Prenatal Exposure to Delta-9-tetrahydrocannabinol (THC) Alters the Expression of miR-122-5p and Its Target Igf1r in the Adult Rat Ovary.
Annia A Martínez-PeñaKendrick LeeMadison PereiraAhmed AyyashJames J PetrikDaniel B HardyAlison C HollowayPublished in: International journal of molecular sciences (2022)
As cannabis use during pregnancy increases, it is important to understand its effects on the developing fetus. Particularly, the long-term effects of its psychoactive component, delta-9-tetrahydrocannabinol (THC), on the offspring's reproductive health are not fully understood. This study examined the impact of gestational THC exposure on the miRNA profile in adult rat ovaries and the possible consequences on ovarian health. Prenatal THC exposure resulted in the differential expression of 12 out of 420 evaluated miRNAs. From the differentially expressed miRNAs, miR-122-5p, which is highly conserved among species, was the only upregulated target and had the greatest fold change. The upregulation of miR-122-5p and the downregulation of its target insulin-like growth factor 1 receptor ( Igf1r ) were confirmed by RT-qPCR. Prenatally THC-exposed ovaries had decreased IGF-1R-positive follicular cells and increased follicular apoptosis. Furthermore, THC decreased Igf1r expression in ovarian explants and granulosa cells after 48 h. As decreased IGF-1R has been associated with diminished ovarian health and fertility, we propose that these THC-induced changes may partially explain the altered ovarian follicle dynamics observed in THC-exposed offspring. Taken together, our data suggests that prenatal THC exposure may impact key pathways in the developing ovary, which could lead to subfertility or premature reproductive senescence.
Keyphrases
- cell cycle arrest
- binding protein
- pi k akt
- pregnant women
- poor prognosis
- induced apoptosis
- oxidative stress
- growth hormone
- public health
- signaling pathway
- healthcare
- cell proliferation
- cell death
- high fat diet
- mental health
- endoplasmic reticulum stress
- dna damage
- type diabetes
- physical activity
- body mass index
- metabolic syndrome
- long non coding rna
- diabetic rats
- electronic health record
- endothelial cells
- deep learning
- weight loss
- preterm birth
- drug induced
- artificial intelligence
- health promotion