P-272 Cannabis negatively impacts female fertility: an in vitro and clinical investigation
Bibliographic record
Abstract
Abstract Study question How does tetrahydrocannabinol (THC) impacts human oocyte maturation and female fertility? Summary answer THC alters the oocyte’s RNA profile and affects meiotic spindle formation resulting in an increased rate of aneuploidy in the oocyte and in the blastocyst. What is known already In the past decades, cannabis consumption and legalization has been increasing globally. It is the third most used substance by reproductive aged people and our group demonstrated that tetrahydrocannabinol (THC) reaches the ovarian follicle. THC is known to impact male fertility, but due to the challenges associated with investigating the female gamete in humans, there is no study about the human oocyte. Animal studies have shown that THC impacts oocyte maturation in a concentration dependent manner, but between models, the results are conflicting. Study design, size, duration For the in vitro exposure assessment, GV oocytes naïve to THC were collected from consenting patients undergoing IVF-ICSI from July 2022 to June 2024 (IRB: Veritas #16518). Per patient, oocytes were split into three groups: Control, THC1 (physiological concentration of THC, based on previous human studies) and THC2 (supra-physiological concentration, based on animal studies), and cultured for 24h in our standard clinical in vitro maturation media. Participants/materials, setting, methods Single-cell RNAseq and pathway analysis were conducted to identify key pathways altered by THC treatments (n = 86 from 24 patients). Spindle morphology was assessed using confocal microscopy. Polar body biopsy was performed and ploidy assessed using our clinical low pass whole genome sequencing pipeline. Also, we conducted a multi-year retrospective study (n = 1059 patients) by measuring the concentration of THC in their follicular fluid by mass spectrometry and collecting and comparing IVF outcomes between cases and controls. Main results and the role of chance In vitro, THC treatment marginally increased the maturation rate (46% for Ctrl (n = 103), 51% for THC1 (n = 103) and 58% for THC2 (n = 102)). Using time-lapse imaging, no difference was observed between key developmental stages of oocyte maturation including GVBD and polar body extrusion. Single-cell RNAseq revealed significant alterations to the transcriptome profile of THC treated oocytes. When treated with THC1 (physiological concentration), 89 upregulated and 227 downregulated genes were identified, this was exaggerated when treated with THC2 (supraphysiologic concentration) 402 upregulated and 62 downregulated genes were identified. Pathway analysis showed that differentially expressed genes in THC1 group were associated with immune system and synaptic transmission, while THC2 group showed genes enriched in meiotic spindle formation and apoptosis. Moreover, preliminary results demonstrated abnormal spindle configuration and misaligned chromosomes in THC-treated groups and a concurrent decrease in the number of euploid oocytes. Furthermore, retrospective analysis of clinical IVF outcomes revealed that patients whose FF was positive for THC (62 patients, 6%) also had a slight increased maturation rate (77% vs 73%, p=ns), but a significant reduction of their embryo euploid rate when compared to control patients (59% vs 70%, p < 0.01). Limitations, reasons for caution The in vitro exposure to THC utilized GV oocytes that did not mature after ovarian stimulation, so they might have a reduced capacity of becoming MII. The THC measurement was assessed only on the day of retrieval and we do not know the route, dose, or duration of THC consumption. Wider implications of the findings This is the first study investigating the impact of cannabis on human oocytes. Our data suggests that cannabis consumption may reduce the number of euploid embryos available for transfer. With cannabis legalization increasing worldwide, further investigation into its consequences is critical for clinical consultation and legalization guidelines. Trial registration number Not applicable
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".