Contraception and endometriosis: challenges, efficacy, and therapeutic importance

The role of peroxisome proliferator-activated receptors in endometriosis

Endometriosis constitutes the most common cause of chronic pelvic pain in female patients and is associated with infertility. Although there is no known cause for the disease, it is a heritable condition that is determined by numerous genetic, epigenetic, and environmental aspects. Peroxisome proliferator-activated receptors (PPARs) represent nuclear receptor proteins that control gene expression. By using the MEDLINE and LIVIVO databases we conducted a literature review in order to look into the role of PPARs in the endometriosis pathophysiology and succeeded in revealing 36 pertinent publications between 2001 and 2022. In regards to PPAR expression in endometriosis, PPARγ seems to represent the most studied PPAR isoform in endometriosis and to influence various pathways involved in the disease onset and progression. It's interesting to note that diverse treatment agents targeting the PPAR system have been identified as innovative, effective therapeutic alternatives in the context of endometriosis treatment. In conclusion, PPARs appear to contribute an important role in both endometriosis pathophysiology and therapy.

Horizons in Endometriosis: Proceedings of the Montreux Reproductive Summit, 14-15 July 2023

Endometriosis is a complex and chronic gynaecological disorder that affects millions of women worldwide, leading to significant morbidity and impacting reproductive health. This condition affects up to 10% of women of reproductive age and is characterised by the presence of endometrial-like tissue outside the uterus, potentially leading to symptoms such as chronic pelvic pain, dysmenorrhoea, dyspareunia, and infertility. The Montreux summit brought a number of experts in this field together to provide a platform for discussion and exchange of ideas. These proceedings summarise the six main topics that were discussed at this summit to shed light on future directions of endometriosis classification, diagnosis, and therapeutical management. The first question addressed the possibility of preventing endometriosis in the future by identifying risk factors, genetic predispositions, and further understanding of the pathophysiology of the condition to develop targeted interventions. The clinical presentation of endometriosis is varied, and the correlation between symptoms severity and disease extent is unclear. While there is currently no universally accepted optimal classification system for endometriosis, several attempts striving towards its optimisation - each with its own advantages and limitations - were discussed. The ideal classification should be able to reconcile disease status based on the various diagnostic tools, and prognosis to guide proper patient tailored management. Regarding diagnosis, we focused on future tools and critically discussed emerging approaches aimed at reducing diagnostic delay. Preserving fertility in endometriosis patients was another debatable aspect of management that was reviewed. Moreover, besides current treatment modalities, potential novel medical therapies that can target underlying mechanisms, provide effective symptom relief, and minimise side effects in endometriotic patients were considered, including hormonal therapies, immunomodulation, and regenerative medicine. Finally, the question of hormonal substitution therapy after radical treatment for endometriosis was debated, weighing the benefits of hormone replacement.

Genistein Ameliorated Vascular Endothelial Growth Factor-A (VEGF-A) and Estrogen Receptor-Alpha (ER-α) in Endometriosis Mice Model, In Vivo and In Silico

Endometriosis (EM) is a gynecological disorder that causes morbidity in women and is characterized by endometrial tissue in the uterus cavity. This study investigated the mechanism of genistein in the VEGF-A and ER-α expression through in vivo and in silico approaches. An in vivo study was conducted by thirty-six mice that were divided into six groups including control, EM, and EM treatment with genistein with the doses of 1.3, 1.95, 2.6, and 3.25 mg/day for 14 days. Peritoneal tissues with lesions were collected and analyzed by immunohistochemistry to measure the VEGF-A and ER-α expression. The data were analyzed using a statistical approach using one-way ANOVA followed by Tukey HSD test with a significant value p < 0.05. In silico study was conducted for investigating the inhibition mechanism of genistein in VEGF-A and ER-α protein. Genistein significantly reduced the VEGF-A and ER-α expression with the optimum dose of 3.25 mg/day. Molecular docking showed that genistein inhibited VEGF-A in several active site residues of VEGF-A, also blocked the ER-α protein in estradiol binding sites. This study concluded that genistein prevented endometriosis by performing the antiangiogenic activity and showed a similar function to estradiol.

Oral Contraceptives and the Risk of Psychiatric Side Effects: A Review

Background

Oral contraceptives (OCs) are an essential medicine used by millions of people every day. Given the widespread usage of these medicines, even a small increase in psychiatric risk could be of clinical significance. Although mood-related side effects are a common reason for OC hesitancy and discontinuation, studies investigating psychiatric responses to OC treatment have had inconsistent results.

Summary

While OCs are beneficial for most users, there is evidence that a subgroup of users is susceptible to mood side effects. Randomized controlled trials have generally failed to find differences in mood symptoms between OC and placebo users, but observational studies comparing OC users to non-users have reported increases in symptoms of depression, anxiety, and eating disorders. Additionally, observational evidence suggests that OC users may be more likely to use prescription psychotropic medications and to attempt or die by suicide. However, responses to OC treatment are highly heterogeneous, and some users report mood improvement. A variety of factors may increase the likelihood of negative psychiatric side effects, including younger age, previous experience of side effects from OCs, and preexisting psychiatric disorders. Progestin-only pills may confer a higher psychiatric risk than combination pills.

Key Messages

Further research investigating factors that contribute to susceptibility to the mood-related side effects of OCs is clearly warranted. Genomic approaches may provide insight as to why some users experience side effects while others do not. Research elucidating who is most at risk and why will be essential to addressing prevalent concerns about the psychiatric risk of OCs.

Evaluating the risk of endometriosis based on patients' self-assessment questionnaires

BACKGROUND

Endometriosis is a condition that significantly affects the quality of life of about 10 % of reproductive-aged women. It is characterized by the presence of tissue similar to the uterine lining (endometrium) outside the uterus, which can lead lead scarring, adhesions, pain, and fertility issues. While numerous factors associated with endometriosis are documented, a wide range of symptoms may still be undiscovered.

METHODS

In this study, we employed machine learning algorithms to predict endometriosis based on the patient symptoms extracted from 13,933 questionnaires. We compared the results of feature selection obtained from various algorithms (i.e., Boruta algorithm, Recursive Feature Selection) with experts' decisions. As a benchmark model architecture, we utilized a LightGBM algorithm, along with Multivariate Imputation by Chained Equations (MICE) and k-nearest neighbors (KNN), for missing data imputation. Our primary objective was to assess the model's performance and feature importance compared to existing studies.

RESULTS

We identified the top 20 predictors of endometriosis, uncovering previously overlooked features such as Cesarean section, ovarian cysts, and hernia. Notably, the model's performance metrics were maximized when utilizing a combination of multiple feature selection methods. Specifically, the final model achieved an area under the receiver operator characteristic curve (AUC) of 0.85 on the training dataset and an AUC of 0.82 on the testing dataset.

CONCLUSIONS

The application of machine learning in diagnosing endometriosis has the potential to significantly impact clinical practice, streamlining the diagnostic process and enhancing efficiency. Our questionnaire-based prediction approach empowers individuals with endometriosis to proactively identify potential symptoms, facilitating informed discussions with healthcare professionals about diagnosis and treatment options.

Medical conditions, pregnancy perspectives and contraceptive decision-making among young people: an exploratory, qualitative analysis

OBJECTIVE

To explore perspectives on family planning among young people who perceive they are infertile or will have difficulty carrying a pregnancy to term owing to medical conditions or procedures.

METHODS

This exploratory analysis examined pregnancy plans and contraceptive behavior among 12 young adults with a diagnosed medical condition or who had undergone a medical procedure associated with impaired fertility, and who had discussed fertility with a healthcare provider. We utilized data from a larger study investigating prospective pregnancy intentions and plans among 50 young (ages 18-24) women and their male partners (n=100).

RESULTS

Medical conditions included endometriosis, polycystic ovary syndrome, and lupus. For some, medical conditions/procedures led to use of no or less effective contraception; perceived risk for pregnancy was low, though seven participants had previously experienced pregnancies. Participants also described how medical conditions altered their timelines for pregnancy and overall desire for children; for example, one participant described continuing an unplanned pregnancy because she feared it would be her only chance to parent.

CONCLUSION

This exploratory analysis suggests that among young people, medical issues perceived to affect fertility and pregnancy may influence pregnancy planning and contraceptive behavior. Young people may lack knowledge about fertility and the impact of a medical condition; thus it is critical that providers clarify the difference between anticipated difficulty conceiving and complete infertility. Tailored contraceptive care is needed for young adults with medical conditions that may affect fertility to ensure they have the necessary information to make informed family planning decisions.

IMPLICATIONS

Medical conditions known to affect fertility may influence young people's family planning desires and behaviors. Understanding how young adults process information about medical conditions' impact on their fertility and change or make plans in response is important in order to best meet their family planning needs.