Normative Modeling of Brain Morphometry in Clinical High Risk for Psychosis

Lifespan development of thalamic nuclei and characterizing thalamic nuclei abnormalities in schizophrenia using normative modeling

Thalamic abnormalities have been repeatedly implicated in the pathophysiology of schizophrenia and other neurodevelopmental disorders. Uncovering the etiology of thalamic abnormalities and how they may contribute to illness phenotypes faces at least two obstacles. First, the typical developmental trajectories of thalamic nuclei and their association with cognition across the lifespan are largely unknown. Second, modest effect sizes indicate marked individual differences and pose a significant challenge to personalized medicine. To address these knowledge gaps, we characterized the development of thalamic nuclei volumes using normative models generated from the Human Connectome Project Lifespan datasets (5-100+ years), then applied them to an independent clinical cohort to determine the frequency of thalamic volume deviations in people with schizophrenia (17-61 years). Normative models revealed diverse non-linear age effects across the lifespan. Association nuclei exhibited negative age effects during youth but stabilized in adulthood until turning negative again with older age. Sensorimotor nuclei volumes remained relatively stable through youth and adulthood until also turning negative with older age. Up to 18% of individuals with schizophrenia exhibited abnormally small (i.e., below the 5th centile) mediodorsal and pulvinar volumes, and the degree of deviation, but not raw volumes, correlated with the severity of cognitive impairment. While case-control differences are robust, only a minority of patients demonstrate unusually small thalamic nuclei volumes. Normative modeling enables the identification of these individuals, which is a necessary step toward precision medicine.

Individualized functional connectome abnormalities obtained using two normative model unveil neurophysiological subtypes of obsessive compulsive disorder

The high heterogeneity observed among patients with obsessive-compulsive disorder (OCD) underscores the need to identify neurophysiological OCD subtypes to facilitate personalized diagnosis and treatment. In this study, our aim was to identify potential OCD subtypes based on individualized functional connectome abnormalities. We recruited a total of 99 patients with OCD and 104 healthy controls (HCs) matched for demographic characteristics. Individualized functional connectome abnormalities were obtained using normative models of functional connectivity strength (FCS) and used as features to unveil OCD subtypes. Sensitivity analyses were conducted to assess the reproducibility and robustness of the clustering outcomes. Patients exhibited significant intersubject heterogeneity in individualized functional connectome abnormalities. Two subtypes with distinct patterns of FCS abnormalities relative to HCs were identified. Subtype 1 patients primarily exhibited significantly decreased FCS in regions including the frontal gyrus, insula, hippocampus, and precentral/postcentral gyrus, whereas subtype 2 patients demonstrated increased FCS in widespread brain regions. When all patients were combined, no significant differences were observed. Additionally, the identified subtypes showed significant differences in age of onset. Furthermore, sensitivity analyses confirmed the reproducibility of our subtyping results. In conclusion, the identified OCD subtypes shed new light on the taxonomy and neurophysiological heterogeneity of OCD.

Clinical High-Risk for Psychosis (CHR-P) circa 2024: Synoptic analysis and synthesis of contemporary treatment guidelines

The construct of Clinical-High Risk for Psychosis (CHR-P) identifies young help-seeking subjects in putative prodromal stages of psychosis and is a central component of the Early Intervention (EI) paradigm in Mental Health, aimed at facilitating rapid entry into appropriate care pathways to prevent the onset of psychosis or mitigate is biopsychosocial consequences. This approach, which promotes an innovative culture of care for early, at risk situations, is inspired by a clinical staging concept as a guide to optimal treatment. The objective of this article is to map the existing guidelines in the field of CHR-P treatment recommendations, examine overlaps and differences, and critically evaluate blind spots to be addressed in future guideline updated. The search identified 9 guidelines focused on CHR-P or schizophrenia and other psychotic conditions but containing a specific section on CHR-P or prodromal psychosis. All guidelines acknowledge that psychosis is preceded by more or less pronounced prodromal stages, and most detail CHR-P criteria. Among guidelines, 8 out of 9 indicate cognitive-behavioural therapy as the best psychotherapeutic option and 7 out of 9 suggest that antipsychotics can be prescribed as second option in case psychosocial and/or other pharmacological interventions prove insufficient or inadequate in reducing clinical severity and subjective suffering. Antidepressants, mood stabilizers, and benzodiazepines were considered for the treatment of comorbid disorders. Only the European Psychiatric Association Guidance paper distinguished treatment recommendations for adults and minors. Agreements in treatment guidelines were discussed in light of recent meta-analytical evidences on pharmacological and non-pharmacological treatments for CHR-P, suggesting the need to provide an updated, age-sensitive consensus on how to manage CHR-P individuals.

Adjustment of Regional Cortical Thickness Measures for Global Cortical Thickness Obscures Deficits Across the Schizophrenia Spectrum: A Cautionary Note About Normative Modeling of Brain Imaging Data

Recent neuroimaging studies and publicly disseminated analytic tools suggest that regional morphometric analyses covary for global thickness. We empirically demonstrated that this statistical approach severely underestimates regional thickness dysmorphology in psychiatric disorders. Study 1 included 90 healthy control participants, 51 participants at clinical high risk for psychosis, and 78 participants with early-illness schizophrenia. Study 2 included 56 healthy control participants, 83 participants with nonaffective psychosis, and 30 participants with affective psychosis. We examined global and regional thickness correlations, global thickness group differences, and regional thickness group differences with and without global thickness covariation. Global and regional thickness were strongly correlated across groups. Global thickness was lower in the schizophrenia spectrum groups than the other groups. Regional thickness deficits in schizophrenia spectrum groups were attenuated or eliminated with global thickness covariation. Eliminating the variation that regional thickness shares with global thickness eliminated disease-related effects. This statistical approach results in erroneous conclusions that regional thickness is normal in disorders like schizophrenia or clinical high risk syndrome.

Heterogeneity of morphometric similarity networks in health and schizophrenia

Introduction

Morphometric similarity is a recently developed neuroimaging phenotype of inter-regional connectivity by quantifying the similarity of a region to other regions based on multiple MRI parameters. Altered average morphometric similarity has been reported in psychotic disorders at the group level, with considerable heterogeneity across individuals. We used normative modeling to address cross-sectional and longitudinal inter-individual heterogeneity of morphometric similarity in health and schizophrenia.

Methods

Morphometric similarity for 62 cortical regions was obtained from baseline and follow-up T1-weighted scans of healthy individuals and patients with chronic schizophrenia. Cortical regions were classified into seven predefined brain functional networks. Using Bayesian Linear Regression and taking into account age, sex, image quality and scanner, we trained and validated normative models in healthy controls from eleven datasets (n = 4310). Individual deviations from the norm (z-scores) in morphometric similarity were computed for each participant for each network and region at both timepoints. A z-score ≧ than 1.96 was considered supra-normal and a z-score ≦ -1.96 infra-normal. As a longitudinal metric, we calculated the change over time of the total number of infra- or supra-normal regions per participant.

Results

At baseline, patients with schizophrenia had decreased morphometric similarity of the default mode network and increased morphometric similarity of the somatomotor network when compared with healthy controls. The percentage of patients with infra- or supra-normal values for any region at baseline and follow-up was low (<6%) and did not differ from healthy controls. Mean intra-group changes over time in the total number of infra- or supra-normal regions were small in schizophrenia and healthy control groups (<1) and there were no significant between-group differences.

Conclusions

In a case-control setting, a decrease of morphometric similarity within the default mode network may be a robust finding implicated in schizophrenia. However, normative modeling suggests that significant reductions and changes over time of regional morphometric similarity are evident only in a minority of patients.

Developmental perspectives on the origins of psychotic disorders: The need for a transdiagnostic approach

Research on serious mental disorders, particularly psychosis, has revealed highly variable symptom profiles and developmental trajectories prior to illness-onset. As Dante Cicchetti pointed out decades before the term "transdiagnostic" was widely used, the pathways to psychopathology emerge in a system involving equifinality and multifinality. Like most other psychological disorders, psychosis is associated with multiple domains of risk factors, both genetic and environmental, and there are many transdiagnostic developmental pathways that can lead to psychotic syndromes. In this article, we discuss our current understanding of heterogeneity in the etiology of psychosis and its implications for approaches to conceptualizing etiology and research. We highlight the need for examining risk factors at multiple levels and to increase the emphasis on transdiagnostic developmental trajectories as a key variable associated with etiologic subtypes. This will be increasingly feasible now that large, longitudinal datasets are becoming available and researchers have access to more sophisticated analytic tools, such as machine learning, which can identify more homogenous subtypes with the ultimate goal of enhancing options for treatment and preventive intervention.

Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization

We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain (https://centilebrain.org/).