Menopausal Changes in the Microbiome-A Review Focused on the Genitourinary Microbiome

Advanced drug delivery technologies for postmenopausal effects

Postmenopause is the 12-month absence of menstrual periods, characterized by decreased estrogen and progesterone levels, leading to physical and psychological alterations such as hot flashes, mood swings, sleep disruptions, and skin changes. Present postmenopausal treatments include hormone replacement therapy, non-hormonal drugs, lifestyle modifications, vaginal estrogen therapy, bone health treatments, and alternative therapies. Advanced drug delivery systems (ADDSs) are essential in managing postmenopausal effects (PMEs), offering targeted and controlled delivery to alleviate symptoms and improve overall health. This review emphasizes such ADDSs for addressing PMEs. Emerging trends such as artificial ovaries are also reviewed. Additionally, the prospects of technologies such as additive manufacturing (3D and 4D printing) and artificial intelligence in further tailoring therapeutic strategies against PMEs are provided.

Evaluation of the vaginal and urinary microbiota of healthy cycling bitches

BACKGROUND

While the urogenital microbiota has recently been characterized in healthy male and female dogs, the influence of sex hormones on the urogenital microbiome of bitches is still unknown. A deeper understanding of the cyclic changes in urinary and vaginal microbiota would allow us to compare the bacterial populations in healthy dogs and assess the impact of the microbiome on various urogenital diseases. Therefore, the aim of this study was to characterize and compare the urogenital microbiota during different phases of the estrous cycle in healthy female dogs. DNA extraction, 16 S rDNA library preparation, sequencing and informatic analysis were performed to determine the vaginal and urinary microbiota in 10 healthy beagle dogs at each phase of the estrous cycle.

RESULTS

There were no significant differences in alpha and beta diversity of the urinary microbiota across the different cycle phases. Similarly, alpha diversity, richness and evenness of vaginal bacterial populations were not significantly different across the cycle phases. However, there were significant differences in vaginal beta diversity between the different cycle phases, except for between anestrus and diestrus.

CONCLUSION

This study strongly suggests that estrogen influences the abundance of the vaginal microbiota in healthy female dogs, but does not appear to affect the urinary microbiome. Furthermore, our data facilitate a deeper understanding of the native urinary and vaginal microbiota in healthy female dogs.

Korean urobiome platform (KUROM) study for acute uncomplicated sporadic versus recurrent cystitis in women: Clinical significance

PURPOSE

To investigate urine microbiome differences among healthy women, women with recurrent uncomplicated cystitis (rUC), and those with sporadic/single uncomplicated cystitis (sUC) to challenge traditional beliefs about origins of these infections.

MATERIALS AND METHODS

Patients who underwent both conventional urine culture and next-generation sequencing (NGS) of urine were retrospectively reviewed. Symptom-free women with normal urinalysis results as a control group were also studied. Samples were collected via transurethral catheterization.

RESULTS

In the control group, urine microbiome was detected on NGS in 83.3%, with Lactobacillus and Prevotella being the most abundant genera. The sensitivity of urine NGS was significantly higher than that of conventional urine culture in both the sUC group (91.2% vs. 32.4%) and the rUC group (82.4% vs. 16.4%). In urine NGS results, Enterobacterales, Prevotella, and Escherichia/Shigella were additionally found in the sUC group, while the recurrent urinary tract infection (rUTI)/rUC group exhibited the presence of Lactobacillus, Prevotella, Enterobacterales, Escherichia/Shigella, and Propionibacterium. Moreover, distinct patterns of urine NGS were observed based on menopausal status and ingestion of antibiotics or probiotics prior to NGS test sampling.

CONCLUSIONS

Urine microbiomes in control, sUC, and rUTI/rUC groups exhibited distinct characteristics. Notably, sUC and rUC might represent entirely separate pathological processes, given their distinct urine microbiomes. Consequently, the use of urine NGS might be essential to enhancing sensitivity compared to conventional urine culture in both sUC and rUTI/rUC groups.

Association between vaginal microbiota and vaginal inflammatory immune markers in postmenopausal women

OBJECTIVE

In premenopausal individuals, vaginal microbiota diversity and lack of Lactobacillus dominance are associated with greater mucosal inflammation, which is linked to a higher risk of cervical dysplasia and infections. It is not known if the association between the vaginal microbiota and inflammation is present after menopause, when the vaginal microbiota is generally higher-diversity and fewer people have Lactobacillus dominance.

METHODS

This is a post hoc analysis of a subset of postmenopausal individuals enrolled in a randomized trial for treatment of moderate-severe vulvovaginal discomfort that compared vaginal moisturizer, estradiol, or placebo. Vaginal fluid samples from 0, 4, and 12 weeks were characterized using 16S rRNA gene sequencing (microbiota) and MesoScale Discovery (vaginal fluid immune markers: IL-1b, IL-1a, IL-2, IL-6, IL-18, IL-10, IL-9, IL-13, IL-8, IP10, MIP1a, MIP1b, MIP3a). Global associations between cytokines and microbiota (assessed by relative abundance of individual taxa and Shannon index for alpha, or community, diversity) were explored, adjusting for treatment arm, using linear mixed models, principal component analysis, and Generalized Linear Mixed Model + Microbiome Regression-based Kernel Association Test (GLMM-MiRKAT).

RESULTS

A total of 119 individuals with mean age of 61 years were included. At baseline, 29.5% of participants had a Lactobacillus -dominant vaginal microbiota. Across all timepoints, alpha diversity (Shannon index, P = 0.003) was highly associated with immune markers. Individual markers that were associated with Lactobacillus dominance were similar to those observed in premenopausal people: IL-10, IL-1b, IL-6, IL-8 (false discovery rate [FDR] < 0.01), IL-13 (FDR = 0.02), and IL-2 (FDR = 0.09). Over 12 weeks, change in alpha diversity was associated with change in cytokine concentration (Shannon, P = 0.018), with decreased proinflammatory cytokine concentrations observed with decreasing alpha diversity.

CONCLUSIONS

In this cohort of postmenopausal individuals, Lactobacillus dominance and lower alpha diversity were associated with lower concentrations of inflammatory immune markers, as has been reported in premenopausal people. This suggests that after menopause lactobacilli continue to have beneficial effects on vaginal immune homeostasis, despite lower prevalence.

Longitudinal profiles of the vaginal microbiota of pre-, peri-, and postmenopausal women: preliminary insights from a secondary data analysis

OBJECTIVE

Menopause is often accompanied by lowered Lactobacillus spp. relative abundance and increased abundance of diverse anaerobic/aerobic bacteria in the vaginal microbiota due in part to declines in estrogen. These microbiota are associated with urogenital symptoms and infections. In premenopause, vaginal microbiota can fluctuate rapidly, particularly with menstrual cycles and sexual activity; however, the longitudinal dynamics of vaginal microbiota are understudied in peri- and postmenopause. We described vaginal community stability across reproductive stages.

METHODS

Pre- (n = 83), peri- (n = 8), and postmenopausal (n = 11) participants provided twice-weekly mid-vaginal samples (total, 1,556; average, 15 per participant) over 8 weeks in an observational study. Composition of the vaginal microbiota was characterized by 16S rRNA gene amplicon sequencing, and a community state type (CST) was assigned to each sample. Clustering of longitudinal CST profiles, CST transition rates, duration of low-Lactobacillus/high bacterial diversity CSTs, and other metrics of bacterial community dynamics were assessed across reproductive stages.

RESULTS

The proportion of participants with longitudinal CST profiles characterized by low-Lactobacillus CSTs was similar among pre- (38.6%), peri- (37.5%), and postmenopausal (36.4%) participants (P = 0.69). CST transition rates between consecutive samples were 21.1%, 16.7%, and 14.6% for pre-, peri-, and postmenopausal participants, respectively (P = 0.49). Low-Lactobacillus CST tended to persist for at least 4 weeks, irrespective of reproductive stage.

CONCLUSIONS

Findings from this small yet frequently sampled cohort revealed vaginal bacterial fluctuations over 8 weeks that were similar across reproductive stages. Larger and longer-term studies based on these preliminary data could provide insights into the influence of microbiota dynamics on urogenital outcomes during menopause.

Human Papillomavirus Carcinogenicity and the Need of New Perspectives: Thoughts from a Retrospective Analysis on Human Papillomavirus Outcomes Conducted at the Hospital University of Bari, Apulia, Italy, between 2011 and 2022

BACKGROUND

The current manuscript's aim was to determine the human papillomavirus (HPV) genotype-specific prevalence and distribution among individuals, males, and females, of different ages in the region of Apulia, Italy, highlighting the possible variables involved in the carcinogenicity mechanism. In addition, we proposed two hypothetical models of HPV's molecular dynamics, intending to clarify the impact of prevention and therapeutic strategies, explicitly modeled by recent survey data.

METHODS

We presented clinical data from 9647 participants tested for either high-risk (HR) or low-risk (LR) HPV at the affiliated Bari Policlinic University Hospital of Bari from 2011 to 2022. HPV DNA detection was performed using nested-polymerase chain reaction (PCR) and multiplex real-time PCR assay. Statistical analysis showed significant associations for all genders and ages and both HR- and LR-HPV types. A major number of significant pairwise associations were detected for the higher-risk types and females and lower-risk types and males.

RESULTS

The overall prevalence of HPV was 50.5% (n-4.869) vs. 49.5% (n-4.778) of the study population, of which 74.4% (n-3621) were found to be HPV high-risk (HR-HPV) genotypes and 57.7% (n-2.807) low-risk HPV (LR-HPV) genotypes, of which males were 58% and females 49%; the three most prevalent HR-HPV genotypes were HPV 53 (n707-15%), 16 (n704-14%), and 31 (n589-12%), and for LR-HPV, they were 42 (19%), 6 (16%), and 54 (13%); 56% of patients screened for HPV were ≤ 30 years old, 53% were between 31 and 40 years old, 46% were 41-50 and 51-60 years old, and finally, 44% of subjects were >60 years old.

CONCLUSIONS

Our study provided comprehensive epidemiological data on HPV prevalence and genotype distribution among 9647 participants, which could serve as a significant reference for clinical practice, and it implied the necessity for more effective screening methods for HPV carcinogenesis covering the use of more specific molecular investigations. Although this is a predominantly descriptive and epidemiological study, the data obtained offer not only a fairly unique trend compared to other studies of different realities and latitudes but also lead us to focus on the HPV infection within two groups of young people and adults and hypothesize the possible involvement of dysbiosis, stem cells, and the retrotransposition mechanism.

Approach to the diagnosis and management of dysbiosis

All microorganisms like bacteria, viruses and fungi that reside within a host environment are considered a microbiome. The number of bacteria almost equal that of human cells, however, the genome of these bacteria may be almost 100 times larger than the human genome. Every aspect of the physiology and health can be influenced by the microbiome living in various parts of our body. Any imbalance in the microbiome composition or function is seen as dysbiosis. Different types of dysbiosis are seen and the corresponding symptoms depend on the site of microbial imbalance. The contribution of the intestinal and extra-intestinal microbiota to influence systemic activities is through interplay between different axes. Whole body dysbiosis is a complex process involving gut microbiome and non-gut related microbiome. It is still at the stage of infancy and has not yet been fully understood. Dysbiosis can be influenced by genetic factors, lifestyle habits, diet including ultra-processed foods and food additives, as well as medications. Dysbiosis has been associated with many systemic diseases and cannot be diagnosed through standard blood tests or investigations. Microbiota derived metabolites can be analyzed and can be useful in the management of dysbiosis. Whole body dysbiosis can be addressed by altering lifestyle factors, proper diet and microbial modulation. The effect of these interventions in humans depends on the beneficial microbiome alteration mostly based on animal studies with evolving evidence from human studies. There is tremendous potential for the human microbiome in the diagnosis, treatment, and prognosis of diseases, as well as, for the monitoring of health and disease in humans. Whole body system-based approach to the diagnosis of dysbiosis is better than a pure taxonomic approach. Whole body dysbiosis could be a new therapeutic target in the management of various health conditions.

Menopause and facial skin microbiomes: a pilot study revealing novel insights into their relationship

Introduction: The human skin microbial composition is affected by age. Previous studies reported skin microbiome diversity shifts between elderly and significantly younger subjects. Some studies implied that menopausal status, which is inherently linked to age, could be associated with changes in skin microbial compositions. Nevertheless, the influence of menopausal status on skin microbiome profiles while minimizing the impact of aging-associated changes in skin parameters still needs further clarification. Methods: We performed an observational study on healthy Caucasian female volunteers, which were grouped according to their pre- or postmenopausal status. Bacterial community structures on facial skin were analyzed using 16S rRNA gene sequencing. Cutometer® measurements were performed to evaluate aging-associated changes in facial skin biophysical properties. Results: The relative abundance of the lipophilic Cutibacterium genus was decreased, and bacterial diversity was increased in skin samples of postmenopausal volunteers. The mean age difference between examined groups in this study was 12.4 years only. Accordingly, Cutometer® measurements revealed no differences in aging-associated skin biophysical parameters between pre- and postmenopausal groups. Consequently, no correlation was detected between Shannon diversity and measured age-dependent biomechanical properties of facial skin. Discussion: These findings are in line with previous studies, which investigated the wide-ranging impact of chronological aging on skin microbial communities. However, this work reports for the first time a direct association between menopausal status and facial microbiomes on skin of similarly aged study participants, and hence uncouples aging-associated skin biophysical parameters, such as viscoelastic properties, from the equation. These findings open avenues for the development of microbiome-targeting strategies for treatment of menopause-associated skin disorders.

From Gut to Hormones: Unraveling the Role of Gut Microbiota in (Phyto)Estrogen Modulation in Health and Disease

The human gut microbiota regulates estrogen metabolism through the "estrobolome," the collection of bacterial genes that encode enzymes like β-glucuronidases and β-glucosidases. These enzymes deconjugate and reactivate estrogen, influencing circulating levels. The estrobolome mediates the enterohepatic circulation and bioavailability of estrogen. Alterations in gut microbiota composition and estrobolome function have been associated with estrogen-related diseases like breast cancer, enometrial cancer, and polycystic ovarian syndrome (PCOS). This is likely due to dysregulated estrogen signaling partly contributed by the microbial impacts on estrogen metabolism. Dietary phytoestrogens also undergo bacterial metabolism into active metabolites like equol, which binds estrogen receptors and exhibits higher estrogenic potency than its precursor daidzein. However, the ability to produce equol varies across populations, depending on the presence of specific gut microbes. Characterizing the estrobolome and equol-producing genes across populations can provide microbiome-based biomarkers. Further research is needed to investigate specific components of the estrobolome, phytoestrogen-microbiota interactions, and mechanisms linking dysbiosis to estrogen-related pathology. However, current evidence suggests that the gut microbiota is an integral regulator of estrogen status with clinical relevance to women's health and hormonal disorders.