Identifying Sleep Biomarkers to Evaluate Cognition in HIV

Sleep disturbance and cognitive impairment now represent two of the most common and debilitating conditions facing seropositive (HIV+) individuals who are otherwise well controlled with antiretroviral therapy. Sleep-assessment-based biomarkers represent an important step towards improving understanding the unique mechanistic features that may link sleep disruption and cognition in HIV+ individuals and can ultimately advance early detection and treatment opportunities in this cohort. In this study, a risk score was computed via a generalized linear model (GLM), which optimally combines polysomnography (PSG) features extracted from EEG, EMG, and EOG signals, to distinguish 18 HIV+ Black male individuals with and without cognitive impairment. The optimal set of features was identified via the least absolute shrinkage and selection operator (LASSO) approach, and the risk separation between the two groups, i.e., cognitively normal and cognitive impaired, was significant (and has a P-value < .001). Interestingly, the optimal set of features were all EEG derived and sleep stage-specific. These preliminary findings suggest that sleep-based EEG markers may be used as a diagnostic and prognostic for cognition in HIV+ patients.