Predicting and Characterizing Neurodegenerative Subtypes with Multimodal Neurocognitive Signatures of Social and Cognitive Processes

Abstract

Background: Social cognition is critically compromised across neurodegenerative diseases, including the behavioral variant frontotemporal dementia (bvFTD), Alzheimer’s disease (AD), and Parkinson’s disease (PD). However, no previous study has used social cognition and other cognitive tasks to predict diagnoses of these conditions, let alone reporting the brain correlates of prediction outcomes. Objective: We performed a diagnostic classification analysis using social cognition, cognitive screening (CS), and executive function (EF) measures, and explored which anatomical and functional networks were associated with main predictors. Methods: Multiple group discriminant function analyses (MDAs) and ROC analyses of social cognition (facial emotional recognition, theory of mind), CS, and EF were implemented in 223 participants (bvFTD, AD, PD, controls). Gray matter volume and functional connectivity correlates of top discriminant scores were investigated. Results: Although all patient groups revealed deficits in social cognition, CS, and EF, our classification approach provided robust discriminatory characterizations. Regarding controls, probabilistic social cognition outcomes provided the best characterization for bvFTD (together with CS) and PD, but not AD (for which CS alone was the best predictor). Within patient groups, the best MDA probabilities scores yielded high classification rates for bvFTD versus PD (98.3% , social cognition), AD versus PD (98.6% , social cognition + CS), and bvFTD versus AD (71.7% , social cognition + CS). Top MDA scores were associated with specific patterns of atrophy and functional networks across neurodegenerative conditions. Conclusion: Standardized validated measures of social cognition, in combination with cognitive screening, can provide a dimensional classification with specific pathophysiological markers of neurodegeneration diagnoses.

Multidimensional Clinical Assessment in Frontotemporal Dementia and Its Spectrum in Latin America and the Caribbean: A Narrative Review and a Glance at Future Challenges

“…The validity and discriminative capacity of the IFS was studied in patients with bvFTD, AD, and healthy controls. The IFS differentiates patients with dementia from healthy controls ( 50 , 61 ) and patients with bvFTD from AD ( 50 ). Two studies, one in Argentina and the other in Peru, suggested that the IFS presented greater clinical utility in differentiating bvFTD from AD in comparison with the FAB ( 62 , 63 ).…”

“…Currently, social cognition is primarily assessed with the Mini-SEA. Although there are promising results on the diagnostic utility of the Mini-SEA for the differential diagnosis of bvFTD of PD and AD ( 61 , 198 ), social cognition assessment still faces essential limitations.…”

“…In LAC, research and clinical evaluation of FTD and its spectrum have been conducted by a small group of professionals who share common needs and interests ( 61 , 272 ). Nevertheless, transfer from research to clinical practice is restricted and significant knowledge gaps limit the implementation of multidimensional assessments.…”

“…Additionally, a homogenous evaluation practice could enable providing guidelines for implementing a multiple step approach in the evaluation. This is particularly relevant in LAC considering the lack of knowledge on FTD and its spectrum in health professionals ( 40 , 61 ). In this effort, integrating clinical practice and research is relevant for generating new knowledge to evaluate the clinical utility of a multidimensional assessment, identifying patients that could benefit from this assessment, and elaborating the evidence-based guidelines to define the correct flow for each patient.…”

The neurocognitive impact of loneliness and social networks on social adaptation

“…The resulting functional connectivity (FC) correlation coe cients between all pairs of regions (AAL atlas) were used to perform Spearman's correlations with the scores of each predictor: loneliness (UCLA score), and social network (LSNS-R score). Following procedures from recent research [50][51][52] signi cance thresholding of neuroimaging results was set to p ≤ .001 (uncorrected). Uncorrected statistical threshold has been used previously to avoid the detrimental effects of liberal primary thresholds on false positives (especially in modest sample sizes such as ours) [53][54][55] .…”