Multiscale Functional Dysconnectivity Reveals Sex-Dominant Neurosubtypes and Predicts Unique Neurocognitive Pathways in Psychosis
Psychotic disorders are severe mental conditions whose biological underpinnings remain elusive. This is in part due to marked heterogeneity, which may have precluded advances in precise understanding and treatment of the disorders. Previous work has tried to elucidate this heterogeneity; nevertheless, sex, as an important biological variable, has not been well accounted for despite established…
Psychotic disorders present complex biological factors, partly due to significant variability in affected individuals. Attempts to clarify this variability have been made, yet sex, a crucial biological factor, has not been comprehensively considered despite known differences. Utilizing data from the BSNIP consortium, comprising 1,753 individuals (64.3% with psychosis, including 571 females and 556 males, and 35.7% controls, including 369 females and 257 males), researchers conducted resting-state functional magnetic resonance imaging analyses.
The objective was to extract multiscale functional network connectivity and identify distinct neurobiological profiles through unsupervised learning techniques, termed "sex-dominant Psychosis Imaging Neurosubtypes" or PINs.
Four PINs were identified – two female-dominant (fPIN-1 and fPIN-2) and two male-dominant (mPIN-1 and mPIN-2). Each PIN showcased unique dysconnectivity patterns that played a unique role in cognitive impairments. The researchers developed a method to predict cognitive performance using these PIN-specific dysconnectivity patterns, which correlated with cognitive measurements and exhibited PIN-specific reductions compared to controls.
This confirmed the association between PINs and cognitive performance. Furthermore, fPIN-2's distinct dysconnectivity patterns were linked to positive and negative symptom scores.
The findings corroborate the existence of sex-dominant neurobiological heterogeneity in psychotic disorders, with sex-dominant PINs exhibiting unique dysconnectivity patterns that impact cognitive and symptom outcomes. Despite clinical similarities among neurosubtypes, these results emphasize the importance of sex as a critical biological variable in understanding psychosis heterogeneity.
This insight offers potential for identifying more precise biomarkers for disease characterization and developing personalized treatment strategies.
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