Advanced Brain-Age in Psychotic Psychopathology: Evidence for Transdiagnostic Neurodevelopmental Origins

Abstract

Schizophrenia is characterized by abnormal brain structure such as global reductions in gray matter volume. Machine learning models trained to estimate the age of brains from structural neuroimaging data consistently show advanced brain-age to be associated with schizophrenia. Yet, it is unclear whether advanced brain-age is specific to schizophrenia compared to other psychotic disorders, and whether evidence that brain structure is “older” than chronological age actually reflects neurodevelopmental rather than atrophic processes. It is also unknown whether advanced brain-age is associated with genetic liability for psychosis carried by biological relatives of people with schizophrenia. We used the Brain-Age Regression Analysis and Computation Utility Software (BARACUS) prediction model and calculated the residualized brain-age gap of 332 adults (163 individuals with psychotic disorders: 105 schizophrenia, 17 schizoaffective disorder, 41 bipolar I disorder with psychotic features; 103 first-degree biological relatives; 66 controls). The model estimated advanced brain-ages for people with psychosis in comparison to controls and relatives, with no differences among psychotic disorders or between relatives and controls. Specifically, the model revealed an enlarged brain-age gap for schizophrenia and bipolar disorder with psychotic features. Advanced brain-age was associated with lower cognitive and general functioning in the full sample. Among relatives, cognitive performance and schizotypal symptoms were related to brain-age gap, suggesting that advanced brain-age is associated with the subtle expressions associated with psychosis. Exploratory longitudinal analyses suggested that brain aging was not accelerated in individuals with a psychotic disorder. In sum, we found that people with psychotic disorders, irrespective of specific diagnosis or illness severity, show indications of non-progressive, advanced brain-age. These findings support a transdiagnostic, neurodevelopmental formulation of structural brain abnormalities in psychotic psychopathology.

Potential of brain age in identifying early cognitive impairment in subcortical small-vessel disease patients

“…Consistent with previous studies ( Cole, 2020 ; Demro et al, 2022 ), structural MRI features showed prominent potential for the prediction of brain age. In the present study, brain age-related GMV features were mainly distributed in the subcortical system (e.g., thalamus and hippocampus) and dorsal attention network.…”

Predicting aging trajectories of decline in brain volume, cortical thickness and fractional anisotropy in schizophrenia

“…Chen et al also found that the normalized predicted age difference did not show a significant correlation with the duration of illness in schizophrenia 23 . We found that previous studies had inconsistent results on the association between the brain age gap and duration of illness in individuals with schizophrenia 14,17,21,22 . The relevant studies are still limited.…”

“…Huang and colleagues indicated that the brain age gap of young individuals with schizophrenia was larger than that of healthy controls; however, the same result was not observed in middle-aged individuals with schizophrenia 21 . Demro et al demonstrated that the disease course of psychotic illness was not significantly correlated with their brain age gap 14 . Chen et al also found that the normalized predicted age difference did not show a significant correlation with the duration of illness in schizophrenia 23 .…”

“…The difference between brain age and chronological age, termed the brain age gap, can serve as a parameter for determining correlations with participants' clinicodemographic characteristics 9 . T1-weighted MRI studies have used brain age to examine disease-related brain deterioration in schizophrenia [10][11][12][13][14][15][16] . Schnack and colleagues reported that the brain ages of individuals with schizophrenia were approximately 3.36 years higher than their chronological ages 10 .…”

Sex-difference in the association between social drinking, structural brain aging and cognitive function in older individuals free of cognitive impairment

“…Premature, advanced, or accelerated brain aging are terms used to describe the gap between chronological age and estimated brain age derived from different machine learning algorithms. Accelerated brain aging is a non-specific observation that has been reported in many conditions such as major depression ( 47 – 50 ), psychosis ( 51 , 52 ), obsessive compulsive disorder ( 53 ), traumatic brain injury ( 54 , 55 ), tobacco smoking ( 56 ), diabetes mellitus ( 57 , 58 ), glioma patients following radiotherapy ( 59 ), and in healthy individuals with inadequate sleep ( 60 ). Few studies have reported negative association between accelerated brain aging and cognitive performance in patients with major psychoses ( 51 ), in older patients with depressive symptoms ( 61 ) and in patients with traumatic brain injury ( 54 ).…”