Improving the predictive potential of diffusion MRI in schizophrenia using normative models-Towards subject-level classification.

Diffusion MRI studies consistently report group differences in white matter between individuals diagnosed with schizophrenia and healthy controls. Nevertheless, the abnormalities found at the group-level are often not observed at the individual level. Among the different approaches aiming to study white matter abnormalities at the subject level, normative modeling analysis takes a step towards subject-level predictions by identifying affected brain locations in individual subjects based on extreme deviations from a normative range. Here, we leveraged a large harmonized diffusion MRI dataset from 512 healthy controls and 601 individuals diagnosed with schizophrenia, to study whether normative modeling can improve subject-level predictions from a binary classifier. To this aim, individual deviations from a normative model of standard (fractional anisotropy) and advanced (free-water) dMRI measures, were calculated by means of age and sex-adjusted z-scores relative to control data, in 18 white matter regions. Even though larger effect sizes are found when testing for group differences in z-scores than are found with raw values (p < .001), predictions based on summary z-score measures achieved low predictive power (AUC < 0.63). Instead, we find that combining information from the different white matter tracts, while using multiple imaging measures simultaneously, improves prediction performance (the best predictor achieved AUC = 0.726). Our findings suggest that extreme deviations from a normative model are not optimal features for prediction. However, including the complete distribution of deviations across multiple imaging measures improves prediction, and could aid in subject-level classification

White matter changes in psychosis risk relate to development and are not impacted by the transition to psychosis

Subtle alterations in white matter microstructure are observed in youth at clinical high risk (CHR) for psychosis. However, the timing of these changes and their relationships to the emergence of psychosis remain unclear. Here, we track the evolution of white matter abnormalities in a large, longitudinal cohort of CHR individuals comprising the North American Prodrome Longitudinal Study (NAPLS-3). Multi-shell diffusion magnetic resonance imaging data were collected across multiple timepoints (1–5 over 1 year) in 286 subjects (aged 12–32 years): 25 CHR individuals who transitioned to psychosis (CHR-P; 61 scans), 205 CHR subjects with unknown transition outcome after the 1-year follow-up period (CHR-U; 596 scans), and 56 healthy controls (195 scans). Linear mixed effects models were fitted to infer the impact of age and illness-onset on variation in the fractional anisotropy of cellular tissue (FAT) and the volume fraction of extracellular free water (FW). Baseline measures of white matter microstructure did not differentiate between HC, CHR-U and CHR-P individuals. However, age trajectories differed between the three groups in line with a developmental effect: CHR-P and CHR-U groups displayed higher FAT in adolescence, and 4% lower FAT by 30 years of age compared to controls. Furthermore, older CHR-P subjects (20+ years) displayed 4% higher FW in the forceps major (p &lt; 0.05). Prospective analysis in CHR-P did not reveal a significant impact of illness onset on regional FAT or FW, suggesting that transition to psychosis is not marked by dramatic change in white matter microstructure. Instead, clinical high risk for psychosis—regardless of transition outcome—is characterized by subtle age-related white matter changes that occur in tandem with development

Increased extracellular free-water in adult male rats following in utero exposure to maternal immune activation

BACKGROUND: In previous work, we applied novel in vivo imaging methods to reveal that white matter pathology in patients with first-episode psychosis (FEP) is mainly characterized by excessive extracellular free-water, and to a lesser extent by cellular processes, such as demyelination. Here, we apply a back-translational approach to evaluate whether or not a rodent model of maternal immune activation (MIA) induces patterns of white matter pathology that we observed in patients with FEP. To this end, we examined free-water and tissue-specific white matter alterations in rats born to mothers exposed to the viral mimic polyriboinosinic-polyribocytidylic acid (Poly-I:C) in pregnancy, which is widely used to produce alterations relevant to schizophrenia and is characterized by a robust neuroinflammatory response. METHOD: Pregnant dams were injected on gestational day 15 with the viral mimic Poly-I:C (4 mg/kg) or saline. Diffusion-weighted magnetic resonance images were acquired from 17 male offspring (9 Poly-I:C and 8 saline) on postnatal day 90, after the emergence of brain structural and behavioral abnormalities. The free-water fraction (FW) and tissue-specific fractional anisotropy (FAT), as well as conventional fractional anisotropy (FA) were computed across voxels traversing a white matter skeleton. Voxel-wise and whole-brain averaged white matter were tested for significant microstructural alterations in immune-challenged, relative to saline-exposed offspring. RESULTS: Compared to saline-exposed offspring, those exposed to maternal Poly-I:C displayed increased extracellular FW averaged across voxels comprising a white matter skeleton (t(15) = 2.74; p = 0.01). Voxel-wise analysis ascribed these changes to white matter within the corpus callosum, external capsule and the striatum. In contrast, no significant between-group differences emerged for FAT or for conventional FA, measured across average and voxel-wise white matter. CONCLUSION: We identified excess FW across frontal white matter fibers of rats exposed to prenatal immune activation, analogous to our "bedside" observation in FEP patients. Findings from this initial experiment promote use of the MIA model to examine pathological pathways underlying FW alterations observed in patients with schizophrenia. Establishing these mechanisms has important implications for clinical studies, as free-water imaging reflects a feasible biomarker that has so far yielded consistent findings in the early stages of schizophrenia

Network Analysis of Symptom Comorbidity in Schizophrenia: Relationship to Illness Course and Brain White Matter Microstructure

INTRODUCTION: Recent network-based analyses suggest that schizophrenia symptoms are intricately connected and interdependent, such that central symptoms can activate adjacent symptoms and increase global symptom burden. Here, we sought to identify key clinical and neurobiological factors that relate to symptom organization in established schizophrenia. METHODS: A symptom comorbidity network was mapped for a broad constellation of symptoms measured in 642 individuals with a schizophrenia-spectrum disorder. Centrality analyses were used to identify hub symptoms. The extent to which each patient's symptoms formed clusters in the comorbidity network was quantified with cluster analysis and used to predict (1) clinical features, including illness duration and psychosis (positive symptom) severity and (2) brain white matter microstructure, indexed by the fractional anisotropy (FA), in a subset (n = 296) of individuals with diffusion-weighted imaging (DWI) data. RESULTS: Global functioning, substance use, and blunted affect were the most central symptoms within the symptom comorbidity network. Symptom profiles for some patients formed highly interconnected clusters, whereas other patients displayed unrelated and disconnected symptoms. Stronger clustering among an individual's symptoms was significantly associated with shorter illness duration (t = 2.7; P = .0074), greater psychosis severity (ie, positive symptoms expression) (t = -5.5; P < 0.0001) and lower fractional anisotropy in fibers traversing the cortico-cerebellar-thalamic-cortical circuit (r = .59, P < 0.05). CONCLUSION: Symptom network structure varies over the course of schizophrenia: symptom interactions weaken with increasing illness duration and strengthen during periods of high positive symptom expression. Reduced white matter coherence relates to stronger symptom clustering, and thus, may underlie symptom cascades and global symptomatic burden in individuals with schizophrenia

Quantifying Genetic and Environmental Influence on Gray Matter Microstructure Using Diffusion MRI

Early neuroimaging work in twin studies focused on studying genetic and environmental influence on gray matter macrostructure. However, it is also important to understand how gray matter microstructure is influenced by genes and environment to facilitate future investigations of their influence in mental disorders. Advanced diffusion MRI (dMRI) measures allow more accurate assessment of gray matter microstructure compared with conventional diffusion tensor measures. To understand genetic and environmental influence on gray matter, we used diffusion and structural MRI data from a large twin and sibling study (N = 840) and computed advanced dMRI measures including return to origin probability (RTOP), which is heavily weighted toward intracellular and intra-axonal restricted spaces, and mean squared displacement (MSD), more heavily weighted to diffusion in extracellular space and large cell bodies in gray matter. We show that while macrostructural features like brain volume are mainly genetically influenced, RTOP and MSD can together tap into both genetic and environmental influence on microstructure

White matter abnormalities across the lifespan of schizophrenia: a harmonized multi-site diffusion MRI study.

Several prominent theories of schizophrenia suggest that structural white matter pathologies may follow a developmental, maturational, and/or degenerative process. However, a lack of lifespan studies has precluded verification of these theories. Here, we analyze the largest sample of carefully harmonized diffusion MRI data to comprehensively characterize age-related white matter trajectories, as measured by fractional anisotropy (FA), across the course of schizophrenia. Our analysis comprises diffusion scans of 600 schizophrenia patients and 492 healthy controls at different illness stages and ages (14-65 years), which were gathered from 13 sites. We determined the pattern of age-related FA changes by cross-sectionally assessing the timing of the structural neuropathology associated with schizophrenia. Quadratic curves were used to model between-group FA differences across whole-brain white matter and fiber tracts at each age; fiber tracts were then clustered according to both the effect-sizes and pattern of lifespan white matter FA differences. In whole-brain white matter, FA was significantly lower across the lifespan (up to 7%; p \u3c 0.0033) and reached peak maturation younger in patients (27 years) compared to controls (33 years). Additionally, three distinct patterns of neuropathology emerged when investigating white matter fiber tracts in patients: (1) developmental abnormalities in limbic fibers, (2) accelerated aging and abnormal maturation in long-range association fibers, (3) severe developmental abnormalities and accelerated aging in callosal fibers. Our findings strongly suggest that white matter in schizophrenia is affected across entire stages of the disease. Perhaps most strikingly, we show that white matter changes in schizophrenia involve dynamic interactions between neuropathological processes in a tract-specific manner

Large-Scale Evidence for an Association Between Peripheral Inflammation and White Matter Free Water in Schizophrenia and Healthy Individuals

INTRODUCTION: Clarifying the role of neuroinflammation in schizophrenia is subject to its detection in the living brain. Free-water (FW) imaging is an in vivo diffusion-weighted magnetic resonance imaging (dMRI) technique that measures water molecules freely diffusing in the brain and is hypothesized to detect inflammatory processes. Here, we aimed to establish a link between peripheral markers of inflammation and FW in brain white matter. METHODS: All data were obtained from the Australian Schizophrenia Research Bank (ASRB) across 5 Australian states and territories. We first tested for the presence of peripheral cytokine deregulation in schizophrenia, using a large sample (N = 1143) comprising the ASRB. We next determined the extent to which individual variation in 8 circulating pro-/anti-inflammatory cytokines related to FW in brain white matter, imaged in a subset (n = 308) of patients and controls. RESULTS: Patients with schizophrenia showed reduced interleukin-2 (IL-2) (t = -3.56, P = .0004) and IL-12(p70) (t = -2.84, P = .005) and increased IL-6 (t = 3.56, P = .0004), IL-8 (t = 3.8, P = .0002), and TNFα (t = 4.30, P < .0001). Higher proinflammatory signaling of IL-6 (t = 3.4, P = .0007) and TNFα (t = 2.7, P = .0007) was associated with higher FW levels in white matter. The reciprocal increases in serum cytokines and FW were spatially widespread in patients encompassing most major fibers; conversely, in controls, the relationship was confined to the anterior corpus callosum and thalamic radiations. No relationships were observed with alternative dMRI measures, including the fractional anisotropy and tissue-related FA. CONCLUSIONS: We report widespread deregulation of cytokines in schizophrenia and identify inflammation as a putative mechanism underlying increases in brain FW levels

O5.6. ADVANCED DIFFUSION IMAGING IN PSYCHOSIS RISK: A CROSS-SECTIONAL AND LONGITUDINAL STUDY OF WHITE MATTER DEVELOPMENT

Abstract Background Studies in individuals at clinical high risk (CHR) for psychosis provide a powerful means to predict outcomes and inform putative mechanisms underlying conversion to psychosis. In previous work, we applied advanced diffusion imaging methods to reveal that white matter pathology in a CHR population is characterized by cellular-specific changes in white matter, suggesting a preexisting neurodevelopmental anomaly. However, it remains unknown whether these deficits relate to clinical symptoms and/or conversion to frank psychosis. To address this gap, we examined cross-sectional and longitudinal white matter maturation in the largest imaging population of CHR individuals to date, obtained from the North American Prodrome Longitudinal Study (NAPLS-3). Methods Multi-shell diffusion magnetic resonance imaging (MRI) data were collected across multiple timepoints (1–6 at ~2 month intervals) in 286 subjects (age range=12–32 years). These were 230 unmedicated CHR subjects, including 11% (n=25) who transitioned to psychosis (CHR-converters), as well as 56 age and sex-matched healthy controls. Raw diffusion signals were harmonized to remove scanner/site-induced effects, yielding a unified imaging dataset. Fractional anisotropy of cellular tissue (FAt) and the volume fraction of extracellular free-water (FW) were assessed in 12 major tracts from the IIT Human Brain Atlas (v.5.0). Linear mixed effects (LME) models were fitted to infer developmental trajectories of FAt and FW across age for CHR-converters, CHR-nonconverters and control groups, while accounting for the repeated measurements on each individual. Results The rate at which FAt changed with age significantly differed between the three groups across commissural and association tracts (5 in total; p&lt;0.05). In these tracts, FAt increased with age in controls (0.002% change per year) and in CHR-nonconverters, albeit at a slower rate (0.00074% per year). In contrast, FAt declined with age in CHR-converters at a rate that was significantly faster (-3.944% per year) than the rate of increase in the other two groups. By 25 years of age, FAt was significantly lower in both CHR groups compared to controls (p&lt;0.05). With regard to FW, the rate of change significantly differed between CHR-converters and controls across the forceps major and the left inferior longitudinal and fronto‐occipital fasciculi (IFOF; 3 tracts in total; p&lt;0.05). This was due to increased FW with age in the CHR-converters (0.0024% change per year) relative to controls (-0.0002% per year). Consequently, FW was significantly higher in CHR-converters compared to controls by 20 years of age (p&lt;.05). With regard to symptoms, there was a significant impact of IFOF FW on positive symptom severity across CHR subjects, regardless of conversion status (t=2.37, p&lt;0.05). Discussion Our results revealed that clinical high-risk for psychosis is associated with cellular-specific alterations in white matter, regardless of conversion status. Only converters showed excess extracellular free-water, which involved tracts connecting occipital, posterior temporal, and orbito‐frontal areas. We also demonstrate a direct impact of free-water on positive symptomatology, collectively, suggesting that excess free-water may signal acute psychosis and its onset. This marker may be useful for patient selection for clinical trials and assessment of individuals with prodromal psychosis

White matter abnormalities across the lifespan of schizophrenia: a harmonized multi-site diffusion MRI study

Several prominent theories of schizophrenia suggest that structural white matter pathologies may follow a developmental, maturational, and/or degenerative process. However, a lack of lifespan studies has precluded verification of these theories. Here, we analyze the largest sample of carefully harmonized diffusion MRI data to comprehensively characterize age-related white matter trajectories, as measured by fractional anisotropy (FA), across the course of schizophrenia. Our analysis comprises diffusion scans of 600 schizophrenia patients and 492 healthy controls at different illness stages and ages (14-65 years), which were gathered from 13 sites. We determined the pattern of age-related FA changes by cross-sectionally assessing the timing of the structural neuropathology associated with schizophrenia. Quadratic curves were used to model between-group FA differences across whole-brain white matter and fiber tracts at each age; fiber tracts were then clustered according to both the effect-sizes and pattern of lifespan white matter FA differences. In whole-brain white matter, FA was significantly lower across the lifespan (up to 7%; p < 0.0033) and reached peak maturation younger in patients (27 years) compared to controls (33 years). Additionally, three distinct patterns of neuropathology emerged when investigating white matter fiber tracts in patients: (1) developmental abnormalities in limbic fibers, (2) accelerated aging and abnormal maturation in long-range association fibers, (3) severe developmental abnormalities and accelerated aging in callosal fibers. Our findings strongly suggest that white matter in schizophrenia is affected across entire stages of the disease. Perhaps most strikingly, we show that white matter changes in schizophrenia involve dynamic interactions between neuropathological processes in a tract-specific manner