Genital Microbiota and Outcome of Assisted Reproductive Treatment-A Systematic Review

Clinical Applicability of Microbiota Sampling in a Subfertile Population: Urine versus Vagina

The urogenital microbiota is increasingly gaining recognition as a significant contributor to reproductive health. Recent studies suggest that microbiota can serve as predictors for fertility treatment outcomes. Our objective was to investigate the degree of similarity in microbial composition between patient-collected urine and vaginal samples in a subfertile population. We enrolled women of reproductive age (20-44 years) diagnosed with subfertility and requiring in vitro fertilization (IVF) or IVF with intracytoplasmic sperm injection (IVF-ICSI) treatment. They self-collected both mid-stream urine samples and vaginal swabs before commencing the IVF or IVF-ICSI procedure. All samples were analysed using the intergenic spacer profiling (IS-pro) technique, a rapid clinical microbiota analysis tool. The main outcome measures were the degree of similarity of microbial composition between the two different, but simultaneously collected, samples. Our findings revealed a high correlation (R squared of 0.78) in microbiota profiles between paired urine and vaginal samples from individual patients. Nevertheless, the urinary microbiota profiles contained fewer species compared to the vaginal microbiota, resulting in minor but distinguishable differences. Furthermore, different subfertility diagnoses appeared to be associated with differences in microbial profiles. A noteworthy observation was the exclusive presence of Escherichia coli (E. coli) in both samples of women diagnosed with male factor subfertility. In conclusion, since urinary microbiota profiles seem to represent a diluted version of the vaginal microbiota, vaginal microbiome sampling to predict fertility treatment outcome seems preferable. To enhance the success of fertility treatments, further research is needed to gain deeper insights into a putative causal role of microbiota in the mechanisms of subfertility.

Pilot Study on Next-Generation Sequencing Analysis of Vaginal Microbiota in Clinically Infertile Patients Treated with Probiotics

Background: In this investigation, we aimed to understand the influence of oral probiotic supplementation on the vaginal microbiota of women preparing for assisted reproductive technology (ART) procedures. Given the importance of a healthy microbiome for reproductive success, this study sought to explore how probiotics might alter the bacterial composition in the vaginal environment. Methods: We recruited a cohort of 30 women, averaging 37 years of age (ranging from 31 to 43 years), who were scheduled to undergo ART. Using 16S ribosomal RNA (rRNA) sequencing, we meticulously analyzed the vaginal microbiota composition before and after the administration of oral probiotic supplements. Results: Our analysis identified 17 distinct microorganisms, including 8 species of Lactobacillus. Following probiotic supplementation, we observed subtle yet notable changes in the vaginal microbiota of some participants. Specifically, there was a decrease in Gardnerella abundance by approximately 20%, and increases in Lactobacillus and Bifidobacterium by 10% and 15%, respectively. Additionally, we noted a significant reduction in the Firmicutes/Bacteroidetes (F/B) ratio in the probiotic group, indicating potential shifts in the overall bacterial composition. Conclusions: These preliminary findings suggest that oral probiotic supplementation can induce significant changes in the vaginal microbiota of middle-aged women undergoing ART, potentially improving their overall bacterial profile. Future studies should consider a larger sample size and a narrower age range to validate these results. Investigating factors related to female hormone production could also provide deeper insights. Understanding the effects of probiotics on the vaginal microbiota in patients with ovarian aging may lead to personalized interventions and better reproductive outcomes.

Obesity, Dietary Patterns, and Hormonal Balance Modulation: Gender-Specific Impacts

Understanding the intricate relationship between nutrition, hormonal balance, and gender-specific factors is crucial for developing targeted interventions to mitigate obesity-related endocrine disruptions and improve metabolic health. This narrative review examines the impact of various dietary patterns on hormonal regulation in both men and women, focusing on their effects on hormonal balance and metabolic health in the context of obesity. Calorie restriction, the Western diet, high-fat diets, low-CHO diets, plant-based diets, and the Mediterranean diet are analyzed in relation to their influence on obesity-related endocrine disruptions and metabolic health. Future research directions include investigating the specific mechanisms underlying dietary influences on hormonal regulation, addressing the gender-specific metabolic differences and body fat distribution, and exploring the dietary needs of individuals undergoing gender transition. Personalized dietary interventions tailored to individual metabolic and hormonal profiles are essential for optimizing health outcomes across the gender spectrum. By integrating gender-specific considerations into dietary recommendations, healthcare professionals can better support individuals in achieving optimal metabolic health and hormonal balance.

Molecular Basis of Müllerian Agenesis Causing Congenital Uterine Factor Infertility-A Systematic Review

Infertility affects around 1 in 5 couples in the world. Congenital absence of the uterus results in absolute infertility in females. Müllerian agenesis is the nondevelopment of the uterus. Mayer-Rokitansky-Küster-Hauser (MRKH) syndrome is a condition of uterovaginal agenesis in the presence of normal ovaries and the 46 XX Karyotype. With advancements in reproductive techniques, women with MA having biological offspring is possible. The exact etiology of MA is unknown, although several genes and mechanisms affect the development of Müllerian ducts. Through this systematic review of the available literature, we searched for the genetic basis of MA. The aims included identification of the genes, chromosomal locations, changes responsible for MA, and fertility options, in order to offer proper management and counseling to these women with MA. A total of 85 studies were identified through searches. Most of the studies identified multiple genes at various locations, although the commonest involved chromosomes 1, 17, and 22. There is also conflicting evidence of the involvement of various candidate genes in the studies. The etiology of MA seems to be multifactorial and complex, involving multiple genes and mechanisms including various mutations and mosaicism.

Characterization of vaginal Lactobacillus species as a predictor of fertility among Iranian women with unexplained recurrent miscarriage and fertile women without miscarriage history using machine learning modeling

BACKGROUND

Lactobacillus spp. are the predominant bacteria of the vaginal tract, the alteration of which has been previously linked to miscarriage. Here, we investigated differences between selected vaginal Lactobacillus species of women with a history of recurrent miscarriages and fertile women without a history of miscarriage in Iran.

METHODS AND RESULTS

Vaginal swabs were taken from 29 fertile and 24 infertile women and quantitative real-time PCR (qPCR) assay was used to determine a selection of vaginal Lactobacillus species in both groups. The logistic regression (LR) model, Naive Bayes (NB) model, support vector machine model (SVM), and neural network model (NN) were developed to predict disease outcome by selected variables. LR analysis was used to construct a nomogram indicating predictions of the risk of miscarriage. The most abundant species among the patients were L. rhamnosus, L. ruminis, and L. acidophilus, while L. gasseri, L. vaginalis, L. fermentum, and L. iners were more abundant in healthy subjects. The distribution of L. ruminis, L. iners, and L. rhamnosus was higher in patients, while L. acidophilus, L. gasseri, and L. fermentum were highly distributed among healthy subjects. Higher AUC in predicting the disease outcome was observed for L. gasseri, L. rhamnosus, L. fermentum, and L. plantarum.

CONCLUSION

Our findings provide experimental evidence of vaginal Lactobacillus imbalance in infertile women and a suitable predictor for miscarriage based on the AUC algorithms. Further studies with larger sample size and using high-throughput technologies are needed to boost our understanding of the role of lactobacilli in miscarriage.