This study was the first application of the robust and large scale normative models developed by Ge and colleagues to a clinical sample. Normative modeling provides standards or "norms" at different ages for specific measures. In this case, normative models were generated for each region in the brain in more than 37,000 healthy individuals. These models can then be applied to other datasets, for example patients with a specific mental illness, to determine the degree to which their brains deviate from the norm.
This study investigated deviations in brain morphometry in 1340 individuals at risk for developing psychosis and 1237 healthy individuals pooled from 29 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group. For each regional measure, deviations from the normative range of variation were quantified. Extreme deviations were termed as infranormal (lower end, i.e., reductions in those regions) and supranormal (higher end, referring to enlargement in those regions) deviations corresponding to the 5th percentile and 95th percentiles, respectively. Average deviation scores (ADS) were computed to quantify overall deviation across the entire brain. Finally, links between regional and average deviation scores with positive symptoms, cognition, and conversion to a psychotic disorder were assessed.
Complete overlap was found in the distributions of deviations from the normative reference models in all brain regions of individuals at risk for psychosis (CHR-P), those who later converted to full-blown psychosis (CHR-PC), and healthy individuals. The figure below depicts the example for the left and right hippocampus, which was the region with the greatest difference between individuals at risk for psychosis and healthy individuals.
This was the largest study to investigate deviations in normative trajectories of brain morphometry in individuals at clinical high risk for psychosis. Regional brain morphometry in people at risk for psychosis is nested within normative variation, and is weakly associated with symptoms and cognition. Thus, macroscale brain morphometry may not adequately explain psychosis risk.
This work has been published in JAMA Psychiatry. Readers can access the full article at: https://jamanetwork.com/journals/jamapsychiatry/fullarticle/2810624.
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