Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders

Neuronal guidance signaling in neurodegenerative diseases: Key regulators that function at neuron-glia and neuroimmune interfaces

The nervous system processes a vast amount of information, performing computations that underlie perception, cognition, and behavior. During development, neuronal guidance genes, which encode extracellular cues, their receptors, and downstream signal transducers, organize neural wiring to generate the complex architecture of the nervous system. It is now evident that many of these neuroguidance cues and their receptors are active during development and are also expressed in the adult nervous system. This suggests that neuronal guidance pathways are critical not only for neural wiring but also for ongoing function and maintenance of the mature nervous system. Supporting this view, these pathways continue to regulate synaptic connectivity, plasticity, and remodeling, and overall brain homeostasis throughout adulthood. Genetic and transcriptomic analyses have further revealed many neuronal guidance genes to be associated with a wide range of neurodegenerative and neuropsychiatric disorders. Although the precise mechanisms by which aberrant neuronal guidance signaling drives the pathogenesis of these diseases remain to be clarified, emerging evidence points to several common themes, including dysfunction in neurons, microglia, astrocytes, and endothelial cells, along with dysregulation of neuron-microglia-astrocyte, neuroimmune, and neurovascular interactions. In this review, we explore recent advances in understanding the molecular and cellular mechanisms by which aberrant neuronal guidance signaling contributes to disease pathogenesis through altered cell-cell interactions. For instance, recent studies have unveiled two distinct semaphorin-plexin signaling pathways that affect microglial activation and neuroinflammation. We discuss the challenges ahead, along with the therapeutic potentials of targeting neuronal guidance pathways for treating neurodegenerative diseases. Particular focus is placed on how neuronal guidance mechanisms control neuron-glia and neuroimmune interactions and modulate microglial function under physiological and pathological conditions. Specifically, we examine the crosstalk between neuronal guidance signaling and TREM2, a master regulator of microglial function, in the context of pathogenic protein aggregates. It is well-established that age is a major risk factor for neurodegeneration. Future research should address how aging and neuronal guidance signaling interact to influence an individual's susceptibility to various late-onset neurological diseases and how the progression of these diseases could be therapeutically blocked by targeting neuronal guidance pathways.

Association of aberrant gray matter neurite density with neurovegetative symptom in atypical depression

BACKGROUND

The heterogeneity of symptoms in major depressive disorder is impeding progress toward patient-specific treatment strategies and course trajectories. Origins of such differential clinical manifestations likely have dissociable pathophysiologies, but neural substrates associated with specific atypical depressive symptoms remain elusive.

METHODS

The muti-shell diffusion MRI images were acquired from 50 patients with atypical depression (AD), 97 patients with non-atypical depression (non-AD), and 50 healthy controls (HCs). We used gray matter-specific multi-compartment diffusion models (cortical-neurite orientation dispersion and density imaging and free-water elimination model) to assess abnormalities of gray matter microstructure associated with AD. Superficial U-fibers analysis was performed to clarify short-range cortico-cortical connections.

RESULTS

Abnormalities in intracellular volume fraction (ICVF) and free-water fraction anisotropy were found in the superior frontal gyrus, middle frontal gyrus, inferior parietal gyrus, and superior parietal gyrus across three groups. Post-hoc pairwise comparative analysis yielded similar results. While adjusting for the effects of age, gender, education, and the ICVF mentioned above, AD patients showed significantly higher scores in reversed neurovegetative symptoms and leaden paralysis compared with non-AD patients. Moreover, diagnosis-related alterations in ICVF of right caudal middle frontal gyrus and education-related changes in ICVF of right superior frontal gyrus were significantly associated with hypersomnia. We also found that underlying superficial U-fibers reflected deficits in cortical-derived neurite density.

CONCLUSIONS

Cortical-derived neurite density abnormalities were significantly associated with atypical depressive symptoms, capturing interindividual etiological heterogeneity in patients with major depressive disorder. Cortical-derived neurite density within the medial prefrontal gyrus may be a robust biomarker for atypical depressive symptoms of AD.

The human cerebral cortex morphology in neuropsychiatric disorders: A causal inference based on Mendelian Randomization

BACKGROUND

Neuropsychiatric disorders, including Alzheimer's disease (AD), major depressive disorder (MDD), anxiety disorders, attention-deficit/hyperactivity disorder (ADHD), bipolar disorder, insomnia, and schizophrenia (SCZ), are prevalent and impose substantial morbidity and mortality worldwide. Brain morphometry, is increasingly recognized for its relevance to cognitive, emotional, and behavioral functions, yet its causal links to neuropsychiatric pathologies are not well established.

OBJECTIVE

This study aimed to explore the causal relationships between cortical thickness (TH) and surface area (SA) with 7 neuropsychiatric disorders using Mendelian randomization (MR) analyses.

METHODS

We employed data from genome-wide association studies (GWAS) comprising 51,665 individuals to evaluate cortical SA and TH. We selected single nucleotide polymorphisms (SNPs) as instrumental variables for MR analyses to investigate the causal associations with neuropsychiatric disorders.

RESULTS

Increased TH in the paracentral cortex was associated with a reduced risk of ADHD. Similarly, a thicker temporal pole was linked to a lower risk of MDD. The TH of the lingual region showed an inverse association with anxiety disorders. The SA of the fusiform gyrus was associated with AD risk, and morphological variations in the caudal middle frontal cortex, isthmus cingulate cortex, and temporal pole were correlated with bipolar disorder risk. An increased TH of the posterior cingulate cortex was associated with higher insomnia risk, and the TH of the pericalcarine region negatively correlated with SCZ risk.

CONCLUSION

This research provided novel evidence for the causal role of cerebral cortex morphology in neuropsychiatric disorders, suggesting potential targets for therapeutic intervention.

Transcriptional characteristics of human brain alterations in major depressive disorder: A systematic review

Many patients with major depressive disorder (MDD) experience limited treatment effectiveness due to an incomplete understanding of its neurobiological underpinnings. This review integrates neuroimaging and genetic data to examine structural and functional brain changes in MDD, alongside their genetic bases. A PRISMA-guided systematic review of imaging transcriptomics over the past decade was conducted using PubMed and Web of Science. Studies included MRI scans of both MDD patients and healthy controls, as well as brain-wide gene expression data, excluding those that were purely meta-analytical, lacked spatial correlations, or involved transdiagnostic analyses. Of the 206 studies reviewed, 20 met the inclusion criteria. Consistent patterns across studies reveal that key biological processes-such as synaptic signaling, calcium ion binding, neurodevelopment, immune regulation, and neurotransmitter transport-play a central role in brain alterations associated with MDD. Additionally, our findings suggest that electroconvulsive therapy (ECT) may alleviate symptoms by modulating these shared pathways. This review underscores the link between brain changes in MDD and specific gene expression profiles, offering insights that could inform more targeted therapeutic approaches.

Cortical differences across psychiatric disorders and associated common and rare genetic variants

Genetic studies have identified common and rare variants increasing the risk for neurodevelopmental and psychiatric disorders (NPDs). These risk variants have also been shown to influence the structure of the cerebral cortex. However, it is unknown whether cortical differences associated with genetic variants are linked to the risk they confer for NPDs. To answer this question, we analyzed cortical thickness (CT) and surface area (SA) for common and rare variants associated with NPDs, in ~33000 individuals from the general population and clinical cohorts, as well as ENIGMA summary statistics for 8 NPDs. Rare and common genetic variants increasing risk for NPDs were preferentially associated with total SA, while NPDs were preferentially associated with mean CT. Larger effects on mean CT, but not total SA, were observed in NPD medicated subgroups. At the regional level, genetic variants were preferentially associated with effects in sensorimotor areas, while NPDs showed higher effects in association areas. We show that schizophrenia- and bipolar-disorder-associated SNPs show positive and negative effect sizes on SA suggesting that their aggregated effects cancel out in additive polygenic models. Overall, CT and SA differences associated with NPDs do not relate to those observed across individual genetic variants and may be linked with critical non-genetic factors, such as medication and the lived experience of the disorder.

High urea promotes mitochondrial fission and functional impairments in astrocytes inducing anxiety-like behavior in chronic kidney disease mice

High urea can induce depression and anxiety. Activation of astrocytes is closely associated with psychiatric disorders. However, the pathological mechanism of whether high urea affects astrocyte structure and function to induce anxiety-like behaviors remain unclear. We established a high-urea chronic kidney disease (CKD) mouse model and found that these mice exhibited elevated levels of anxiety through behavioral experiments. Immunofluorescence and transmission electron microscopy studies of astrocytes revealed a decrease in density and branching of mPFC astrocytes. Additionally, we observed a significant reduction in ATP and BDNF levels in the mPFC and primary astrocytes of CKD mice induced by high urea. Analysis of gene expression differences in astrocytes between WT and high-urea mice indicated alterations in mitochondrial dynamics-related signaling pathways in astrocytes. We established a high-urea primary astrocyte model to assess mitochondrial function and levels of fusion and fission proteins. Treatment of primary astrocytes with high urea led to mitochondrial fragmentation and downregulation of Mfn2 expression. These results suggested that high urea downregulates Mfn2 expression in mPFC astrocytes, induced mitochondrial fusion-fission abnormalities, disrupted astrocyte energy metabolism, and promoted high-urea-related anxiety. Mfn2 may represent a potential therapeutic target for high-urea-related anxiety.

Neuroimaging Changes in the Sensorimotor Network and Visual Network in Bipolar Disorder and Their Relationship with Genetic Characteristics

Objective: Patients with bipolar disorder (BD) may exhibit common and significant changes in brain activity across different networks. Our aim was to investigate the changes in functional connectivity (FC) within different brain networks in BD, as well as their neuroimaging homogeneity, heterogeneity, and genetic variation. Methods: In this study, we analyzed the seed points and whole-brain FC of the sensorimotor network (SMN) and visual network (VN) in 83 healthy controls (HCs) and 77 BD patients, along with their genetic neuroimaging associations. Results: The results showed that, compared to HCs, BD patients exhibited abnormal FC in the SMN and VN brain regions. However, after three months of treatment, there were no significant differences in SMN and VN FC in the brain regions of the patients compared to pre-treatment levels. Enrichment analysis indicated that genes associated with changes in FC were shared among different SMN seed points, but no shared genes were found among VN seed points. Conclusions: In conclusion, changes in SMN FC may serve as a potential neuroimaging marker in BD patients. Our genetic neuroimaging association analysis may help to comprehensively understand the molecular mechanisms underlying FC changes in BD patients.

Gaze behaviors during free viewing revealed differences in visual salience processing across four major psychiatric disorders: a mega-analysis study of 1012 individuals

Aberrant salience processing has been proposed as a pathophysiological mechanism underlying psychiatric symptoms in patients with schizophrenia. The gaze trajectories of individuals with schizophrenia have been reported to be abnormal when viewing an image, suggesting anomalous visual salience as one possible pathophysiological mechanism associated with psychiatric diseases. This study was designed to determine whether visual salience is affected in individuals with schizophrenia, and whether this abnormality is unique to patients with schizophrenia. We examined the gaze behaviors of 1012 participants recruited from seven institutes (550 healthy individuals and 238, 41, 50 and 133 individuals with schizophrenia, bipolar disorder, major depressive disorder and autism spectrum disorder, respectively) when they looked at stationary images as they liked, i.e., free-viewing condition. We used an established computational model of salience maps derived from low-level visual features to measure the degree to which the gaze trajectories of individuals were guided by visual salience. The analysis revealed that the saliency at the gaze of individuals with schizophrenia were higher than healthy individuals, suggesting that patients' gazes were guided more by low-level image salience. Among the low-level image features, orientation salience was most affected. Furthermore, a general linear model analysis of the data for the four psychiatric disorders revealed a significant effect of disease. This abnormal salience processing depended on the disease and was strongest in patients with schizophrenia, followed by patients with bipolar disorder, major depressive disorder, and autism spectrum disorder, suggesting a link between abnormalities in salience processing and strength/frequency for psychosis of these disorders.

Childhood trajectories of emotional and behavioral difficulties are related to polygenic liability for mood and anxiety disorders

BACKGROUND

Symptoms related to mood and anxiety disorders (emotional disorders) often present in childhood and adolescence. Some of the genetic liability for mental disorders, and emotional and behavioral difficulties seems to be shared. Yet, it is unclear how genetic liability for emotional disorders and related traits influence trajectories of childhood behavioral and emotional difficulties, and if specific developmental patterns are associated with higher genetic liability for these disorders.

METHODS

This study uses data from a genotyped sample of children (n = 54,839) from the Norwegian Mother, Father, and Child Cohort Study (MoBa). We use latent growth models (1.5-5 years) and latent profile analyses (1.5-8 years) to quantify childhood trajectories and profiles of emotional and behavioral difficulties and diagnoses. We examine associations between these trajectories and profiles with polygenic scores for bipolar disorder (PGSBD), anxiety (PGSANX), depression (PGSDEP), and neuroticism (PGSNEUR).

RESULTS

Associations between PGSDEP, PGSANX, and PGSNEUR, and emotional and behavioral difficulties in childhood were more persistent than age-specific across early childhood (1.5-5 years). Higher PGSANX and PGSDEP were associated with steeper increases in behavioral difficulties across early childhood. Latent profile analyses identified five profiles with different associations with emotional disorder diagnosis. All PGS were associated with the probability of classification into profiles characterized by some form of difficulties (vs. a normative reference profile), but only PGSBD was uniquely associated with a single developmental profile.

CONCLUSIONS

Genetic risk for mood disorders and related traits contribute to both a higher baseline level of, and a more rapid increase in, emotional and behavioral difficulties across early and middle childhood, with some indications for disorder-specific profiles. Our findings may inform research on developmental pathways to emotional disorders and the improvement of initiatives for early identification and targeted intervention.

Multifactorial influences on childhood insomnia: Genetic, socioeconomic, brain development and psychopathology insights

Insomnia is the most prevalent sleep disturbance during childhood and can result in extensively detrimental effects. Children's insomnia involves a complex interplay of biological, neurodevelopmental, social-environmental, and behavioral variables, yet remains insufficiently addressed. This study aimed to investigate the multifactorial etiology of childhood insomnia from its genetic architecture and social-environmental variables to its neural instantiation and the relationship to mental health. This cohort study uses 4340 participants at baseline and 2717 participants at 2-year follow-up from the Adolescent Brain Cognitive Development (ABCD) Study. We assessed the joint effects of polygenic risk score (PRS) and socioeconomic status (SES) on insomnia symptoms and then investigated the underlying neurodevelopmental mechanisms. Structural equation model (SEM) was applied to investigate the directional relationships among these variables. SES and PRS affected children's insomnia symptoms independently and additively (SES: β = -0.089, P = 1.91 × 10-8; PRS: β = 0.041, P = 0.008), which was further indirectly mediated by the deviation of inferior precentral sulcus (β = 0.0027, P = 0.0071). SEM revealed that insomnia (β = 0.457, P < 0.001) and precentral development (β = -0.039, P = 0.009) significantly mediated the effect of SES_PRS (accumulated risks of PRS and SES) on psychopathology symptoms. Furthermore, baseline insomnia symptoms, SES_PRS, and precentral deviation significantly predicted individual total psychopathology syndromes (r = 0.346, P < 0.001). These findings suggest the additive effects of genetic and socioenvironmental factors on childhood insomnia via precentral development and highlight potential targets in early detection and intervention for childhood insomnia.

The striatal matrix compartment is expanded in autism spectrum disorder

BACKGROUND

Autism spectrum disorder (ASD) is the second-most common neurodevelopmental disorder in childhood. This complex developmental disorder manifests with restricted interests, repetitive behaviors, and difficulties in communication and social awareness. The inherited and acquired causes of ASD impact many and diverse brain regions, challenging efforts to identify a shared neuroanatomical substrate for this range of symptoms. The striatum and its connections are among the most implicated sites of abnormal structure and/or function in ASD. Striatal projection neurons develop in segregated tissue compartments, the matrix and striosome, that are histochemically, pharmacologically, and functionally distinct. Immunohistochemical assessment of ASD and animal models of autism described abnormal matrix:striosome volume ratios, with an possible shift from striosome to matrix volume. Shifting the matrix:striosome ratio could result from expansion in matrix, reduction in striosome, spatial redistribution of the compartments, or a combination of these changes. Each type of ratio-shifting abnormality may predispose to ASD but yield different combinations of ASD features.

METHODS

We developed a cohort of 426 children and adults (213 matched ASD-control pairs) and performed connectivity-based parcellation (diffusion tractography) of the striatum. This identified voxels with matrix-like and striosome-like patterns of structural connectivity.

RESULTS

Matrix-like volume was increased in ASD, with no evident change in the volume or organization of the striosome-like compartment. The inter-compartment volume difference (matrix minus striosome) within each individual was 31% larger in ASD. Matrix-like volume was increased in both caudate and putamen, and in somatotopic zones throughout the rostral-caudal extent of the striatum. Subjects with moderate elevations in ADOS (Autism Diagnostic Observation Schedule) scores had increased matrix-like volume, but those with highly elevated ADOS scores had 3.7-fold larger increases in matrix-like volume.

CONCLUSIONS

Matrix and striosome are embedded in distinct structural and functional networks, suggesting that compartment-selective injury or maldevelopment may mediate specific and distinct clinical features. Previously, assessing the striatal compartments in humans required post mortem tissue. Striatal parcellation provides a means to assess neuropsychiatric diseases for compartment-specific abnormalities. While this ASD cohort had increased matrix-like volume, other mechanisms that shift the matrix:striosome ratio may also increase the chance of developing the diverse social, sensory, and motor phenotypes of ASD.

Alternations of Plasma Fatty Acids in Patients With Bipolar Depression Under Acute Treatment of rTMS Combined With Quetiapine and Mood Stabilizer

PURPOSE

Repetitive transcranial magnetic stimulation (rTMS) represents a potential clinical tool in treating bipolar disorder (BD). However, the intervention of rTMS combined with pharmacotherapy on the plasma fatty acids (FAs) in patients with bipolar depression has not been reported yet.

METHOD

In this study, we assessed the clinical symptoms and evaluated plasma FAs from 30 inpatients with bipolar depression at baseline phase (BD group), after 2 weeks of treatment with rTMS combined with quetiapine and mood stabilizer (BD-2w group), and 32 healthy controls (HCs).

FINDING

We found that acetic acid, propionic acid, isovaleric acid, isobutyric acid, and valeric acid, as well as levels of total short-chain fatty acids (SCFAs), were decreased in both BD and BD-2w groups, and levels of several medium- and long-chain fatty acids (MLCFAs) were altered in BD when compared with HC. Moreover, 2 weeks of treatment increased the levels of various MLCFAs. Finally, we developed combinational FAs panels that could distinguish BD from HC (area under the curve [AUC] = 0.961), BD-2w from HC (AUC = 0.978), and BD from BD-2w (AUC = 0.891) effectively.

CONCLUSION

These findings might provide a basis for developing diagnostic methods and reveal the potential relationship between bipolar depression and plasma FAs.

Non-APOE variants predominately expressed in smooth muscle cells contribute to the influence of Alzheimer's disease genetic risk on white matter hyperintensities

INTRODUCTION

White matter hyperintensity volumes (WMHVs) are disproportionally prevalent in individuals with Alzheimer's disease (AD), potentially reflecting neurovascular injury. We quantify the association between AD polygenic risk score (AD-PRS) and WMHV, exploring single-nucleotide polymorphisms (SNPs) that are proximal to genes overexpressed in cerebrovascular cell species.

METHODS

In a UK-Biobank sub-sample (mean age = 64, range = 45-81 years), we associate WMHV with (1) AD-PRS estimated via SNPs across the genome (minus apolipoprotein E [APOE] locus) and (2) AD-PRS estimated with SNPs proximal to specific genes that are overexpressed in cerebrovascular cell species.

RESULTS

We observed a positive association between non-APOE-AD-PRS and WMHVs. We further demonstrate an association between WMHVs and AD-PRS constructed with SNPs that are proximal to genes over-represented in smooth muscles cells (SMCs; β = 0.135, PFWE  < 0.01) and internally replicated (PDISCOVERY+REPLICATION < 0.01).

DISCUSSION

Common AD genetic risk could explain physiological processes underlying vascular pathology in AD. SMC function may offer a treatment target to prevent WMHV-related AD pathophysiology prior to the onset of symptoms.

HIGHLIGHTS

Alzheimer's disease (AD) risk factors such as apolipoprotein E (APOE) ε4, link to increased white matter hyperintensity volume (WMHV). WMHVs indicate vascular risk and neurovascular injury in AD. The broader genetic link between AD risk and WMHV is not fully understood. We quantify AD polygenic risk score (PRS) associations with WMHV, excluding APOE. AD-PRS in smooth muscle cells (SMCs) shows a significant association with increased WMHV.

Psychotropic Taxonomies: Constructing a Therapeutic Framework for Psychiatry

Pharmacological interventions are a cornerstone of psychiatric practice. The taxonomies used to classify these interventions influence the treatment and interpretation of psychiatric symptoms. Disease-based classification systems (e.g., antidepressant and antipsychotic) do not reflect the fact that psychotropic agents are used across diagnostic categories or account for the dimensional nature of both the psychopathology and biology of psychiatric illnesses. In this review, we discuss the history of psychotropic drug taxonomies and their influence on both clinical practice and drug development. We frame taxonomies as existing on a spectrum, with high-level disease-based approaches at one end and target-based molecular approaches at the other. Finally, we consider how data-driven methods might address the issue of classification at an intermediate level, based around transdiagnostic neurobiological and psychopathological markers.

Convergence and divergence in neurostructural signatures of unipolar and bipolar depressions: Insights from surface-based morphometry and prospective follow-up

BACKGROUND

Bipolar disorder (BD) is often misidentified as unipolar depression (UD) during its early stages, typically until the onset of the first manic episode. This study aimed to explore both shared and unique neurostructural changes in patients who transitioned from UD to BD during follow-up, as compared to those with UD.

METHODS

This study utilized high-resolution structural magnetic resonance imaging (MRI) to collect brain data from individuals initially diagnosed with UD. During the average 3-year follow-up, 24 of the UD patients converted to BD (cBD). For comparison, the study included 48 demographically matched UD patients who did not convert and 48 healthy controls. The MRI data underwent preprocessing using FreeSurfer, followed by surface-based morphometry (SBM) analysis to identify cortical thickness (CT), surface area (SA), and cortical volume (CV) among groups.

RESULTS

The SBM analysis identified shared neurostructural characteristics between the cBD and UD groups, specifically thinner CT in the right precentral cortex compared to controls. Unique to the cBD group, there was a greater SA in the right inferior parietal cortex compared to the UD group. Furthermore, no significant correlations were observed between cortical morphological measures and cognitive performance and clinical features in the cBD and UD groups.

LIMITATIONS

The sample size is relatively small.

CONCLUSIONS

Our findings suggest that while cBD and UD exhibit some common alterations in cortical macrostructure, numerous distinct differences are also present. These differences offer valuable insights into the neuropathological underpinnings that distinguish these two conditions.

Patterns of Brain Maturation in Autism and Their Molecular Associations

Importance

In the neurotypical brain, regions develop in coordinated patterns, providing a fundamental scaffold for brain function and behavior. Whether altered patterns contribute to clinical profiles in neurodevelopmental conditions, including autism, remains unclear.

Objectives

To examine if, in autism, brain regions develop differently in relation to each other and how these differences are associated with molecular/genomic mechanisms and symptomatology.

Design, Setting, and Participants

This study was an analysis of one the largest deep-phenotyped, case-control, longitudinal (2 assessments separated by approximately 12-24 months) structural magnetic resonance imaging and cognitive-behavioral autism datasets (EU-AIMS Longitudinal European Autism Project [LEAP]; study dates, February 2014-November 2017) and an out-of-sample validation in the Brain Development Imaging Study (BrainMapASD) independent cohort. Analyses were performed during the 2022 to 2023 period. This multicenter study included autistic and neurotypical children, adolescents, and adults. Autistic participants were included if they had an existing autism diagnosis (DSM-IV/International Statistical Classification of Diseases and Related Health Problems, Tenth Revision or DSM-5 criteria). Autistic participants with co-occurring psychiatric conditions (except psychosis/bipolar disorder) and those taking regular medications were included.

Exposures

Neuroanatomy of neurotypical and autistic participants.

Main Outcomes and Measures

Intraindividual changes in surface area and cortical thickness over time, analyzed via surface-based morphometrics.

Results

A total of 386 individuals in the LEAP cohort (6-31 years at first visit; 214 autistic individuals, mean [SD] age, 17.3 [5.4] years; 154 male [72.0%] and 172 neurotypical individuals, mean [SD] age, 16.35 [5.7] years; 108 male [62.8%]) and 146 individuals in the BrainMapASD cohort (11-18 years at first visit; 49 autistic individuals, mean [SD] age, 14.31 [2.4] years; 42 male [85.7%] and 97 neurotypical individuals, mean [SD] age, 14.10 [2.5] years; 58 male [59.8%]). Maturational between-group differences in cortical thickness and surface area were established that were mostly driven by sensorimotor regions (eg, across features, absolute loadings for early visual cortex ranged from 0.07 to 0.11, whereas absolute loadings for dorsolateral prefrontal cortex ranged from 0.005 to 0.06). Neurodevelopmental differences were transcriptomically enriched for genes expressed in several cell types and during various neurodevelopmental stages, and autism candidate genes (eg, downregulated genes in autism, including those regulating synaptic transmission; enrichment odds ratio =3.7; P =2.6 × -10). A more neurotypical, less autismlike maturational profile was associated with fewer social difficulties and more typical sensory processing (false discovery rate P <.05; Pearson r ≥0.17). Results were replicated in the independently collected BrainMapASD cohort.

Conclusions and Relevance

Results of this case-control study suggest that the coordinated development of brain regions was altered in autism, involved a complex interplay of temporally sensitive molecular mechanisms, and may be associated with both lower-order (eg, sensory) and higher-order (eg, social) clinical features of autism. Thus, examining maturational patterns may provide an analytic framework to study the neurobiological origins of clinical profiles in neurodevelopmental/mental health conditions.

Psychiatric neuroimaging at a crossroads: Insights from psychiatric genetics

Thanks to methodological advances, large-scale data collections, and longitudinal designs, psychiatric neuroimaging is better equipped than ever to identify the neurobiological underpinnings of youth mental health problems. However, the complexity of such endeavors has become increasingly evident, as the field has been confronted by limited clinical relevance, inconsistent results, and small effect sizes. Some of these challenges parallel those historically encountered by psychiatric genetics. In past genetic research, robust findings were historically undermined by oversimplified biological hypotheses, mistaken assumptions about expectable effect sizes, replication problems, confounding by population structure, and shared biological patterns across disorders. Overcoming these challenges has contributed to current successes in the field. Drawing parallels across psychiatric genetics and neuroimaging, we identify key shared challenges as well as pinpoint relevant insights that could be gained in psychiatric neuroimaging from the transition that occurred from the candidate gene to (post) genome-wide "eras" of psychiatric genetics. Finally, we discuss the prominent developmental component of psychiatric neuroimaging and how that might be informed by epidemiological and omics approaches. The evolution of psychiatric genetic research offers valuable insights that may expedite the resolution of key challenges in psychiatric neuroimaging, thus potentially moving our understanding of psychiatric pathophysiology forward.

Individualized gray matter morphological abnormalities uncover two robust transdiagnostic biotypes

Psychiatric disorders exhibit a shared neuropathology, yet the diverse presentations among patients necessitate the identification of transdiagnostic subtypes to enhance diagnostic and treatment strategies. This study aims to unveil potential transdiagnostic subtypes based on personalized gray matter morphological abnormalities. A total of 496 patients with psychiatric disorders and 255 healthy controls (HCs) from three distinct datasets (one for discovery and two for validation) were enrolled. Individualized gray matter morphological abnormalities were determined using normative modeling to identify transdiagnostic subtypes. In the discovery dataset, two transdiagnostic subtypes with contrasting patterns of structural abnormalities compared to HCs were identified. Reproducibility and generalizability analyses demonstrated that these subtypes could be generalized to new patients and even to new disorders in the validation datasets. These subtypes were characterized by distinct disease epicenters. The gray matter abnormal pattern in subtype 1 was mainly linked to excitatory receptors, whereas subtype 2 showed a predominant association with inhibitory receptors. Furthermore, we observed that the gray matter abnormal pattern in subtype 2 was correlated with transcriptional profiles of inflammation-related genes, while subtype 1 did not show this association. Our findings reveal two robust transdiagnostic biotypes, offering novel insights into psychiatric nosology.

Genetic risk factors underlying white matter hyperintensities and cortical atrophy

White matter hyperintensities index structural abnormalities in the cerebral white matter, including axonal damage. The latter may promote atrophy of the cerebral cortex, a key feature of dementia. Here, we report a study of 51,065 individuals from 10 cohorts demonstrating that higher white matter hyperintensity volume associates with lower cortical thickness. The meta-GWAS of white matter hyperintensities-associated cortical 'atrophy' identifies 20 genome-wide significant loci, and enrichment in genes specific to vascular cell types, astrocytes, and oligodendrocytes. White matter hyperintensities-associated cortical 'atrophy' showed positive genetic correlations with vascular-risk traits and plasma biomarkers of neurodegeneration, and negative genetic correlations with cognitive functioning. 15 of the 20 loci regulated the expression of 54 genes in the cerebral cortex that, together with their co-expressed genes, were enriched in biological processes of axonal cytoskeleton and intracellular transport. The white matter hyperintensities-cortical thickness associations were most pronounced in cortical regions with higher expression of genes specific to excitatory neurons with long-range axons traversing through the white matter. The meta-GWAS-based polygenic risk score predicts vascular and all-cause dementia in an independent sample of 500,348 individuals. Thus, the genetics of white matter hyperintensities-related cortical atrophy involves vascular and neuronal processes and increases dementia risk.

Distinct virtual histology of grey matter atrophy in four neuroinflammatory diseases

Grey matter (GM) atrophies are observed in multiple sclerosis, neuromyelitis optica spectrum disorders [NMOSD; both anti-aquaporin-4 antibody-positive (AQP4+) and -negative (AQP4-) subtypes] and myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD). Revealing the pathogenesis of brain atrophy in these disorders would help their differential diagnosis and guide therapeutic strategies. To determine the neurobiological underpinnings of GM atrophies in multiple sclerosis, AQP4+ NMOSD, AQP4- NMOSD and MOGAD, we conducted a virtual histology analysis that links T1-weighted image derived GM atrophy and gene expression using a multicentre cohort of 324 patients with multiple sclerosis, 197 patients with AQP4+ NMOSD, 75 patients with AQP4- NMOSD, 47 patients with MOGAD and 2169 healthy control subjects. First, interregional GM atrophy profiles across the cortical and subcortical regions were determined using Cohen's d between patients with multiple sclerosis, AQP4+ NMOSD, AQP4- NMOSD or MOGAD and healthy controls. The GM atrophy profiles were then spatially correlated with the gene expression levels extracted from the Allen Human Brain Atlas, respectively. Finally, we explored the virtual histology of clinical-feature relevant GM atrophy using a subgroup analysis that stratified by physical disability, disease duration, number of relapses, lesion burden and cognitive function. Multiple sclerosis showed a severe widespread GM atrophy pattern, mainly involving subcortical nuclei and brainstem. AQP4+ NMOSD showed an obvious widespread pattern of GM atrophy, predominately located in occipital cortex as well as cerebellum. AQP4- NMOSD showed a mild widespread GM atrophy pattern, mainly located in frontal and parietal cortices. MOGAD showed GM atrophy mainly involving the frontal and temporal cortices. High expression of genes specific to microglia, astrocytes, oligodendrocytes and endothelial cells in multiple sclerosis, S1 pyramidal cells in AQP4+ NMOSD, as well as S1 and CA1 pyramidal cells in MOGAD, had spatial correlations with GM atrophy profile, while no atrophy profile-related gene expression was found in AQP4- NMOSD. Virtual histology of clinical feature-relevant GM atrophy pointed mainly to the shared neuronal and endothelial cells, among the four neuroinflammatory diseases. The unique underlying virtual histology patterns were microglia, astrocytes and oligodendrocytes for multiple sclerosis; astrocytes for AQP4+ NMOSD; and oligodendrocytes for MOGAD. Neuronal and endothelial cells were shared potential targets across these neuroinflammatory diseases. These findings may help the differential diagnoses of these diseases and promote the use of optimal therapeutic strategies.

Acute Stress Increases Striatal Connectivity With Cortical Regions Enriched for μ and κ Opioid Receptors

BACKGROUND

Understanding the neurobiological effects of stress is critical for addressing the etiology of major depressive disorder (MDD). Using a dimensional approach involving individuals with differing degree of MDD risk, we investigated 1) the effects of acute stress on cortico-cortical and subcortical-cortical functional connectivity (FC) and 2) how such effects are related to gene expression and receptor maps.

METHODS

Across 115 participants (37 control, 39 remitted MDD, 39 current MDD), we evaluated the effects of stress on FC during the Montreal Imaging Stress Task. Using partial least squares regression, we investigated genes whose expression in the Allen Human Brain Atlas was associated with anatomical patterns of stress-related FC change. Finally, we correlated stress-related FC change maps with opioid and GABAA (gamma-aminobutyric acid A) receptor distribution maps derived from positron emission tomography.

RESULTS

Results revealed robust effects of stress on global cortical connectivity, with increased global FC in frontoparietal and attentional networks and decreased global FC in the medial default mode network. Moreover, robust increases emerged in FC of the caudate, putamen, and amygdala with regions from the ventral attention/salience network, frontoparietal network, and motor networks. Such regions showed preferential expression of genes involved in cell-to-cell signaling (OPRM1, OPRK1, SST, GABRA3, GABRA5), similar to previous genetic MDD studies.

CONCLUSIONS

Acute stress altered global cortical connectivity and increased striatal connectivity with cortical regions that express genes that have previously been associated with imaging abnormalities in MDD and are rich in μ and κ opioid receptors. These findings point to overlapping circuitry underlying stress response, reward, and MDD.

Structure-function coupling changes in first-episode, treatment-naïve schizophrenia correlate with cell type-specific transcriptional signature

BACKGROUND

First-episode schizophrenia (FES) is a complex and progressive psychiatric disorder. The etiology of FES involves genetic, environmental, and neurobiological factors. This study investigates the association between alterations in structural-functional (SC-FC) coupling and transcriptional expression in FES.

METHODS

This study encompassed a cohort of 214 participants, comprising 111 FES patients and 103 healthy controls (HC). Furthermore, we examined the abnormalities within SC-FC coupling in FES and their correlations with meta-analytic cognitive terms, neurotransmitters, and transcriptional patterns through partial least squares regression (PLS), involving similarity with other psychiatric disorders or psychiatric-related diseases, functional enrichments, special cell types, peripheral inflammation, and cortical layers.

RESULTS

FES patients exhibited lower SC-FC coupling in the visual, sensorimotor, and ventral attention networks compared to controls. Furthermore, case-control t-maps revealed a negative correlation with neurotransmitters such as serotonin and dopamine, while showing a positive correlation with opioids. Positive t-maps were associated with cognitive functions, including reasoning, judgment, and action, whereas negative t-maps correlated with cognitive functions such as learning, stress, and mood. Moreover, there was a significant overlap between genes linked to abnormalities in SC-FC coupling and those dysregulated in inflammatory bowel diseases. PLS2- genes linked to SC-FC coupling demonstrated significant enrichment in pathways related to immunity and inflammation, as well as in cortical layers I and V. Conversely, PLS2 + genes were primarily enriched in synaptic signaling processes, specific excitatory neurons, and layers II and IV. Additionally, changes in SC-FC coupling were negatively associated with gene expression related to antipsychotics and lymphocytes.

CONCLUSIONS

These findings offer a new perspective on the complex interplay between SC-FC coupling abnormalities and transcriptional expression in the initial phases of schizophrenia.

Neuroimaging Biomarkers for Drug Discovery and Development in Schizophrenia

Schizophrenia is a chronic mental illness that affects up to 1% of the population. While efficacious therapies are available for positive symptoms, effective treatment of cognitive and negative symptoms remains an unmet need after decades of research. New developments in the field of neuroimaging are accelerating our knowledge gain regarding the underlying pathophysiology of symptoms in schizophrenia and psychosis spectrum disorders, inspiring new targets for drug development. However, no validated and qualified biomarkers are currently available to support the development of new therapeutics. This review summarizes the current use of neuroimaging technology in clinical drug development for psychotic disorders. As exemplified by drug development programs that target NMDA receptor hypofunction, neuroimaging results play a critical role in target discovery and establishing target engagement and dose selection. Furthermore, pharmacological neuroimaging may provide response biomarkers that allow for early decision making in proof-of-concept studies that leverage pharmacological challenge models in healthy volunteers. That said, while response and predictive biomarkers are starting to be evaluated in patient populations, they continue to play a limited role. Novel approaches to neuroimaging data acquisition and analysis may aid the establishment of biomarkers that are predictive at the individual level in the future. Nevertheless, various gaps in knowledge need to be addressed and biomarkers need to be validated to establish them as "fit for purpose" in drug development.

Cells and Molecules Underpinning Cannabis-Related Variations in Cortical Thickness during Adolescence

During adolescence, cannabis experimentation is common, and its association with interindividual variations in brain maturation well studied. Cellular and molecular underpinnings of these system-level relationships are, however, unclear. We thus conducted a three-step study. First, we exposed adolescent male mice to Δ-9-tetrahydrocannabinol (THC) or a synthetic cannabinoid WIN 55,212-2 (WIN) and assessed differentially expressed genes (DEGs), spine numbers, and dendritic complexity in their frontal cortex. Second, in human (male) adolescents, we examined group differences in cortical thickness in 34 brain regions, using magnetic resonance imaging, between those who experimented with cannabis before age 16 (n = 140) and those who did not (n = 327). Finally, we correlated spatially these group differences with gene expression of human homologs of mouse-identified DEGs. The spatial expression of 13 THC-related human homologs of DEGs correlated with cannabis-related variations in cortical thickness, and virtual histology revealed coexpression patterns of these 13 genes with cell-specific markers of astrocytes, microglia, and a type of pyramidal cells enriched in dendrite-regulating genes. Similarly, the spatial expression of 18 WIN-related human homologs of DEGs correlated with group differences in cortical thickness and showed coexpression patterns with the same three cell types. Gene ontology analysis indicated that 37 THC-related human homologs are enriched in neuron projection development, while 33 WIN-related homologs are enriched in processes associated with learning and memory. In mice, we observed spine loss and lower dendritic complexity in pyramidal cells of THC-exposed animals (vs controls). Experimentation with cannabis during adolescence may influence cortical thickness by impacting glutamatergic synapses and dendritic arborization.

Genetic and molecular correlates of cortical thickness alterations in adults with obsessive-compulsive disorder: a transcription-neuroimaging association analysis

BACKGROUND

Although numerous neuroimaging studies have depicted neural alterations in individuals with obsessive-compulsive disorder (OCD), a psychiatric disorder characterized by intrusive cognitions and repetitive behaviors, the molecular mechanisms connecting brain structural changes and gene expression remain poorly understood.

METHODS

This study combined the Allen Human Brain Atlas dataset with neuroimaging data from the Meta-Analysis (ENIGMA) consortium and independent cohorts. Later, partial least squares regression and enrichment analysis were performed to probe the correlation between transcription and cortical thickness variation among adults with OCD.

RESULTS

The cortical map of case-control differences in cortical thickness was spatially correlated with cortical expression of a weighted combination of genes enriched for neurobiologically relevant ontology terms preferentially expressed across different cell types and cortical layers. These genes were specifically expressed in brain tissue, spanning all cortical developmental stages. Protein-protein interaction analysis revealed that these genes coded a network of proteins encompassing various highly interactive hubs.

CONCLUSIONS

The study findings bridge the gap between neural structure and transcriptome data in OCD, fostering an integrative understanding of the potential biological mechanisms.

Associations between antagonistic SNPs for neuropsychiatric disorders and human brain structure

A previously published genome-wide association study (GWAS) meta-analysis across eight neuropsychiatric disorders identified antagonistic single-nucleotide polymorphisms (SNPs) at eleven genomic loci where the same allele was protective against one neuropsychiatric disorder and increased the risk for another. Until now, these antagonistic SNPs have not been further investigated regarding their link to brain structural phenotypes. Here, we explored their associations with cortical surface area and cortical thickness (in 34 brain regions and one global measure each) as well as the volumes of eight subcortical structures using summary statistics of large-scale GWAS of brain structural phenotypes. We assessed if significantly associated brain structural phenotypes were previously reported to be associated with major neuropsychiatric disorders in large-scale case-control imaging studies by the ENIGMA consortium. We further characterized the effects of the antagonistic SNPs on gene expression in brain tissue and their association with additional cognitive and behavioral phenotypes, and performed an exploratory voxel-based whole-brain analysis in the FOR2107 study (n = 754 patients with major depressive disorder and n = 847 controls). We found that eight antagonistic SNPs were significantly associated with brain structural phenotypes in regions such as anterior parts of the cingulate cortex, the insula, and the superior temporal gyrus. Case-control differences in implicated brain structural phenotypes have previously been reported for bipolar disorder, major depressive disorder, and schizophrenia. In addition, antagonistic SNPs were associated with gene expression changes in brain tissue and linked to several cognitive-behavioral traits. In our exploratory whole-brain analysis, we observed significant associations of gray matter volume in the left superior temporal pole and left superior parietal region with the variants rs301805 and rs1933802, respectively. Our results suggest that multiple antagonistic SNPs for neuropsychiatric disorders are linked to brain structural phenotypes. However, to further elucidate these findings, future case-control genomic imaging studies are required.

Differences in the neural correlates of schizophrenia with positive and negative formal thought disorder in patients with schizophrenia in the ENIGMA dataset

Formal thought disorder (FTD) is a clinical key factor in schizophrenia, but the neurobiological underpinnings remain unclear. In particular, the relationship between FTD symptom dimensions and patterns of regional brain volume loss in schizophrenia remains to be established in large cohorts. Even less is known about the cellular basis of FTD. Our study addresses these major obstacles by enrolling a large multi-site cohort acquired by the ENIGMA Schizophrenia Working Group (752 schizophrenia patients and 1256 controls), to unravel the neuroanatomy of FTD in schizophrenia and using virtual histology tools on implicated brain regions to investigate the cellular basis. Based on the findings of previous clinical and neuroimaging studies, we decided to separately explore positive, negative and total formal thought disorder. We used virtual histology tools to relate brain structural changes associated with FTD to cellular distributions in cortical regions. We identified distinct neural networks positive and negative FTD. Both networks encompassed fronto-occipito-amygdalar brain regions, but positive and negative FTD demonstrated a dissociation: negative FTD showed a relative sparing of orbitofrontal cortical thickness, while positive FTD also affected lateral temporal cortices. Virtual histology identified distinct transcriptomic fingerprints associated for both symptom dimensions. Negative FTD was linked to neuronal and astrocyte fingerprints, while positive FTD also showed associations with microglial cell types. These results provide an important step towards linking FTD to brain structural changes and their cellular underpinnings, providing an avenue for a better mechanistic understanding of this syndrome.

Shared and Distinct White Matter Alterations in Major Depression and Bipolar Disorder: A Systematic Review and Meta-Analysis

BACKGROUND

Identifying white matter (WM) microstructural similarities and differences between major depressive disorder (MDD) and bipolar disorder (BD) is an important way to understand the potential neuropathological mechanism in emotional disorders. Numerous diffusion tensor imaging (DTI) studies over recent decades have confirmed the presence of WM anomalies in these two affective disorders, but the results were inconsistent. This study aimed to determine the statistical consistency of DTI findings for BD and MDD by using the coordinate-based meta-analysis (CBMA) approach.

METHODS

We performed a systematic search of tract-based spatial statistics (TBSS) studies comparing MDD or BD with healthy controls (HC) as of June 30, 2024. The seed-based d-mapping (SDM) was applied to investigate fractional anisotropy (FA) changes. Meta-regression was then used to analyze the potential correlations between demographics and neuroimaging alterations.

RESULTS

Regional FA reductions in the body of the corpus callosum (CC) were identified in both of these two diseases. Besides, MDD patients also exhibited decreased FA in the genu and splenium of the CC, as well as the left anterior thalamic projections (ATP), while BD patients showed FA reduction in the left median network, and cingulum in addition to the CC.

CONCLUSIONS

The results highlighted that altered integrity in the body of CC served as the shared basis of MDD and BD, and distinct microstructural WM abnormalities also existed, which might induce the various clinical manifestations of these two affective disorders. The study was registered on PROSPERO (http://www.crd.york.ac.uk/PROSPERO), registration number: CRD42022301929.

Retarded astrogliogenesis in response to hypoxia is facilitated by downregulation of CIRBP

The adverse impacts of chronic hypoxia on maternal and infant health at high altitudes warrant significant attention. However, effective protective measures against the resultant growth restrictions and neurodevelopmental disorders in infants and young children are still lacking. This study investigated the neurodevelopment of mice offspring under hypoxic conditions by exposing pregnant mice to a hypobaric oxygen chamber that simulated the hypobaric hypoxia at an altitude of 4000 m until 28 days after delivery. Our findings suggested that prolonged exposure to hypoxia might result in emotional abnormalities and social disorders in offspring. The significant reduction in astrogliogenesis was a characteristic feature associated with neurodevelopmental disorders induced by hypoxia. Further studies demonstrated that cold-induced RNA-binding protein (CIRBP) was a key transcriptional regulator in astrogliogenesis, which downregulated astrocytic differentiation under hypoxia through its crosstalk with the NFIA. Our study emphasized the crucial role of CIRBP in regulating astrogliogenesis and highlighted its potential as a promising target for therapeutic interventions in neurodevelopmental disorders associated with hypoxia.

Regional patterns of human cortex development correlate with underlying neurobiology

Human brain morphology undergoes complex changes over the lifespan. Despite recent progress in tracking brain development via normative models, current knowledge of underlying biological mechanisms is highly limited. We demonstrate that human cortical thickness development and aging trajectories unfold along patterns of molecular and cellular brain organization, traceable from population-level to individual developmental trajectories. During childhood and adolescence, cortex-wide spatial distributions of dopaminergic receptors, inhibitory neurons, glial cell populations, and brain-metabolic features explain up to 50% of variance associated with a lifespan model of regional cortical thickness trajectories. In contrast, modeled cortical thickness change patterns during adulthood are best explained by cholinergic and glutamatergic neurotransmitter receptor and transporter distributions. These relationships are supported by developmental gene expression trajectories and translate to individual longitudinal data from over 8,000 adolescents, explaining up to 59% of developmental change at cohort- and 18% at single-subject level. Integrating neurobiological brain atlases with normative modeling and population neuroimaging provides a biologically meaningful path to understand brain development and aging in living humans.

Obesity and the cerebral cortex: Underlying neurobiology in mice and humans

Obesity is a major modifiable risk factor for Alzheimer's disease (AD), characterized by progressive atrophy of the cerebral cortex. The neurobiology of obesity contributions to AD is poorly understood. Here we show with in vivo MRI that diet-induced obesity decreases cortical volume in mice, and that higher body adiposity associates with lower cortical volume in humans. Single-nuclei transcriptomics of the mouse cortex reveals that dietary obesity promotes an array of neuron-adverse transcriptional dysregulations, which are mediated by an interplay of excitatory neurons and glial cells, and which involve microglial activation and lowered neuronal capacity for neuritogenesis and maintenance of membrane potential. The transcriptional dysregulations of microglia, more than of other cell types, are like those in AD, as assessed with single-nuclei cortical transcriptomics in a mouse model of AD and two sets of human donors with the disease. Serial two-photon tomography of microglia demonstrates microgliosis throughout the mouse cortex. The spatial pattern of adiposity-cortical volume associations in human cohorts interrogated together with in silico bulk and single-nucleus transcriptomic data from the human cortex implicated microglia (along with other glial cells and subtypes of excitatory neurons), and it correlated positively with the spatial profile of cortical atrophy in patients with mild cognitive impairment and AD. Thus, multi-cell neuron-adverse dysregulations likely contribute to the loss of cortical tissue in obesity. The dysregulations of microglia may be pivotal to the obesity-related risk of AD.

Shared atypical spontaneous brain activity pattern in early onset schizophrenia and autism spectrum disorders: evidence from cortical surface-based analysis

Schizophrenia and autism spectrum disorders (ASD) were considered as two neurodevelopmental disorders and had shared clinical features. we hypothesized that they have some common atypical brain functions and the purpose of this study was to explored the shared brain spontaneous activity strength alterations in early onset schizophrenia (EOS) and ASD in the children and adolescents with a multi-center large-sample study. A total of 171 EOS patients (aged 14.25 ± 1.87), 188 ASD patients (aged 9.52 ± 5.13), and 107 healthy controls (aged 11.52 ± 2.82) had scanned with Resting-fMRI and analyzed surface-based amplitude of low-frequency fluctuations (ALFF). Results showed that both EOS and ASD had hypoactivity in the primary sensorimotor regions (bilateral primary and early visual cortex, left ventral visual stream, left primary auditory cortex) and hyperactivity in the high-order transmodal regions (bilateral SFL, bilateral DLPFC, right frontal eye fields), and bilateral thalamus. EOS had more severe abnormality than ASD. This study revealed shared functional abnormalities in the primary sensorimotor regions and the high-order transmodal regions in EOS and ASD, which provided neuroimaging evidence of common changes in EOS and ASD, and may help with better early recognition and precise treatment for EOS and ASD.

Genetic influences on brain and cognitive health and their interactions with cardiovascular conditions and depression

Approximately 40% of dementia cases could be prevented or delayed by modifiable risk factors related to lifestyle and environment. These risk factors, such as depression and vascular disease, do not affect all individuals in the same way, likely due to inter-individual differences in genetics. However, the precise nature of how genetic risk profiles interact with modifiable risk factors to affect brain health is poorly understood. Here we combine multiple data resources, including genotyping and postmortem gene expression, to map the genetic landscape of brain structure and identify 367 loci associated with cortical thickness and 13 loci associated with white matter hyperintensities (P < 5×10-8), with several loci also showing a significant association with cognitive function. We show that among 220 unique genetic loci associated with cortical thickness in our genome-wide association studies (GWAS), 95 also showed evidence of interaction with depression or cardiovascular conditions. Polygenic risk scores based on our GWAS of inferior frontal thickness also interacted with hypertension in predicting executive function in the Canadian Longitudinal Study on Aging. These findings advance our understanding of the genetic underpinning of brain structure and show that genetic risk for brain and cognitive health is in part moderated by treatable mid-life factors.

Factor analysis of lifetime psychopathology and its brain morphometric and genetic correlates in a transdiagnostic sample

There is a lack of knowledge regarding the relationship between proneness to dimensional psychopathological syndromes and the underlying pathogenesis across major psychiatric disorders, i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizoaffective Disorder (SZA), and Schizophrenia (SZ). Lifetime psychopathology was assessed using the OPerational CRITeria (OPCRIT) system in 1,038 patients meeting DSM-IV-TR criteria for MDD, BD, SZ, or SZA. The cohort was split into two samples for exploratory and confirmatory factor analyses. All patients were scanned with 3-T MRI, and data was analyzed with the CAT-12 toolbox in SPM12. Psychopathological factor scores were correlated with gray matter volume (GMV) and cortical thickness (CT). Finally, factor scores were used for exploratory genetic analyses including genome-wide association studies (GWAS) and polygenic risk score (PRS) association analyses. Three factors (paranoid-hallucinatory syndrome, PHS; mania, MA; depression, DEP) were identified and cross-validated. PHS was negatively correlated with four GMV clusters comprising parts of the hippocampus, amygdala, angular, middle occipital, and middle frontal gyri. PHS was also negatively associated with the bilateral superior temporal, left parietal operculum, and right angular gyrus CT. No significant brain correlates were observed for the two other psychopathological factors. We identified genome-wide significant associations for MA and DEP. PRS for MDD and SZ showed a positive effect on PHS, while PRS for BD showed a positive effect on all three factors. This study investigated the relationship of lifetime psychopathological factors and brain morphometric and genetic markers. Results highlight the need for dimensional approaches, overcoming the limitations of the current psychiatric nosology.

Connectome architecture shapes large-scale cortical alterations in schizophrenia: a worldwide ENIGMA study

Schizophrenia is a prototypical network disorder with widespread brain-morphological alterations, yet it remains unclear whether these distributed alterations robustly reflect the underlying network layout. We tested whether large-scale structural alterations in schizophrenia relate to normative structural and functional connectome architecture, and systematically evaluated robustness and generalizability of these network-level alterations. Leveraging anatomical MRI scans from 2439 adults with schizophrenia and 2867 healthy controls from 26 ENIGMA sites and normative data from the Human Connectome Project (n = 207), we evaluated structural alterations of schizophrenia against two network susceptibility models: (i) hub vulnerability, which examines associations between regional network centrality and magnitude of disease-related alterations; (ii) epicenter mapping, which identifies regions whose typical connectivity profile most closely resembles the disease-related morphological alterations. To assess generalizability and specificity, we contextualized the influence of site, disease stages, and individual clinical factors and compared network associations of schizophrenia with that found in affective disorders. Our findings show schizophrenia-related cortical thinning is spatially associated with functional and structural hubs, suggesting that highly interconnected regions are more vulnerable to morphological alterations. Predominantly temporo-paralimbic and frontal regions emerged as epicenters with connectivity profiles linked to schizophrenia's alteration patterns. Findings were robust across sites, disease stages, and related to individual symptoms. Moreover, transdiagnostic comparisons revealed overlapping epicenters in schizophrenia and bipolar, but not major depressive disorder, suggestive of a pathophysiological continuity within the schizophrenia-bipolar-spectrum. In sum, cortical alterations over the course of schizophrenia robustly follow brain network architecture, emphasizing marked hub susceptibility and temporo-frontal epicenters at both the level of the group and the individual. Subtle variations of epicenters across disease stages suggest interacting pathological processes, while associations with patient-specific symptoms support additional inter-individual variability of hub vulnerability and epicenters in schizophrenia. Our work outlines potential pathways to better understand macroscale structural alterations, and inter- individual variability in schizophrenia.

Principal component analysis as an efficient method for capturing multivariate brain signatures of complex disorders-ENIGMA study in people with bipolar disorders and obesity

Multivariate techniques better fit the anatomy of complex neuropsychiatric disorders which are characterized not by alterations in a single region, but rather by variations across distributed brain networks. Here, we used principal component analysis (PCA) to identify patterns of covariance across brain regions and relate them to clinical and demographic variables in a large generalizable dataset of individuals with bipolar disorders and controls. We then compared performance of PCA and clustering on identical sample to identify which methodology was better in capturing links between brain and clinical measures. Using data from the ENIGMA-BD working group, we investigated T1-weighted structural MRI data from 2436 participants with BD and healthy controls, and applied PCA to cortical thickness and surface area measures. We then studied the association of principal components with clinical and demographic variables using mixed regression models. We compared the PCA model with our prior clustering analyses of the same data and also tested it in a replication sample of 327 participants with BD or schizophrenia and healthy controls. The first principal component, which indexed a greater cortical thickness across all 68 cortical regions, was negatively associated with BD, BMI, antipsychotic medications, and age and was positively associated with Li treatment. PCA demonstrated superior goodness of fit to clustering when predicting diagnosis and BMI. Moreover, applying the PCA model to the replication sample yielded significant differences in cortical thickness between healthy controls and individuals with BD or schizophrenia. Cortical thickness in the same widespread regional network as determined by PCA was negatively associated with different clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. PCA outperformed clustering and provided an easy-to-use and interpret method to study multivariate associations between brain structure and system-level variables. PRACTITIONER POINTS: In this study of 2770 Individuals, we confirmed that cortical thickness in widespread regional networks as determined by principal component analysis (PCA) was negatively associated with relevant clinical and demographic variables, including diagnosis, age, BMI, and treatment with antipsychotic medications or lithium. Significant associations of many different system-level variables with the same brain network suggest a lack of one-to-one mapping of individual clinical and demographic factors to specific patterns of brain changes. PCA outperformed clustering analysis in the same data set when predicting group or BMI, providing a superior method for studying multivariate associations between brain structure and system-level variables.

Unraveling the molecular relevance of brain phenotypes: A comparative analysis of null models and test statistics

Correlating transcriptional profiles with imaging-derived phenotypes has the potential to reveal possible molecular architectures associated with cognitive functions, brain development and disorders. Competitive null models built by resampling genes and self-contained null models built by spinning brain regions, along with varying test statistics, have been used to determine the significance of transcriptional associations. However, there has been no systematic evaluation of their performance in imaging transcriptomics analyses. Here, we evaluated the performance of eight different test statistics (mean, mean absolute value, mean squared value, max mean, median, Kolmogorov-Smirnov (KS), Weighted KS and the number of significant correlations) in both competitive null models and self-contained null models. Simulated brain maps (n = 1,000) and gene sets (n = 500) were used to calculate the probability of significance (Psig) for each statistical test. Our results suggested that competitive null models may result in false positive results driven by co-expression within gene sets. Furthermore, we demonstrated that the self-contained null models may fail to account for distribution characteristics (e.g., bimodality) of correlations between all available genes and brain phenotypes, leading to false positives. These two confounding factors interacted differently with test statistics, resulting in varying outcomes. Specifically, the sign-sensitive test statistics (i.e., mean, median, KS, Weighted KS) were influenced by co-expression bias in the competitive null models, while median and sign-insensitive test statistics were sensitive to the bimodality bias in the self-contained null models. Additionally, KS-based statistics produced conservative results in the self-contained null models, which increased the risk of false negatives. Comprehensive supplementary analyses with various configurations, including realistic scenarios, supported the results. These findings suggest utilizing sign-insensitive test statistics such as mean absolute value, max mean in the competitive null models and the mean as the test statistic for the self-contained null models. Additionally, adopting the confounder-matched (e.g., coexpression-matched) null models as an alternative to standard null models can be a viable strategy. Overall, the present study offers insights into the selection of statistical tests for imaging transcriptomics studies, highlighting areas for further investigation and refinement in the evaluation of novel and commonly used tests.

Systematic review and meta-analysis: multimodal functional and anatomical neural alterations in autism spectrum disorder

BACKGROUND

This meta-analysis aimed to explore the most robust findings across numerous existing resting-state functional imaging and voxel-based morphometry (VBM) studies on the functional and structural brain alterations in individuals with autism spectrum disorder (ASD).

METHODS

A whole-brain voxel-wise meta-analysis was conducted to compare the differences in the intrinsic functional activity and gray matter volume (GMV) between individuals with ASD and typically developing individuals (TDs) using Seed-based d Mapping software.

RESULTS

A total of 23 functional imaging studies (786 ASD, 710 TDs) and 52 VBM studies (1728 ASD, 1747 TDs) were included. Compared with TDs, individuals with ASD displayed resting-state functional decreases in the left insula (extending to left superior temporal gyrus [STG]), bilateral anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), left angular gyrus and right inferior temporal gyrus, as well as increases in the right supplementary motor area and precuneus. For VBM meta-analysis, individuals with ASD displayed decreased GMV in the ACC/mPFC and left cerebellum, and increased GMV in the left middle temporal gyrus (extending to the left insula and STG), bilateral olfactory cortex, and right precentral gyrus. Further, individuals with ASD displayed decreased resting-state functional activity and increased GMV in the left insula after overlapping the functional and structural differences.

CONCLUSIONS

The present multimodal meta-analysis demonstrated that ASD exhibited similar alterations in both function and structure of the insula and ACC/mPFC, and functional or structural alterations in the default mode network (DMN), primary motor and sensory regions. These findings contribute to further understanding of the pathophysiology of ASD.

Brain Structural Network Connectivity of Formal Thought Disorder Dimensions in Affective and Psychotic Disorders

BACKGROUND

The psychopathological syndrome of formal thought disorder (FTD) is not only present in schizophrenia (SZ), but also highly prevalent in major depressive disorder and bipolar disorder. It remains unknown how alterations in the structural white matter connectome of the brain correlate with psychopathological FTD dimensions across affective and psychotic disorders.

METHODS

Using FTD items of the Scale for the Assessment of Positive Symptoms and Scale for the Assessment of Negative Symptoms, we performed exploratory and confirmatory factor analyses in 864 patients with major depressive disorder (n= 689), bipolar disorder (n = 108), or SZ (n = 67) to identify psychopathological FTD dimensions. We used T1- and diffusion-weighted magnetic resonance imaging to reconstruct the structural connectome of the brain. To investigate the association of FTD subdimensions and global structural connectome measures, we employed linear regression models. We used network-based statistic to identify subnetworks of white matter fiber tracts associated with FTD symptomatology.

RESULTS

Three psychopathological FTD dimensions were delineated, i.e., disorganization, emptiness, and incoherence. Disorganization and incoherence were associated with global dysconnectivity. Network-based statistics identified subnetworks associated with the FTD dimensions disorganization and emptiness but not with the FTD dimension incoherence. Post hoc analyses on subnetworks did not reveal diagnosis × FTD dimension interaction effects. Results remained stable after correcting for medication and disease severity. Confirmatory analyses showed a substantial overlap of nodes from both subnetworks with cortical brain regions previously associated with FTD in SZ.

CONCLUSIONS

We demonstrated white matter subnetwork dysconnectivity in major depressive disorder, bipolar disorder, and SZ associated with FTD dimensions that predominantly comprise brain regions implicated in speech. Results open an avenue for transdiagnostic, psychopathology-informed, dimensional studies in pathogenetic research.

Genetic and phenotypic similarity across major psychiatric disorders: a systematic review and quantitative assessment

There is widespread overlap across major psychiatric disorders, and this is the case at different levels of observations, from genetic variants to brain structures and function and to symptoms. However, it remains unknown to what extent these commonalities at different levels of observation map onto each other. Here, we systematically review and compare the degree of similarity between psychiatric disorders at all available levels of observation. We searched PubMed and EMBASE between January 1, 2009 and September 8, 2022. We included original studies comparing at least four of the following five diagnostic groups: Schizophrenia, Bipolar Disorder, Major Depressive Disorder, Autism Spectrum Disorder, and Attention Deficit Hyperactivity Disorder, with measures of similarities between all disorder pairs. Data extraction and synthesis were performed by two independent researchers, following the PRISMA guidelines. As main outcome measure, we assessed the Pearson correlation measuring the degree of similarity across disorders pairs between studies and biological levels of observation. We identified 2975 studies, of which 28 were eligible for analysis, featuring similarity measures based on single-nucleotide polymorphisms, gene-based analyses, gene expression, structural and functional connectivity neuroimaging measures. The majority of correlations (88.6%) across disorders between studies, within and between levels of observation, were positive. To identify a consensus ranking of similarities between disorders, we performed a principal component analysis. Its first dimension explained 51.4% (95% CI: 43.2, 65.4) of the variance in disorder similarities across studies and levels of observation. Based on levels of genetic correlation, we estimated the probability of another psychiatric diagnosis in first-degree relatives and showed that they were systematically lower than those observed in population studies. Our findings highlight that genetic and brain factors may underlie a large proportion, but not all of the diagnostic overlaps observed in the clinic.

Correlation between frailty and reduction in cortical thickness in patients with chronic obstructive pulmonary disease

Physical inactivity and cognitive impairment in patients with chronic obstructive pulmonary disease (COPD) can lead to frailty and poor prognoses. However, little is known regarding the association between frailty and the human brain. We hypothesized that the brain structure could change according to frailty in patients with COPD and focused on cortical thickness. Cortical thickness measured by magnetic resonance imaging and frailty scores using the Kihon Checklist (KCL) were assessed in 40 patients with stable COPD and 20 healthy controls. Among the 34 regions assessed, multiple regions were thinner in patients with COPD than in healthy individuals (p < 0.05). We found significant negative correlations between the eight regions and the KCL scores only in patients with COPD. After adjusting for age and cognitive impairment, the association between the left and six right regions remained statistically significant. The correlation coefficient was the strongest in the bilateral superior frontal gyrus (left: ρ = - 0.5319, p = 0.0006) (right: ρ = - 0.5361, p = 0.0005). Interestingly, among the KCL scores, the daily activity domain showed the strongest correlation (sensitivity, 90%; specificity, 73%) with the bottom quartile of the reduction in the superior frontal gyrus. Frailty in patients with COPD is associated with a thickness reduction in the cortical regions, reflecting social vulnerability.

General and specific patterns of cortical gene expression as spatial correlates of complex cognitive functioning

Gene expression varies across the brain. This spatial patterning denotes specialised support for particular brain functions. However, the way that a given gene's expression fluctuates across the brain may be governed by general rules. Quantifying patterns of spatial covariation across genes would offer insights into the molecular characteristics of brain areas supporting, for example, complex cognitive functions. Here, we use principal component analysis to separate general and unique gene regulatory associations with cortical substrates of cognition. We find that the region-to-region variation in cortical expression profiles of 8235 genes covaries across two major principal components: gene ontology analysis suggests these dimensions are characterised by downregulation and upregulation of cell-signalling/modification and transcription factors. We validate these patterns out-of-sample and across different data processing choices. Brain regions more strongly implicated in general cognitive functioning (g; 3 cohorts, total meta-analytic N = 39,519) tend to be more balanced between downregulation and upregulation of both major components (indicated by regional component scores). We then identify a further 29 genes as candidate cortical spatial correlates of g, beyond the patterning of the two major components (|β| range = 0.18 to 0.53). Many of these genes have been previously associated with clinical neurodegenerative and psychiatric disorders, or with other health-related phenotypes. The results provide insights into the cortical organisation of gene expression and its association with individual differences in cognitive functioning.

BDNF, DRD4, and HTR2A Gene Allele Frequency Distribution and Association with Mental Illnesses in the European Part of Russia

The prevalence of mental disorders and how they are diagnosed represent some of the major problems in psychiatry. Modern genetic tools offer the potential to reduce the complications concerning diagnosis. However, the vast genetic diversity in the world population requires a closer investigation of any selected populations. In the current research, four polymorphisms, namely rs6265 in BDNF, rs10835210 in BDNF, rs6313 in HTR2A, and rs1800955 in DRD4, were analyzed in a case-control study of 2393 individuals (1639 patients with mental disorders (F20-F29, F30-F48) and 754 controls) from the European part of Russia using the TaqMan SNP genotyping method. Significant associations between rs6265 BDNF and rs1800955 DRD4 and mental impairments were detected when comparing the general group of patients with mental disorders (without separation into diagnoses) to the control group. Associations of rs6265 in BDNF, rs1800955 in DRD4, and rs6313 in HTR2A with schizophrenia in patients from the schizophrenia group separately compared to the control group were also found. The obtained results can extend the concept of a genetic basis for mental disorders in the Russian population and provide a basis for the future improvement in psychiatric diagnostics.

Intrauterine growth and the tangential expansion of the human cerebral cortex in times of food scarcity and abundance

Tangential growth of the human cerebral cortex is driven by cell proliferation during the first and second trimester of pregnancy. Fetal growth peaks in mid-gestation. Here, we explore how genes associated with fetal growth relate to cortical growth. We find that both maternal and fetal genetic variants associated with higher birthweight predict larger cortical surface area. The relative dominance of the maternal vs. fetal variants in these associations show striking variations across birth years (1943 to 1966). The birth-year patterns vary as a function of the epigenetic status near genes differentially methylated in individuals exposed (or not) to famine during the Dutch Winter of 1944/1945. Thus, it appears that the two sets of molecular processes contribute to early cortical development to a different degree in times of food scarcity or its abundance.

Dimensional Neuroimaging Endophenotypes: Neurobiological Representations of Disease Heterogeneity Through Machine Learning

Machine learning has been increasingly used to obtain individualized neuroimaging signatures for disease diagnosis, prognosis, and response to treatment in neuropsychiatric and neurodegenerative disorders. Therefore, it has contributed to a better understanding of disease heterogeneity by identifying disease subtypes that present significant differences in various brain phenotypic measures. In this review, we first present a systematic literature overview of studies using machine learning and multimodal MRI to unravel disease heterogeneity in various neuropsychiatric and neurodegenerative disorders, including Alzheimer's disease, schizophrenia, major depressive disorder, autism spectrum disorder, multiple sclerosis, as well as their potential in transdiagnostic settings. Subsequently, we summarize relevant machine learning methodologies and discuss an emerging paradigm which we call dimensional neuroimaging endophenotype (DNE). DNE dissects the neurobiological heterogeneity of neuropsychiatric and neurodegenerative disorders into a low-dimensional yet informative, quantitative brain phenotypic representation, serving as a robust intermediate phenotype (i.e., endophenotype) largely reflecting underlying genetics and etiology. Finally, we discuss the potential clinical implications of the current findings and envision future research avenues.

Resolving heterogeneity in schizophrenia, bipolar I disorder, and attention-deficit/hyperactivity disorder through individualized structural covariance network analysis

Disruptions in large-scale brain connectivity are hypothesized to contribute to psychiatric disorders, including schizophrenia, bipolar I disorder, and attention-deficit/hyperactivity disorder. However, high inter-individual variation among patients with psychiatric disorders hinders achievement of unified findings. To this end, we adopted a newly proposed method to resolve heterogeneity of differential structural covariance network in schizophrenia, bipolar I disorder, and attention-deficit/hyperactivity disorder. This method could infer individualized structural covariance aberrance by assessing the deviation from healthy controls. T1-weighted anatomical images of 114 patients with psychiatric disorders (schizophrenia: n = 37; bipolar I disorder: n = 37; attention-deficit/hyperactivity disorder: n = 37) and 110 healthy controls were analyzed to obtain individualized differential structural covariance network. Patients exhibited tremendous heterogeneity in profiles of individualized differential structural covariance network. Despite notable heterogeneity, patients with the same disorder shared altered edges at network level. Moreover, individualized differential structural covariance network uncovered two distinct psychiatric subtypes with opposite differences in structural covariance edges, that were otherwise obscured when patients were merged, compared with healthy controls. These results provide new insights into heterogeneity and have implications for the nosology in psychiatric disorders.

A statistical method for image-mediated association studies discovers genes and pathways associated with four brain disorders

Brain imaging and genomics are critical tools enabling characterization of the genetic basis of brain disorders. However, imaging large cohorts is expensive and may be unavailable for legacy datasets used for genome-wide association studies (GWASs). Using an integrated feature selection/aggregation model, we developed an image-mediated association study (IMAS), which utilizes borrowed imaging/genomics data to conduct association mapping in legacy GWAS cohorts. By leveraging the UK Biobank image-derived phenotypes (IDPs), the IMAS discovered genetic bases underlying four neuropsychiatric disorders and verified them by analyzing annotations, pathways, and expression quantitative trait loci (eQTLs). A cerebellar-mediated mechanism was identified to be common to the four disorders. Simulations show that, if the goal is identifying genetic risk, our IMAS is more powerful than a hypothetical protocol in which the imaging results were available in the GWAS dataset. This implies the feasibility of reanalyzing legacy GWAS datasets without conducting additional imaging, yielding cost savings for integrated analysis of genetics and imaging.

Population Neuroscience: Principles and Advances

In population neuroscience, three disciplines come together to advance our knowledge of factors that shape the human brain: neuroscience, genetics, and epidemiology (Paus, Human Brain Mapping 31:891-903, 2010). Here, I will come back to some of the background material reviewed in more detail in our previous book (Paus, Population Neuroscience, 2013), followed by a brief overview of current advances and challenges faced by this integrative approach.

Transcriptomics : Approaches to Quantifying Gene Expression and Their Application to Studying the Human Brain

To date, the field of transcriptomics has been characterized by rapid methods development and technological advancement, with new technologies continuously rendering older ones obsolete.This chapter traces the evolution of approaches to quantifying gene expression and provides an overall view of the current state of the field of transcriptomics, its applications to the study of the human brain, and its place in the broader emerging multiomics landscape.

Modelling the overlap and divergence of autistic and schizotypal traits on hippocampal subfield volumes and regional cerebral blood flow

Psychiatric disorders show high co-morbidity, including co-morbid expressions of subclinical psychopathology across multiple disease spectra. Given the limitations of classical case-control designs in elucidating this overlap, new approaches are needed to identify biological underpinnings of spectra and their interaction. We assessed autistic-like traits (using the Autism Quotient, AQ) and schizotypy - as models of subclinical expressions of disease phenotypes and examined their association with volumes and regional cerebral blood flow (rCBF) of anterior, mid- and posterior hippocampus segments from  structural MRI scans in 318 and arterial spin labelling (ASL) in 346 nonclinical subjects, which overlapped with the structural imaging sample (N = 298). We demonstrate significant interactive effects of positive schizotypy and AQ social skills as well as of positive schizotypy and AQ imagination on hippocampal subfield volume variation. Moreover, we show that AQ attention switching modulated hippocampal head rCBF, while positive schizotypy by AQ attention to detail interactions modulated hippocampal tail rCBF. In addition, we show significant correlation of hippocampal volume and rCBF in both region-of-interest and voxel-wise analyses, which were robust after removal of variance related to schizotypy and autistic traits. These findings provide empirical evidence for both the modulation of hippocampal subfield structure and function through subclinical traits, and in particular how only the interaction of phenotype facets leads to significant reductions or variations in these parameters. This makes a case for considering the synergistic impact of different (subclinical) disease spectra on transdiagnostic biological parameters in psychiatry.