Placental endocannabinoid metabolism and gene expression gestational age-related alterations across preterm and term birth.

Synova T.; Cifkova E.; Libra A.; Portillo R.; Abad C.; Kacerovsky M.; Stranik J.; Lisa M.; Karahoda R.; Staud F. · Reproductive biomedicine online · 2026

**Background & Methods** This study examined placental endocannabinoid system (ECS) variation across gestation in 102 pregnancies stratified by delivery timing: extremely to very preterm (<32 weeks), moderate to late preterm (32-37 weeks), and term (≥37 weeks). Researchers measured 10 ECS-related genes via reverse transcription quantitative real-time PCR and 20 endocannabinoid-related metabolites using targeted ultra-high performance liquid chromatography-mass spectrometry, with statistical analysis including univariate/multivariate approaches and hierarchical clustering. **Key Findings** • **Gene expression alterations with prematurity**: DAGLB and NAPEPLD expression were significantly lower in both preterm groups compared to term placentas (DAGLB, P<0.001; NAPEPLD, P=0.035-0.045). ABHD6 expression was reduced specifically in extremely to very preterm placentas (P=0.010), while CNR1 was elevated in moderate to late preterm compared to term placentas (P=0.009). • **Metabolite profile changes**: Monoacylglycerols (MAGs) were the primary metabolites distinguishing preterm from term placentas, with strong inverse associations to gestational age (β≈-0.131 to -0.16; R²≈0.49-0.65; P<0.001). N-Acylethanolamines showed weaker or non-significant associations with gestational age. • **Gestational maturation as primary driver**: Integrative clustering identified three preterm placental clusters differing in gestational age, neonatal birthweight, and maternal pregnancy weight gain, suggesting that ECS profile differences primarily reflect normal gestational maturation rather than distinct pathological phenotypes of preterm birth. **Dosage & Administration** Not reported. **Safety & Adverse Effects** Not reported. **Evidence Quality** This observational study provides moderate evidence with notable limitations. The sample size of 102 pregnancies across three groups is relatively modest for biomarker discovery. As a cross-sectional design, causality cannot be established. The study describes associations between ECS markers and gestational age but lacks mechanistic insight into whether these changes are protective, pathological, or simply maturational. The finding that preterm ECS profiles reflect gestational age rather than distinct pathology suggests caution in interpreting biomarker significance for clinical phenotyping. No adjustment for potential confounders (maternal BMI, inflammation, infection) is mentioned. The study adds valuable descriptive data on placental ECS development but requires prospective validation to clarify clinical implications for preterm birth prediction or intervention.

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