Similarities and differences between multivariate patterns of cognitive and socio-cognitive deficits in schizophrenia, bipolar disorder and related risk

Abstract

Cognition and social cognition anomalies in patients with bipolar disorder (BD) and schizophrenia (SCZ) have been largely documented, but the degree of overlap between the two disorders remains unclear in this regard. We used machine learning to generate and combine two classifiers based on cognitive and socio-cognitive variables, thus delivering unimodal and multimodal signatures aimed at discriminating BD and SCZ from two independent groups of Healthy Controls (HC1 and HC2 respectively). Multimodal signatures discriminated well between patients and controls in both the HC1-BD and HC2-SCZ cohorts. Although specific disease-related deficits were characterized, the HC1 vs. BD signature successfully discriminated HC2 from SCZ, and vice-versa. Such combined signatures allowed to identify also individuals at First Episode of Psychosis (FEP), but not subjects at Clinical High Risk (CHR), which were classified neither as patients nor as HC. These findings suggest that both trans-diagnostic and disease-specific cognitive and socio-cognitive deficits characterize SCZ and BD. Anomalous patterns in these domains are also relevant to early stages of disease and offer novel insights for personalized rehabilitative programs.

Digital phenotyping correlates of mobile cognitive measures in schizophrenia: A multisite global mental health feasibility trial

“…A 2023 review of repetition in DSM-5 constructs found that difficulty with concentration is the second most repeated symptom and featured in 17 unique diagnoses [ 32 ]. Using cross-sectional measures of working memory accuracy and global memory quotient in patients with bipolar disorder and schizophrenia, another recent paper suggested metrics of cognitive impairment may serve as intermediate phenotypes [ 33 ] The use of novel cognitive measures to enhance the stratification of mental health disorders thus offers a potential application of this work. But before these cognitive tasks can be used for monitoring disease progression or as diagnostic tools, more work is needed to validate their use against both gold standards and real-world functional outcomes.…”

Advances in the understanding of the pathophysiology of schizophrenia and bipolar disorder through induced pluripotent stem cell models

“…Therefore, common alterations traced in schizophrenia and bipolar disorder in neurobiological pathways may be linked to psychopathological or clinical dimensions rather than to a specific diagnosis. 27 , 32 , 33 , 255 , 256 Consequently, a detailed clinical characterization — including the content of psychotic symptoms, the temporal pattern of the association between psychotic symptoms and mood symptoms, and neurodevelopmental trajectories — may help to distinguish more clearly which patients showed substantial overlap in terms of genetic background, etiopathogenetic mechanisms, clinical presentations, and outcomes.…”