Data-driven neuroimaging reveals cognition-circuit pathology prior to diagnosis in psychotic disorders

BACKGROUND: Schizophrenia is a diverse disorder comprising positive, negative, and cognitive symptoms. While several cognitive domains have been alleged to influence symptom severity and quality of life, impaired information processing speed (IPS) is the most profoundly affected and is present even before a diagnosis of a psychotic disorder. Although extensively studied, reliable and reproducible pathological neural circuitry leading to cognitive dysfunction has yet to be fully identified or understood. OBJECTIVE: Our study seeks to identify the neurobiological connections responsible for diminished processing speed in a group of patients with psychotic disorders and a group of individuals at risk to develop a psychotic disorder. METHODS: This data-driven evaluation of resting-state fMRI data and cognitive testing considers two populations: one cohort of adults diagnosed with psychotic disorders and another cohort of individuals identified as being at risk for developing psychotic disorders (ShangHai At-Risk for Psychosis). The images were processed and evaluated using multivariate pattern analysis (MVPA) to compare brain connectivity to information processing speed. The MVPA calculations generated a map to determine the regions where brain connectivity has the strongest correlation to information processing speed as measured by the Brief Assessment in Cognition for Schizophrenia (BACS). RESULTS: The results of the cognitive assessments demonstrate that information processing speed (IPS) is the most impaired domain of cognition in adults with psychotic disorders. Multivariate distance matrix regression (MDMR) was used to identify the cerebellum as the specific brain location where connectivity was most strongly correlated to information processing speed. Specifically, the cerebellar (CBM) connectivity to the dorsal medial prefrontal cortex (dmPFC) exhibited the strongest positive correlation with IPS. The cohort of individuals diagnosed with a psychotic disorder (n = 103) exhibited a moderately strong relationship (r = 0.396, p = 0.000036) between the CBM-dmPFC coactivation and IPS. This finding was then replicated in the SHARP dataset. The clinical high risk sample (n = 137) also identified the CBM-dmPFC circuit as the strongest correlation to information processing speed (r=0.39, p = 0.000002057). Furthermore, the CBM-dmPFC circuit relationship to IPS became stronger as we considered the most impaired subjects. Individuals who would go on to be diagnosed with a psychotic disorder (converters, n = 19) exhibited the strongest relationship between CBM-dmPFC and information processing speed (r = 0.56, p = 0.01). CONCLUSIONS: The reduction in functional connectivity between cerebellum and dmPFC appears to be critically related to the generalized decrease in information processing speed in patients with psychotic disorders and patients at risk of developing a psychotic disorder in the future. The finding is reproduced in two culturally, linguistically, and geographically disparate populations. Interestingly, the finding demonstrates a link between the functional dysconnectivity and cognitive dysfunction in the years before and during the onset of a diagnosis of a psychotic disorder. The research indicates a diagnostic role for assessing information processing speed to identify prodromal patients at risk of developing a psychotic disorder. Finally, the identification of a specific neurological circuit related to impaired cognition would provide a therapeutic target to alleviate cognitive deficits in patients with psychotic disorders in the future