Some of the most difficult challenges for many of those diagnosed with Neurofibromatosis1 (NF1) are the cognitive alterations, including intellectual disability, attention deficit hyperactivity disorder, and autism spectrum disorder. Previous studies have implicated one group of neurons, those that inhibit brain activity, in the underlying symptoms that cause the cognitive changes in NF1. However, there have been few advancements in understanding how these important cells could lead to the cognitive changes. We found that loss of the Nf1 gene in mice resulted in a drastic impairment of a key factor necessary to program inhibitory neurons. Loss of this factor also correlates with behavioral changes in mice that are observed after loss of just one copy of the Nf1 gene. We can rescue the loss of this factor using a MEK inhibitor, suggesting that cognitive changes in NF1 may be therapeutically treated or prevented. We will test whether the recent FDA-approved MEK inhibitor, selumetinib, is effective at rescuing the altered behaviors in our model and establish whether an optimal window may exist.

Sleep disruptions are also common in those diagnosed with NF1. We found that the same factor mentioned above is repressed in a brain region involved in sleep onset and its loss in a previous study resulted in sleep deficits and disrupted circadian function, a brain region that helps us maintain normal wake/sleep over a 24-hour day. Moreover, circadian time utilizes RAS/MAPK signaling to properly function. We will examine whether these brain regions lead to altered sleep using a combination of genetic models to delete Nf1 in different sleep regions and answer whether dysfunction in these regions work alone or together. Overall, we will determine whether dysfunctional inhibitory neurons can be rescued by MEK inhibition and whether this correlates to improved behavioral outcomes. Moreover, we will use a combination of genetic tools to test whether distinct brain regions involved in sleep and circadian time underlie sleep deficits in our model.