Prenatal poly(I:C) exposure, rather than altered maternal care, causes offspring behavioural and cognitive deficits in a rat model of neurodevelopmental disorders.

BACKGROUND

Cognitive deficits are core features of neurodevelopmental disorders (NDD), arising from interacting genetic and environmental (GxE) factors. Maternal immune activation (MIA) is an established environmental risk factor, differentially affecting offspring cognition depending on exposure timing and severity. Maternal pro-inflammatory cytokines (e.g. tumor necrosis factor-alpha, TNFα) and altered maternal-offspring interactions are both implicated in MIA-induced NDD pathogenesis, but their relative impact on offspring cognition remains unclear. Understanding these mechanisms is crucial for developing targeted therapies for NDD-related cognitive deficits.

METHODS

We used a split-litter cross-fostering design in a validated rat MIA model to examine prenatal and postnatal maternal influences on NDD-related cognitive traits. MIA was induced in pregnant Wistar dams (N = 22; gestational day 15) followed by cross-fostering (postnatal day (PD)1). Maternal behaviours, offspring ultrasonic vocalisations (USV), and cognition were assessed in both sexes. Phenotypic clustering of USV and cognitive traits was performed, and high-throughput Western blot quantified glutamic acid decarboxylase-67 (GAD67) and parvalbumin (PVALB) expression in the adult prefrontal cortex (PFC).

RESULTS

Prenatal MIA, but not postnatal rearing, increased offspring USVs, maternal care behaviours, and impaired adult cognitive flexibility without affecting sociability. Offspring clustered into three groups based on PD10 USVs, with high USVs associated with reduced PD100 sociability. MIA did not alter PFC GAD67/PVALB expression.

CONCLUSIONS

The prenatal maternal response to MIA drives developmental and cognitive deficits. Offspring USVs influenced maternal care behaviours, but postnatal rearing did not affect cognitive development. USV trait clustering predicted adult social deficits, highlighting its potential for identifying at-risk and resilient offspring in NDDs.