA, and 54 (12.2%) were born LGA. Compared with AGA counterparts, CPP girls born SGA were more prone to have elevated HbA1c (adjusted OR = 4.54; 95% CI, 1.43-14.42) and low HDL cholesterol (adjusted OR = 2.33; 95% CI, 1.18-4.61). In contrast, being born LGA was not associated with increased risk for any glucose or lipid derangements. Despite the fact that elevated CMR score was more common among individuals born LGA than AGA (adjusted OR = 1.84; 95% CI, 1.07-4.35), no significant difference was found on non-obesity CMR score (adjusted OR = 0.75; 95% CI, 0.30-1.88). When controlling for age, birth weight SDS, and current BMI-SDS, individuals with high DHEAS exhibited higher HDL cholesterol and apolipoprotein A-1 concentrations and lower triglyceride level and non-obesity CMR score. Furthermore, DHEAS correlated positively with HDL cholesterol and apolipoprotein A-1 and negatively with triglyceride, prominently in girls born SGA, after adjustments for the three abovementioned confounders. Sensitivity analyses corroborated the findings.

Conclusion

Among CPP girls, those born SGA were more likely to possess cardiometabolic risk factors compared to their AGA peers. The difference we observed in cardiometabolic risk between individuals born LGA and AGA was driven by BMI. High DHEAS was associated with favorable lipid profile in CPP girls, even in subjects born SGA.

Non-PCOS Hyperandrogenic Disorders in Adolescents

Hyperandrogenism-clinical features resulting from increased androgen production and/or action-is not uncommon in peripubertal girls. Hyperandrogenism affects 3 to 20% of adolescent girls and often is associated with hyperandrogenemia. In prepubertal girls, the most common etiologies of androgen excess are premature adrenarche (60%) and congenital adrenal hyperplasia (CAH; 4%). In pubertal girls, polycystic ovary syndrome (PCOS; 20-40%) and CAH (14%) are the most common diagnoses related to androgen excess. Androgen-secreting ovarian or adrenal tumors are rare (0.2%). Early pubic hair, acne, and/or hirsutism are the most common clinical manifestations, but signs of overt virilization in adolescent girls-rapid progression of pubic hair or hirsutism, clitoromegaly, voice deepening, severe cystic acne, growth acceleration, increased muscle mass, and bone age advancement past height age-should prompt detailed evaluation. This article addresses the clinical manifestations of and management considerations for non-PCOS-related hyperandrogenism in adolescent girls. We propose an algorithm to aid diagnostic evaluation of androgen excess in this specific patient population.

Early identification of metabolic syndrome risk: A review of reviews and proposal for defining pre-metabolic syndrome status

AIMS

a) To analyze the relationship of known and emerging biomarkers/indicators for early risk identification of cardiometabolic health risk; b) to identify early risk markers to be used in both clinical and nonclinical settings; and c) to propose a definition of early risk identification in terms of pre-metabolic syndrome (PreMetSyn).

DATA SYNTHESIS

Pubmed/Medline, Web of Science, Embase, and Cochrane were searched for Systematic Reviews and Meta-analysis. Selected studies were evaluated, and relevant data were extracted and synthesized.

CONCLUSIONS

Serum uric acid is a good predictive biomarker of metabolic syndrome (MetSyn) and has been associated with non-alcoholic liver fat disease (NAFLD) and type 2 diabetes. NAFLD emerges as an early risk indicator of PreMetSyn by itself. Muscle strength should also be included as an early risk marker of cardiometabolic health. High serum triglycerides and waist circumference confirm their predictive value regarding MetSyn. Indicators related to an inflammatory/pro-inflammatory status usually linked to MetSyn showed limited evidence as robust biomarkers for PreMetSyn. Authors suggest defining PreMetSyn related to cardiometabolic risk. It is also necessary to determine how close people are to the cut-off point of MetSyn components, including emerging indicators proposed by our review. Some biomarkers could be used as indicators of PreMetSyn, before any of the MetSyn components appear, allowing early health interventions to prevent its development. Defining a PreMetSyn status might consider both emerging indicators and those variables already included in the definition of MetSyn. New indicators should be considered to create a new risk score specifically meant for PreMetSyn.