Journal of Assisted Reproduction and Genetics最新文献

Purpose: Endometriosis (EM) is a chronic inflammatory gynecological disorder characterized by ectopic endometrial-like lesions, where aberrant angiogenesis is a hallmark driving lesion establishment and progression. However, the transcriptional mechanisms underlying pathological vascular remodeling in EM remain unclear.

Methods: In this study, we identified E26 transformation-specific 1 (ETS1) as a key transcriptional regulator in EM pathogenesis through integrative analysis of bulk and single-cell transcriptomic datasets.

Results: Across three independent transcriptome datasets and two validation cohorts, ETS1 expression was consistently elevated in endometriosis lesions, particularly in ovarian endometrioma. Single-cell RNA sequencing further revealed that ETS1 was predominantly expressed in endothelial cells and dynamically upregulated along the endothelial differentiation trajectory. Functional enrichment and pseudotime analyses indicated that ETS1 + endothelial cells exhibited enhanced angiogenic activity and vascular remodeling potential. Mechanistically, ETS1 amplified VEGF signaling by upregulating VEGFR1 and VEGFR2, while macrophage-derived VEGFA acted as the principal upstream activator within the lesion microenvironment.

Conclusions: Collectively, our findings delineate the VEGF-ETS1 axis as a central driver of pathological angiogenesis in endometriosis, positioning ETS1 as both a mechanistic hallmark and a promising therapeutic target for endometriosis.

Purpose: Poor ovarian response and primary ovarian insufficiency remain major challenges in assisted reproductive technologies. Recent advances propose mechanical approaches-such as in vitro activation, drug-free IVA, and whole ovarian laparoscopic incision (WOLI)-as well as biological strategies like platelet-rich plasma (PRP) injections to improve ovarian function. This study aims to evaluate the impact of WOLI and PRP on ovarian follicular activation, with a particular focus on the associated biomechanical alterations in the ovarian cortex.

Methods: Experimental pilot study includes six aged female Merino sheep. Group A underwent WOLI on one ovary, and group B received PRP injections. Contralateral ovaries served as controls. Laparoscopic bilateral oophorectomies were performed at 2, 4, and 6 months. Atomic force microscopy (AFM) measured ovarian cortical stiffness, and histological analysis assessed follicular activation. Analyses were performed by comparing the operated ovary to the contralateral, non-operated ovary.

Results: AFM measurements showed that in group A, ovarian stiffness significantly increased at 6 months (8.683 kPa vs. 5.551 kPa; p < 0.001), with no significant differences at 2 or 4 months. In group B, stiffness increased significantly at 2 months (11.177 kPa vs. 6.590 kPa; p < 0.001), but not at 4 or 6 months post-intervention. Growing follicle proportions differed between treated and control ovaries respectively, with activation at 2 months (58.95% vs. 29.73%) in group A and 6 months in group B (53.01% vs. 20.33%).

Conclusion: The study suggests that the activating effect on ovarian folliculogenesis of both the surgical procedure and PRP administration shows a different time course and that could be related to its effect on ovarian cortex mechanobiology.

Purpose: To assess the impact of transvaginal ovarian drilling (TVOD) on euploidy rates following repeat in vitro fertilization (IVF) in subjects with polycystic ovarian syndrome (PCOS).

Materials and methods: A single institution retrospective cohort study between January 2017 and December 2024, all patients with PCOS, as confirmed by Rotterdam criteria, who had TVOD performed prior to a repeat IVF cycle and underwent PGT-A in both the prior and repeat cycles were included and compared to a well-matched control. The primary outcome was the number of transferable embryos per cycle. Secondary outcomes included: blastocyst yield, euploid yield, and rates of aneuploidy.

Results: Eighteen subjects met criteria in our study time frame and were compared to 57 control subjects. The mean age for the TVOD and control groups was 35.3 ± 4.6 and 36.5 ± 4.4 respectively (p = 0.34). TVOD was associated with a doubling of blastocyst yield, a sixfold increase in the yield of euploid blasts, and a nearly fourfold decrease in the percentage of aneuploid blasts. When compared to controls, TVOD resulted in a significant improvement in the yield of euploid embryos, from + 1.3 to + 2.4 (p = 0.01), and transferable embryos from + 1.5 to + 3.9 (p = 0.001). TVOD also resulted in a decrease in the percentage of aneuploid embryos from - 8.5 to - 49% (p < 0.001).

Conclusion: TVOD appears to have positively impacted the yield of transferable embryos and euploid embryos in patients with PCOS when compared to a well-matched control.

Background and objective: Artificial intelligence (AI) has emerged as a promising tool for clinical decision support in reproductive medicine, yet the performance of general-purpose large language models (LLMs) in predicting in vitro fertilization (IVF) outcomes remains insufficiently characterized. This exploratory proof-of-concept study aimed to evaluate and compare the out-of-the-box performance of three widely accessible LLM-based systems (ChatGPT, DeepSeek, and Gemini) in forecasting key clinical and laboratory outcomes of IVF treatments.

Methods: This retrospective single-center study used data from 1473 autologous IVF/ICSI cycles, each representing a unique patient. For each cycle, relevant clinical and laboratory variables were incorporated into a standardized anonymized patient-level vignette and submitted via the publicly available web interfaces of three LLMs (ChatGPT, DeepSeek, Gemini) without any fine-tuning or internal customization. The models were asked to predict stimulation protocol, ovulation trigger type, total and mature oocyte counts, usable embryo counts, and clinical pregnancy. Predictive performance was evaluated using accuracy and tolerance-based accuracy for categorical and count-based outcomes, mean absolute error for numerical predictions, and the area under the receiver operating characteristic (ROC) curve for clinical pregnancy.

Results: Gemini achieved the highest accuracy in predicting stimulation protocols (51.26%) and embryo counts (68.22%), while DeepSeek demonstrated the lowest numerical error for oocyte count predictions. Clinical pregnancy prediction was the most challenging task; all models showed only moderate discrimination, with Gemini achieving the highest AUC (0.711), followed by ChatGPT (0.690) and DeepSeek (0.676). Overall, model performance varied considerably across tasks and remained below thresholds that would be considered sufficient for reliable stand-alone clinical use.

Conclusions: In this exploratory proof-of-concept setting, general-purpose AI systems showed variable and overall suboptimal performance in predicting IVF outcomes from standardized clinical vignettes. Although certain models demonstrated relative strengths in specific tasks, none reached the reliability, consistency, or interpretability required for safe clinical implementation. These findings indicate that, in their current form, such models should not be used as clinical decision-support tools for IVF decision-making and that their use should remain restricted to carefully controlled research settings until they have been prospectively validated in multicenter cohorts and systematically compared with rigorously developed, task-specific prediction models. This study provides comparative insight into how these AI systems behave in IVF-related prediction tasks and underscores the need for cautious interpretation of AI-generated outputs.

We report a case of fertility preservation using random-start controlled ovarian stimulation and embryo cryopreservation in a patient with a recent second trimester termination. A 32-year-old patient at 17 weeks of gestation was diagnosed with advanced colorectal cancer after presenting with hematochezia and acute blood loss anemia. To initiate urgent chemotherapy, the patient underwent an elective termination at 18-week gestation. Random-start controlled ovarian stimulation (COS) was initiated seven days later using a gonadotropin-releasing hormone antagonist protocol. Despite a β-human chorionic gonadotropin level of 52.4 mIU/mL, ovarian stimulation was started. Nineteen oocytes were retrieved after 10 days of ovarian stimulation, of which 15 were mature. Eleven mature oocytes fertilized successfully using intracytoplasmic sperm injection. All 11 embryos developed into the blastocyst stage and underwent biopsy for preimplantation genetic testing for aneuploidy screening. Five blastocysts were found to be euploid. The patient subsequently initiated chemotherapy seven days after her oocyte retrieval. This case highlights the feasibility of random-start COS and embryo cryopreservation for fertility preservation immediately after a second trimester termination in a patient with newly diagnosed colorectal cancer.

Purpose: Since 2021, elective egg freezing (EEF) without medical indication has been authorized and fully reimbursed in France for women aged 29 to 37. While this regulatory change represents a significant advancement in reproductive rights, it also raises new ethical and organizational challenges. This study aimed to explore the ethical issues experienced by infertility specialists involved in the clinical implementation of EEF in France.

Methods: This prospective, qualitative, monocentric study was conducted in a university-based ART center. All physicians involved in EEF at the center were invited to participate in semi-structured interviews. Data were analyzed inductively using Grounded Theory methodology.

Results: Eight practitioners participated. Four main themes emerged: (1) challenges in accessing EEF due to resource constraints and growing demand; (2) a new relationship between caregiver and patient in a context where care is no longer strictly medical; (3) a need to redefine the role of EEF in society, including the terminology used and funding mechanisms; and (4) questions about the future of EEF, including prioritization criteria, equitable access, and sustainability of the current model.

Conclusions: While EEF is widely supported by healthcare professionals, its integration into routine practice reveals tensions between autonomy, justice, beneficence, and public resource management. National guidelines, improved access to information, and further research-particularly incorporating women's perspectives-are essential to ensure ethically sound implementation.

Purpose: Ultrasound measurement of follicle diameter is essential in IVF monitoring. This study evaluates the analytical performance of follicle counts and size measurements from two-dimensional images using an AI-based platform, compared to assessments by certified sonographers.

Methods: A total of 5508 TVUS scans from 1689 patients undergoing controlled ovarian stimulation across four IVF centers (Poland, Argentina, Colombia, and the USA) were retrospectively analyzed. All visible follicles were marked using bounding boxes. The dataset included three subsets: training/validation for model development, independent test for evaluating performance across ultrasound systems, and a consensus test set (102 scans from 27 patients) annotated by three expert sonographers. Model performance was assessed using precision, recall, and F1 score. Annotation efficiency was measured by comparing manual and AI-assisted times. Real-world performance was evaluated on a prospective cohort of 904 scans from 269 patients, based on expert adjustments to AI annotations.

Results: For follicles ≥ 10 mm, the model achieved 98.2% precision (95% CI, 96.5-99.2), 88.9% recall (85.0-91.8), and 93.3% F1 score (90.7-95.1). For all follicles, precision and recall were 94.2% (92.8-95.4) and 68.9% (65.9-71.9). Annotation time was reduced 2.5-fold (p < 0.01), with an average of 0.54 expert adjustments per scan (CI, 0.47-0.62). Model performance was stable across ultrasound platforms.

Conclusion: This AI platform enables accurate, automated follicle counting and measurement during ovarian stimulation. It matches expert-level performance, improves efficiency, and supports scalable, cost-effective fertility care without compromising quality.

Purpose: To systematically investigate the genetic architecture of severe male infertility in Indian men, with a specific focus on chromosomal abnormalities and the contribution of de novo variants.

Method: We recruited 247 infertile males between 2021 and 2024 presenting with severe quantitative and qualitative sperm defects. All patients underwent karyotyping and Y chromosome microdeletion STS-PCR. A single molecule molecular inversion probe-based targeted sequencing assay covering 39 male infertility genes was performed in 120 patients, while whole exome sequencing (WES) was conducted in 48 patients using a duo/trio-based approach to enable segregation and de novo variant detection.

Result: Gonosomal aneuploidies were observed in 3/247 patients (1.2%, 95% CI 0.3-3.5%) and causal AZF microdeletions in 8/247 (3.2%, 95% CI 1.4-6.3%). Targeted sequencing identified pathogenic/likely pathogenic (P/LP) variants in 4/120 patients (3.3%, 95% CI 0.9-8.3%), with additional CFTR variants in 3 patients where parental DNA was unavailable for phasing. WES yielded P/LP variants in 4/48 patients (8.3%, 95% CI 2.3-19.9%) affecting PMFBP1, DNAH1, and AR genes, confirmed via segregation analysis. No de novo or copy number variants were confirmed as causative, though several candidate genes were prioritised. Sequencing-based approaches provided an additional ~ 6-8% diagnostic yield, with the overall diagnostic rate reaching 7.7% (19/247; 95% CI 4.7-11.8%).

Conclusion: Sequencing-based strategies, particularly family-based trio WES, significantly enhance diagnostic yield beyond current guideline-recommended tests, with data supporting their adoption as first-tier investigations for severe male infertility. This represents India's largest cohort-based genomic study on male infertility to date. Larger family-based cohorts will be essential to delineate the contribution of de novo variants to male infertility genetics.

Objective: Fertility preservation (FP) is an important aspect of care for reproductive-aged cancer patients since treatment can significantly impact fertility. Despite professional recommendations for early referral to FP, rates remain low. This study evaluates predictors of FP referrals by Oncologists to Reproductive Endocrinology and Infertility (REI) physicians among reproductive-aged cancer patients at a large academic institution.

Materials and methods: This cross-sectional study evaluated patients ages 14-42 years seen by an Oncologist from 2022 to 2024 with a new diagnosis of cancer for whom planned treatment is either gonadotoxic or requires delayed pregnancy. Referral rates to REI physicians were assessed by patient demographics and cancer and Oncologist characteristics as potential predictors. Statistical analysis used chi-square tests, Fisher's exact tests, and multivariable logistic regression.

Results: Of 510 patients seen by an Oncologist for a newly diagnosed cancer, only 127 (22.5%) were referred for FP. Patients > 30 years were less likely to be referred than younger patients (aOR = 0.15, 95% CI = 0.05, 0.47, p = 0.001). Patients with breast cancer were most likely to be referred compared to other cancers. There was no difference in referral rates by physician gender. Physicians with 21-30 years of experience were more likely to refer than those with < 10 years (aOR = 2.89, 95% CI = 1.50, 5.62, p = 0.002).

Conclusions: There was a low rate of FP referral and significant disparities based on patient demographics and clinical factors. Referral rates were higher among younger patients and breast cancer patients. Standardizing FP referrals across oncology specialties, consideration of electronic health record "soft stops" for referral and increasing patient and provider education are essential to improving referral rates.