Vezzani, A. | bioRxiv Science

bioRxiv2023

The interplay between oxidative stress and inflammation supports autistic-related behaviors in mice

Autism Spectrum Disorder (ASD) is a highly prevalent neurodevelopmental condition characterized by social communication deficits and repetitive/restricted behaviors. Several studies showed that inflammation may contribute to ASD. Here we used RT-qPCR, RNA sequencing, immunohistochemistry, and flow cytometry to show that pro-inflammatory molecules were increased in the cerebellum and periphery of mice lacking Cntnap2 (Cntnap2-/-), a robust model of ASD. In parallel, oxidative stress was present in the cerebellum of mutant animals. Systemic treatment with N-acetyl-cysteine (NAC) rescued cerebellar oxidative stress and inflammation as well as motor and social impairments in Cntnap2-/- mice. This was accompanied by improved function of microglia cells in NAC-treated mutant animals. Intriguingly, social deficits, cerebellar inflammation and microglia dysfunction were induced by NAC in Cntnap2+/+animals. Our findings therefore suggest that the interplay between oxidative stress and inflammation may support ASD-related behaviors in mice.

immunology↗

bioRxiv2021

A phenomenological model of neuroimmune interactions in epileptogenesis

Epilepsy can have many different causes and its development (epileptogenesis) involves a bewildering complexity of interacting processes. Here, we present a first-of-its-kind computational model to better understand the role of neuroimmune interactions in the development of acquired epilepsy. Our model describes the interactions between neuroinflammation, blood-brain barrier disruption, neuronal loss, circuit remodeling, and seizures. Formulated as a system of nonlinear differential equations, the model is validated using data from animal models that mimic human epileptogenesis caused by infection, status epilepticus, and blood-brain barrier disruption. The mathematical model successfully explains characteristic features of epileptogenesis such as its paradoxically long timescales (up to decades) despite short and transient injuries, or its dependence on the intensity of an injury. Furthermore, stochasticity in the model captures the variability of epileptogenesis outcomes in individuals exposed to identical injury. Notably, in line with the concept of degeneracy, our simulations reveal multiple routes towards epileptogenesis with neuronal loss as a sufficient but non-necessary component. We show that our framework allows for in silico predictions of therapeutic strategies, providing information on injury-specific therapeutic targets and optimal time windows for intervention.

neuroscience↗