Longitudinal assessment of ventricular volume trajectories in early-stage schizophrenia: evidence of both enlargement and shrinkage.

BACKGROUND: Lateral ventricular enlargement represents a canonical morphometric finding in chronic patients with schizophrenia; however, longitudinal studies elucidating complex dynamic trajectories of ventricular volume change during critical early disease stages are sparse. METHODS: We measured lateral ventricular volumes in 113 first-episode schizophrenia patients (FES) at baseline visit (11.7 months after illness onset, SD = 12.3) and 128 age- and sex-matched healthy controls (HC) using 3T MRI. MRI was then repeated in both FES and HC one year later. RESULTS: Compared to controls, ventricular enlargement was identified in 18.6% of patients with FES (14.1% annual ventricular volume (VV) increase; 95%CI: 5.4; 33.1). The ventricular expansion correlated with the severity of PANSS-negative symptoms at one-year follow-up (p = 0.0078). Nevertheless, 16.8% of FES showed an opposite pattern of statistically significant ventricular shrinkage during ≈ one-year follow-up (-9.5% annual VV decrease; 95%CI: -23.7; -2.4). There were no differences in sex, illness duration, age of onset, duration of untreated psychosis, body mass index, the incidence of Schneiderian symptoms, or cumulative antipsychotic dose among the patient groups exhibiting ventricular enlargement, shrinkage, or no change in VV. CONCLUSION: Both enlargement and ventricular shrinkage are equally present in the early stages of schizophrenia. The newly discovered early reduction of VV in a subgroup of patients emphasizes the need for further research to understand its mechanisms.

Alterations in subcortical magnetic susceptibility and disease-specific relationship with brain volume in major depressive disorder and schizophrenia.

Quantitative susceptibility mapping is a magnetic resonance imaging technique that measures brain tissues' magnetic susceptibility, including iron deposition and myelination. This study examines the relationship between subcortical volume and magnetic susceptibility and determines specific differences in these measures among patients with major depressive disorder (MDD), patients with schizophrenia, and healthy controls (HCs). This was a cross-sectional study. Sex- and age- matched patients with MDD (n = 49), patients with schizophrenia (n = 24), and HCs (n = 50) were included. Magnetic resonance imaging was conducted using quantitative susceptibility mapping and T1-weighted imaging to measure subcortical susceptibility and volume. The acquired brain measurements were compared among groups using analyses of variance and post hoc comparisons. Finally, a general linear model examined the susceptibility-volume relationship. Significant group-level differences were found in the magnetic susceptibility of the nucleus accumbens and amygdala (p = 0.045). Post-hoc analyses indicated that the magnetic susceptibility of the nucleus accumbens and amygdala for the MDD group was significantly higher than that for the HC group (p = 0.0054, p = 0.0065, respectively). However, no significant differences in subcortical volume were found between the groups. The general linear model indicated a significant interaction between group and volume for the nucleus accumbens in MDD group but not schizophrenia or HC groups. This study showed susceptibility alterations in the nucleus accumbens and amygdala in MDD patients. A significant relationship was observed between subcortical susceptibility and volume in the MDD group's nucleus accumbens, which indicated abnormalities in myelination and the dopaminergic system related to iron deposition.

From brain to body: exploring the connection between altered reward processing and physical fitness in schizophrenia.

Understanding the underlying mechanisms that link psychopathology and physical comorbidities in schizophrenia is crucial since decreased physical fitness and overweight pose major risk factors for cardio-vascular diseases and decrease the patients' life expectancies. We hypothesize that altered reward anticipation plays an important role in this. We implemented the Monetary Incentive Delay task in a MR scanner and a fitness test battery to compare schizophrenia patients (SZ, n = 43) with sex- and age-matched healthy controls (HC, n = 36) as to reward processing and their physical fitness. We found differences in reward anticipation between SZs and HCs, whereby increased activity in HCs positively correlated with overall physical condition and negatively correlated with psychopathology. On the other handy, SZs revealed stronger activity in the posterior cingulate cortex and in cerebellar regions during reward anticipation, which could be linked to decreased overall physical fitness. These findings demonstrate that a dysregulated reward system is not only responsible for the symptomatology of schizophrenia, but might also be involved in physical comorbidities which could pave the way for future lifestyle therapy interventions.

A concerted neuron-astrocyte program declines in ageing and schizophrenia.

Human brains vary across people and over time; such variation is not yet understood in cellular terms. Here we describe a relationship between people's cortical neurons and cortical astrocytes. We used single-nucleus RNA sequencing to analyse the prefrontal cortex of 191 human donors aged 22-97 years, including healthy individuals and people with schizophrenia. Latent-factor analysis of these data revealed that, in people whose cortical neurons more strongly expressed genes encoding synaptic components, cortical astrocytes more strongly expressed distinct genes with synaptic functions and genes for synthesizing cholesterol, an astrocyte-supplied component of synaptic membranes. We call this relationship the synaptic neuron and astrocyte program (SNAP). In schizophrenia and ageing-two conditions that involve declines in cognitive flexibility and plasticity1,2-cells divested from SNAP: astrocytes, glutamatergic (excitatory) neurons and GABAergic (inhibitory) neurons all showed reduced SNAP expression to corresponding degrees. The distinct astrocytic and neuronal components of SNAP both involved genes in which genetic risk factors for schizophrenia were strongly concentrated. SNAP, which varies quantitatively even among healthy people of similar age, may underlie many aspects of normal human interindividual differences and may be an important point of convergence for multiple kinds of pathophysiology.

The volume of gray matter mediates the relationship between glucolipid metabolism and neurocognition in first-episode, drug-naïve patients with schizophrenia.

We aimed to examine the hypotheses that glucolipid metabolism is linked to neurocognition and gray matter volume (GMV) and that GMV mediates the association of glucolipid metabolism with neurocognition in first-episode, drug-naïve (FEDN) patients with schizophrenia. Parameters of glucolipid metabolism, neurocognition, and magnetic resonance imaging were assessed in 63 patients and 31 controls. Compared to controls, patients exhibited higher levels of fasting glucose, triglyceride, and insulin resistance index, lower levels of cholesterol and high-density lipoprotein cholesterol, poorer neurocognitive functions, and decreased GMV in the bilateral insula, left middle occipital gyrus, and left postcentral gyrus. In the patient group, triglyceride levels and the insulin resistance index exhibited a negative correlation with Rapid Visual Information Processing (RVP) mean latency, a measure of attention within the Cambridge Neurocognitive Test Automated Battery (CANTAB), while showing a positive association with GMV in the right insula. The mediation model revealed that triglyceride and insulin resistance index had a significant positive indirect (mediated) influence on RVP mean latency through GMV in the right insula. Glucolipid metabolism was linked to both neurocognitive functions and GMV in FEDN patients with schizophrenia, with the effect pattern differing from that observed in chronic schizophrenia or schizophrenia comorbid with metabolic syndrome. Moreover, glucolipid metabolism might indirectly contribute to neurocognitive deficits through the mediating role of GMV in these patients.

BrainAGE: Revisited and reframed machine learning workflow.

Since the introduction of the BrainAGE method, novel machine learning methods for brain age prediction have continued to emerge. The idea of estimating the chronological age from magnetic resonance images proved to be an interesting field of research due to the relative simplicity of its interpretation and its potential use as a biomarker of brain health. We revised our previous BrainAGE approach, originally utilising relevance vector regression (RVR), and substituted it with Gaussian process regression (GPR), which enables more stable processing of larger datasets, such as the UK Biobank (UKB). In addition, we extended the global BrainAGE approach to regional BrainAGE, providing spatially specific scores for five brain lobes per hemisphere. We tested the performance of the new algorithms under several different conditions and investigated their validity on the ADNI and schizophrenia samples, as well as on a synthetic dataset of neocortical thinning. The results show an improved performance of the reframed global model on the UKB sample with a mean absolute error (MAE) of less than 2 years and a significant difference in BrainAGE between healthy participants and patients with Alzheimer's disease and schizophrenia. Moreover, the workings of the algorithm show meaningful effects for a simulated neocortical atrophy dataset. The regional BrainAGE model performed well on two clinical samples, showing disease-specific patterns for different levels of impairment. The results demonstrate that the new improved algorithms provide reliable and valid brain age estimations.

Relationships among the gut microbiome, brain networks, and symptom severity in schizophrenia patients: A mediation analysis.

The microbiome-gut-brain axis (MGBA) plays a critical role in schizophrenia (SZ). However, the underlying mechanisms of the interactions among the gut microbiome, brain networks, and symptom severity in SZ patients remain largely unknown. Fecal samples, structural and functional magnetic resonance imaging (MRI) data, and Positive and Negative Syndrome Scale (PANSS) scores were collected from 38 SZ patients and 38 normal controls, respectively. The data of 16S rRNA gene sequencing were used to analyze the abundance of gut microbiome and the analysis of human brain networks was applied to compute the nodal properties of 90 brain regions. A total of 1,691,280 mediation models were constructed based on 261 gut bacterial, 810 nodal properties, and 4 PANSS scores in SZ patients. A strong correlation between the gut microbiome and brain networks (r = 0.89, false discovery rate (FDR) -corrected p < 0.05) was identified. Importantly, the PANSS scores were linearly correlated with both the gut microbiome (r = 0.5, FDR-corrected p < 0.05) and brain networks (r = 0.59, FDR-corrected p < 0.05). The abundance of genus Sellimonas significantly affected the PANSS negative scores of SZ patients via the betweenness centrality of white matter networks in the inferior frontal gyrus and amygdala. Moreover, 19 significant mediation models demonstrated that the nodal properties of 7 brain regions, predominately from the systems of visual, language, and control of action, showed significant mediating effects on the PANSS scores with the gut microbiome as mediators. Together, our findings indicated the tripartite relationships among the gut microbiome, brain networks, and PANSS scores and suggested their potential role in the neuropathology of SZ.

Using normative modeling to assess pharmacological treatment effect on brain state in patients with schizophrenia.

Quantifying individual differences in neuroimaging metrics is attracting interest in clinical studies with mental disorders. Schizophrenia is diagnosed exclusively based on symptoms, and the biological heterogeneity makes it difficult to accurately assess pharmacological treatment effects on the brain state. Using the Cambridge Centre for Ageing and Neuroscience data set, we built normative models of brain states and mapped the deviations of the brain characteristics of each patient, to test whether deviations were related to symptoms, and further investigated the pharmacological treatment effect on deviation distributions. Specifically, we found that the patients can be divided into 2 groups: the normalized group had a normalization trend and milder symptoms at baseline, and the other group showed a more severe deviation trend. The baseline severity of the depression as well as the overall symptoms could predict the deviation of the static characteristics for the dorsal and ventral attention networks after treatment. In contrast, the positive symptoms could predict the deviations of the dynamic fluctuations for the default mode and dorsal attention networks after treatment. This work evaluates the effect of pharmacological treatment on static and dynamic brain states using an individualized approach, which may assist in understanding the heterogeneity of the illness pathology as well as the treatment response.

The relationship between gray/white matter contrast and cognitive performance in first-episode schizophrenia.

Previous postmortem brain studies have revealed disturbed myelination in the intracortical regions in patients with schizophrenia, possibly reflecting anomalous brain maturational processes. However, it currently remains unclear whether this anomalous myelination is already present in early illness stages and/or progresses during the course of the illness. In this magnetic resonance imaging study, we examined gray/white matter contrast (GWC) as a potential marker of intracortical myelination in 63 first-episode schizophrenia (FESz) patients and 77 healthy controls (HC). Furthermore, we investigated the relationships between GWC findings and clinical/cognitive variables in FESz patients. GWC in the bilateral temporal, parietal, occipital, and insular regions was significantly higher in FESz patients than in HC, which was partly associated with the durations of illness and medication, the onset age, and lower executive and verbal learning performances. Because higher GWC implicates lower myelin in the deeper layers of the cortex, these results suggest that schizophrenia patients have less intracortical myelin at the time of their first psychotic episode, which underlies lower cognitive performance in early illness stages.

Activation of prefrontal parvalbumin interneurons ameliorates working memory deficit even under clinically comparable antipsychotic treatment in a mouse model of schizophrenia.

One of the critical unmet medical needs in schizophrenia is the treatment for cognitive deficits. However, the neural circuit mechanisms of them remain unresolved. Previous studies utilizing animal models of schizophrenia did not consider the fact that patients with schizophrenia generally cannot discontinue antipsychotic medication due to the high risk of relapse. Here, we used multi-dimensional approaches, including histological analysis of the prelimbic cortex (PL), LC-MS/MS-based in vivo dopamine D2 receptor occupancy analysis for antipsychotics, in vivo calcium imaging, and behavioral analyses of mice using chemogenetics to investigate neural mechanisms and potential therapeutic strategies for working memory deficit in a chronic phencyclidine (PCP) mouse model of schizophrenia. Chronic PCP administration led to alterations in excitatory and inhibitory synapses, specifically in dendritic spines of pyramidal neurons, vesicular glutamate transporter 1 (VGLUT1) positive terminals, and parvalbumin (PV) positive GABAergic interneurons located in layer 2-3 of the PL. Continuous administration of olanzapine, which achieved a sustained therapeutic window of dopamine D2 receptor occupancy (60-80%) in the striatum, did not ameliorate these synaptic abnormalities and working memory deficit in the chronic PCP-treated mice. We demonstrated that chemogenetic activation of PV neurons in the PL, as confirmed by in vivo calcium imaging, ameliorated working memory deficit in this model even under clinically comparable olanzapine treatment which by itself inhibited only PCP-induced psychomotor hyperactivity. Our study suggests that targeting prefrontal PV neurons could be a promising therapeutic intervention for cognitive deficits in schizophrenia in combination with antipsychotic medication.

Linking Polygenic Risk of Schizophrenia to Variation in Magnetic Resonance Imaging Brain Measures: A Comprehensive Systematic Review.

BACKGROUND AND HYPOTHESIS: Schizophrenia is highly heritable, with a polygenic effect of many genes conferring risk. Evidence on whether cumulative risk also predicts alterations in brain morphology and function is inconsistent. This systematic review examined evidence for schizophrenia polygenic risk score (sczPRS) associations with commonly used magnetic resonance imaging (MRI) measures. We expected consistent evidence to emerge for significant sczPRS associations with variation in structure and function, specifically in frontal, temporal, and insula cortices that are commonly implicated in schizophrenia pathophysiology. STUDY DESIGN: In accordance with Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched MEDLINE, Embase, and PsycINFO for peer-reviewed studies published between January 2013 and March 2022. Studies were screened against predetermined criteria and National Institutes of Health (NIH) quality assessment tools. STUDY RESULTS: In total, 57 studies of T1-weighted structural, diffusion, and functional MRI were included (age range = 9-80 years, Nrange = 64-76 644). We observed moderate, albeit preliminary, evidence for higher sczPRS predicting global reductions in cortical thickness and widespread variation in functional connectivity, and to a lesser extent, region-specific reductions in frontal and temporal volume and thickness. Conversely, sczPRS does not predict whole-brain surface area or gray/white matter volume. Limited evidence emerged for sczPRS associations with diffusion tensor measures of white matter microstructure in a large community sample and smaller cohorts of children and young adults. These findings were broadly consistent across community and clinical populations. CONCLUSIONS: Our review supports the hypothesis that schizophrenia is a disorder of disrupted within and between-region brain connectivity, and points to specific whole-brain and regional MRI metrics that may provide useful intermediate phenotypes.

Familial Risk for Schizophrenia vs Bipolar Disorder and Task-Based Neural Activation: A functional Magnetic Resonance Imaging Meta-Analysis.

BACKGROUND AND HYPOTHESIS: Individuals at familial risk for developing schizophrenia (FRSZ) or bipolar disorder (FRBD) have shared and unique genetic risks. Few studies have compared neural activation between these two groups. Therefore, the present meta-analysis investigated functional brain similarities and differences between FRSZ and FRBD individuals. STUDY DESIGN: A systematic literature review was conducted of articles that compared FRSZ or FRBD individuals to healthy controls (31 FRSZ and 22 FRBD). Seed-based d mapping was used to conduct the meta-analysis. Analyses included comparisons of FRSZ to controls, FRBD to controls, and both relative groups to each other. STUDY RESULTS: Using a highly conservative family-wise error rate correction, there were no significant findings. Using a less conservative threshold, FRSZ compared to controls had lower activation in the left precuneus (Puncorrected = .02) across all studies and in the left middle frontal gyrus (Puncorrected = .03) in nonsocial cognition studies. FRBD compared to controls had lower activation in the left superior parietal gyrus (Puncorrected = .03) and right angular gyrus (Puncorrected = .03) in nonsocial cognition studies, and higher activation in the left superior frontal gyrus (Puncorrected = .01) in social tasks. Differences between FRSZ and FRBD were not significant. CONCLUSIONS: There were few robust differences between FRSZ or FRBD compared to controls. This suggests only weak support for neural activation differences between individuals at genetic risk for schizophrenia or bipolar disorder and controls. The tentative findings observed were in different brain regions for FRSZ and FRBD, with no strong evidence for shared effects between schizophrenia and bipolar genetic risk on neural activation.

Assessing the association between global structural brain age and polygenic risk for schizophrenia in early adulthood: A recall-by-genotype study.

Neuroimaging studies consistently show advanced brain age in schizophrenia, suggesting that brain structure is often 'older' than expected at a given chronological age. Whether advanced brain age is linked to genetic liability for schizophrenia remains unclear. In this pre-registered secondary data analysis, we utilised a recall-by-genotype approach applied to a population-based subsample from the Avon Longitudinal Study of Parents and Children to assess brain age differences between young adults aged 21-24 years with relatively high (n = 96) and low (n = 93) polygenic risk for schizophrenia (SCZ-PRS). A global index of brain age (or brain-predicted age) was estimated using a publicly available machine learning model previously trained on a combination of region-wise gray-matter measures, including cortical thickness, surface area and subcortical volumes derived from T1-weighted magnetic resonance imaging (MRI) scans. We found no difference in mean brain-PAD (the difference between brain-predicted age and chronological age) between the high- and low-SCZ-PRS groups, controlling for the effects of sex and age at time of scanning (b = -.21; 95% CI -2.00, 1.58; p = .82; Cohen's d = -.034; partial R2 = .00029). These findings do not support an association between SCZ-PRS and brain-PAD based on global age-related structural brain patterns, suggesting that brain age may not be a vulnerability marker of common genetic risk for SCZ. Future studies with larger samples and multimodal brain age measures could further investigate global or localised effects of SCZ-PRS.

ASCL1 Is Involved in the Pathogenesis of Schizophrenia by Regulation of Genes Related to Cell Proliferation, Neuronal Signature Formation, and Neuroplasticity.

Schizophrenia (SZ) is a common psychiatric neurodevelopmental disorder with a complex genetic architecture. Genome-wide association studies indicate the involvement of several transcription factors, including ASCL1, in the pathogenesis of SZ. We aimed to identify ASCL1-dependent cellular and molecular mechanisms associated with SZ. We used Capture-C, CRISPR/Cas9 systems and RNA-seq analysis to confirm the involvement of ASCL1 in SZ-associated pathogenesis, establish a mutant SH-SY5Y line with a functional ASCL1 knockout (ASCL1-del) and elucidate differentially expressed genes that may underlie ASCL1-dependent pathogenic mechanisms. Capture-C confirmed the spatial interaction of the ASCL1 promoter with SZ-associated loci. Transcriptome analysis showed that ASCL1 regulation may be through a negative feedback mechanism. ASCL1 dysfunction affects the expression of genes associated with the pathogenesis of SZ, as well as bipolar and depressive disorders. Genes differentially expressed in ASCL1-del are involved in cell mitosis, neuronal projection, neuropeptide signaling, and the formation of intercellular contacts, including the synapse. After retinoic acid (RA)-induced differentiation, ASCL1 activity is restricted to a small subset of genes involved in neuroplasticity. These data suggest that ASCL1 dysfunction promotes SZ development predominantly before the onset of neuronal differentiation by slowing cell proliferation and impeding the formation of neuronal signatures.

Neural correlates of mental state decoding and mental state reasoning in schizophrenia.

Theory of mind skills are disrupted in schizophrenia. However, various theory of mind tasks measure different neurocognitive domains. This multimodal neuroimaging study aimed to investigate the neuroanatomical correlates of mental state decoding and reasoning components of theory of mind in schizophrenia and healthy controls (HCs) using T1-weighted and diffusion-weighted (DTI) magnetic resonance imaging (MRI). Sixty-two patients with schizophrenia and 34 HCs were included. The Reading the Mind in the Eyes (RMET) and Hinting tests were used to evaluate mental state decoding and reasoning, respectively. Correlations between social cognition and cortical parameters (thickness, volume, surface area), or DTI scalars (fractional anisotropy, axial diffusivity, radial diffusivity) were cluster-based corrected for multiple comparisons. In schizophrenia, RMET scores showed positive correlations in 3 clusters, including left insula thickness, right superior-temporal thickness, left superior-temporal-sulcus volume, and DTI analysis revealed that fractional anisotropy showed positive correlations in 3 clusters, including right inferior-fronto-occipital fasciculus, left forceps-major, left inferior-fronto-occipital fasciculus. In schizophrenia, Hinting test scores showed positive correlations in 3 clusters in T1-weighted MRI, including left superior-temporal-sulcus volume, left superior-temporal-sulcus surface area, left pars-orbitalis volume. In conclusion, this study provided evidence for the involvement of particular cortical regions and white matter tracts in mental state decoding and reasoning.

Cross-modal associative memory impairment in schizophrenia.

Impaired associative memory function in patients with schizophrenia has received considerable attention. However, previous studies have primarily concentrated on unisensory materials, which limits our understanding of the broader implications of this impairment. In this study, we sought to expand on this knowledge by examining two types of associative memory domains in individuals with schizophrenia, leveraging both visual (Vis) and auditory (Aud) materials. A total of 32 patients with schizophrenia and 29 healthy controls were recruited to participate in the study. Each participant participated in an experiment composed of three paradigms in which different abstract materials (Aud-Aud, Aud-Vis, and Vis-Vis) were presented. Subsequently, the discriminability scores of the two groups were calculated and compared in different modal tasks. Results from the study indicated that individuals with schizophrenia demonstrated varying degrees of associative memory dysfunction in both the same and cross-modalities, with the latter having a significantly lower score than healthy controls (t = 4.120, p < 0.001). Additionally, the cross-modal associative memory function was significantly and negatively correlated with the severity of negative symptoms among individuals diagnosed with schizophrenia (r = -0.362, p = 0.042). This study provides evidence of abnormalities in the processing and memorization of information that integrates multiple sensory modalities in individuals with schizophrenia. This is of great significance for further understanding the cognitive symptoms and pathological mechanisms of schizophrenia, potentially guiding the development of relevant interventions and treatment methods.

Birth season and gross brain morphology associated with early neurodevelopment in schizophrenia spectrum patients and healthy subjects.

This MRI study examined the effects of birth seasons on gross brain characteristics, such as the prevalence/size of midline brain structures (cavum septi pellucidi and adhesio interthalamica), orbitofrontal surface morphology, and insular gross anatomy, in 135 patients with schizophrenia, 47 with schizotypal disorder, and 88 healthy controls. Birth seasons only affected the insular anatomy. Summer-born subjects (N = 110) were characterized by more developed left insular gyri than winter-born subjects; however, this effect had no diagnostic specificity. The present results do not support birth seasons affecting the neurodevelopmental pathology of schizophrenia spectrum.

Shared and distinct abnormalities of brain magnetization transfer ratio in schizophrenia and major depressive disorder: a comparative voxel-based meta-analysis.

BACKGROUND: Patients with schizophrenia (SCZ) and major depressive disorder (MDD) share significant clinical overlap, although it remains unknown to what extent this overlap reflects shared neural profiles. To identify the shared and specific abnormalities in SCZ and MDD, we performed a whole-brain voxel-based meta-analysis using magnetization transfer imaging, a technique that characterizes the macromolecular structural integrity of brain tissue in terms of the magnetization transfer ratio (MTR). METHODS: A systematic search based on Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines was conducted in PubMed, EMBASE, International Scientific Index (ISI) Web of Science, and MEDLINE for relevant studies up to March 2022. Two researchers independently screened the articles. Rigorous scrutiny and data extraction were performed for the studies that met the inclusion criteria. Voxel-wise meta-analyses were conducted using anisotropic effect size-signed differential mapping with a unified template. Meta-regression was used to explore the potential effects of demographic and clinical characteristics. RESULTS: A total of 15 studies with 17 datasets describing 365 SCZ patients, 224 MDD patients, and 550 healthy controls (HCs) were identified. The conjunction analysis showed that both disorders shared higher MTR than HC in the left cerebellum ( P =0.0006) and left fusiform gyrus ( P =0.0004). Additionally, SCZ patients showed disorder-specific lower MTR in the anterior cingulate/paracingulate gyrus, right superior temporal gyrus, and right superior frontal gyrus, and higher MTR in the left thalamus, precuneus/cuneus, posterior cingulate gyrus, and paracentral lobule; and MDD patients showed higher MTR in the left middle occipital region. Meta-regression showed no statistical significance in either group. CONCLUSIONS: The results revealed a structural neural basis shared between SCZ and MDD patients, emphasizing the importance of shared neural substrates across psychopathology. Meanwhile, distinct disease-specific characteristics could have implications for future differential diagnosis and targeted treatment.

Detecting schizophrenia with 3D structural brain MRI using deep learning.

Schizophrenia is a chronic neuropsychiatric disorder that causes distinct structural alterations within the brain. We hypothesize that deep learning applied to a structural neuroimaging dataset could detect disease-related alteration and improve classification and diagnostic accuracy. We tested this hypothesis using a single, widely available, and conventional T1-weighted MRI scan, from which we extracted the 3D whole-brain structure using standard post-processing methods. A deep learning model was then developed, optimized, and evaluated on three open datasets with T1-weighted MRI scans of patients with schizophrenia. Our proposed model outperformed the benchmark model, which was also trained with structural MR images using a 3D CNN architecture. Our model is capable of almost perfectly (area under the ROC curve = 0.987) distinguishing schizophrenia patients from healthy controls on unseen structural MRI scans. Regional analysis localized subcortical regions and ventricles as the most predictive brain regions. Subcortical structures serve a pivotal role in cognitive, affective, and social functions in humans, and structural abnormalities of these regions have been associated with schizophrenia. Our finding corroborates that schizophrenia is associated with widespread alterations in subcortical brain structure and the subcortical structural information provides prominent features in diagnostic classification. Together, these results further demonstrate the potential of deep learning to improve schizophrenia diagnosis and identify its structural neuroimaging signatures from a single, standard T1-weighted brain MRI.