Background:White matter alterations observed using diffusion weighted imaging have become a hallmark of chronic schizophrenia, but it is unclear when these changes arise over the course of the disease. Nearly all studies reported to date have been cross-sectional, so despite their large sample sizes, they cannot determine whether changes accumulate as a degenerative process or patients with preexisting white matter damage are predisposed to more chronic forms of schizophrenia. Methods:We examined 160 scans comprising 2 years of annual follow-up data from 42 control participants and 28 patients with schizophrenia recruited in the first 2 years since their diagnosis, totaling 2 to 3 scans per participant. We also examined 6-month follow-up data obtained from an ultra-high field (7T) scanner (68 scans; n = 19 patients with first-episode schizophrenia, n = 15 control participants) as a validation dataset. A longitudinal model was used to compare the trajectory of diffusion tensor parameters in patients and control participants. Results:Positive and negative symptom scores were correlated with diffusion parameters using region of interest-based approaches. No longitudinal differences between patients and control participants were observed for any diffusion tensor imaging parameter in either dataset. However, we did observe consistent associations between white matter alterations and negative symptoms in both datasets. Conclusions:White matter does not appear to be susceptible to schizophrenia-linked degeneration in the early stages of disease, but preexisting pathology may be linked to disease severity.

Diffusion weighted imaging has been frequently used to characterize the white matter in patients with schizophrenia, but the most commonly used model, diffusion tensor imaging (DTI), is not specific to the histological nature of microstructural changes. This is particularly true in the more complex grey matter tissue. Furthermore, DTI changes have not been consistently reported in early schizophrenia populations, but this does not exclude more subtle changes that may not affect the model fit. Recently developed biophysical models of diffusion, such as the neurite orientation dispersion and density imaging (NODDI) model, may overcome these issues by quantifying specific tissue subcompartments, capturing diffusion profiles characteristic of intra-neurite, extra-neurite, and free water space. We applied the NODDI model to early schizophrenia patients (n=54) and healthy controls (n=51) from the Human Connectome Project - Early Psychosis dataset, investigating both the grey and white matter. We observed a diffuse, increased free water fraction throughout the grey matter, especially in the left insula, though there were not notable changes in the white matter. The spatial variation in the grey matter free water was not fully explained by the partial volume effects from the cerebrospinal fluid, indicating a role for tissue edema. The role of vasogenic processes in early stages of psychosis that may precede white matter anomalies documented in later disease stages warrant further investigation. ### Competing Interest Statement PVD reports no conflicts of interest. AK reports no conflicts of interest. LP reports personal fees for serving as chief editor from the Canadian Medical Association Journals, speaker/consultant fee from Janssen Canada and Otsuka Canada, SPMM Course Limited, UK, Canadian Psychiatric Association; book royalties from Oxford University Press; investigator-initiated educational grants from Janssen Canada, Sunovion and Otsuka Canada outside the submitted work.

The superficial white matter, the layer of white matter immediately deep to the cortical grey matter, is a highly complex, heterogeneous tissue region comprising dense meshes of neural fibres, a robust population of interstitial neurons, and ongoing glial activity and myelination. It originates from the histologically distinct, developmentally vital subplate in the foetal brain, maintains thalamo-cortical connections throughout adult life, and is a necessary passage for all axons passing between the grey and white matter. Despite these features, the superficial white matter is among the most poorly understood regions of the brain, in part due to its complex makeup and the resulting difficulty of its study. In this review, we present our current knowledge of superficial white matter (SWM) anatomy, development, and response to disease. We discuss the unique challenges encountered in the neuroimaging of this region, including the lack of standard definition and the non-specificity of neuroimaging markers amplified by the complexity of the tissue. We discuss recent innovations and offer potential pathways forward.

Background and Hypothesis Schizophrenia is associated with white matter disruption and topological reorganization of cortical connectivity but the trajectory of these changes, from the first psychotic episode to established illness, is poorly understood. Current studies in first-episode psychosis (FEP) patients using diffusion magnetic resonance imaging (dMRI) suggest such disruption may be detectable at the onset of psychosis, but specific results vary widely, and few reports have contextualized their findings with direct comparison to young adults with established illness.Study Design Diffusion and T1-weighted 7T MR scans were obtained from N = 112 individuals (58 with untreated FEP, 17 with established schizophrenia, 37 healthy controls) recruited from London, Ontario. Voxel- and network-based analyses were used to detect changes in diffusion microstructural parameters. Graph theory metrics were used to probe changes in the cortical network hierarchy and to assess the vulnerability of hub regions to disruption. The analysis was replicated with N = 111 (57 patients, 54 controls) from the Human Connectome Project-Early Psychosis (HCP-EP) dataset.Study Results Widespread microstructural changes were found in people with established illness, but changes in FEP patients were minimal. Unlike the established illness group, no appreciable topological changes in the cortical network were observed in FEP patients. These results were replicated in the early psychosis patients of the HCP-EP datasets, which were indistinguishable from controls in most metrics.Conclusions The white matter structural changes observed in established schizophrenia are not a prominent feature in the early stages of this illness.

Astrocytes are intimately linked with brain blood vessels, an essential relationship for neuronal function. However, astroglial factors driving these physical and functional associations during postnatal brain development have yet to be identified. By characterizing structural and transcriptional changes in mouse cortical astrocytes during the first two postnatal weeks, we find that high-mobility group box 1 ( Hmgb1 ), normally upregulated with injury and involved in adult cerebrovascular repair, is highly expressed in astrocytes at birth and then decreases rapidly. Astrocyte-selective ablation of Hmgb1 at birth affects astrocyte morphology and endfoot placement, alters distribution of endfoot proteins connexin43 and aquaporin-4, induces transcriptional changes in astrocytes related to cytoskeleton remodeling, and profoundly disrupts endothelial ultrastructure. While lack of astroglial Hmgb1 does not affect the blood-brain barrier or angiogenesis postnatally, it impairs neurovascular coupling and behavior in adult mice. These findings identify astroglial Hmgb1 as an important player in postnatal gliovascular maturation.

Fetal functional magnetic resonance imaging (fMRI) offers critical insight into the developing brain and could aid in predicting developmental outcomes. As the fetal brain is surrounded by heterogeneous tissue, it is not possible to use adult- or child-based segmentation toolboxes. Manually-segmented masks can be used to extract the fetal brain; however, this comes at significant time costs. Here, we present a new BIDS App for masking fetal fMRI, funcmasker-flex, that overcomes these issues with a robust 3D convolutional neural network (U-net) architecture implemented in an extensible and transparent Snakemake workflow. Open-access fetal fMRI data with manual brain masks from 159 fetuses (1103 total volumes) were used for training and testing the U-net model. We also tested generalizability of the model using 82 locally acquired functional scans from 19 fetuses, which included over 2300 manually segmented volumes. Dice metrics were used to compare performance of funcmasker-flex to the ground truth manually segmented volumes, and segmentations were consistently robust (all Dice metrics ≥ 0.74). The tool is freely available and can be applied to any BIDS dataset containing fetal bold sequences. Funcmasker-flex reduces the need for manual segmentation, even when applied to novel fetal functional datasets, resulting in significant time-cost savings for performing fetal fMRI analysis.

While the neuronal underpinnings of autism spectrum disorder (ASD) are being unraveled, vascular contributions to ASD remain elusive. Here, we investigated postnatal cerebrovascular development in the 16p11.2df/+ mouse model of 16p11.2 deletion ASD syndrome. We discover that 16p11.2 hemizygosity leads to male-specific, endothelium-dependent structural and functional neurovascular abnormalities. In 16p11.2df/+ mice, endothelial dysfunction results in impaired cerebral angiogenesis at postnatal day 14, and in altered neurovascular coupling and cerebrovascular reactivity at postnatal day 50. Moreover, we show that there is defective angiogenesis in primary 16p11.2df/+ mouse brain endothelial cells and in induced-pluripotent-stem-cell-derived endothelial cells from human carriers of the 16p11.2 deletion. Finally, we find that mice with an endothelium-specific 16p11.2 deletion (16p11.2ΔEC) partially recapitulate some of the behavioral changes seen in 16p11.2 syndrome, specifically hyperactivity and impaired motor learning. By showing that developmental 16p11.2 haploinsufficiency from endothelial cells results in neurovascular and behavioral changes in adults, our results point to a potential role for endothelial impairment in ASD.

Metabolic syndrome, which includes diabetes and obesity, is one of the most widespread medical conditions. It induces systemic inflammation, causing far reaching effects on the body that are still being uncovered. Neuropathologies triggered by metabolic syndrome often result from increased permeability of the blood-brain-barrier (BBB). The BBB, a system designed to restrict entry of toxins, immune cells, and pathogens to the brain, is vital for proper neuronal function. Local and systemic inflammation induced by obesity or type 2 diabetes mellitus can cause BBB breakdown, decreased removal of waste, and increased infiltration of immune cells. This leads to disruption of glial and neuronal cells, causing hormonal dysregulation, increased immune sensitivity, or cognitive impairment depending on the affected brain region. Inflammatory effects of metabolic syndrome have been linked to neurodegenerative diseases. In this review, we discuss the effects of obesity and diabetes-induced inflammation on the BBB, the roles played by leptin and insulin resistance, as well as BBB changes occurring at the molecular level. We explore signaling pathways including VEGF, HIFs, PKC, Rho/ROCK, eNOS, and miRNAs. Finally, we discuss the broader implications of neural inflammation, including its connection to Alzheimer's disease, multiple sclerosis, and the gut microbiome.