Subcortical brain volume abnormalities in 2028 individuals with schizophrenia and 2540 healthy controls via the ENIGMA consortium

Antipsychotics cause reversible structural brain changes within one week

Determining the effects of antipsychotics on MRI brain structural metrics without the potential confounding effects related to the natural course of a psychotic illness is challenging. However, it is crucial to understand these effects to interpret the results of cross-sectional and longitudinal studies in medicated patients and, ultimately, to understand better the biological mechanisms driving antipsychotics' effects. In this work, we aim to determine whether exposure to antipsychotics is associated with alterations in brain MRI structural metrics in the absence of disease effects. A randomized, double-blind, counter-balanced order, crossover, placebo-controlled study in healthy volunteers was performed. The study comprised two arms. Within arms, participants were randomized to receive daily doses of either the active compound (Arm 1= amisulpride 400 mg/day, N = 24; Arm 2= aripiprazole 10 mg/day, N = 24) for one week, followed by placebo or vice versa. We found increased MRI volume estimates in the left putamen and in the right caudate in the amisulpride condition as compared to placebo and increased right putamen volume estimates after aripiprazole compared to placebo. No other effects were found in cortical volume estimates, cortical thickness, cortical surface area, and T1-relaxation time. Striatal changes reversed within weeks of drug withdrawal. Short-term exposure to either one of two different antipsychotics results in a transient increase in striatal volume measured with T1-weighted MRI that normalizes rapidly on stopping treatment without cortical changes. Our findings suggest that striatal volumetric MRI differences detected in people with schizophrenia taking antipsychotics are, at least in part, attributable to pharmacological effects.

Highly demarcated structural alterations in the brain and impaired social incentive learning in Tbx1 heterozygous mice

Copy number variants (CNVs) are robustly associated with psychiatric disorders and changes in brain structures. However, because CNVs contain many genes, the precise gene-phenotype relationship remains unclear. Although various volumetric alterations in the brains of 22q11.2 CNV carriers have been identified in humans and mouse models, it is unknown how each gene encoded in the 22q11.2 region contributes to structural alterations, associated mental illnesses, and their dimensions. Our previous studies identified Tbx1, a T-box family transcription factor encoded in the 22q11.2 CNV, as a driver gene for social interaction and communication, spatial and working memory, and cognitive flexibility. However, it remains unclear how TBX1 impacts the volumes of various brain regions and their functionally linked behavioral dimensions. In this study, we used volumetric magnetic resonance imaging analysis to comprehensively evaluate brain region volumes and behavioral alterations relevant to affected structures in congenic Tbx1 heterozygous mice. Our data showed that the volumes of the anterior and posterior portions of the amygdaloid complex and its surrounding cortical regions were most robustly reduced in Tbx1 heterozygous mice. In an amygdala-dependent task, Tbx1 heterozygous mice were impaired in their ability to learn the incentive value of a social partner. The volumes of the primary and secondary auditory cortexes were increased, and acoustic, but not non-acoustic, sensorimotor gating was impaired in Tbx1 heterozygous mice. Our findings identify the brain's regional volume alterations and their relevant behavioral dimensions associated with Tbx1 heterozygosity.

Functional vs Structural Cortical Deficit Pattern Biomarkers for Major Depressive Disorder

Importance

Major depressive disorder (MDD) is a severe mental illness characterized more by functional rather than structural brain abnormalities. The pattern of regional homogeneity (ReHo) deficits in MDD may relate to underlying regional hypoperfusion. Capturing this functional deficit pattern provides a brain pattern-based biomarker for MDD that is linked to the underlying pathophysiology.

Objective

To examine whether cortical ReHo patterns provide a replicable biomarker for MDD that is more sensitive than reduced cortical thickness and evaluate whether the ReHo MDD deficit pattern reflects regional cerebral blood flow (RCBF) deficit patterns in MDD and whether a regional vulnerability index (RVI) thus constructed may provide a concise brain pattern-based biomarker for MDD.

Design, Settings, and Participants

The UK Biobank (UKBB) participants had ReHo and structural measurements. Participants from the Enhancing Neuroimaging Genetics Through Meta-Analysis (ENIGMA) Consortium were included for measuring the MDD structural cortical deficit pattern. The UKBB ReHo and ENIGMA cortical thickness effect sizes for MDD were used to test the deficit patterns in the Amish Connectome Project (ACP) with ReHo, structural, and RCBF data. Finally, the Ament Clinic Inc (ACI) sample had RCBF data measured using single-photon emission computed tomography. Data were analyzed from August 2021 to September 2024.

Exposures

ReHo and structural measurements.

Results

Included in this analysis were 4 datasets: (1) UKBB (N = 4810 participants; 2220 with recurrent MDD and 2590 controls; mean [SD] age, 63.0 [7.5] years; 1121 female [50%]), (2) ENIGMA (N = 10 115 participants; 2148 with MDD and 7957 healthy controls; mean [SD] age, 39.9 [10.0] years; 5927 female [59%]), (3) ACP (N = 204 participants; 68 with a lifetime diagnosis of MDD and 136 controls; mean [SD] age, 41.0 [14.5] years; 104 female [51%]), and (4) ACI (N = 372 participants; 296 with recurrent MDD and 76 controls; mean [SD] age, 45.3 [17.2] years; 189 female [51%]). MDD participants had lower cortical ReHo in the cingulum, superior temporal lobe, frontal lobe, and several other areas, with no significant differences in cortical thickness. The regional pattern of ReHo MDD effect sizes was significantly correlated with that of RCBF obtained from 2 independent datasets (Pearson r = 0.52 and Pearson r = 0.46; P < 10-4). ReHo and RCBF functional RVIs showed numerically stronger effect sizes (Cohen d = 0.33-0.90) compared with structural RVIs (Cohen d = 0.09-0.20). Elevated ReHo-based RVI-MDD values in individuals with MDD were associated with higher depression symptom severity across cohorts.

Conclusions and Relevance

Results of this case-control study suggest that the ReHo MDD deficit pattern reflected cortical hypoperfusion and was regionally specific in MDD. ReHo-based RVI may serve as a sensitive functional biomarker for MDD.

Spatial patterns of individual morphological deformation in schizophrenia: Putative cortical compensatory of unaffected sibling

BACKGROUND

Neuroimaging advancements have revealed morphological deformation across various indicators, illuminating the neuropathological origins of schizophrenia. However, consolidating the findings across indicators and assessing regional global deformation at individual-level poses a significant challenge.

METHODS

We propose individual morphological deformation index (IMDI) as potential biomarker for schizophrenia leveraging a distance algorithm that incorporates three key indicators (cortical thickness, gyrification, and volume), and applied it for 199 schizophrenia patients, 218 healthy controls, and 47 unaffected siblings. Additionally, we studied the relationships between polygenic risks, symptomology, cognition, social functioning and regional IMDI.

RESULTS

Our findings reveal significantly higher IMDI in specific brain regions (bilateral pars opercularis, lateral orbitofrontal, left superior parietal, right pars orbitalis, and superior temporal) in patients, demonstrating two distinct spatial patterns linked to either isolated indicator reduction or concurrent declines across multiple indicators. Notably, unaffected siblings exhibited higher IMDI than controls, primarily due to cortical volume expansion in the right pars opercularis and superior temporal regions. Patients with higher IMDI had more severe positive symptoms, impaired cognition, reduced social functioning and selfcare ability. Participants with higher polygenic scores showed higher IMDI specifically in left caudal middle frontal regions.

CONCLUSIONS

The proposed IMDI biomarker offers an objective, interpretable way to quantify global regional deformation and integrate disparate neuroimaging indicators. Our results indicate that schizophrenia-related cortical deformations encompass sensorimotor, attention, default mode, and frontoparietal networks, exhibiting at least two spatial patterns. Moreover, siblings may exhibit compensation in cortical volume. These insights offer a novel perspective on the neuroanatomical underpinnings of schizophrenia.

Identifying novel chemical-related susceptibility genes for five psychiatric disorders through integrating genome-wide association study and tissue-specific 3'aQTL annotation datasets

The establishment of 3'aQTLs comprehensive database provides an opportunity to help explore the functional interpretation from the genome-wide association study (GWAS) data of psychiatric disorders. In this study, we aim to search novel susceptibility genes, pathways, and related chemicals of five psychiatric disorders via GWAS and 3'aQTLs datasets. The GWAS datasets of five psychiatric disorders were collected from the open platform of Psychiatric Genomics Consortium (PGC, https://www.med.unc.edu/pgc/ ) and iPSYCH ( https://ipsych.dk/ ) (Demontis et al. in Nat Genet 51(1):63-75, 2019; Grove et al. in Nat Genet 51:431-444, 2019; Genomic Dissection of Bipolar Disorder and Schizophrenia in Cell 173: 1705-1715.e1716, 2018; Mullins et al. in Nat Genet 53: 817-829; Howard et al. in Nat Neurosci 22: 343-352, 2019). The 3'untranslated region (3'UTR) alternative polyadenylation (APA) quantitative trait loci (3'aQTLs) summary datasets of 12 brain regions were obtained from another public platform ( https://wlcb.oit.uci.edu/3aQTLatlas/ ) (Cui et al. in Nucleic Acids Res 50: D39-D45, 2022). First, we aligned the GWAS-associated SNPs of psychiatric disorders and datasets of 3'aQTLs, and then, the GWAS-associated 3'aQTLs were identified from the overlap. Second, gene ontology (GO) and pathway analysis was applied to investigate the potential biological functions of matching genes based on the methods provided by MAGMA. Finally, chemical-related gene-set analysis (GSA) was also conducted by MAGMA to explore the potential interaction of GWAS-associated 3'aQTLs and multiple chemicals in the mechanism of psychiatric disorders. A number of susceptibility genes with 3'aQTLs were found to be associated with psychiatric disorders and some of them had brain-region specificity. For schizophrenia (SCZ), HLA-A showed associated with psychiatric disorders in all 12 brain regions, such as cerebellar hemisphere (P = 1.58 × 10-36) and cortex (P = 1.58 × 10-36). GO and pathway analysis identified several associated pathways, such as Phenylpropanoid Metabolic Process (GO:0009698, P = 6.24 × 10-7 for SCZ). Chemical-related GSA detected several chemical-related gene sets associated with psychiatric disorders. For example, gene sets of Ferulic Acid (P = 6.24 × 10-7), Morin (P = 4.47 × 10-2) and Vanillic Acid (P = 6.24 × 10-7) were found to be associated with SCZ. By integrating the functional information from 3'aQTLs, we identified several susceptibility genes and associated pathways especially chemical-related gene sets for five psychiatric disorders. Our results provided new insights to understand the etiology and mechanism of psychiatric disorders.

Estimating Multimodal Structural Brain Variability in Schizophrenia Spectrum Disorders: A Worldwide ENIGMA Study

OBJECTIVE

The clinical diversity of schizophrenia is reflected by structural brain variability. It remains unclear how this variability manifests across different gray and white matter features. In this meta- and mega-analysis, the authors investigated how brain heterogeneity in schizophrenia is distributed across multimodal structural indicators.

METHODS

The authors used the ENIGMA dataset of MRI-based brain measures from 22 international sites with up to 6,037 individuals for a given brain measure. Variability and mean values of cortical thickness, cortical surface area, cortical folding index, subcortical volume, and fractional anisotropy were examined in individuals with schizophrenia and healthy control subjects.

RESULTS

Individuals with schizophrenia showed greater variability in cortical thickness, cortical surface area, subcortical volume, and fractional anisotropy within the frontotemporal and subcortical network. This increased structural variability was mainly associated with psychopathological symptom domains, and the schizophrenia group frequently displayed lower mean values in the respective structural measures. Unexpectedly, folding patterns were more uniform in individuals with schizophrenia, particularly in the right caudal anterior cingulate region. The mean folding values of the right caudal anterior cingulate region did not differ between the schizophrenia and healthy control groups, and folding patterns in this region were not associated with disease-related parameters.

CONCLUSIONS

In patients with schizophrenia, uniform folding patterns in the right caudal anterior cingulate region contrasted with the multimodal variability in the frontotemporal and subcortical network. While variability in the frontotemporal and subcortical network was associated with disease-related diversity, uniform folding may indicate a less flexible interplay between genetic and environmental factors during neurodevelopment.

Cognitive impairment following maternal separation in rats mediated by the NAD+/SIRT3 axis via modulation of hippocampal synaptic plasticity

Maternal separation (MS) during early life can induce behaviors in adult animals that resemble those seen in schizophrenia, manifesting cognitive deficits. These cognitive deficits may be indicative of oxidative stress linked to mitochondrial dysfunction. However, there is limited understanding of the molecular mechanisms regulating mitochondria in neural circuits that govern cognitive impairment relevant to schizophrenia, and their impact on neuronal structure and function. A 24-h MS rat model was utilized to simulate features associated with schizophrenia. Schizophrenia-associated behaviors and cognitive impairment were assessed using the open field test, pre-pulse inhibition, novel object recognition test, and Barnes maze test. The levels of mitochondrial proteins were measured using western blot analysis. Additionally, alterations in mitochondrial morphology, reduced hippocampal neuronal spine density, and impaired LTP in the hippocampus were observed. Nicotinamide (NAM) supplementation, administration of honokiol (HNK) (a SIRT3 activator), or overexpression of SIRT3 could inhibit cognitive deficits and cellular dysfunction. Conversely, administration of 3-TYP (a SIRT3 inhibitor) or knocking down SIRT3 expression in control rats led to deficits in behavioral and hippocampal neuronal phenotype. Our results suggest a causal role for the NAD+/SIRT3 axis in modulating cognitive behaviors via effects on hippocampal neuronal synaptic plasticity. The NAD+/SIRT3 axis could be a promising therapeutic target for addressing cognitive dysfunctions, such as those seen in schizophrenia.

Genetic overlap between schizophrenia and constipation: insights from a genome-wide association study in a European population

BACKGROUND

Patients with schizophrenia (SCZ) experience constipation at significantly higher rates compared with the general population. This relationship suggests a potential genetic overlap between these two conditions.

METHODS

We analyzed genome-wide association study (GWAS) data for both SCZ and constipation using a five-part approach. The first and second parts assessed the overall and local genetic correlations using methods such as linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics (HESS). The third part investigated the causal association between the two traits using Mendelian randomization (MR). The fourth part employed conditional/conjunctional false discovery rate (cond/conjFDR) to analyze the genetic overlap with different traits based on the statistical theory. Finally, an LDSC-specifically expressed gene (LDSC-SEG) analysis was conducted to explore the tissue-level associations.

RESULTS

Our analyses revealed both overall and specific genetic correlations between SCZ and constipation at the genomic level. The MR analysis suggests a positive causal relationship between SCZ and constipation. The ConjFDR analysis confirms the genetic overlap between the two conditions and identifies two genetic risk loci (rs7583622 and rs842766) and seven mapped genes (GPR75-ASB3, ASB3, CHAC2, ERLEC1, GPR75, PSME4, and ACYP2). Further investigation into the functions of these genes could provide valuable insights. Interestingly, disease-related tissue analysis revealed associations between SCZ and constipation in eight brain regions (substantia nigra, anterior cingulate cortex, hypothalamus, cortex, hippocampus, cortex, amygdala, and spinal cord).

CONCLUSION

This study provides the first genetic evidence for the comorbidity of SCZ and constipation, enhancing our understanding of the pathophysiology of both conditions.

Structural neuroimaging abnormality and neurocognitive deficit in the first-degree relatives of schizophrenia patients (FDR) compared to the first-episode patients with schizophrenia (FEP) and healthy controls

The existing evidence regarding structural neuroimaging alternations during the premorbid and prodromal stages of psychosis remains limited and inconsistent. Gaining a deeper insight into the morphological brain variations could potentially advance the early diagnosis of high-risk individuals for psychosis, thereby offering a clearer understanding of the underlying mechanisms that lead to the progression towards mental disorders, particularly schizophrenia. In our study, we conducted comprehensive face-to-face clinical interviews, psychiatric symptom assessments, and neurocognitive evaluation for 25 first-episode patients with schizophrenia (FEP), 35 first-degree relatives of schizophrenia patients (FDR), and 22 healthy controls (HC). We also collected structural magnetic resonance imaging (sMRI) data for all participants. The results demonstrated that the FEP group experienced the most severe clinical symptoms, the lowest global function, and the poorest neurocognitive function, followed by the FDR and HC groups. FEP group exhibited significant reductions in the surface area, cortical thickness, or volume of the right cuneus cortex, bilateral entorhinal cortex, left para-hippocampal gyrus, bilateral temporal pole, and right insula cortex compared to the FDR and HC groups. However, no significant difference in surface area, cortical thickness, and volume of all the regions of interest (ROIs) were found between the FDR group and HC group. To conclude, neurocognitive decline and gray matter reduction could serve as neuroimaging biomarkers for the onset and progression of psychosis. It is imperative to conduct further comprehensive researches to identify additional promising biomarkers, which will facilitate the early detection and intervention for individuals at risk of developing psychosis.

Proposal for a Novel Classification of Patients With Enlarged Ventricles and Cognitive Impairment Based on Data-Driven Analysis of Neuroimaging Results in Patients With Psychiatric Disorders

One of the challenges in diagnosing psychiatric disorders is that the results of biological and neuroscience research are not reflected in the diagnostic criteria. Thus, data-driven analyses incorporating biological and cross-disease perspectives, regardless of the diagnostic category, have recently been proposed. A data-driven clustering study based on subcortical volumes in 5604 subjects classified into four brain biotypes associated with cognitive/social functioning. Among the four brain biotypes identified in controls and patients with schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorder, and other psychiatric disorders, we further analyzed the brain biotype 1 subjects, those with an extremely small limbic region, for clinical utility. We found that the representative feature of brain biotype 1 is enlarged lateral ventricles. An enlarged ventricle, defined by an average z-score of left and right lateral ventricle volumes > 3, had a sensitivity of 99.1% and a specificity of 98.1% for discriminating brain biotype 1. However, the presence of an enlarged ventricle was not sufficient to classify patient subgroups, as 1% of the controls also had enlarged ventricles. Reclassification of patients with enlarged ventricles according to cognitive impairment resulted in a stratified subgroup that included patients with a high proportion of schizophrenia diagnoses, electroencephalography abnormalities, and rare pathological genetic copy number variations. Data-driven clustering analysis of neuroimaging data revealed subgroups with enlarged ventricles and cognitive impairment. This subgroup could be a new diagnostic candidate for psychiatric disorders. This concept and strategy may be useful for identifying biologically defined psychiatric disorders in the future.

Applications of MRI in Schizophrenia: Current Progress in Establishing Clinical Utility

Schizophrenia is a severe mental illness that significantly impacts the lives of affected individuals and with increasing mortality rates. Early detection and intervention are crucial for improving outcomes but the lack of validated biomarkers poses great challenges in such efforts. The use of magnetic resonance imaging (MRI) in schizophrenia enables the investigation of the disorder's etiological and neuropathological substrates in vivo. After decades of research, promising findings of MRI have been shown to aid in screening high-risk individuals and predicting illness onset, and predicting symptoms and treatment outcomes of schizophrenia. The integration of machine learning and deep learning techniques makes it possible to develop intelligent diagnostic and prognostic tools with extracted or selected imaging features. In this review, we aimed to provide an overview of current progress and prospects in establishing clinical utility of MRI in schizophrenia. We first provided an overview of MRI findings of brain abnormalities that might underpin the symptoms or treatment response process in schizophrenia patients. Then, we summarized the ongoing efforts in the computer-aided utility of MRI in schizophrenia and discussed the gap between MRI research findings and real-world applications. Finally, promising pathways to promote clinical translation were provided. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 3.

Automatic rating of incomplete hippocampal inversions evaluated across multiple cohorts

Incomplete Hippocampal Inversion (IHI), sometimes called hippocampal malrotation, is an atypical anatomical pattern of the hippocampus found in about 20% of the general population. IHI can be visually assessed on coronal slices of T1 weighted MR images, using a composite score that combines four anatomical criteria. IHI has been associated with several brain disorders (epilepsy, schizophrenia). However, these studies were based on small samples. Furthermore, the factors (genetic or environmental) that contribute to the genesis of IHI are largely unknown. Large-scale studies are thus needed to further understand IHI and their potential relationships to neurological and psychiatric disorders. However, visual evaluation is long and tedious, justifying the need for an automatic method. In this paper, we propose, for the first time, to automatically rate IHI. We proceed by predicting four anatomical criteria, which are then summed up to form the IHI score, providing the advantage of an interpretable score. We provided an extensive experimental investigation of different machine learning methods and training strategies. We performed automatic rating using a variety of deep learning models ("conv5-FC3", ResNet and "SECNN") as well as a ridge regression. We studied the generalization of our models using different cohorts and performed multi-cohort learning. We relied on a large population of 2,008 participants from the IMAGEN study, 993 and 403 participants from the QTIM and QTAB studies as well as 985 subjects from the UKBiobank. We showed that deep learning models outperformed a ridge regression. We demonstrated that the performances of the "conv5-FC3" network were at least as good as more complex networks while maintaining a low complexity and computation time. We showed that training on a single cohort may lack in variability while training on several cohorts improves generalization (acceptable performances on all tested cohorts including some that are not included in training). The trained models are available at https://github.com/LisaHemforth/AutomaticIHIRating.

Mismatch Negativity as an Index of Auditory Short-Term Plasticity: Associations with Cortisol, Inflammation, and Gray Matter Volume in Youth at Clinical High Risk for Psychosis

Mismatch negativity (MMN) event-related potential (ERP) component reduction, indexing N-methyl-D-aspartate receptor (NMDAR)-dependent auditory echoic memory and short-term plasticity, is a well-established biomarker of schizophrenia that is sensitive to psychosis risk among individuals at clinical high-risk (CHR-P). Based on the NMDAR-hypofunction model of schizophrenia, NMDAR-dependent plasticity is predicted to contribute to aberrant neurodevelopmental processes involved in the pathogenesis of schizophrenia during late adolescence or young adulthood, including gray matter loss. Moreover, stress and inflammation disrupt plasticity. Therefore, using data collected during the 8-center North American Prodrome Longitudinal Study (NAPLS-2), we explored relationships between MMN amplitudes and salivary cortisol, gray matter volumes, and inflammatory cytokines. Participants included 303 CHR-P individuals with baseline electroencephalography (EEG) data recorded during an MMN paradigm as well as structural magnetic resonance imaging (MRI) and salivary cortisol, of which a subsample (n = 57) also completed blood draws. More deficient MMN amplitudes were associated with greater salivary cortisol and pro-inflammatory cytokine levels in future CHR-Converters, but not among those who did not convert to psychosis within the next two years. More deficient MMN amplitude was also associated with smaller total gray matter volume across participants regardless of future clinical outcomes, and with subcortical gray matter volumes among future CHR-Converters only. These findings are consistent with the theory that deficient NMDAR-dependent plasticity results in an overabundance of weak synapses that are subject to over-pruning during psychosis onset, contributing to gray matter loss. Further, MMN plasticity mechanisms may interact with stress, cortisol, and neuroinflammatory processes, representing a proximal influence of psychosis.

Constructing and exploring neuroimaging projects: a survey from clinical practice to scientific research

Over the past decades, numerous large-scale neuroimaging projects that involved the collection and release of multimodal data have been conducted globally. Distinguished initiatives such as the Human Connectome Project, UK Biobank, and Alzheimer's Disease Neuroimaging Initiative, among others, stand as remarkable international collaborations that have significantly advanced our understanding of the brain. With the advancement of big data technology, changes in healthcare models, and continuous development in biomedical research, various types of large-scale projects are being established and promoted worldwide. For project leaders, there is a need to refer to common principles in project construction and management. Users must also adhere strictly to rules and guidelines, ensuring data safety and privacy protection. Organizations must maintain data integrity, protect individual privacy, and foster stakeholders' trust. Regular updates to legislation and policies are necessary to keep pace with evolving technologies and emerging data-related challenges. CRITICAL RELEVANCE STATEMENT: By reviewing global large-scale neuroimaging projects, we have summarized the standards and norms for establishing and utilizing their data, and provided suggestions and opinions on some ethical issues, aiming to promote higher-quality neuroimaging data development. KEY POINTS: Global neuroimaging projects are increasingly advancing but still face challenges. Constructing and utilizing neuroimaging projects should follow set rules and guidelines. Effective data management and governance should be developed to support neuroimaging projects.

Psychiatric Disease as a Potential Risk Factor for Dementia: A Narrative Review

Neurodegenerative disease is a major global health problem with 150 million people predicted to have dementia by 2050. Genetic factors, environmental factors, demographics, and some diseases have been associated with dementia. In addition to associations between diseases such as hypertension and cerebrovascular disease and dementia, emerging findings associate some psychiatric disorders with incident dementia. Because of the high and increasing global prevalence of dementia and the high worldwide prevalence of psychiatric disorders, the primary objective of this narrative review was to evaluate published findings that evaluate the association between bipolar disorder, depression, anxiety, post-traumatic stress disorder, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, autism spectrum disorder, schizophrenia and other psychosis syndromes, and personality disorders and personality traits and incident dementia. Here, we highlight findings indicating possible associations between these psychiatric disorders and subsequent dementia and suggest that some psychiatric disorders may be risk factors for incident dementia. Further research, including more large longitudinal studies and additional meta-analyses, however, is needed to better characterize the associations between psychiatric disorders and incident dementia, to identify possible mechanisms for these putative associations, and to identify risk factors within psychiatric disorders that predispose some people with a psychiatric disorder but not others to subsequent dementia. Additional important questions concern how the treatment of psychiatric disorders might affect the risk of incident dementia.

Neurostructural subgroup in 4291 individuals with schizophrenia identified using the subtype and stage inference algorithm

Machine learning can be used to define subtypes of psychiatric conditions based on shared biological foundations of mental disorders. Here we analyzed cross-sectional brain images from 4,222 individuals with schizophrenia and 7038 healthy subjects pooled across 41 international cohorts from the ENIGMA, non-ENIGMA cohorts and public datasets. Using the Subtype and Stage Inference (SuStaIn) algorithm, we identify two distinct neurostructural subgroups by mapping the spatial and temporal 'trajectory' of gray matter change in schizophrenia. Subgroup 1 was characterized by an early cortical-predominant loss with enlarged striatum, whereas subgroup 2 displayed an early subcortical-predominant loss in the hippocampus, striatum and other subcortical regions. We confirmed the reproducibility of the two neurostructural subtypes across various sample sites, including Europe, North America and East Asia. This imaging-based taxonomy holds the potential to identify individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

New Advances in the Pharmacology and Toxicology of Lithium: A Neurobiologically Oriented Overview

Over the last six decades, lithium has been considered the gold standard treatment for the long-term management of bipolar disorder due to its efficacy in preventing both manic and depressive episodes as well as suicidal behaviors. Nevertheless, despite numerous observed effects on various cellular pathways and biologic systems, the precise mechanism through which lithium stabilizes mood remains elusive. Furthermore, there is recent support for the therapeutic potential of lithium in other brain diseases. This review offers a comprehensive examination of contemporary understanding and predominant theories concerning the diverse mechanisms underlying lithium's effects. These findings are based on investigations utilizing cellular and animal models of neurodegenerative and psychiatric disorders. Recent studies have provided additional support for the significance of glycogen synthase kinase-3 (GSK3) inhibition as a crucial mechanism. Furthermore, research has shed more light on the interconnections between GSK3-mediated neuroprotective, antioxidant, and neuroplasticity processes. Moreover, recent advancements in animal and human models have provided valuable insights into how lithium-induced modifications at the homeostatic synaptic plasticity level may play a pivotal role in its clinical effectiveness. We focused on findings from translational studies suggesting that lithium may interface with microRNA expression. Finally, we are exploring the repurposing potential of lithium beyond bipolar disorder. These recent findings on the therapeutic mechanisms of lithium have provided important clues toward developing predictive models of response to lithium treatment and identifying new biologic targets. SIGNIFICANCE STATEMENT: Lithium is the drug of choice for the treatment of bipolar disorder, but its mechanism of action in stabilizing mood remains elusive. This review presents the latest evidence on lithium's various mechanisms of action. Recent evidence has strengthened glycogen synthase kinase-3 (GSK3) inhibition, changes at the level of homeostatic synaptic plasticity, and regulation of microRNA expression as key mechanisms, providing an intriguing perspective that may help bridge the mechanistic gap between molecular functions and its clinical efficacy as a mood stabilizer.

Heterogeneous Brain Abnormalities in Schizophrenia Converge on a Common Network Associated With Symptom Remission

BACKGROUND AND HYPOTHESIS

There is a huge heterogeneity of magnetic resonance imaging findings in schizophrenia studies. Here, we hypothesized that brain regions identified by structural and functional imaging studies of schizophrenia could be reconciled in a common network.

STUDY DESIGN

We systematically reviewed the case-control studies that estimated the brain morphology or resting-state local function for schizophrenia patients in the literature. Using the healthy human connectome (n = 652) and a validated technique "coordinate network mapping" to identify a common brain network affected in schizophrenia. Then, the specificity of this schizophrenia network was examined by independent data collected from 13 meta-analyses. The clinical relevance of this schizophrenia network was tested on independent data of medication, neuromodulation, and brain lesions.

STUDY RESULTS

We identified 83 morphological and 60 functional studies comprising 7389 patients with schizophrenia and 7408 control subjects. The "coordinate network mapping" showed that the atrophy and dysfunction coordinates were functionally connected to a common network although they were spatially distant from each other. Taking all 143 studies together, we identified the schizophrenia network with hub regions in the bilateral anterior cingulate cortex, insula, temporal lobe, and subcortical structures. Based on independent data from 13 meta-analyses, we showed that these hub regions were specifically connected with regions of cortical thickness changes in schizophrenia. More importantly, this schizophrenia network was remarkably aligned with regions involving psychotic symptom remission.

CONCLUSIONS

Neuroimaging abnormalities in cross-sectional schizophrenia studies converged into a common brain network that provided testable targets for developing precise therapies.

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.

Longitudinal hippocampal subfield development associated with psychotic experiences in young people

Hippocampal volumetric reductions are observed across the psychosis spectrum, with interest in the localisation of these reductions within the hippocampal subfields increasing. Deficits of the CA1 subfield in particular have been implicated in the neuropathophysiology of psychotic disorders. Investigating the trajectory of these abnormalities in healthy adolescents reporting sub-threshold psychotic experiences (PE) can provide insight into the neural mechanisms underlying psychotic symptoms without the potentially confounding effects of a formal disorder, or antipsychotic medication. In this novel investigation, a sample of 211 young people aged 11-13 participated initially in the Adolescent Brain Development study. PE classification was determined by expert consensus at each timepoint. Participants underwent neuroimaging at 3 timepoints, over 6 years. 78 participants with at least one scan were included in the final sample; 33 who met criteria for a definite PE at least once across all the timepoints (PE group), and 45 controls. Data from bilateral subfields of interest (CA1, CA2/3, CA4/DG, presubiculum and subiculum) were extracted for Linear Mixed Effects analyses. Before correction, subfield volumes were found to increase in the control group and decrease in the PE group for the right CA2 and CA2/3 subfields, with moderate to large effect sizes (d = -0.61, and d = -0.79, respectively). Before correction, right subiculum and left presubiculum volumes were reduced in the PE group compared to controls, regardless of time, with moderate effect sizes (d = -0.52, and d = -0.59, respectively). However, none of these effects survived correction. Severity of symptoms were not associated with any of the noted subfields. These findings provide novel insight to the discussion of the role of hippocampal subfield abnormalities in the pathophysiology underlying psychotic experiences.

Normative Modeling of Brain Morphometry in Clinical High Risk for Psychosis

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.

THC improves behavioural schizophrenia-like deficits that CBD fails to overcome: a comprehensive multilevel approach using the Poly I:C maternal immune activation

Prenatal infections and cannabis use during adolescence are well-recognized risk factors for schizophrenia. As inflammation and oxidative stress (OS) contribute to this disorder, anti-inflammatory drugs have been proposed as potential therapies. This study aimed to evaluate the association between delta-9-tetrahydrocannabinol (THC) and schizophrenia-like abnormalities in a maternal immune activation (MIA) model. Additionally, we assessed the preventive effect of cannabidiol (CBD), a non-psychotropic/anti-inflammatory cannabinoid. THC and/or CBD were administered to Saline- and MIA-offspring during periadolescence. At adulthood, THC-exposed MIA-offspring showed significant improvements in sensorimotor gating deficits. Structural and metabolic brain changes were evaluated by magnetic resonance imaging, revealing cortical shrinkage in Saline- and enlargement in MIA-offspring after THC-exposure. Additionally, MIA-offspring displayed enlarged ventricles and decreased hippocampus, which were partially reverted by both cannabinoids. CBD prevented THC-induced reduction in the corpus callosum, despite affecting white matter structure. Post-mortem studies revealed detrimental effects of THC, including increased inflammation and oxidative stress. CBD partially reverted these pro-inflammatory alterations and modulated THC's effects on the endocannabinoid system. In conclusion, contrary to expectations, THC exhibited greater behavioural and morphometric benefits, despite promoting a pro-inflammatory state that CBD partially reverted. Further research is needed to elucidate the underlying mechanisms involved in the observed benefits of THC.

Altered Sex Differences in Hippocampal Subfield Volumes in Schizophrenia

BACKGROUND AND HYPOTHESIS

The hippocampus is a heterogenous brain structure that differs between the sexes and has been implicated in the pathophysiology of psychiatric illnesses. Here, we explored sex and diagnostic group differences in hippocampal subfield volumes, in individuals with schizophrenia spectrum disorder (SZ), bipolar disorders (BD), and healthy controls (CTL).

STUDY DESIGN

One thousand and five hundred and twenty-one participants underwent T1-weighted magnetic resonance imaging (SZ, n = 452, mean age 30.7 ± 9.2 [SD] years, males 59.1%; BD, n = 316, 33.7 ± 11.4, 41.5%; CTL, n = 753, 34.1 ± 9.1, 55.6%). Total hippocampal, subfield, and intracranial volumes were estimated with Freesurfer (v6.0.0). Analysis of covariance and multiple regression models were fitted to examine sex-by-diagnostic (sub)group interactions in volume. In SZ and BD, separately, associations between volumes and clinical as well as cognitive measures were examined between the sexes using regression models.

STUDY RESULTS

Significant sex-by-group interactions were found for the total hippocampus, dentate gyrus, molecular layer, presubiculum, fimbria, hippocampal-amygdaloid transition area, and CA4, indicating a larger volumetric deficit in male patients relative to female patients when compared with same-sex CTL. Subgroup analyses revealed that this interaction was driven by males with schizophrenia. Effect sizes were overall small (partial η < 0.02). We found no significant sex differences in the associations between hippocampal volumes and clinical or cognitive measures in SZ and BD.

CONCLUSIONS

Using a well-powered sample, our findings indicate that the pattern of morphological sex differences in hippocampal subfields is altered in individuals with schizophrenia relative to CTL, due to higher volumetric deficits in males.

Psychomotor slowing in schizophrenia is associated with cortical thinning of primary motor cortex: A three cohort structural magnetic resonance imaging study

Psychomotor slowing (PS) is characterized by slowed movements and lower activity levels. PS is frequently observed in schizophrenia (SZ) and distressing because it impairs performance of everyday tasks and social activities. Studying brain topography contributing to PS in SZ can help to understand the underlying neurobiological mechanisms as well as help to develop more effective treatments that specifically target affected brain areas. Here, we conducted structural magnetic resonance imaging (sMRI) of three independent cohorts of right-handed SZ patients (SZ#1: n = 72, SZ#2: n = 37, SZ#3: n = 25) and age, gender and education matched healthy controls (HC) (HC#1: n = 40, HC#2: n = 37, HC#3: n = 38). PS severity in the three SZ cohorts was determined using the Positive and Negative Syndrome Scale (PANSS) item #G7 (motor retardation) and Trail-Making-Test B (TMT-B). FreeSurfer v7.2 was used for automated parcellation and segmentation of cortical and subcortical regions. SZ#1 patients showed reduced cortical thickness in right precentral gyrus (M1; p = 0.04; Benjamini-Hochberg [BH] corr.). In SZ#1, cortical thinning in right M1 was associated with PANSS item #G7 (p = 0.04; BH corr.) and TMT-B performance (p = 0.002; BH corr.). In SZ#1, we found a significant correlation between PANSS item #G7 and TMT-B (p = 0.005, ρ=0.326). In conclusion, PANSS G#7 and TMT-B might have a surrogate value for predicting PS in SZ. Cortical thinning of M1 rather than alterations of subcortical structures may point towards cortical pathomechanism underlying PS in SZ.

The impact of placental genomic risk for schizophrenia and birth asphyxia on brain development

The placenta plays a role in fetal brain development, and pregnancy and birth complications can be signs of placental dysfunction. Birth asphyxia is associated with smaller head size and higher risk of developing schizophrenia (SZ), but whether birth asphyxia and placental genomic risk factors associated with SZ are related and how they might impact brain development is unclear. 433 adult patients with SZ and 870 healthy controls were clinically evaluated and underwent brain magnetic resonance imaging. Pregnancy and birth information were obtained from the Medical Birth Registry of Norway. Polygenic risk scores (PRS) from the latest genome-wide association study in SZ were differentiated into placental PRS (PlacPRS) and non-placental PRS. If the interaction between PRSs and birth asphyxia on case-control status was significant, neonatal head circumference (nHC) and adult intracranial volume (ICV) were further evaluated with these variables using multiple regression. PlacPRS in individuals with a history of birth asphyxia was associated with a higher likelihood of being a patient with SZ (t = 2.10, p = 0.018). We found a significant interaction between PlacPRS and birth asphyxia on nHC in the whole sample (t = -2.43, p = 0.008), with higher placental PRS for SZ associated with lower nHC in those with birth asphyxia. This relationship was specific to males (t = -2.71, p = 0.005) and also found with their adult ICV (t = -1.97, p = 0.028). These findings suggest that placental pathophysiology and birth asphyxia may affect early and late trajectories of brain development, particularly in males with a higher vulnerability to SZ. This knowledge might lead to new strategies of treatment and prevention in SZ.

Two neurostructural subtypes: results of machine learning on brain images from 4,291 individuals with schizophrenia

Machine learning can be used to define subtypes of psychiatric conditions based on shared clinical and biological foundations, presenting a crucial step toward establishing biologically based subtypes of mental disorders. With the goal of identifying subtypes of disease progression in schizophrenia, here we analyzed cross-sectional brain structural magnetic resonance imaging (MRI) data from 4,291 individuals with schizophrenia (1,709 females, age=32.5 years±11.9) and 7,078 healthy controls (3,461 females, age=33.0 years±12.7) pooled across 41 international cohorts from the ENIGMA Schizophrenia Working Group, non-ENIGMA cohorts and public datasets. Using a machine learning approach known as Subtype and Stage Inference (SuStaIn), we implemented a brain imaging-driven classification that identifies two distinct neurostructural subgroups by mapping the spatial and temporal trajectory of gray matter (GM) loss in schizophrenia. Subgroup 1 (n=2,622) was characterized by an early cortical-predominant loss (ECL) with enlarged striatum, whereas subgroup 2 (n=1,600) displayed an early subcortical-predominant loss (ESL) in the hippocampus, amygdala, thalamus, brain stem and striatum. These reconstructed trajectories suggest that the GM volume reduction originates in the Broca's area/adjacent fronto-insular cortex for ECL and in the hippocampus/adjacent medial temporal structures for ESL. With longer disease duration, the ECL subtype exhibited a gradual worsening of negative symptoms and depression/anxiety, and less of a decline in positive symptoms. We confirmed the reproducibility of these imaging-based subtypes across various sample sites, independent of macroeconomic and ethnic factors that differed across these geographic locations, which include Europe, North America and East Asia. These findings underscore the presence of distinct pathobiological foundations underlying schizophrenia. This new imaging-based taxonomy holds the potential to identify a more homogeneous sub-population of individuals with shared neurobiological attributes, thereby suggesting the viability of redefining existing disorder constructs based on biological factors.

Glucose metabolism, hippocampal subfields and cognition in first-episode and never-treated schizophrenia

Background

Previous studies have indicated that glucose metabolism and altered hippocampal structure and function play a pivotal role in cognitive deficits in schizophrenia (SZ). This study was designed to explore the inter-relationship between glucose metabolism, hippocampal subfield volume, and cognitive function in the antipsychotics-naive first episode (ANFE) SZ patients.

Methods

We chose the fasting insulin, glucose, and insulin resistance (HOMA-IR) index as biomarkers of glucose metabolism. Cognitive function was assessed by the MATRICS Consensus Cognitive Battery (MCCB). The hippocampal subfield volume, glucose metabolism biomarkers, and cognitive function were evaluated in 43 ANFE SZ and 29 healthy controls (HCs).

Results

Compared with HCs, SZ patients had higher fasting blood glucose and insulin levels and HOMA-IR (all p < 0.05). Correlation analysis revealed that category fluency performance was positively associated with fasting glucose level. Fasting insulin or HOMA-IR was positively associated with the hippocampal subfield volume in patients (all p<0.05). Moreover, the spatial span index score was associated with the volume of the right presubiculum, subiculum, and right hippocampal tail. In addition, multiple regression analysis found that the interaction effects of insulin × right fimbria or insulin × left fimbria were independent predictors of the MCCB total score.

Conclusions

Our findings suggest that abnormal glucose metabolism and cognitive decline occur in the early stage of SZ. The interaction between abnormal glucose metabolism and hippocampal subfields was associated with cognitive functions in SZ.

Phase-and disorder-specific differences in peripheral metabolites of the kynurenine pathway in major depression, bipolar affective disorder and schizophrenia

OBJECTIVES

Kynurenine, kynurenic and quinolinic acid are important metabolites in tryptophan metabolism. Due to an involvement in glutamatergic neurotransmission and immune response, previous studies have investigated this pathway in mental disorders such as major depressive disorder (MDD), bipolar disorder (BD) or schizophrenia (SCZ). Tryptophan and kynurenine have been shown to be decreased across disorders, hinting at the missing link how inflammation causes neurotoxicity and psychiatric symptoms. The main aim of our study was to investigate if individual catabolites could serve as diagnostic biomarkers for MDD, BD and SCZ.

METHODS

We measured plasma levels of tryptophan, kynurenine, kynurenic acid, quinolinic acid and ratio of quinolinic acid/kynurenic acid using mass spectrometry in n = 175 participants with acute episodes and after remission, compared with controls.

RESULTS

Decreased levels of all tryptophan catabolites were found in the whole patient group, driven by the difference between BD and HC. Manic and mixed phase BD individuals displayed significantly lower kynurenine and kynurenic acid levels. We could not find significant differences between disorders. Upon reaching remission, changes in catabolite levels partially normalised.

CONCLUSIONS

Our data suggests an involvement of the kynurenine pathway in mental disorders, especially BD but disqualifying those metabolites as biomarkers for differential diagnosis.

Subcortical structures associated with childhood trauma and perceived stress in schizophrenia

BACKGROUND

Childhood trauma influences the clinical features of schizophrenia. In this study, we examined how childhood trauma and perceived stress are associated with clinical manifestations and subcortical gray matter volumes (GMVs) in patients with schizophrenia.

METHODS

We recruited 127 patients with schizophrenia and 83 healthy controls for assessment of early childhood trauma, perceived stress, and clinical symptoms. With structural brain imaging, we identified the GMVs of subcortical structures and examined the relationships between childhood trauma, perceived stress, clinical symptoms, and subcortical GMVs.

RESULTS

Compared to controls, patients with schizophrenia showed higher levels of childhood trauma and perceived stress. Patients with schizophrenia showed significantly smaller amygdala and hippocampus GMVs as well as total cortical GMVs than age-matched controls. Childhood trauma score was significantly correlated with the severity of clinical symptoms, depression, perceived stress, and amygdala GMVs. Perceived stress was significantly correlated with clinical symptoms, depression, and hippocampus and amygdala GMVs. Further, the association between childhood trauma (emotional neglect) and stress coping ability was mediated by right amygdala GMV in patients with schizophrenia.

CONCLUSIONS

Patients with schizophrenia had more exposure to early-life trauma and poorer stress coping. Both childhood trauma and perceived stress were associated with smaller amygdala volumes. The relationship between early-life trauma and perceived stress was mediated by right amygdala GMV in patients with schizophrenia. These findings together suggest the long-term effects of childhood trauma on perceived stress and the subcortical volumetric correlates of the effects in schizophrenia.

Ancestral, Pregnancy, and Negative Early-Life Risks Shape Children's Brain (Dis)similarity to Schizophrenia

BACKGROUND

Familial, obstetric, and early-life environmental risks for schizophrenia spectrum disorder (SSD) alter normal cerebral development, leading to the formation of characteristic brain deficit patterns prior to onset of symptoms. We hypothesized that the insidious effects of these risks may increase brain similarity to adult SSD deficit patterns in prepubescent children.

METHODS

We used data collected by the Adolescent Brain Cognitive Development (ABCD) Study (N = 8940, age = 9.9 ± 0.1 years, 4307/4633 female/male), including 727 (age = 9.9 ± 0.1 years, 351/376 female/male) children with family history of SSD, to evaluate unfavorable cerebral effects of ancestral SSD history, pre/perinatal environment, and negative early-life environment. We used a regional vulnerability index to measure the alignment of a child's cerebral patterns with the adult SSD pattern derived from a large meta-analysis of case-control differences.

RESULTS

In children with a family history of SSD, the regional vulnerability index captured significantly more variance in ancestral history than traditional whole-brain and regional brain measurements. In children with and without family history of SSD, the regional vulnerability index also captured more variance associated with negative pre/perinatal environment and early-life experiences than traditional brain measurements.

CONCLUSIONS

In summary, in a cohort in which most children will not develop SSD, familial, pre/perinatal, and early developmental risks can alter brain patterns in the direction observed in adult patients with SSD. Individual similarity to adult SSD patterns may provide an early biomarker of the effects of genetic and developmental risks on the brain prior to psychotic or prodromal symptom onset.

Cortical and subcortical brain morphometry abnormalities in youth at clinical high-risk for psychosis and individuals with early illness schizophrenia

Neuroimaging studies have documented morphometric brain abnormalities in schizophrenia, but less is known about them in individuals at clinical high-risk for psychosis (CHR-P), including how they compare with those observed in early schizophrenia (ESZ). Accordingly, we implemented multivariate profile analysis of regional morphometric profiles in CHR-P (n = 89), ESZ (n = 93) and healthy controls (HC; n = 122). ESZ profiles differed from HC and CHR-P profiles, including 1) cortical thickness: significant level reduction and regional non-parallelism reflecting widespread thinning, except for entorhinal and pericalcarine cortex, 2) basal ganglia volume: significant level increase and regional non-parallelism reflecting larger caudate and pallidum, and 3) ventricular volume: significant level increase with parallel regional profiles. CHR-P and ESZ cerebellar profiles showed significant non-parallelism with HC profiles. Regional profiles did not significantly differ between groups for cortical surface area or subcortical volume. Compared to CHR-P followed for ≥18 months without psychosis conversion (n = 31), CHR-P converters (n = 17) showed significant non-parallel ventricular volume expansion reflecting specific enlargement of lateral and inferolateral regions. Antipsychotic dosage in ESZ was significantly correlated with frontal cortical thinning. Results suggest that morphometric abnormalities in ESZ are not present in CHR-P, except for ventricular enlargement, which was evident in CHR-P who developed psychosis.

Associations among body mass index, working memory performance, gray matter volume, and brain activation in healthy children

To investigate the neural mechanisms underlying the association between poorer working memory performance and higher body mass index (BMI) in children. We employed structural-(sMRI) and functional magnetic resonance imaging (fMRI) with a 2-back working memory task to examine brain abnormalities and their associations with BMI and working memory performance in 232 children with overweight/obesity (OW/OB) and 244 normal weight children (NW) from the Adolescent Brain Cognitive Development dataset. OW/OB had lower working memory accuracy, which was associated with higher BMI. They showed smaller gray matter (GM) volumes in the left superior frontal gyrus (SFG_L), dorsal anterior cingulate cortex, medial orbital frontal cortex, and medial superior frontal gyrus, which were associated with lower working memory accuracy. During the working memory task, OW/OB relative to NW showed weaker activation in the left superior temporal pole, amygdala, insula, and bilateral caudate. In addition, caudate activation mediated the relationship between higher BMI and lower working memory accuracy. Higher BMI is associated with smaller GM volumes and weaker brain activation in regions involved with working memory. Task-related caudate dysfunction may account for lower working memory accuracy in children with higher BMI.

Amygdala subdivisions exhibit aberrant whole-brain functional connectivity in relation to stress intolerance and psychotic symptoms in 22q11.2DS

The amygdala is a key region in emotional regulation, which is often impaired in psychosis. However, it is unclear if amygdala dysfunction directly contributes to psychosis, or whether it contributes to psychosis through symptoms of emotional dysregulation. We studied the functional connectivity of amygdala subdivisions in patients with 22q11.2DS, a known genetic model for psychosis susceptibility. We investigated how dysmaturation of each subdivision's connectivity contributes to positive psychotic symptoms and impaired tolerance to stress in deletion carriers. Longitudinally-repeated MRI scans from 105 patients with 22q11.2DS (64 at high-risk for psychosis and 37 with impaired tolerance to stress) and 120 healthy controls between the ages of 5 to 30 years were included. We calculated seed-based whole-brain functional connectivity for amygdalar subdivisions and employed a longitudinal multivariate approach to evaluate the developmental trajectory of functional connectivity across groups. Patients with 22q11.2DS presented a multivariate pattern of decreased basolateral amygdala (BLA)-frontal connectivity alongside increased BLA-hippocampal connectivity. Moreover, associations between developmental drops in centro-medial amygdala (CMA)-frontal connectivity to both impaired tolerance to stress and positive psychotic symptoms in deletion carriers were detected. Superficial amygdala hyperconnectivity to the striatum was revealed as a specific pattern arising in patients who develop mild to moderate positive psychotic symptoms. Overall, CMA-frontal dysconnectivity was found as a mutual neurobiological substrate in both impaired tolerance to stress and psychosis, suggesting a role in prodromal dysregulation of emotions in psychosis. While BLA dysconnectivity was found to be an early finding in patients with 22q11.2DS, which contributes to impaired tolerance to stress.

Thalamic nuclei volumes in schizophrenia and bipolar spectrum disorders - Associations with diagnosis and clinical characteristics

BACKGROUND

The thalamus is central to brain functions ranging from primary sensory processing to higher-order cognition. Structural deficits in thalamic association nuclei such as the pulvinar and mediodorsal nuclei have previously been reported in schizophrenia. However, the specificity with regards to clinical presentation, and whether or not bipolar disorder (BD) is associated with similar alterations is unclear.

METHODS

We investigated thalamic nuclei volumes in 334 patients with schizophrenia spectrum disorders (SSD) (median age 29 years, 59 % male), 322 patients with BD (30 years, 40 % male), and 826 healthy controls (HC) (34 years, 54 % male). Volumes of 25 thalamic nuclei were extracted from T1-weighted magnetic resonance imaging using an automated Bayesian segmentation method and compared between groups. Furthermore, we explored associations with clinical characteristics across diagnostic groups, including psychotic and mood symptoms and medication use, as well as diagnostic subtype in BD.

RESULTS

Significantly smaller volumes were found in the mediodorsal, pulvinar, and lateral and medial geniculate thalamic nuclei in SSD. Similarly, smaller volumes were found in BD in the same four regions, but mediodorsal nucleus volume alterations were limited to its lateral part and pulvinar alterations to its anterior region. Smaller volumes in BD compared to HC were seen only in BD type I, not BD type II. Across diagnoses, having more negative symptoms was associated with smaller pulvinar volumes.

CONCLUSIONS

Structural alterations were found in both SSD and BD, mainly in the thalamic association nuclei. Structural deficits in the pulvinar may be of relevance for negative symptoms.

Lack of correlation between hippocampal substructure atrophy and attention dysfunction in deficit schizophrenia

Hippocampal abnormalities are an established finding in the neuroimaging study of schizophrenia. However, no studies have examined the possibility of regional hippocampal abnormalities specific to deficit schizophrenia (DS) and associations with the unique symptoms of this schizophrenia subtype. This study compared 33 DS and 39 non-deficit schizophrenia (NDS) patients and 38 healthy subjects for hippocampal subfield volumetry. Clinical symptoms were assessed by PANSS, cognition by the neurocognitive battery on the day of the MRI scan. The automatic hippocampal segmentation were preprocesses use FreeSurfer 7.2.0. Unfortunately, the associations between neurocognitive scores and hippocampal subfield volumes in the DS group were not significant after the Bonferroni correction. Our results did not support a causal relationship between hippocampal subregional atrophy and cognitive deficits in DS.

Brain deficit patterns of metabolic illnesses overlap with those for major depressive disorder: A new metric of brain metabolic disease

Metabolic illnesses (MET) are detrimental to brain integrity and are common comorbidities in patients with mental illnesses, including major depressive disorder (MDD). We quantified effects of MET on standard regional brain morphometric measures from 3D brain MRI as well as diffusion MRI in a large sample of UK BioBank participants. The pattern of regional effect sizes of MET in non-psychiatric UKBB subjects was significantly correlated with the spatial profile of regional effects reported by the largest meta-analyses in MDD but not in bipolar disorder, schizophrenia or Alzheimer's disease. We used a regional vulnerability index (RVI) for MET (RVI-MET) to measure individual's brain similarity to the expected patterns in MET in the UK Biobank sample. Subjects with MET showed a higher effect size for RVI-MET than for any of the individual brain measures. We replicated elevation of RVI-MET in a sample of MDD participants with MET versus non-MET. RVI-MET scores were significantly correlated with the volume of white matter hyperintensities, a neurological consequence of MET and age, in both groups. Higher RVI-MET in both samples was associated with obesity, tobacco smoking and frequent alcohol use but was unrelated to antidepressant use. In summary, MET effects on the brain were regionally specific and individual similarity to the pattern was more strongly associated with MET than any regional brain structural metric. Effects of MET overlapped with the reported brain differences in MDD, likely due to higher incidence of MET, smoking and alcohol use in subjects with MDD.

A preliminary choroid plexus volumetric study in individuals with psychosis

The choroid plexus (ChP) is part of the blood-cerebrospinal fluid barrier, regulating brain homeostasis and the brain's response to peripheral events. Its upregulation and enlargement are considered essential in psychosis. However, the timing of the ChP enlargement has not been established. This study introduces a novel magnetic resonance imaging-based segmentation method to examine ChP volumes in two cohorts of individuals with psychosis. The first sample consists of 41 individuals with early course psychosis (mean duration of illness = 1.78 years) and 30 healthy individuals. The second sample consists of 30 individuals with chronic psychosis (mean duration of illness = 7.96 years) and 34 healthy individuals. We utilized manual segmentation to measure ChP volumes. We applied ANCOVAs to compare normalized ChP volumes between groups and partial correlations to investigate the relationship between ChP, LV volumes, and clinical characteristics. Our segmentation demonstrated good reliability (.87). We further showed a significant ChP volume increase in early psychosis (left: p < .00010, right: p < .00010) and a significant positive correlation between higher ChP and higher LV volumes in chronic psychosis (left: r = .54, p = .0030, right: r = .68; p < .0010). Our study suggests that ChP enlargement may be a marker of acute response around disease onset. It might also play a modulatory role in the chronic enlargement of lateral ventricles, often reported in psychosis. Future longitudinal studies should investigate the dynamics of ChP enlargement as a promising marker for novel therapeutic strategies.

Elucidating gut microbiota-hippocampus interactions in emerging psychosis: A new perspective for the development of early interventions for memory impairments

Hippocampal dysregulation might be a key pathophysiological factor for memory impairments in psychosis. Contemporary models particularly postulate that an imbalance of hippocampal glutamate and GABA leads to impaired memory and may thus serve as a therapeutic target to improve memory deficits. However, currently available interventions in early stages of psychosis do not explicitly target hippocampal pathology. A novel approach for manipulating hippocampus-dependent memory processes is provided via the gut microbiota. In this perspective article, we first recapitulate compelling evidence for emerging hippocampus pathology during the development of psychosis. The following sections emphasize the critical role of the gut microbiota in hippocampus plasticity and memory, and summarize existing evidence of gut microbiota alterations in different stages of psychosis. Finally, we propose a novel conceptual roadmap for future studies deciphering gut microbiota-hippocampus synergisms in emerging psychosis and argue that specific microbial supplementation might be promising for improving hippocampus-dependent memory deficits in early stages of psychosis.

Large-Scale Thalamocortical Triple Network Dysconnectivities in Patients With First-Episode Psychosis and Individuals at Risk for Psychosis

BACKGROUND AND HYPOTHESIS

Aberrant thalamocortical connectivity and large-scale network interactions among the default mode network (DMN), salience network (SN), and executive control network (ECN) (ie, triple networks) have been regarded as critical in schizophrenia pathophysiology. Despite the importance of network properties and the role of the thalamus as an integrative hub, large-scale thalamocortical triple network functional connectivities (FCs) in different stages of the psychotic disorder have not yet been reported.

STUDY DESIGN

Thirty-nine first-episode psychosis (FEP) patients, 75 individuals at clinical high risk (CHR) for psychosis, 46 unaffected relatives (URs) of schizophrenia patients with high genetic loading, and 110 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI). Modular community detection was used to identify cortical and thalamic resting-state networks, and thalamocortical network interactions were compared across the groups.

STUDY RESULTS

Thalamic triple networks included higher-order thalamic nuclei. Thalamic SN-cortical ECN FC was greater in the FEP group than in the CHR, UR, and HC groups. Thalamic DMN-cortical DMN and thalamic SN-cortical DMN FCs were greater in FEP and CHR participants. Thalamic ECN-cortical DMN and thalamic ECN-cortical SN FCs were greater in FEP patients and URs.

CONCLUSIONS

These results highlight critical modulatory functions of thalamic triple networks and the shared and distinct patterns of thalamocortical triple network dysconnectivities across different stages of psychotic disorders. The current study findings suggest that large-scale thalamocortical triple network dysconnectivities may be used as an integrative biomarker for extending our understanding of the psychosis pathophysiology and for targeting network-based neuromodulation therapeutics.

Subcortical brain alterations in carriers of genomic copy number variants

Objectives

Copy number variants (CNVs) are well-known genetic pleiotropic risk factors for multiple neurodevelopmental and psychiatric disorders (NPDs) including autism (ASD) and schizophrenia (SZ). Overall, little is known about how different CNVs conferring risk for the same condition may affect subcortical brain structures and how these alterations relate to the level of disease risk conferred by CNVs. To fill this gap, we investigated gross volume, and vertex level thickness and surface maps of subcortical structures in 11 different CNVs and 6 different NPDs.

Methods

Subcortical structures were characterized using harmonized ENIGMA protocols in 675 CNV carriers (at the following loci: 1q21.1, TAR, 13q12.12, 15q11.2, 16p11.2, 16p13.11, and 22q11.2) and 782 controls (Male/Female: 727/730; age-range: 6-80 years) as well as ENIGMA summary-statistics for ASD, SZ, ADHD, Obsessive-Compulsive-Disorder, Bipolar-Disorder, and Major-Depression.

Results

Nine of the 11 CNVs affected volume of at least one subcortical structure. The hippocampus and amygdala were affected by five CNVs. Effect sizes of CNVs on subcortical volume, thickness and local surface area were correlated with their previously reported effect sizes on cognition and risk for ASD and SZ. Shape analyses were able to identify subregional alterations that were averaged out in volume analyses. We identified a common latent dimension - characterized by opposing effects on basal ganglia and limbic structures - across CNVs and across NPDs.

Conclusion

Our findings demonstrate that subcortical alterations associated with CNVs show varying levels of similarities with those associated with neuropsychiatric conditions. We also observed distinct effects with some CNVs clustering with adult conditions while others clustered with ASD. This large cross-CNV and NPDs analysis provide insight into the long-standing questions of why CNVs at different genomic loci increase the risk for the same NPD, as well as why a single CNV increases the risk for a diverse set of NPDs.

Functional connectivity and gray matter deficits within the auditory attention circuit in first-episode psychosis

Background

Selective attention deficits in first episode of psychosis (FEP) can be indexed by impaired attentional modulation of auditory M100. It is unknown if the pathophysiology underlying this deficit is restricted to auditory cortex or involves a distributed attention network. We examined the auditory attention network in FEP.

Methods

MEG was recorded from 27 FEP and 31 matched healthy controls (HC) while alternately ignoring or attending tones. A whole-brain analysis of MEG source activity during auditory M100 identified non-auditory areas with increased activity. Time-frequency activity and phase-amplitude coupling were examined in auditory cortex to identify the attentional executive carrier frequency. Attention networks were defined by phase-locking at the carrier frequency. Spectral and gray matter deficits in the identified circuits were examined in FEP.

Results

Attention-related activity was identified in prefrontal and parietal regions, markedly in precuneus. Theta power and phase coupling to gamma amplitude increased with attention in left primary auditory cortex. Two unilateral attention networks were identified with precuneus seeds in HC. Network synchrony was impaired in FEP. Gray matter thickness was reduced within the left hemisphere network in FEP but did not correlate with synchrony.

Conclusion

Several extra-auditory attention areas with attention-related activity were identified. Theta was the carrier frequency for attentional modulation in auditory cortex. Left and right hemisphere attention networks were identified, with bilateral functional deficits and left hemisphere structural deficits, though FEP showed intact auditory cortex theta phase-gamma amplitude coupling. These novel findings indicate attention-related circuitopathy early in psychosis potentially amenable to future non-invasive interventions.

Biological hypotheses, risk factors, and biomarkers of schizophrenia

Both the discovery of biomarkers of schizophrenia and the verification of biological hypotheses of schizophrenia are an essential part of the process of understanding the etiology of this mental disorder. Schizophrenia has long been considered a neurodevelopmental disease whose symptoms are caused by impaired synaptic signal transduction and brain neuroplasticity. Both the onset and chronic course of schizophrenia are associated with risk factors-induced disruption of brain function and the establishment of a new homeostatic setpoint characterized by biomarkers. Different risk factors and biomarkers can converge to the same symptoms of schizophrenia, suggesting that the primary cause of the disease can be highly individual. Schizophrenia-related biomarkers include measurable biochemical changes induced by stress (elevated allostatic load), mitochondrial dysfunction, neuroinflammation, oxidative and nitrosative stress, and circadian rhythm disturbances. Here is a summary of selected valid biological hypotheses of schizophrenia formulated based on risk factors and biomarkers, neurodevelopment, neuroplasticity, brain chemistry, and antipsychotic medication. The integrative neurodevelopmental-vulnerability-neurochemical model is based on current knowledge of the neurobiology of the onset and progression of the disease and the effects of antipsychotics and psychotomimetics and reflects the complex and multifactorial nature of schizophrenia.

Cumulative Impact of Morphometric Features in Schizophrenia in Two Independent Samples

Schizophrenia and bipolar disorder share a common structural brain alteration profile. However, there is considerable between- and within-diagnosis variability in these features, which may underestimate informative individual differences. Using a recently established morphometric risk score (MRS) approach, we aim to provide confirmation that individual MRS scores are higher in individuals with a psychosis diagnosis, helping to parse individual heterogeneity. Using the Human Connectome Project Early Psychosis (N = 124), we estimate MRS for psychosis and specifically for bipolar/schizophrenia using T1-weighted MRI data and prior meta-analysis effect sizes. We confirm associations in an independent replication sample (N = 69). We assess (1) the impact of diagnosis on these MRS, (2) compare effect sizes of MRS to all individual, cytoarchitecturally defined brain regions, and (3) perform negative control analyses to assess MRS specificity. The MRS specifically for SCZ was higher in the whole psychosis group (Cohen's d = 0.56; P = 0.003) and outperformed any single region of interest in standardized mean difference (ZMRS>75 ROIS = 2.597; P = 0.009) and correlated with previously reported effect sizes (PSPIN/SHUFFLE < 0.005). MRS without Enhancing Neuroimaging Genomics through Meta-Analysis weights did not delineate groups with empirically null associations (t = 2.29; P = 0.02). We replicate MRS specifically for SCZ associations in the independent sample. Akin to polygenic risk scoring and individual allele effect sizes, these observations suggest that assessing the combined impact of regional structural alterations may be more informative than any single cytoarchitecturally constrained cortical region, where well-powered, meta-analytical samples are informative in the delineation of diagnosis and within psychosis case differences, in smaller independent samples.

Schizophrenia: One Name, Many Different Manifestations

Schizophrenia is a disabling condition impacting approximately 1% of the worldwide population. Symptoms include positive symptoms (eg, hallucinations, delusions), negative symptoms (eg, avolition, anhedonia), and cognitive impairment. There are likely many different environmental and pathophysiologic etiologies involving distinct neurotransmitters and neurocircuits. Pharmacologic treatment at present consists of dopamine receptor antagonists, which are reasonably effective at treating positive symptoms, but less effective at treating cognitive and negative symptoms. Nondopaminergic medications targeting alternative receptors are under investigation. Supportive psychosocial treatments can work in tandem with antipsychotic medications and optimize patient care.

Brain-wide versus genome-wide vulnerability biomarkers for severe mental illnesses

Severe mental illnesses (SMI), including major depressive (MDD), bipolar (BD), and schizophrenia spectrum (SSD) disorders have multifactorial risk factors and capturing their complex etiopathophysiology in an individual remains challenging. Regional vulnerability index (RVI) was used to measure individual's brain-wide similarity to the expected SMI patterns derived from meta-analytical studies. It is analogous to polygenic risk scores (PRS) that measure individual's similarity to genome-wide patterns in SMI. We hypothesized that RVI is an intermediary phenotype between genome and symptoms and is sensitive to both genetic and environmental risks for SMI. UK Biobank sample of N = 17,053/19,265 M/F (age = 64.8 ± 7.4 years) and an independent sample of SSD patients and controls (N = 115/111 M/F, age = 35.2 ± 13.4) were used to test this hypothesis. UKBB participants with MDD had significantly higher RVI-MDD (Cohen's d = 0.20, p = 1 × 10-23 ) and PRS-MDD (d = 0.17, p = 1 × 10-15 ) than nonpsychiatric controls. UKBB participants with BD and SSD showed significant elevation in the respective RVIs (d = 0.65 and 0.60; p = 3 × 10-5 and .009, respectively) and PRS (d = 0.57 and 1.34; p = .002 and .002, respectively). Elevated RVI-SSD were replicated in an independent sample (d = 0.53, p = 5 × 10-5 ). RVI-MDD and RVI-SSD but not RVI-BD were associated with childhood adversity (p < .01). In nonpsychiatric controls, elevation in RVI and PRS were associated with lower cognitive performance (p < 10-5 ) in six out of seven domains and showed specificity with disorder-associated deficits. In summary, the RVI is a novel brain index for SMI and shows similar or better specificity for SMI than PRS, and together they may complement each other in the efforts to characterize the genomic to brain level risks for SMI.

Neuroanatomical subtypes of schizophrenia and relationship with illness duration and deficit status

BACKGROUND

The heterogeneity of schizophrenia (SCZ) regarding psychopathology, illness trajectory and their inter-relationships with underlying neural substrates remain incompletely understood. In a bid to reduce illness heterogeneity using neural substrates, our study aimed to replicate the findings of an earlier study by Chand et al. (2020). We employed brain structural measures for subtyping SCZ patients, and evaluate each subtype's relationship with clinical features such as illness duration, psychotic psychopathology, and additionally deficit status.

METHODS

Overall, 240 subjects (160 SCZ patients, 80 healthy controls) were recruited for this study. The participants underwent brain structural magnetic resonance imaging scans and clinical rating using the Positive and Negative Syndrome Scale. Neuroanatomical subtypes of SCZ were identified using "Heterogeneity through discriminative analysis" (HYDRA), a clustering technique which accounted for relevant covariates and the inter-group normalized percentage changes in brain volume were also calculated.

RESULTS

As replicated, two neuroanatomical subtypes (SG-1 and SG-2) were found amongst our patients with SCZ. The subtype SG-1 was associated with enlargements in the third and lateral ventricles, volume increase in the basal ganglia (putamen, caudate, pallidum), longer illness duration, and deficit status. The subtype SG-2 was associated with reductions of cortical and subcortical structures (hippocampus, thalamus, basal ganglia).

CONCLUSIONS

These replicated findings have clinical implications in the early intervention, response monitoring, and prognostication of SCZ. Future studies may adopt a multi-modal neuroimaging approach to enhance insights into the neurobiological composition of relevant subtypes.

Nicotinamide reverses deficits in puberty-born neurons and cognitive function after maternal separation

Background

Early life stress (ELS) is associated with the development of schizophrenia later in life. The hippocampus develops significantly during childhood and is extremely reactive to stress. In rodent models, ELS can induce neuroinflammation, hippocampal neuronal loss, and schizophrenia-like behavior. While nicotinamide (NAM) can inhibit microglial inflammation, it is unknown whether NAM treatment during adolescence reduces hippocampal neuronal loss and abnormal behaviors induced by ELS.

Methods

Twenty-four hours of maternal separation (MS) of Wistar rat pups on post-natal day (PND)9 was used as an ELS. On PND35, animals received a single intraperitoneal injection of BrdU to label dividing neurons and were given NAM from PND35 to PND65. Behavioral testing was performed. Western blotting and immunofluorescence staining were used to detect nicotinamide adenine dinucleotide (NAD⁺)/Sirtuin3 (Sirt3)/superoxide dismutase 2 (SOD2) pathway-related proteins.

Results

Compared with controls, only MS animals in the adult stage (PND56–65) but not the adolescent stage (PND31–40) exhibited pre-pulse inhibition deficits and cognitive impairments mimicking schizophrenia symptoms. MS decreased the survival and activity of puberty-born neurons and hippocampal NAD⁺ and Sirt3 expression in adulthood. These observations were related to an increase in acetylated SOD2, microglial activation, and significant increases in pro-inflammatory IL-1β, TNF-α, and IL-6 expression. All the effects of MS at PND9 were reversed by administering NAM in adolescence (PND35–65).

Conclusions

MS may lead to schizophrenia-like phenotypes and persistent hippocampal abnormalities. NAM may be a safe and effective treatment in adolescence to restore normal hippocampal function and prevent or ameliorate schizophrenia-like behavior.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12974-022-02591-y.

Evidence of genetic overlap and causal relationships between blood-based biochemical traits and human cortical anatomy

Psychiatric disorders such as schizophrenia are commonly associated with structural brain alterations affecting the cortex. Recent genetic evidence suggests circulating metabolites and other biochemical traits play a causal role in many psychiatric disorders which could be mediated by changes in the cerebral cortex. Here, we leveraged publicly available genome-wide association study data to explore shared genetic architecture and evidence for causal relationships between a panel of 50 biochemical traits and measures of cortical thickness and surface area. Linkage disequilibrium score regression identified 191 genetically correlated biochemical-cortical trait pairings, with consistent representation of blood cell counts and other biomarkers such as C-reactive protein (CRP), haemoglobin and calcium. Spatially organised patterns of genetic correlation were additionally uncovered upon clustering of region-specific correlation profiles. Interestingly, by employing latent causal variable models, we found strong evidence suggesting CRP and vitamin D exert causal effects on region-specific cortical thickness, with univariable and multivariable Mendelian randomization further supporting a negative causal relationship between serum CRP levels and thickness of the lingual region. Our findings suggest a subset of biochemical traits exhibit shared genetic architecture and potentially causal relationships with cortical structure in functionally distinct regions, which may contribute to alteration of cortical structure in psychiatric disorders.