Temporal lobe epilepsy (TLE) is the most common form of focal epilepsy, and it is often characterized by debilitating and progressive cognitive impairment. As a result, patients with TLE often report poor quality of life and impaired daily functioning. However, there is significant variability in the nature and severity of cognitive impairments observed across patients with TLE, with some patients demonstrating generalized impairment and others demonstrating relatively normal cognitive profiles. Despite the well-known variability in cognitive impairment that is observed across patients, few studies have focused on identifying distinct cognitive phenotypes within the syndrome of TLE. In addition, very little is known about other health-related risk or individual factors that may contribute to this variability. Health-related risk factors such as vascular factors and metabolic biomarkers, and modifiable risk factors such as hypertension, obesity, physical inactivity, and smoking have been linked to accelerated cognitive aging and even dementia. In contrast, individual factors such as high pre-morbid IQ, more years of education, higher occupational attainment, and bilingualism have been shown to offer a protective factor against the effects of neuropathology on cognition. Given that TLE is now understood to represent a spectrum of disorders, identifying groups of patients with similar cognitive profiles may provide unique insight into the underlying neuropathology that exists in individual patients with TLE, which could have important prognostic value. The proposed study will be the first to integrate advanced neuroimaging data, cognitive data, and health-related risk factors and protective factors in an effort to unravel the heterogeneity of cognitive impairment in TLE. In this study, we will identify and define cognitive phenotypes in TLE based on impairment across neuropsychological measures of language, memory, executive function, and motor speed. We will then investigate brain network differences and clinical features associated with each phenotype. Differences in brain networks will be evaluated using structural and diffusion data utilizing both a regional and a novel connectome-based approach. In addition, we will identify important health-related risk factors (i.e., BMI, pulse pressure proxy, fasting glucose, history of past or current vascular disease, history of smoking, diet, and exercise) and protective factors (i.e., pre-morbid IQ, education, occupation attainment, bilingualism) that moderate the relationship between brain network abnormalities and cognitive dysfunction. The ultimate goal of this proposal is to address the National Institutes of Neurological Diseases and Strokes (NINDS) major benchmark focused on the prevention and reversal of comorbidities in epilepsy. Given that cognitive impairment is the most common and problematic comorbidity in TLE and epilepsy in general, the results from this proposal may help identify those at greatest risk for progressive cognitive dysfunction and/or post-operative cognitive decline. Furthermore, this proposal can directly address this request by helping identify modifiable risk/protective factors that may be used to develop interventions targeted at reducing the risk of further cognitive decline.
Cognitive dysfunction is the most common and debilitating comorbidity in individuals with temporal lobe epilepsy (TLE), leading to poor quality of life and impaired daily functioning. There is considerable variability in the nature and severity of cognitive impairments observed across patients, with some patients demonstrating severely impaired profiles and others demonstrating normal cognitive profiles despite similar clinical features. The aim of this proposal is to identify distinct cognitive phenotypes in TLE and evaluate differences in brain networks and clinical features across phenotypes, as well as identify health-related risk factors and protective factors that moderate the relationship between brain network abnormalities and cognitive dysfunction.
