Assessing Brain Dysfunction in Individuals with SLE: Heterogeneity, Mechanisms and Metrics

ABSTRACT – Project 2 Cognitive impairment, depression, anxiety and fatigue are highly prevalent in Systemic Lupus Erythematosus (SLE); all are components of brain dysfunction related to SLE, and all contribute significantly to the poor quality of life experienced by individuals with SLE. The overall goal of the proposed research is to continue our investigation of biologic mechanisms contributing to SLE-related brain dysfunction. Reliant on our historical strong collaboration with those engaged in preclinical studies, the studies in Project 2 have been designed based on the murine model being studied in Project 1 and the two projects will inform each other. We propose using a novel PET tracer, 18F-SynVesT-1, to evaluate regional neuronal synaptic activity in individuals with SLE compared to healthy individuals (Aim 1). We will determine whether regional metabolic abnormalities, previously documented by us in SLE that correlate with poor cognitive performance, correlate with synaptic changes in the same regions. This will have therapeutic implications. In Aim 2 we propose using independent component analysis and artificial intelligence (AI) methods (deep learning) for analysis of rs-fMRI data to identify resting state functional networks for prediction of SLE-related cognitive impairment, depression, anxiety, and fatigue. Analyses of relationships between individual network expression scores and clinical, cognitive, behavioral and immunologic (assessments of serum DNRAb titers and other autoantibodies, complement, IFNα gene expression, quinolinic acid/kynurenic acid ratios) parameters will inform us about biological mechanisms. Once identified, the networks will also allow assessment of heterogeneity; each subject will have expression scores for 4 networks (cognition, depression, anxiety, fatigue) that will reflect relative contributions of each network to their brain dysfunction. A “brain signature” that reflects clinical phenotypes and can be used for precision treatment and assessment of treatment response. We will also use scalp EEG recording to determine whether alterations in theta-gamma wave co-modulation can act as a biomarker for SLE-related cognitive impairment (Aim 3). Abnormal theta-gamma coupling (TGC) in the hippocampus has been shown during a behavioral task in the DNRAb murine model and we expect that regional TGC abnormalities measured with superficial EEG in subjects with SLE will correlate with hypermetabolism in the hippocampus and related areas. Regional hypermetabolism in these areas has been previously shown by us to correlate with poor cognitive performance and we will assess whether TGC may be a biomarker for SLE-related cognitive impairment alone or in combination with the SLE-related networks identified in Aim 2. Successful completion of the proposed research will provide insight into biological mechanisms with potential for identification of therapeutic targets. Identification of accurate and sensitive biomarkers, resting state functional networks and/or altered TGC, will permit symptom and mechanism focused clinical trials. With Project 1, these studies will extend our understanding of pathogenesis of neuropsychiatric symptoms of SLE and may develop clinically useful biomarkers.