Connecting Neuronal Hyperexcitability and Sex Differences in Alzheimer's Disease (AD) using biophysically-informed in-silico brain simulations and experimental data from mouse models of AD

The mechanism underlying neuronal hyperexcitability, as a result of excitation-inhibition (E-I) imbalance, leading to cognitive deterioration in Alzheimer’s disease (AD) is not fully understood and effective approaches to prevent or reverse memory deficits are unavailable. Our multimodal MRI connectomics demonstrated a hyperexcitation connectome phenotype in healthy women ApoE4 carriers as they age, raising the possibility that at least some sex differences in AD may be explained by E4 female carrier-specific neuronal hyperexcitation. In support of this, resting state functional magnetic resonance imaging (rs-fMRI) in APPNL-G-F/NL-G-F revealed higher interhemispheric functional connectivity in the hippocampus of female mid-life mice. Further, we observed reduced functional anisotropy, altered myelin and oligodendrocyte count, and importantly, altered transcription phenotype of excitatory and inhibitory neurons in the hippocampus of these female mice. The antiseizure drug Levetiracetam (LEV) is currently being tested in human trials, with early data suggesting that it does improve cognition in those with signs of hyperexcitability. However, there is conflicting information concerning the efficacy of the drug and its mechanism is not fully understood. This collaborative, multidisciplinary MPI program is aimed at unraveling the efficacy of LEV in humans and mouse models by leveraging expertise in computational and experimental neuroscience. We will test the hypothesis that hyperexcitability is more prevalent both in ApoE4 woman carriers and in female FAD-linked APPNL-G-F/NL-G-F and LOAD-linked ApoE4 knockin mice and that LEV treatment will normalize hyperexcitability and cognitive deficits in a sex-dependent manner. In the R21 Phase, the experimental approach will establish feasibility of LEV treatment in APPNL-G-F/NL-G-F female mice. The computational approach will develop new biophysically - informed computational framework for modeling experimental mouse data. In the R33 Phase, we will establish the effect of LEV on hyperexcitability and pathology in association with sex, ApoE4 and amyloidosis, and generalize our computational approaches from mouse hippocampus to the entire brain to characterize the whole-brain biophysical parameters of E-I balance in AD with or without LEV treatment. The results of this program will provide novel insight into the molecular mechanism of E-I and LEV, and its therapeutic value in AD.