Personalized Estimates of Brain Structural Variability in Individuals With Early Psychosis

Abstract

Background Early psychosis in first-episode psychosis (FEP) and clinical high-risk (CHR) individuals has been associated with alterations in mean regional measures of brain morphology. Examination of variability in brain morphology could assist in quantifying the degree of brain structural heterogeneity in clinical relative to healthy control (HC) samples. Methods Structural magnetic resonance imaging data were obtained from CHR (n = 71), FEP (n = 72), and HC individuals (n = 55). Regional brain variability in cortical thickness (CT), surface area (SA), and subcortical volume (SV) was assessed with the coefficient of variation (CV). Furthermore, the person-based similarity index (PBSI) was employed to quantify the similarity of CT, SA, and SV profile of each individual to others within the same diagnostic group. Normative modeling of the PBSI-CT, PBSI-SA, and PBSI-SV was used to identify CHR and FEP individuals whose scores deviated markedly from those of the healthy individuals. Results There was no effect of diagnosis on the CV for any regional measure (P > .38). CHR and FEP individuals differed significantly from the HC group in terms of PBSI-CT (P < .0001), PBSI-SA (P < .0001), and PBSI-SV (P = .01). In the clinical groups, normative modeling identified 32 (22%) individuals with deviant PBSI-CT, 12 (8.4%) with deviant PBSI-SA, and 21 (15%) with deviant PBSI-SV; differences of small effect size indicated that individuals with deviant PBSI scores had lower IQ and higher psychopathology. Conclusions Examination of brain structural variability in early psychosis indicated heterogeneity at the level of individual profiles and encourages further large-scale examination to identify individuals that deviate markedly from normative reference data.

Neuroanatomical heterogeneity and homogeneity in individuals at clinical high risk for psychosis

“…The personalised estimates of inter-individual variability were investigated using the PBSI, calculated according to the formula below, for each SA, CT and SV profiles [ 34 – 37 ]. The process for calculating the PBSI scores begins with concatenating the respective regional measures into vectors that represent the profile of each specific brain phenotype; PBSI-SA, PBSI-CT and PBSI-SV, respectively.…”

“…Second, to quantify how similar an individuals’ brain profile is respective to a normative estimate, i.e. the average of the healthy control group (normativeness) [ 37 ]. The PBSI of the i th individual is the average correlation between his/her brain measures ( y i ) and the brain measures of any other individual of the reference sample ( y j , for j ≠ i ).…”

“…The Person-Based Similarity Index (PBSI) yields a personalised metric representing inter-subject correlations of neuroanatomical profiles [ 34 – 36 ], and has received recent attention in the context of psychiatric samples, including individuals with bipolar disorder [ 35 , 36 ] and schizophrenia [ 36 ]. The PBSI was recently compared between CHR-P ( n = 71), FEP ( n = 72) and HC ( n = 55) [ 37 ], revealing heterogeneity at a personalised level in CHR-P samples. Further, those demonstrating the most marked deviation also demonstrated generally lower IQ and poorer psychopathology [ 37 ].…”

“…The PBSI was recently compared between CHR-P ( n = 71), FEP ( n = 72) and HC ( n = 55) [ 37 ], revealing heterogeneity at a personalised level in CHR-P samples. Further, those demonstrating the most marked deviation also demonstrated generally lower IQ and poorer psychopathology [ 37 ]. These findings are in contrast with the former meta-analytic findings [ 33 ].…”

“…These findings are in contrast with the former meta-analytic findings [ 33 ]. However, these incongruities may be explained by the discrepant indices applied, the narrow focus of the brain regions studied meta-analytically [ 33 ] and/or the relatively small sample recruited for the PBSI investigations [ 37 ]. Taken together, the existing literature offers an ambiguous picture of neuroanatomical heterogeneity in the CHR-P state; as such, further investigations are warranted.…”