Centre for Youth Mental Health - Research Publications

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Non-psychotic Outcomes in Young People at Ultra-High Risk of Developing a Psychotic Disorder: A Long-Term Follow-up Study

Spiteri-Staines, AE ; Yung, AR ; Lin, A ; Hartmann, JA ; Amminger, P ; Mcgorry, PD ; Thompson, A ; Wood, SJ ; Nelson, B (OXFORD UNIV PRESS, 2024-02-16)

BACKGROUND: The majority of individuals at ultra-high risk (UHR) for psychosis do not transition to a full threshold psychotic disorder. It is therefore important to understand their longer-term clinical and functional outcomes, particularly given the high prevalence of comorbid mental disorders in this population at baseline. AIMS: This study investigated the prevalence of non-psychotic disorders in the UHR population at entry and long-term follow-up and their association with functional outcomes. Persistence of UHR status was also investigated. STUDY DESIGN: The sample comprised 102 UHR young people from the Personal Assessment and Crisis Evaluation (PACE) Clinic who had not transitioned to psychosis by long-term follow-up (mean = 8.8 years, range = 6.8-12.1 years since baseline). RESULTS: Eighty-eight percent of participants at baseline were diagnosed with at least one mental disorder, the majority of which were mood disorders (78%), anxiety disorders (35%), and substance use disorders (SUDs) (18%). This pattern of disorder prevalence continued at follow-up, though prevalence was reduced, with 52% not meeting criteria for current non-psychotic mental disorder. However, 35% of participants developed a new non-psychotic mental disorder by follow-up. Presence of a continuous non-psychotic mental disorder was associated with poorer functional outcomes at follow-up. 28% of participants still met UHR criteria at follow-up. CONCLUSIONS: The study adds to the evidence base that a substantial proportion of UHR individuals who do not transition to psychosis experience persistent attenuated psychotic symptoms and persistent and incident non-psychotic disorders over the long term. Long-term treatment and re-entry into services is indicated.
A multivariate cognitive approach to predict social functioning in recent onset psychosis in response to computerized cognitive training

Walter, N ; Wenzel, J ; Haas, SS ; Squarcina, L ; Bonivento, C ; Ruef, A ; Dwyer, D ; Lichtenstein, T ; Bastruek, O ; Stainton, A ; Antonucci, LA ; Brambilla, P ; Wood, SJ ; Upthegrove, R ; Borgwardt, S ; Lencer, R ; Meisenzahl, E ; Salokangas, RKR ; Pantelis, C ; Bertolino, A ; Koutsouleris, N ; Kambeitz, J ; Kambeitz-Ilankovic, L (PERGAMON-ELSEVIER SCIENCE LTD, 2024-01-10)

Clinical and neuroimaging data has been increasingly used in recent years to disentangle heterogeneity of treatment response to cognitive training (CT) and predict which individuals may achieve the highest benefits. CT has small to medium effects on improving cognitive and social functioning in recent onset psychosis (ROP) patients, who show the most profound cognitive and social functioning deficits among psychiatric patients. We employed multivariate pattern analysis (MVPA) to investigate the potential of cognitive data to predict social functioning improvement in response to 10 h of CT in patients with ROP. A support vector machine (SVM) classifier was trained on the naturalistic data of the Personalized Prognostic Tools for Early Psychosis Management (PRONIA) study sample to predict functioning in an independent sample of 70 ROP patients using baseline cognitive data. PRONIA is a part of a FP7 EU grant program that involved 7 sites across 5 European countries, designed and conducted with the main aim of identifying (bio)markers associated with an enhanced risk of developing psychosis in order to improve early detection and prognosis. Social functioning was predicted with a balanced accuracy (BAC) of 66.4% (Sensitivity 78.8%; Specificity 54.1%; PPV 60.5%; NPV 74.1%; AUC 0.64; P = 0.01). The most frequently selected cognitive features (mean feature weights > ± 0.2) included the (1) correct number of symbol matchings within the Digit Symbol Substitution Test, (2) the number of distracting stimuli leading to an error within 300 and 200 trials in the Continuous Performance Test and (3) the dynamics of verbal fluency between 15 and 30 s within the Verbal Fluency Test, phonetic part. Next, the SVM classifier generated on the PRONIA sample was applied to the intervention sample, that obtained 54 ROP patients who were randomly assigned to a social cognitive training (SCT) or treatment as usual (TAU) group and dichotomized into good (GF-S ≥ 7) and poor (GF-S < 7) functioning patients based on their level of Global Functioning-Social (GF-S) score at follow-up (FU). By applying the initial PRONIA classifier, using out-of-sample cross-validation (OOCV) to the sample of ROP patients who have undergone the CT intervention, a BAC of 59.3% (Sensitivity 70.4%; Specificity 48.1%; PPV 57.6%; NPV 61.9%; AUC 0.63) was achieved at T0 and a BAC of 64.8% (Sensitivity 66.7%; Specificity 63.0%; PPV 64.3%; NPV 65.4%; AUC 0.66) at FU. After SCT intervention, a significant improvement in predicted social functioning values was observed in the SCT compared to TAU group (P ≤0.05; ES[Cohens' d] = 0.18). Due to a small sample size and modest variance of social functioning of the intervention sample it was not feasible to predict individual response to SCT in the current study. Our findings suggest that the use of baseline cognitive data could provide a robust individual estimate of future social functioning, while prediction of individual response to SCT using cognitive data that can be generated in the routine patient care remains to be addressed in large-scale cognitive training trials.
Acceptability and feasibility of a multidomain harmonized data collection protocol in youth mental health

Youn, S ; Mamsa, S ; Allott, K ; Berger, M ; Polari, A ; Rice, S ; Schmaal, L ; Wood, S ; Lavoie, S (WILEY, 2023-05)

OBJECTIVE: To develop targeted treatment for young people experiencing mental illness, a better understanding of the biological, psychological, and social changes is required, particularly during the early stages of illness. To do this, large datasets need to be collected using standardized methods. A harmonized data collection protocol was tested in a youth mental health research setting to determine its acceptability and feasibility. METHOD: Eighteen participants completed the harmonization protocol, including a clinical interview, self-report measures, neurocognitive measures, and mock assessments of magnetic resonance imaging (MRI) and blood. The feasibility of the protocol was assessed by recording recruitment rates, study withdrawals, missing data, and protocol deviations. Subjective responses from participant surveys and focus groups were used to examine the acceptability of the protocol. RESULTS: Twenty-eight young people were approached, 18 consented, and four did not complete the study. Most participants reported positive subjective impressions of the protocol as a whole and showed interest in participating in the study again, if given the opportunity. Participants generally perceived the MRI and neurocognitive tasks as interesting and suggested that the assessment of clinical presentation could be shortened. CONCLUSION: Overall, the harmonized data collection protocol appeared to be feasible and generally well-accepted by participants. With a majority of participants finding the assessment of clinical presentation too long and repetitive, the authors have made suggestions to shorten the self-reports. The broader implementation of this protocol could allow researchers to create large datasets and better understand how psychopathological and neurobiological changes occur in young people with mental ill-health.
Combining Clinical With Cognitive or Magnetic Resonance Imaging Data for Predicting Transition to Psychosis in Ultra High-Risk Patients: Data From the PACE 400 Cohort.

Hartmann, S ; Cearns, M ; Pantelis, C ; Dwyer, D ; Cavve, B ; Byrne, E ; Scott, I ; Yuen, HP ; Gao, C ; Allott, K ; Lin, A ; Wood, SJ ; Wigman, JTW ; Amminger, GP ; McGorry, PD ; Yung, AR ; Nelson, B ; Clark, SR (Elsevier BV, 2024-04)

BACKGROUND: Multimodal modeling that combines biological and clinical data shows promise in predicting transition to psychosis in individuals who are at ultra-high risk. Individuals who transition to psychosis are known to have deficits at baseline in cognitive function and reductions in gray matter volume in multiple brain regions identified by magnetic resonance imaging. METHODS: In this study, we used Cox proportional hazards regression models to assess the additive predictive value of each modality-cognition, cortical structure information, and the neuroanatomical measure of brain age gap-to a previously developed clinical model using functioning and duration of symptoms prior to service entry as predictors in the Personal Assessment and Crisis Evaluation (PACE) 400 cohort. The PACE 400 study is a well-characterized cohort of Australian youths who were identified as ultra-high risk of transitioning to psychosis using the Comprehensive Assessment of At Risk Mental States (CAARMS) and followed for up to 18 years; it contains clinical data (from N = 416 participants), cognitive data (n = 213), and magnetic resonance imaging cortical parameters extracted using FreeSurfer (n = 231). RESULTS: The results showed that neuroimaging, brain age gap, and cognition added marginal predictive information to the previously developed clinical model (fraction of new information: neuroimaging 0%-12%, brain age gap 7%, cognition 0%-16%). CONCLUSIONS: In summary, adding a second modality to a clinical risk model predicting the onset of a psychotic disorder in the PACE 400 cohort showed little improvement in the fit of the model for long-term prediction of transition to psychosis.
Effects of risperidone/paliperidone versus placebo on cognitive functioning over the first 6 months of treatment for psychotic disorder: secondary analysis of a triple-blind randomised clinical trial

Allott, K ; Yuen, HP ; Baldwin, L ; O'Donoghue, B ; Fornito, A ; Chopra, S ; Nelson, B ; Graham, J ; Kerr, MJJ ; Proffitt, T-M ; Ratheesh, A ; Alvarez-Jimenez, M ; Harrigan, S ; Brown, E ; Thompson, ADD ; Pantelis, C ; Berk, M ; McGorry, PDD ; Francey, SMM ; Wood, SJJ (SPRINGERNATURE, 2023-06-10)

The drivers of cognitive change following first-episode psychosis remain poorly understood. Evidence regarding the role of antipsychotic medication is primarily based on naturalistic studies or clinical trials without a placebo arm, making it difficult to disentangle illness from medication effects. A secondary analysis of a randomised, triple-blind, placebo-controlled trial, where antipsychotic-naive patients with first-episode psychotic disorder were allocated to receive risperidone/paliperidone or matched placebo plus intensive psychosocial therapy for 6 months was conducted. A healthy control group was also recruited. A cognitive battery was administered at baseline and 6 months. Intention-to-treat analysis involved 76 patients (antipsychotic medication group: 37; 18.6Mage [2.9] years; 21 women; placebo group: 39; 18.3Mage [2.7]; 22 women); and 42 healthy controls (19.2Mage [3.0] years; 28 women). Cognitive performance predominantly remained stable (working memory, verbal fluency) or improved (attention, processing speed, cognitive control), with no group-by-time interaction evident. However, a significant group-by-time interaction was observed for immediate recall (p = 0.023), verbal learning (p = 0.024) and delayed recall (p = 0.005). The medication group declined whereas the placebo group improved on each measure (immediate recall: p = 0.024; ηp2 = 0.062; verbal learning: p = 0.015; ηp2 = 0.072 both medium effects; delayed recall: p = 0.001; ηp2 = 0.123 large effect). The rate of change for the placebo and healthy control groups was similar. Per protocol analysis (placebo n = 16, medication n = 11) produced similar findings. Risperidone/paliperidone may worsen verbal learning and memory in the early months of psychosis treatment. Replication of this finding and examination of various antipsychotic agents are needed in confirmatory trials. Antipsychotic effects should be considered in longitudinal studies of cognition in psychosis.Trial registration: Australian New Zealand Clinical Trials Registry ( http://www.anzctr.org.au/ ; ACTRN12607000608460).
The relationship between subjective sleep disturbance and attenuated psychotic symptoms after accounting for anxiety and depressive symptoms

Formica, MJC ; Fuller-Tyszkiewicz, M ; Hickie, I ; Olive, L ; Wood, SJ ; Purcell, R ; Yung, AR ; Phillips, LJ ; Nelson, B ; Pantelis, C ; Mcgorry, PD ; Hartmann, JA (ELSEVIER, 2023-08)

BACKGROUND AND HYPOTHESES: Sleep disturbances are increasingly recognized as cooccurring with psychotic symptoms. The potential importance of this relationship is complicated when considering the effects of anxiety and depressive symptoms which commonly present in early-stage illness states. This study aimed to investigate the relationship between self-reported sleep disturbance on the development of attenuated psychotic symptoms (APS) cross-sectionally and longitudinally while adjusting for roles of anxiety and depressive symptoms. DESIGN: Eight-hundred and two help-seeking young people aged 12 to 25 years who engaged with our Australian early intervention services were included in the study (the "Transitions" cohort). Cross sectional mediation and cross-lagged longitudinal (12-month) mediation models were developed with outcomes being different APS domains. RESULTS: Only baseline excessive daytime sleepiness predicted later APS when accounting for previous APS, anxiety and depressive symptomatology. Cross sectionally, self-reported sleep disturbance showed both direct and indirect predictive relationships with all APS domains. Partial mediation through anxiety and depression was shown for unusual thought content, perceptual abnormalities, and disorganised speech, while full mediation through depression was shown for non-bizarre ideas. CONCLUSIONS: The specificity of the relationship between self-reported sleep disturbance on APS highlights the potential for different roles in mechanistic models of psychotic symptom expression. This further indicates the need for further experimental research to illuminate potential causal pathways. Future research should continue to use continuous, symptom level approaches across a range of timeframes to more accurately model the complex dynamics present in the sleep-psychosis relationship.
Structural and Functional Brain Patterns Predict Formal Thought Disorder's Severity and Its Persistence in Recent-Onset Psychosis: Results From the PRONIA Study

Buciuman, M-O ; Oeztuerk, OF ; Popovic, D ; Enrico, P ; Ruef, A ; Bieler, N ; Sarisik, E ; Weiske, J ; Dong, MS ; Dwyer, DB ; Kambeitz-Ilankovic, L ; Haas, SS ; Stainton, A ; Ruhrmann, S ; Chisholm, K ; Kambeitz, J ; Riecher-Rossler, A ; Upthegrove, R ; Schultze-Lutter, F ; Salokangas, RKR ; Hietala, J ; Pantelis, C ; Lencer, R ; Meisenzahl, E ; Wood, SJ ; Brambilla, P ; Borgwardt, S ; Falkai, P ; Antonucci, LA ; Bertolino, A ; Liddle, P ; Koutsouleris, N (ELSEVIER, 2023-12)

BACKGROUND: Formal thought disorder (FThD) is a core feature of psychosis, and its severity and long-term persistence relates to poor clinical outcomes. However, advances in developing early recognition and management tools for FThD are hindered by a lack of insight into the brain-level predictors of FThD states and progression at the individual level. METHODS: Two hundred thirty-three individuals with recent-onset psychosis were drawn from the multisite European Prognostic Tools for Early Psychosis Management study. Support vector machine classifiers were trained within a cross-validation framework to separate two FThD symptom-based subgroups (high vs. low FThD severity), using cross-sectional whole-brain multiband fractional amplitude of low frequency fluctuations, gray matter volume and white matter volume data. Moreover, we trained machine learning models on these neuroimaging readouts to predict the persistence of high FThD subgroup membership from baseline to 1-year follow-up. RESULTS: Cross-sectionally, multivariate patterns of gray matter volume within the salience, dorsal attention, visual, and ventral attention networks separated the FThD severity subgroups (balanced accuracy [BAC] = 60.8%). Longitudinally, distributed activations/deactivations within all fractional amplitude of low frequency fluctuation sub-bands (BACslow-5 = 73.2%, BACslow-4 = 72.9%, BACslow-3 = 68.0%), gray matter volume patterns overlapping with the cross-sectional ones (BAC = 62.7%), and smaller frontal white matter volume (BAC = 73.1%) predicted the persistence of high FThD severity from baseline to follow-up, with a combined multimodal balanced accuracy of BAC = 77%. CONCLUSIONS: We report the first evidence of brain structural and functional patterns predictive of FThD severity and persistence in early psychosis. These findings open up avenues for the development of neuroimaging-based diagnostic, prognostic, and treatment options for the early recognition and management of FThD and associated poor outcomes.
Inflammatory subgroups of schizophrenia and their association with brain structure: A semi-supervised machine learning examination of heterogeneity

Lalousis, PA ; Schmaal, L ; Wood, SJ ; Reniers, RLEP ; Cropley, VL ; Watson, A ; Pantelis, C ; Suckling, J ; Barnes, NM ; Pariante, C ; Jones, PB ; Joyce, E ; Barnes, TRE ; Lawrie, SM ; Husain, N ; Dazzan, P ; Deakin, B ; Weickert, CS ; Upthegrove, R (ACADEMIC PRESS INC ELSEVIER SCIENCE, 2023-10)

OBJECTIVE: Immune system dysfunction is hypothesised to contribute to structural brain changes through aberrant synaptic pruning in schizophrenia. However, evidence is mixed and there is a lack of evidence of inflammation and its effect on grey matter volume (GMV) in patients. We hypothesised that inflammatory subgroups can be identified and that the subgroups will show distinct neuroanatomical and neurocognitive profiles. METHODS: The total sample consisted of 1067 participants (chronic patients with schizophrenia n = 467 and healthy controls (HCs) n = 600) from the Australia Schizophrenia Research Bank (ASRB) dataset, together with 218 recent-onset patients with schizophrenia from the external Benefit of Minocycline on Negative Symptoms of Psychosis: Extent and Mechanism (BeneMin) dataset. HYDRA (HeterogeneitY through DiscRiminant Analysis) was used to separate schizophrenia from HC and define disease-related subgroups based on inflammatory markers. Voxel-based morphometry and inferential statistics were used to explore GMV alterations and neurocognitive deficits in these subgroups. RESULTS: An optimal clustering solution revealed five main schizophrenia groups separable from HC: Low Inflammation, Elevated CRP, Elevated IL-6/IL-8, Elevated IFN-γ, and Elevated IL-10 with an adjusted Rand index of 0.573. When compared with the healthy controls, the IL-6/IL-8 cluster showed the most widespread, including the anterior cingulate, GMV reduction. The IFN-γ inflammation cluster showed the least GMV reduction and impairment of cognitive performance. The CRP and the Low Inflammation clusters dominated in the younger external dataset. CONCLUSIONS: Inflammation in schizophrenia may not be merely a case of low vs high, but rather there are pluripotent, heterogeneous mechanisms at play which could be reliably identified based on accessible, peripheral measures. This could inform the successful development of targeted interventions.
Network-Based Spreading of Gray Matter Changes Across Different Stages of Psychosis

Chopra, S ; Segal, A ; Oldham, S ; Holmes, A ; Sabaroedin, K ; Orchard, ER ; Francey, SM ; O'Donoghue, B ; Cropley, V ; Nelson, B ; Graham, J ; Baldwin, L ; Tiego, J ; Yuen, HP ; Allott, K ; Alvarez-Jimenez, M ; Harrigan, S ; Fulcher, BD ; Aquino, K ; Pantelis, C ; Wood, SJ ; Bellgrove, M ; Mcgorry, PD ; Fornito, A (AMER MEDICAL ASSOC, 2023-12)

IMPORTANCE: Psychotic illness is associated with anatomically distributed gray matter reductions that can worsen with illness progression, but the mechanisms underlying the specific spatial patterning of these changes is unknown. OBJECTIVE: To test the hypothesis that brain network architecture constrains cross-sectional and longitudinal gray matter alterations across different stages of psychotic illness and to identify whether certain brain regions act as putative epicenters from which volume loss spreads. DESIGN, SETTINGS, AND PARTICIPANTS: This case-control study included 534 individuals from 4 cohorts, spanning early and late stages of psychotic illness. Early-stage cohorts included patients with antipsychotic-naive first-episode psychosis (n = 59) and a group of patients receiving medications within 3 years of psychosis onset (n = 121). Late-stage cohorts comprised 2 independent samples of people with established schizophrenia (n = 136). Each patient group had a corresponding matched control group (n = 218). A sample of healthy adults (n = 356) was used to derive representative structural and functional brain networks for modeling of network-based spreading processes. Longitudinal illness-related and antipsychotic-related gray matter changes over 3 and 12 months were examined using a triple-blind randomized placebo-control magnetic resonance imaging study of the antipsychotic-naive patients. All data were collected between April 29, 2008, and January 15, 2020, and analyses were performed between March 1, 2021, and January 14, 2023. MAIN OUTCOMES AND MEASURES: Coordinated deformation models were used to estimate the extent of gray matter volume (GMV) change in each of 332 parcellated areas by the volume changes observed in areas to which they were structurally or functionally coupled. To identify putative epicenters of volume loss, a network diffusion model was used to simulate the spread of pathology from different seed regions. Correlations between estimated and empirical spatial patterns of GMV alterations were used to quantify model performance. RESULTS: Of 534 included individuals, 354 (66.3%) were men, and the mean (SD) age was 28.4 (7.4) years. In both early and late stages of illness, spatial patterns of cross-sectional volume differences between patients and controls were more accurately estimated by coordinated deformation models constrained by structural, rather than functional, network architecture (r range, >0.46 to <0.57; P < .01). The same model also robustly estimated longitudinal volume changes related to illness (r ≥ 0.52; P < .001) and antipsychotic exposure (r ≥ 0.50; P < .004). Network diffusion modeling consistently identified, across all 4 data sets, the anterior hippocampus as a putative epicenter of pathological spread in psychosis. Epicenters of longitudinal GMV loss were apparent in posterior cortex early in the illness and shifted to the prefrontal cortex with illness progression. CONCLUSION AND RELEVANCE: These findings highlight a central role for white matter fibers as conduits for the spread of pathology across different stages of psychotic illness, mirroring findings reported in neurodegenerative conditions. The structural connectome thus represents a fundamental constraint on brain changes in psychosis, regardless of whether these changes are caused by illness or medication. Moreover, the anterior hippocampus represents a putative epicenter of early brain pathology from which dysfunction may spread to affect connected areas.
Normative Modeling of Brain Morphometry in Clinical High Risk for Psychosis

Haas, SS ; Ge, R ; Agartz, I ; Amminger, GP ; Andreassen, OA ; Bachman, P ; Baeza, I ; Choi, S ; Colibazzi, T ; Cropley, VL ; de la Fuente-Sandoval, C ; Ebdrup, BH ; Fortea, A ; Fusar-Poli, P ; Glenthoj, BY ; Glenthoj, LB ; Haut, KM ; Hayes, RA ; Heekeren, K ; Hooker, CI ; Hwang, WJ ; Jahanshad, N ; Kaess, M ; Kasai, K ; Katagiri, N ; Kim, M ; Kindler, J ; Koike, S ; Kristensen, TD ; Kwon, JS ; Lawrie, SM ; Lebedeva, I ; Lee, J ; Lemmers-Jansen, ILJ ; Lin, A ; Ma, X ; Mathalon, DH ; McGuire, P ; Michel, C ; Mizrahi, R ; Mizuno, M ; Moller, P ; Mora-Duran, R ; Nelson, B ; Nemoto, T ; Nordentoft, M ; Nordholm, D ; Omelchenko, MA ; Pantelis, C ; Pariente, JC ; Raghava, JM ; Reyes-Madrigal, F ; Rossberg, JI ; Roessler, W ; Salisbury, DF ; Sasabayashi, D ; Schall, U ; Smigielski, L ; Sugranyes, G ; Suzuki, M ; Takahashi, T ; Tamnes, CK ; Theodoridou, A ; Thomopoulos, SI ; Thompson, PM ; Tomyshev, AS ; Uhlhaas, PJ ; Vaernes, TG ; van Amelsvoort, TAMJ ; van Erp, TGM ; Waltz, JA ; Wenneberg, C ; Westlye, LT ; Wood, SJ ; Zhou, JH ; Hernaus, D ; Jalbrzikowski, M ; Kahn, RS ; Corcoran, CM ; Frangou, S (AMER MEDICAL ASSOC, 2024-01)

IMPORTANCE: The lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in individuals at psychosis risk may be nested within the range observed in healthy individuals. OBJECTIVE: To quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder. DESIGN, SETTING, AND PARTICIPANTS: This case-control study used clinical-, IQ-, and neuroimaging software (FreeSurfer)-derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1340 individuals with CHR-P and 1237 healthy individuals pooled from 29 international sites participating in the Enhancing Neuroimaging Genetics Through Meta-analysis (ENIGMA) Clinical High Risk for Psychosis Working Group. Healthy individuals and individuals with CHR-P were matched on age and sex within each recruitment site. Data were analyzed between September 1, 2021, and November 30, 2022. MAIN OUTCOMES AND MEASURES: For each regional morphometric measure, deviation scores were computed as z scores indexing the degree of deviation from their normative means from a healthy reference population. Average deviation scores (ADS) were also calculated for regional CT, SA, and SV measures and globally across all measures. Regression analyses quantified the association of deviation scores with clinical severity and cognition, and 2-proportion z tests identified case-control differences in the proportion of individuals with infranormal (z < -1.96) or supranormal (z > 1.96) scores. RESULTS: Among 1340 individuals with CHR-P, 709 (52.91%) were male, and the mean (SD) age was 20.75 (4.74) years. Among 1237 healthy individuals, 684 (55.30%) were male, and the mean (SD) age was 22.32 (4.95) years. Individuals with CHR-P and healthy individuals overlapped in the distributions of the observed values, regional z scores, and all ADS values. For any given region, the proportion of individuals with CHR-P who had infranormal or supranormal values was low (up to 153 individuals [<11.42%]) and similar to that of healthy individuals (<115 individuals [<9.30%]). Individuals with CHR-P who converted to a psychotic disorder had a higher percentage of infranormal values in temporal regions compared with those who did not convert (7.01% vs 1.38%) and healthy individuals (5.10% vs 0.89%). In the CHR-P group, only the ADS SA was associated with positive symptoms (β = -0.08; 95% CI, -0.13 to -0.02; P = .02 for false discovery rate) and IQ (β = 0.09; 95% CI, 0.02-0.15; P = .02 for false discovery rate). CONCLUSIONS AND RELEVANCE: In this case-control study, findings suggest that macroscale neuromorphometric measures may not provide an adequate explanation of psychosis risk.

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