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The Cardinal Edge

Program/Event

Undergraduate Research Showcase Spring 2025

Abstract

Prenatal cigarette smoke exposure (CSE) is associated with chronic metabolic disease in adulthood, including obesity, type 2 diabetes, and metabolic dysfunction-associated fatty liver disease. Maternal cigarette smoking reduces uterine and placental blood flow, limiting nutrients and oxygen supply to the fetus. According to the Developmental Origins of Health and Disease hypothesis, these conditions may cause developmental adaptations that are maladaptive in calorie-rich environments. We hypothesized that gestational CSE would sensitize affected offspring to the effects of an adulthood high-fat (40 kcal%), high fructose (20 kcal%) diet. C57BL/6J mice were exposed either to filtered room air (sham) or the smoke generated from Marlboro Red™ cigarettes (CSE) for 3 hours a day, every day throughout gestation. At postnatal week (PW) 15, they began a 5-week diet challenge, ending at PW20. We performed triglyceride assays using liver samples taken from littermates before the diet (PW10) and after (PW20). For PW10, the study was conducted as a 2 (sex) x 2 (exposure) factorial arrangement of treatments. PW10 contained a total of 16 liver samples: male sham (n=4), male CSE (n=5), female sham (n=3), and female CSE (n=4). For PW20, the study was conducted as a 2 (sex) x 2 (exposure) x 2 (diet) factorial arrangement of treatments. PW20 contained a total of 50 liver samples. Most groups had n=6 except for the male CSE high-fat (n=9) and female CSE low-fat (n=5). A two-way ANOVA of the PW10 samples conducted using GraphPad showed a significant effect of exposure (p=0.017), with higher liver triglycerides in CSE-exposed mice compared to shams, regardless of sex. A three-way ANOVA of the PW20 data found no significant main or interaction effects on liver triglycerides. These findings suggest that prenatal CSE may predispose offspring to increased hepatic fat deposition in early adulthood. Future studies will investigate the molecular mechanisms driving these differences using transcriptomic and proteomic analyses.

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