Amer, H. M.; Shamseldin, M. M.; Faber, S.; Eltobgy, M.; Webb, A.; El-Mergawy, R.; Chamblee, M.; Perez, R.; Whitham, O.; Badr, A.; Gupta, G.; Omran, J.; Bissel, D.; Yount, J.; Cormet-Boyaka, E.; Boyaka, P. N.; Li, J.; Zhang, X.; Peeples, M. E.; KC, M.; Pietrzak, M.; Seveau, S.; Kokiko-Cochran, O.; Amer, M.; Barrientos, R. M.; Schamess, A.; Oltz, E.; Amer, A. O.

Long COVID (LC) following SARS-CoV-2 infection affects millions of individuals world-wide and manifests with a variety of symptoms including cognitive dysfunction also known as brain fog . This is characterized by difficulties in executive functions, planning, decision-making, working memory, impairments in complex attention, loss of ability to learn new skills and perform sophisticated brain tasks. No effective treatment options currently exist for LC-related cognitive dysfunction. Here, we use the IntelliCage, which is an automated tracking system of cognitive functions, following SARS-CoV-2 infection in mice, measuring the ability of each mouse within a group to perform tasks that mimic complex human behaviors, such as planning, decision-making, cognitive flexibility, and working memory. Artificial intelligence and machine learning analyses of the tracking data classified LC mice into distinct behavioral categories from non-infected control mice, permitting precise identification and quantification of complex cognitive dysfunction in a controlled, replicable manner. Importantly, we find that brains from LC mice with cognitive dysfunction exhibit transcriptomic alterations similar to those observed in humans suffering from LC-related cognitive impairments, including altered expression of genes involved in learning, executive functions, synaptic functions, neurotransmitters and memory. Together, our findings establish a validated murine model and an automated unbiased approach to study LC-related cognitive dysfunction for the first time, and providing a valuable tool for screening potential treatments and therapeutic interventions.