Cortical patterning of abnormal morphometric similarity in psychosis is associated with brain expression of schizophrenia-related genes

Neuromorphic deviations associated with transcriptomic expression and specific cell type in Alzheimer's disease

Alzheimer's disease (AD) is known to be associated with cortical anatomical atrophy and neurodegeneration across various brain regions. However, the relationships between brain structural changes in AD and gene expression remain unclear. We perform the morphometric similarity network (MSN) analysis to reveal the consistent cortical structural differences in individuals with AD compared to controls, and investigate the associations between brain-wide gene expression and morphometric changes. Furthermore, we identify abnormally MSN-related genes linked to specific cell types as the major contributors to transcriptomic relationships. MSN-related structural changes are located in the lateral ventral prefrontal cortex, temporal pole and medial prefrontal lobe, which are highly associated with the AD's cognitive decline. Analysis of gene expression shows the spatial correlations between AD-related genes and MSN differences. Examination of cell type-specific signature genes indicates that changes in microglia and neuronal transcriptional profiles largely contribute to AD-specific MSN differences. The study map the disease-specific structural alterations in AD down to the cellular level, offering a novel perspective on the linking surface-level changes to molecular mechanisms.

Cerebral blood flow alterations and host genetic association in individuals with long COVID: A transcriptomic-neuroimaging study

Neuroimaging studies have indicated that altered cerebral blood flow (CBF) was associated with the long-term symptoms of postacute sequelae of SARS-CoV-2 infection (PASC), also known as "long COVID". COVID-19 and long COVID were found to be strongly associated with host gene expression. Nevertheless, the relationships between altered CBF, clinical symptoms, and gene expression in the central nervous system (CNS) remain unclear in individuals with long COVID. This study aimed to explore the genetic mechanisms of CBF abnormalities in individuals with long COVID by transcriptomic-neuroimaging spatial association. Lower CBF in the left frontal-temporal gyrus was associated with higher fatigue and worse cognition in individuals with long COVID. This CBF pattern was spatially associated with the expression of 2,178 genes, which were enriched in the molecular functions and biological pathways of COVID-19. Our study suggested that lower CBF is associated with persistent clinical symptoms in long COVID individuals, possibly as a consequence of the complex interactions among multiple COVID-19-related genes, which contributes to our understanding of the impact of adverse CNS outcomes and the trajectory of development to long COVID.

Association of cortical macrostructural and microstructural changes with cognitive performance and gene expression in subcortical ischemic vascular disease patients with cognitive impairment

OBJECTIVE

Previous researches have demonstrated that patients with subcortical ischemic vascular disease (SIVD) exhibited brain structure abnormalities. However, the cortical macrostructural and microstructural characteristics and their relationship with cognitive scores and gene expression in SIVD patients remain largely unknown.

METHODS

This study collected 3D-T1 and diffusion tensor imaging data from 30 SIVD patients with cognitive impairment (SIVD-CI) and 32 normal controls. The between-group comparative analyses of cortical thickness, area, volume, local gyrification index (LGI), and mean diffusivity (MD) were conducted with a general linear model. Moreover, the associations between the significant neuroimaging values and the cognitive scores and gene expression values from Allen Human Brain Atlas database were evaluated using partial least squares regression and partial correlation analysis.

RESULTS

SIVD-CI patients showed significant decreases in cortical thicknesses across 18 regions, cortical volumes across three regions, and cortical LGI across five regions, as well as significant increases in cortical MD across five regions (P < 0.05). The significantly reduced cortical thicknesses of the right insula, left superior temporal gyrus, left central anterior gyrus, and left caudal anterior cingulate cortex, as well as the significantly reduced cortical LGI in left caudal anterior cingulate cortex, were significantly positively correlated with different cognitive scores (P < 0.05). Furthermore, the abnormal cortical structural indicators were found to be significantly related to nine risk genes (VCAN, APOE, EFEMP1, SALL1, BCAN, KCNK2, EPN2, DENND1B and XKR6) (P < 0.05).

CONCLUSIONS

The specific cortical structural damage may be related to specific cognitive decline and specific risk genes in SIVD-CI patients.

Polygenic scores for autism are associated with reduced neurite density in adults and children from the general population

Genetic variants linked to autism are thought to change cognition and behaviour by altering the structure and function of the brain. Although a substantial body of literature has identified structural brain differences in autism, it is unknown whether autism-associated common genetic variants are linked to changes in cortical macro- and micro-structure. We investigated this using neuroimaging and genetic data from adults (UK Biobank, N = 31,748) and children (ABCD, N = 4928). Using polygenic scores and genetic correlations we observe a robust negative association between common variants for autism and a magnetic resonance imaging derived phenotype for neurite density (intracellular volume fraction) in the general population. This result is consistent across both children and adults, in both the cortex and in white matter tracts, and confirmed using polygenic scores and genetic correlations. There were no sex differences in this association. Mendelian randomisation analyses provide no evidence for a causal relationship between autism and intracellular volume fraction, although this should be revisited using better powered instruments. Overall, this study provides evidence for shared common variant genetics between autism and cortical neurite density.

Artificial intelligence in insanity evaluation. Potential opportunities and current challenges

The formulation of a scientific opinion on whether the individual who committed a crime should be held responsible for his/her actions or should be considered not responsible by reason of insanity is very difficult. Indeed, forensic psychopathological decision on insanity is highly prone to errors and is affected by human cognitive biases, resulting in low inter-rater reliability. In this context, artificial intelligence can be extremely useful to improve the inter-subjectivity of insanity evaluation. In this paper, we discuss the possible applications of artificial intelligence in this field as well as the challenges and pitfalls that hamper the effective implementation of AI in insanity evaluation. In particular, thus far, it is possible to apply only supervised algorithms without knowing which is the ground truth and which data should be used to train and test the algorithms. In addition, it is not known which percentage of accuracy of the algorithms is sufficient to support partial or total insanity, nor which are the boundaries between sanity and partial or total insanity. Finally, ethical aspects have not been sufficiently investigated. We conclude that these pitfalls should be resolved before AI can be safely and reliably applied in criminal trials.

Topographic Axes of Wiring Space Converge to Genetic Topography in Shaping the Human Cortical Layout

Genetic information is involved in the gradual emergence of cortical areas since the neural tube begins to form, shaping the heterogeneous functions of neural circuits in the human brain. Informed by invasive tract-tracing measurements, the cortex exhibits marked interareal variation in connectivity profiles, revealing the heterogeneity across cortical areas. However, it remains unclear about the organizing principles possibly shared by genetics and cortical wiring to manifest the spatial heterogeneity across the cortex. Instead of considering a complex one-to-one mapping between genetic coding and interareal connectivity, we hypothesized the existence of a more efficient way that the organizing principles are embedded in genetic profiles to underpin the cortical wiring space. Leveraging vertex-wise tractography in diffusion-weighted MRI, we derived the global connectopies (GCs) in both female and male to reliably index the organizing principles of interareal connectivity variation in a low-dimensional space, which captured three dominant topographic patterns along the dorsoventral, rostrocaudal, and mediolateral axes of the cortex. More importantly, we demonstrated that the GCs converge with the gradients of a vertex-by-vertex genetic correlation matrix on the phenotype of cortical morphology and the cortex-wide spatiomolecular gradients. By diving into the genetic profiles, we found that the critical role of genes scaffolding the GCs was related to brain morphogenesis and enriched in radial glial cells before birth and excitatory neurons after birth. Taken together, our findings demonstrated the existence of a genetically determined space that encodes the interareal connectivity variation, which may give new insights into the links between cortical connections and arealization.

Motor Functional Hierarchical Organization of Cerebrum and Its Underlying Genetic Architecture in Parkinson's Disease

Hierarchy has been identified as a principle underlying the organization of human brain networks. However, it remains unclear how the network hierarchy is disrupted in Parkinson's disease (PD) motor symptoms and how it is modulated by the underlying genetic architecture. The aim of this study was to explore alterations in the motor functional hierarchical organization of the cerebrum and their underlying genetic mechanism. In this study, the brain network hierarchy of each group was described through a connectome gradient analysis among 68 healthy controls (HC), 70 postural instability and gait difficulty (PIGD) subtype, and 69 tremor-dominant (TD) subtype, including both male and female participants, according to its motor symptoms. Furthermore, transcription-neuroimaging association analyses using gene expression data from Allen Human Brain Atlas and case-control gradient differences were performed to identify genes associated with gradient alterations. Different PD motor subtypes exhibited contracted principal and secondary functional gradients relative to HC. The identified genes in different PD motor subtypes enriched for shared biological processes like metal ion transport and inorganic ion transmembrane transport. In addition, these genes were overexpressed in Ntsr+ neurons cell, enriched in extensive cortical regions and wide developmental time windows. Aberrant cerebral functional gradients in PD-related motor symptoms have been detected, and the motor-disturbed genes have shared biological functions. The present findings may contribute to a more comprehensive understanding of the molecular mechanisms underlying hierarchical alterations in PD.

Transcriptional and neurochemical signatures of cerebral blood flow alterations in schizophrenia and individuals at clinical high-risk for psychosis

BACKGROUND

The brain integrates multiple scales of description, from the level of cells and molecules to large-scale networks and behaviour. Understanding relationships across these scales may be fundamental to advancing understanding of brain function in health and disease. Recent neuroimaging research has shown that functional brain alterations that are associated with schizophrenia spectrum disorders (SSD) are already present in young adults at clinical high-risk for psychosis (CHR-P), yet the cellular and molecular determinants of these alterations remain unclear.

METHODS

Here, we used regional cerebral blood flow (rCBF) data from 425 individuals (122 SSD compared to 116 HCs, and 129 CHR-P compared to 58 HCs) and applied a novel pipeline to integrate brain-wide rCBF case-control maps with publicly available transcriptomic data (17,205 gene maps) and neurotransmitter atlases (19 maps) from 1074 healthy volunteers.

RESULTS

We identified significant correlations between astrocyte, oligodendrocyte precursor cell, and vascular leptomeningeal cell gene modules for both SSD and CHR-P rCBF phenotypes, and additionally microglia and oligodendrocytes in CHR-P. Receptor distribution significantly predicted case-control rCBF differences, with dominance analysis highlighting dopamine (D1, D2, DAT), acetylcholine (VAChT, M1), GABAA, and NMDA receptors as key predictors for SSD (R2adj=.58, PFDR<.05) and CHR-P (R2adj=.6, PFDR<.05) rCBF phenotypes. These associations were primarily localised in subcortical regions and implicate cell-types involved in stress response and inflammation, alongside specific neuroreceptor systems, in shared and distinct rCBF phenotypes in psychosis.

CONCLUSIONS

Our findings underscore the value of integrating multi-scale data as a promising hypothesis-generating approach towards decoding biological pathways involved in neuroimaging-based psychosis phenotypes, potentially guiding novel interventions.

Brain connectivity and transcriptomic similarity inform abnormal morphometric similarity patterns in first-episode, treatment-naïve major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is associated with disrupted brain structural integration. Morphometric similarity offers a means to capture the coordinated patterns of various structural features. However, it remains unknown whether MDD-related changes can be detected in cortical morphometric similarity through the Morphometric Inverse Divergence (MIND) network. Additionally, the role of brain connectivity in shaping these alterations, and their links to neuroreceptors and gene expression, have yet to be investigated.

METHODS

Using the T1-weighted MRI data from 71 patients with first-episode, treatment-naïve MDD and 69 healthy controls, we constructed the MIND network for all participants. We then performed between-group comparisons to investigate abnormalities in the network and spatial relationships between the observed patterns of MIND disruption and the patterns of neuroreceptors were estimated. Network-based spreading was utilized to explore the abnormalities constrained by brain connectivity based on structural, functional, and transcriptional connectome architecture and to further identify potential epicenters of MDD. In addition, partial least squares regression was conducted to examine the associations of gene expression profiles with MIND changes in MDD.

RESULTS

Patients with MDD showed significantly increased MIND in regions associated with sensation and cognition compared with healthy controls, with this altered pattern being influenced by a combination of transcriptional and structural connectivity, and potential epicenters of MDD were identified in the frontal, parietal, and paracentral cortices. Furthermore, the cortical map of case-control differences in MIND was spatially correlated with the cannabinoid CB1 receptor and the brain-wide expression of a weighted combination of genes. These genes were enriched for neurobiologically relevant pathways and preferentially expressed in different cell classes and cortical layers.

CONCLUSION

These results highlight the abnormal pattern of morphometric similarity observed in MDD, shedding light on the complex interplay between disrupted macroscale coordinated morphology and microscale molecular organization in MDD.

Age-Specific Functional Connectivity Changes After Partial Sleep Deprivation Are Correlated With Neurocognitive and Molecular Signatures

BACKGROUND

This study aimed to investigate age-specific alterations in functional connectivity after sleep deprivation (SD) and decode brain functional changes from neurocognitive and transcriptomic perspectives.

METHODS

Here, we examined changes in global and regional graph measures, particularly regional network strength (RNS), in 41 young participants and 36 older participants with normal sleep and after 3 h of SD. Additionally, by utilizing cognitive probabilistic maps from Neurosynth and gene expression data from the Allen Human Brain Atlas, we applied partial least-squares regression analysis to identify the neurocognitive and transcriptional correlates of these RNS changes.

RESULTS

After SD, older participants exhibited decreased RNS in the default mode network (DMN) and dorsal attention network, with increased RNS in the visual network. Young participants also showed decreased RNS in the DMN, notably in the left inferior parietal lobe, left dorsolateral prefrontal cortex, and left posterior cingulate cortex. In young participants, SD-induced RNS changes significantly correlated with cognitive processes such as "attention," "cognitive control," and "working memory," while in older participants, they correlated with "learning," "focus," and "decision." Gene-category enrichment analysis indicated that specific genes related to signal transduction, ion channels, and immune signaling might influence SD pathophysiology by affecting functional connectivity in young participants.

CONCLUSIONS

This study elucidates shared and age-specific brain functional network alterations associated with SD, providing a neurocognitive and molecular basis for understanding the underlying pathophysiology.

Neural Activity Alterations and Their Association With Neurotransmitter and Genetic Profiles in Schizophrenia: Evidence From Clinical Patients and Unaffected Relatives

BACKGROUND

The pattern of abnormal resting-state brain function has been documented in schizophrenia (SCZ). However, as of yet, it remains unclear whether this pattern is of genetic predisposition or related to the illness itself.

METHODS

A systematical meta-analysis was performed to identify resting-state functional differences in probands and their high-risk first-degree relatives of schizophrenia (FDRs-SCZ) using Seed-based d Mapping software. Subsequently, spatial associations between postmortem gene expression and neurotransmitters distribution data and neural activity alterations were conducted to uncover neural mechanisms underlaying FDRs-SCZ and SCZ from a multidimensional perspective.

RESULTS

A total of 13 studies comprising 503 FDRs-SCZ and 605 healthy controls (HCs) and 129 studies comprising 6506 patients with SCZ and 6982 HCs were included. Compared to HCs, FDRs-SCZ displayed increased spontaneous functional activity in the bilateral anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC); patients with SCZ showed decreased spontaneous functional activity in the bilateral ACC/mPFC, bilateral postcentral gyrus, and right middle temporal gyrus as well as increased spontaneous functional activity in the bilateral striatum. The altered functional activity in FDRs-SCZ and SCZ shared similar spatial associations with genes enriched in potassium ion transmembrane transport, channel activity, and complex. The FDRs-SCZ and SCZ-related brain functional patterns were additionally associated with dopaminergic, serotonergic, and cholinergic neurotransmitter distribution.

CONCLUSIONS

SCZ-related resting-state functional, neuroimaging transcriptomes, and neurotransmitters abnormalities may exist in high-risk unaffected FDRs-SCZ, rather than just in overt SCZ. The study extended the evidence that altered brain function, along with their spatial correlations to genetics and neurotransmitter systems, may associate with genetic vulnerability for SCZ.

Association between functional alterations and specific transcriptional expression patterns in craniocervical dystonia

PURPOSE

Craniocervical dystonia (CCD) is a large-scale network disorder that involves functional changes in multiple brain regions. However, the association between these functional changes and the underlying molecular mechanisms has not been explored.

OBJECTIVE

We aimed to characterize the molecular changes associated with the imaging-defined functional architecture of the brain in CCD.

METHODS

Resting-state functional magnetic resonance imaging (rs-fMRI) data were obtained from 146 patients with CCD and 137 healthy controls (HCs). Differences in the amplitude of low-frequency fluctuations (ALFF), fractional ALFF (fALFF), and regional homogeneity (ReHo) were compared between groups. Transcriptomic data were obtained from the Allen Human Brain Atlas to identify the gene expression patterns underlying the affected functional architecture in CCD using partial least squares regression.

RESULTS

Compared to HCs, patients with CCD showed common functional alterations, mainly in the left middle occipital gyrus, right middle occipital gyrus, right calcarine, right precentral gyrus, and left postcentral gyrus. These functional alteration patterns were positively associated with 1763 genes (including five risk genes for dystonia) enriched for synaptic signaling, regulation of trans-synaptic signaling, and neuronal systems, while they were negatively associated with 2318 genes (including eight risk genes for dystonia), which were enriched for monoatomic cation transport, DNA damage response and neurodevelopment.

CONCLUSIONS

Our study reveals a genetic pathological mechanism explaining CCD-related brain functional changes.

Associations between morphometric similarity network and brain gene expression in type 2 diabetes mellitus

Abnormal functional and structural connectivity of brain networks is commonly observed in patients with type 2 diabetes mellitus (T2DM) and accompanied bycognitive impairment. In this study, we revealed differences in brain structure in T2DM using a Morphometric Similarity Network (MSN) method, which quantifies structural similarities between brain regions. The associations between T2DM-associated changes in morphometric similarity (MS) and gene expression were analyzed to explore the molecular and cellular mechanism underlying MS changes in T2DM. Our research involved 3D-T1WI and DTI data from 157 T2DM patients and 147 healthy controls (HCs) adequately matched. In patients with T2DM, the global MS was decreased. The MS decreased in the regions within the left sensorimotor network and the right salience/ventral attention network and increased in the regions within the bilateral visual network in the patient group. The increased MS of the bilateral visual networks in T2DM patients was negatively correlated with memory function. The transcription-neuroimaging association analysis indicated that the expression of 298 genes was significantly spatially correlated with the T2DM-related MSN abnormalities, and some of these genes are involved in biological processes such as central nervous system development and neurotransmitter transmission, which may provide possible molecular and cellular substrates for MS abnormalities and cognitive decline in T2DM.

Aberrant Modular Dynamics of Functional Networks in Schizophrenia and Their Relationship with Neurotransmitter and Gene Expression Profiles

Introduction

Numerous studies have emphasized the time-varying modular architecture of functional brain networks and its relevance to cognitive functions in healthy participants. However, how brain modular dynamics change in schizophrenia and how these alterations relate to neurotransmitter and transcriptomic signatures have not been well elucidated.

Methods

We harmonized resting-state fMRI data from a multi-site sample including 223 patients and 279 healthy controls and applied the multilayer network method to estimate the regional module switching rate (flexibility) of functional brain connectomes. We examined aberrant flexibility in patients relative to controls and explored its relations to neurotransmitter systems and postmortem gene expression.

Results

Compared with controls, patients with schizophrenia had significantly higher flexibility in the somatomotor and right visual regions, and lower flexibility in the left parahippocampal gyrus, right supramarginal gyrus, right frontal-operculum-insula, bilateral precuneus posterior cingulate cortex, and bilateral inferior parietal gyrus. These alterations were associated with multiple neurotransmitter systems and weighted gene transcriptomic profiles. The most relevant genes were preferentially enriched for biological processes of transmembrane transport and brain development, specific cell types, and previously identified schizophrenia-related genes.

Conclusions

This study reveals aberrant modular dynamics in schizophrenia and its relations to neurotransmitter systems and schizophrenia-related transcriptomic profiles, providing insights into the understanding of the pathophysiology underlying schizophrenia.

Rightward brain structural asymmetry in young children with autism

To understand the neural mechanism of autism spectrum disorder (ASD) and developmental delay/intellectual disability (DD/ID) that can be associated with ASD, it is important to investigate individuals at an early stage with brain, behavioural and also genetic measures, but such research is still lacking. Here, using the cross-sectional sMRI data of 1030 children under 8 years old, we employed developmental normative models to investigate the atypical development of gray matter volume (GMV) asymmetry in individuals with ASD without DD/ID, ASD with DD/ID and individuals with only DD/ID, and their associations with behavioral and clinical measures and transcription profiles. By extracting the individual deviations of patients from the typical controls with normative models, we found a commonly abnormal pattern of GMV asymmetry across all ASD children: more rightward laterality in the inferior parietal lobe and precentral gyrus, and higher individual variability in the temporal pole. Specifically, ASD with DD/ID children showed a severer and more extensive abnormal pattern in GMV asymmetry deviation values, which was linked with both ASD symptoms and verbal IQ. The abnormal pattern of ASD without DD/ID children showed higher and more extensive individual variability, which was linked with ASD symptoms only. DD/ID children showed no significant differences from healthy population in asymmetry. Lastly, the GMV laterality patterns of all patient groups were significantly associated with both shared and unique gene expression profiles. Our findings provide evidence for rightward GMV asymmetry of some cortical regions in young ASD children (1-7 years) in a large sample (1030 cases), show that these asymmetries are related to ASD symptoms, and identify genes that are significantly associated with these differences.

NRN1 genetic variability and methylation changes as biomarkers for cognitive remediation therapy response in schizophrenia

Cognitive remediation therapy (CRT) demonstrates potential in enhancing cognitive function in schizophrenia (SZ), though the identification of molecular biomarkers remains challenging. The Neuritin-1 gene (NRN1) emerges as a promising candidate gene due to its association with SZ, cognitive performance and response to neurotherapeutic treatments. We aimed to investigate whether NRN1 genetic variability and methylation changes following CRT are related to cognitive improvements. Twenty-five SZ patients were randomly assigned to CRT or treatment-as-usual (TAU) groups, with cognitive function and NRN1 methylation assessed pre- and post-intervention using the MATRICS Consensus Cognitive Battery and EpiTYPER. Besides, eleven NRN1 polymorphisms were genotyped. Methylation changes (Δm = post - pre) were analyzed via sparse Partial Least Square Discriminant Analysis (sPLS-DA) to identify latent components (LCs) distinguishing CRT from TAU. To further explore methylation patterns of these LCs, CpG units were grouped into two subsets, yielding Δm means for those with increased and decreased methylation. Cognitive changes (Δcog = post - pre) were used to identify CRT improvers (CRT-I, Δcog ≥ 1), and the association between methylation changes and cognitive improvements post-therapy was also tested. We identified two LCs that differentiated CRT from TAU with a classification error rate of 0.28. The main component, LC1, included 25 CpG units. The subsets of CpG units with increased and decreased post-therapy methylation differed significantly between the two treatment arms, suggesting that differences were not merely data-driven but reflected meaningful biological variation. Additionally, CpG units linked to therapy were also associated with cognitive improvement, with LC1 and the subset of CpG units showing increased methylation post-therapy distinguishing CRT-I from the rest of the patients across multiple cognitive domains. Furthermore, the effect of LC1 on speed processing improvement after CRT was enhanced by considering the NRN1-rs9405890 polymorphism. Notably, these CpG units, particularly those with increased methylation after CRT, overlapped with key gene regulatory elements. Our model, integrating genetics and epigenetics, boosts the understanding of CRT response variability and highlights this multi-level approach as a promising strategy for identifying potential NRN1-related biomarkers of CRT effects, though further studies with larger samples are needed.

Transcriptionally downregulated GABAergic genes associated with synaptic density network dysfunction in temporal lobe epilepsy

PURPOSE

Temporal lobe epilepsy (TLE) is a brain network disorder closely associated with synaptic loss and has a genetic basis. However, the in vivo whole-brain synaptic changes at the network-level and the underlying gene expression patterns in patients with TLE remain unclear.

METHODS

In this study, we utilized a positron emission tomography with the synaptic vesicle glycoprotein 2 A radioligand [18F]SynVesT-1 cohort and two independent transcriptome datasets to investigate the topological properties of the synaptic density similarity network (SDSN) in TLE and its correlation with significantly dysregulated risk genes.

RESULTS

We observed an overall decrease in strength, reduced clustering coefficient, and increased path length of SDSN in TLE, suggesting a loss of connectivity that is accompanied by network reorganization. These changes were predominantly distributed in the temporo-limbic circuit and fronto-parietal networks. Moreover, connectivity changes in SDSN were found to be spatially correlated with the brain-wide expression of TLE risk genes, and the transcriptional correlate of SDSN changes showed a significant relationship with gene dysregulation. In particular, we identified a total of 183 downregulated genes that were functionally enriched for synaptic transmission pathways, forming a highly connected genetic interaction network. Within this set of genes, GABAergic genes such as RBFOX1 play a central role.

DISCUSSION

Our study provides the first evidence that the spatial expression patterns of downregulated risk genes underlie in vivo synaptic density network dysfunction in TLE. These imaging-transcriptomic findings have the potential to guide the development of molecular and genetic network-based therapeutic approaches for TLE.

Molecular architecture of the altered cortical complexity in autism

Autism spectrum disorder (ASD) is characterized by difficulties in social interaction, communication challenges, and repetitive behaviors. Despite extensive research, the molecular mechanisms underlying these neurodevelopmental abnormalities remain elusive. We integrated microscale brain gene expression data with macroscale MRI data from 1829 participants, including individuals with ASD and typically developing controls, from the autism brain imaging data exchange I and II. Using fractal dimension as an index for quantifying cortical complexity, we identified significant regional alterations in ASD, within the left temporoparietal, left peripheral visual, right central visual, left somatomotor (including the insula), and left ventral attention networks. Partial least squares regression analysis revealed gene sets associated with these cortical complexity changes, enriched for biological functions related to synaptic transmission, synaptic plasticity, mitochondrial dysfunction, and chromatin organization. Cell-specific analyses, protein-protein interaction network analysis and gene temporal expression profiling further elucidated the dynamic molecular landscape associated with these alterations. These findings indicate that ASD-related alterations in cortical complexity are closely linked to specific genetic pathways. The combined analysis of neuroimaging and transcriptomic data enhances our understanding of how genetic factors contribute to brain structural changes in ASD.

Shared and distinct morphometric similarity network abnormalities in generalized anxiety disorder, posttraumatic stress disorder and social anxiety disorder

BACKGROUND

The high comorbidity and symptom overlap of generalized anxiety disorder (GAD), posttraumatic stress disorder (PTSD), and social anxiety disorder (SAD), has led to the study of their shared and disorder-specific neural substrates. However, the morphometric similarity network (MSN) differences among these disorders remain unknown.

METHODS

MSN derived from T1-weighted images in patients of GAD, PTSD, and SAD, and health controls (HC) using a Siemens 3T magnetic resonance imaging system. Covariance analysis and post hoc tests were used to investigate group differences. In addition, the relationship between MSN and clinical characteristics was analyzed.

RESULTS

Increased morphometric similarity (MS) between left bankssts (BA22, superior temporal cortex, STC) and right precentral gyrus, and decreased MS between left precentral gyrus and right cuneus_part1/part2, and between right rostral middle frontal cortex (rMFC) and right STC were common in GAD and PTSD relative to HC and SAD. Compared to the other three groups, SAD exhibited disorder-specific alterations of increased MS between right rMFC and right STC, and between left cuneus and right inferior parietal cortex. Additionally, increased regional MSN in left precentral gyrus was found in PTSD compared to HC and SAD. A mild positive correlation of the MS value between left bankssts and right precentral gyrus and the Hamilton Anxiety Rating Scale scores (uncorrected p = 0.041) was found in PTSD.

CONCLUSIONS

Our study provides the first evidence for common and distinct brain MSN abnormalities underlying the pathophysiology of GAD, PTSD, and SAD, which may aid in differential diagnosis and determining potential disorder-specific intervention targets.

Regional brain iron correlates with transcriptional and cellular signatures in Alzheimer's disease

INTRODUCTION

The link between overload brain iron and transcriptional/cellular signatures in Alzheimer's disease (AD) remains inconclusive.

METHODS

Iron deposition in 41 cortical and subcortical regions of 30 AD patients and 26 healthy controls (HCs) was measured using quantitative susceptibility mapping (QSM). The expression of 15,633 genes was estimated in the same regions using transcriptomic data from the Allen Human Brain Atlas (AHBA). Partial least square (PLS) regression was used to identify the association between the healthy brain gene transcription and aberrant regional QSM signal in AD. The biological processes and cell types associated with the linked genes were evaluated.

RESULTS

Gene ontological analyses showed that the first PLS component (PLS1) genes were enriched for biological processes relating to the "protein phosphorylation" and "metal ion transport". Additionally, these genes were expressed in microglia (MG) and glutamatergic neurons (GLUs).

DISCUSSION

Our findings provide mechanistic insights from transcriptional and cellular signatures into regional iron accumulation measured by QSM in AD.

HIGHLIGHTS

Spatial patterns of iron deposition changes in AD correlate with cortical spatial expression genes in healthy subjects. The identified gene transcription profile underlies aberrant iron accumulation in AD was enriched for biological processes relating to "protein phosphorylation" and "metal ion transport". The related genes were predominantly expressed in MG and GLUs.

Structural MRI of brain similarity networks

Recent advances in structural MRI analytics now allow the network organization of individual brains to be comprehensively mapped through the use of the biologically principled metric of anatomical similarity. In this Review, we offer an overview of the measurement and meaning of structural MRI similarity, especially in relation to two key assumptions that often underlie its interpretation: (i) that MRI similarity can be representative of architectonic similarity between cortical areas and (ii) that similar areas are more likely to be axonally connected, as predicted by the homophily principle. We first introduce the historical roots and technical foundations of MRI similarity analysis and compare it with the distinct MRI techniques of structural covariance and tractography analysis. We contextualize this empirical work with two generative models of homophilic networks: an economic model of cost-constrained connectional homophily and a heterochronic model of ontogenetically phased cortical maturation. We then review (i) studies of the genetic and transcriptional architecture of MRI similarity in population-averaged and disorder-specific contexts and (ii) developmental studies of normative cohorts and clinical studies of neurodevelopmental and neurodegenerative disorders. Finally, we prioritize knowledge gaps that must be addressed to consolidate structural MRI similarity as an accessible, valid marker of the architecture and connectivity of an individual brain network.

Subtypes of Insomnia Disorder Identified by Cortical Morphometric Similarity Network

Insomnia disorder (ID) is a highly heterogeneous psychiatric disease, and the use of neuroanatomical data to objectively define biological subtypes is essential. We aimed to examine the neuroanatomical subtypes of ID by morphometric similarity network (MSN) and the association between MSN changes and specific transcriptional expression patterns. We recruited 144 IDs and 124 healthy controls (HC). We performed heterogeneity through discriminant analysis (HYDRA) and identified subtypes within the MSN strength. Differences in MSN between subtypes and HC were compared, and clinical behavioral differences were compared between subtypes. In addition, we investigated the association between MSN changes and brain gene expression in different ID subtypes using partial least squares regression to assess genetic commonalities in psychiatric disorders and further performed functional enrichment analyses. Two distinct subtypes of ID were identified, each exhibiting different MSN changes compared to HC. Furthermore, subtype 1 is characterized by objective short sleep, impaired cognitive function, and some relationships with major depressive disorder and autism spectrum disorder (ASD). In contrast, subtype 2 has normal objective sleep duration but subjectively reports poor sleep and is only related to ASD. The pathogenesis of subtype 1 may be related to genes that regulate sleep rhythms and sleep-wake cycles. In contrast, subtype 2 is more due to adverse emotion perception and regulation. Overall, these findings provide insights into the neuroanatomical subtypes of ID, elucidating the relationships between structural and molecular aspects of the relevant subtypes.

Altered topology in cortical morphometric similarity network in recurrent major depressive disorder

BACKGROUND

Recurrent major depressive disorder (RDD) is increasingly understood to be associated with a 'disconnection' within the brain areas. But, the true understanding of cortical connectivities remains challenging. Morphometric similarity network (MSN) with multi-modal magnetic resonance imaging (MRI) could provide more information about cortical micro-architecture changes in individuals with RDD.

METHODS

Here, we integrated multi-modal features from T1-weighted imaging, diffusion tensor imaging (DTI), and inhomogeneous magnetization transfer imaging (ihMT) to construct MSN. We used graph theory to calculate topological changes in MSN and explore their relationship with the severity and recurrence. The topological properties of 42 RDD patients were compared with 56 age, sex, and education-matched healthy controls.

RESULTS

RDD subjects showed significantly decreased global efficiency, increased characteristic path length, reduced nodal efficiencies in the parietal lobe, subcortical area, and temporal lobe, increased betweenness centrality in the left supplementary motor area (SMA), decreased intra-modular connections in the parietal module and decreased inter-modular connections between the parietal and prefrontal modules. Notably, the global efficiency, characteristic path length, local efficiency of the right superior parietal gyrus, and inter-modular connections between the parietal and prefrontal modules were significantly associated with the number of depressive episodes. The betweenness centrality in SMA and the intra-modular connections in the parietal module showed a positive relationship with 17-item Hamilton Rating Scale for Depression (HAMD) scores.

CONCLUSIONS

The altered topology of MSN may serve as potential underlying pathological mechanisms of RDD. The impaired information integration of the network, particularly the disconnection within the fronto-parietal network, may be associated with the recurrence of depression. The SMA and the fronto-parietal network may be related to the severity of depression.

Correlation between polygenic risk scores of depression and cortical morphology networks

BACKGROUND

Cortical morphometry is an intermediate phenotype that is closely related to the genetics and onset of major depressive disorder (MDD), and cortical morphometric networks are considered more relevant to disease mechanisms than brain regions. We sought to investigate changes in cortical morphometric networks in MDD and their relationship with genetic risk in healthy controls.

METHODS

We recruited healthy controls and patients with MDD of Han Chinese descent. Participants underwent DNA extraction and magnetic resonance imaging, including T 1-weighted and diffusion tensor imaging. We calculated polygenic risk scores (PRS) based on previous summary statistics from a genome-wide association study of the Chinese Han population. We used a novel method based on Kullback-Leibler divergence to construct the morphometric inverse divergence (MIND) network, and we included the classic morphometric similarity network (MSN) as a complementary approach. Considering the relationship between cortical and white matter networks, we also constructed a streamlined density network. We conducted group comparison and PRS correlation analyses at both the regional and network level.

RESULTS

We included 130 healthy controls and 195 patients with MDD. The results indicated enhanced connectivity in the MIND network among patients with MDD and people with high genetic risk, particularly in the somatomotor (SMN) and default mode networks (DMN). We did not observe significant findings in the MSN. The white matter network showed disruption among people with high genetic risk, also primarily in the SMN and DMN. The MIND network outperformed the MSN network in distinguishing MDD status.

LIMITATIONS

Our study was cross-sectional and could not explore the causal relationships between cortical morphological changes, white matter connectivity, and disease states. Some patients had received antidepressant treatment, which may have influenced brain morphology and white matter network structure.

CONCLUSION

The genetic mechanisms of depression may be related to white matter disintegration, which could also be associated with decoupling of the SMN and DMN. These findings provide new insights into the genetic mechanisms and potential biomarkers of MDD.

mFusion: a multiscale fusion method bridging neuroimages to genes through neurotransmissions in mental health disorders

Mental health disorders emerge from complex interactions among neurobiological processes across multiple scales, which poses challenges in uncovering pathological pathways from molecular dysfunction to neuroimaging changes. Here, we proposed a multiscale fusion (mFusion) method to evaluate the relevance of each gene to the neuroimaging traits of mental health disorders. We combined gene-neuroimaging associations with gene-positron emission tomography (PET) and PET-neuroimaging associations using protein-protein interaction networks, where various genes traced by PET maps are involved in neurotransmission. Compared with previous methods, the proposed algorithm identified more disease genes on both simulated and empirical data sets. Applying mFusion to eight mental health disorders, we found that these disorders formed three clusters with distinct associated genes. In summary, mFusion is a promising tool of prioritizing genes for mental health disorders by establishing gene-PET-neuroimaging pathways.

Development and early life stress sensitivity of the rat cortical microstructural similarity network

The rat offers a uniquely valuable animal model in neuroscience, but we currently lack an individual-level understanding of the in vivo rat brain network. Here, leveraging longitudinal measures of cortical magnetization transfer ratio (MTR) from in vivo neuroimaging between postnatal days 20 (weanling) and 290 (mid-adulthood), we design and implement a computational pipeline that captures the network of structural similarity (MIND, morphometric inverse divergence) between each of 53 distinct cortical areas. We first characterized the normative development of the network in a cohort of rats undergoing typical development (N=47), and then contrasted these findings with a cohort exposed to early life stress (ELS, N=40). MIND as a metric of cortical similarity and connectivity was validated by cortical cytoarchitectonics and axonal tract-tracing data. The normative rat MIND network had high between-study reliability and complex topological properties including a rich club. Similarity changed during post-natal and adolescent development, including a phase of fronto-hippocampal convergence, or increasing inter-areal similarity. An inverse process of increasing fronto-hippocampal dissimilarity was seen with post-adult aging. Exposure to ELS in the form of maternal separation appeared to accelerate the normative trajectory of brain development - highlighting embedding of stress in the dynamic rat brain network. Our work provides novel tools for systems-level study of the rat brain that can now be used to understand network-based underpinnings of complex lifespan behaviors and experimental manipulations that this model organism allows.

Functional Connectome Hierarchy in Schizotypy and Its Associations With Expression of Schizophrenia-Related Genes

BACKGROUND AND HYPOTHESIS

Schizotypy has been conceptualized as a continuum of symptoms with marked genetic, neurobiological, and sensory-cognitive overlaps to schizophrenia. Hierarchical organization represents a general organizing principle for both the cortical connectome supporting sensation-to-cognition continuum and gene expression variability across the cortex. However, a mapping of connectome hierarchy to schizotypy remains to be established. Importantly, the underlying changes of the cortical connectome hierarchy that mechanistically link gene expressions to schizotypy are unclear.

STUDY DESIGN

The present study applied novel connectome gradient on resting-state fMRI data from 1013 healthy young adults to investigate schizotypy-associated sensorimotor-to-transmodal connectome hierarchy and assessed its similarity with the connectome hierarchy of schizophrenia. Furthermore, normative and differential postmortem gene expression data were utilized to examine transcriptional profiles linked to schizotypy-associated connectome hierarchy.

STUDY RESULTS

We found that schizotypy was associated with a compressed functional connectome hierarchy. Moreover, the pattern of schizotypy-related hierarchy exhibited a positive correlation with the connectome hierarchy observed in schizophrenia. This pattern was closely colocated with the expression of schizophrenia-related genes, with the correlated genes being enriched in transsynaptic, receptor signaling and calcium ion binding.

CONCLUSIONS

The compressed connectome hierarchy suggests diminished functional system differentiation, providing a novel and holistic system-level basis for various sensory-cognition deficits in schizotypy. Importantly, its linkage with schizophrenia-altered hierarchy and schizophrenia-related gene expression yields new insights into the neurobiological continuum of psychosis. It also provides mechanistic insight into how gene variation may drive alterations in functional hierarchy, mediating biological vulnerability of schizotypy to schizophrenia.

Shared genetic architecture of cortical thickness alterations in major depressive disorder and schizophrenia

BACKGROUND

Major depressive disorder (MDD) and schizophrenia (SCZ) are heritable brain disorders characterized by alterations in cortical thickness. However, the shared genetic basis for cortical thickness changes in these disorders remains unclear.

METHODS

We conducted a systematic literature search on cortical thickness in MDD and SCZ through PubMed and Web of Science. A coordinate-based meta-analysis was performed to identify cortical thickness changes. Additionally, utilizing summary statistics from the largest genome-wide association studies for depression (Ncase = 268,615, Ncontrol = 667,123) and SCZ (Ncase = 53,386, Ncontrol = 77,258), we explored shared genomic loci using conjunctional false discovery rate (conjFDR) analysis. Transcriptome-neuroimaging association analysis was then employed to identify shared genes associated with cortical thickness alterations, and enrichment analysis was finally carried out to elucidate the biological significance of these genes.

RESULTS

Our search yielded 34 MDD (Ncase = 1621, Ncontrol = 1507) and 19 SCZ (Ncase = 1170, Ncontrol = 1043) neuroimaging studies for cortical thickness meta-analysis. Specific alterations in the left supplementary motor area were observed in MDD, while SCZ exhibited widespread reductions in various brain regions, particularly in the frontal and temporal areas. The conjFDR approach identified 357 genomic loci jointly associated with MDD and SCZ. Within these loci, 55 genes were found to be associated with cortical thickness alterations in both disorders. Enrichment analysis revealed their involvement in nervous system development, apoptosis, and cell communication.

CONCLUSION

This study revealed the shared genetic architecture underlying cortical thickness alterations in MDD and SCZ, providing insights into common neurobiological pathways. The identified genes and pathways may serve as potential transdiagnostic markers, informing precision medicine approaches in psychiatric care.

Age-related changes of node degree in the multiple-demand network predict fluid intelligence

Fluid intelligence is an individual's innate ability to cope with complex situations and is gradually reduced across adults aging. The realization of fluid intelligence requires the simultaneous activity of multiple brain regions and depends on the structural connection of distributed brain regions. Uncovering the structural features of brain connections associated with fluid intelligence decline will provide reference for the development of intervention and treatment programs for cognitive decline. Using structural magnetic resonance imaging data of 454 healthy participants (18-87 years) from the Cam-CAN dataset, we constructed structural similarity network for each participant and calculated the node degree. Spearman correlation analysis showed that age was positively correlated with degree centrality in the cingulate cortex, left insula and subcortical regions, while negatively correlated with that in the orbito-frontal cortex, right middle temporal and precentral regions. Partial least squares (PLS) regression showed that the first PLS components explained 32 % (second PLS component: 20 %, p perm < 0.001) of the variance in fluid intelligence. Additionally, the degree centralities of anterior insula, supplementary motor area, prefrontal, orbito-frontal and anterior cingulate cortices, which are critical nodes of the multiple-demand network (MDN), were linked to fluid intelligence. Increased degree centrality in anterior cingulate cortex and left insula partially mediated age-related decline in fluid intelligence. Collectively, these findings suggest that the structural stability of MDN might contribute to the maintenance of fluid intelligence.

Transcriptional signatures of cortical structural changes in chronic insomnia disorder

Chronic insomnia disorder (CID) is a multidimensional disease that may influence various levels of brain organization, spanning the macroscopic structural connectome to microscopic gene expression. However, the connection between genomic variations and morphological alterations in CID remains unclear. Here, we investigated brain structural changes in CID patients at the whole-brain level and whether these link to transcriptional characteristics. Brain structural data from 104 CID patients and 102 matched healthy controls (HC) were acquired to examine cortical structural alterations using morphometric similarity (MS) analysis. Partial least squares (PLS) regression and transcriptome data from the Allen Human Brain Atlas were used to extract genomes related to MS changes. Gene-category enrichment analysis (GCEA) was used to identify potential molecular mechanisms behind the observed structural changes. We found that CID patients exhibited MS reductions in the parietal and limbic regions, along with enhancements in the temporal and frontal regions compared to HCs (pFDR < .05). Subsequently, PLS and GCEA revealed that these MS alterations were spatially correlated with a set of genes, especially those significantly correlated with excitatory and inhibitory neurons and chronic neuroinflammation. This neuroimaging-transcriptomic study bridges the gap between cortical structural changes and the molecular mechanisms in CID patients, providing novel insight into the pathophysiology of insomnia and targeted treatments.

Morphometric Similarity Patterning of Amyloid-β and Tau Proteins Correlates with Transcriptomics in the Alzheimer's Disease Continuum

Bridging the gap between cortical morphometric remodeling and gene expression can help to clarify the effects of the selective brain accumulation of Amyloid-β (Aβ) and tau proteins occurring in the Alzheimer's disease (AD). To this aim, we derived morphometric similarity (MS) networks from 126 Aβ- and tau-positive (Aβ+/tau+) and 172 Aβ-/tau- subjects, and we investigated the association between group-wise regional MS differences and transcriptional correlates thanks to an imaging transcriptomics approach grounded in the Allen Human Brain Atlas (AHBA). The expressed gene with the highest correlation with MS alterations was BCHE, a gene related to Aβ homeostasis. In addition, notably, among the most promising results derived from the enrichment analysis, we found the immune response to be a biological process and astrocytes, microglia, and oligodendrocyte precursors for the cell types. In summary, by relating cortical MS and AHBA-derived transcriptomics, we were able to retrieve findings suggesting the biological mechanisms underlying the Aβ- and tau- induced cortical MS alterations in the AD continuum.

Transcriptional patterns of brain structural abnormalities in CSVD-related cognitive impairment

Background

Brain structural abnormalities have been associated with cognitive impairment in individuals with small cerebral vascular disease (CSVD). However, the molecular and cellular factors making the different brain structural regions more vulnerable to CSVD-related cognitive impairment remain largely unknown.

Materials and methods

Voxel-based morphology (VBM) was performed on the structural magnetic resonance imaging data of 46 CSVD-related cognitive impairment and 73 healthy controls to analyze and compare the gray matter volume (GMV) between the 2 groups. Transcriptome-neuroimaging spatial correlation analysis was carried out in combination with the Allen Human Brain Atlas to explore gene expression profiles associated with changes in cortical morphology in CSVD-related cognitive impairment.

Results

VBM analysis demonstrated extensive decreased GMV in CSVD-related cognitive impairment in the bilateral temporal lobe and thalamus, especially the hippocampus, thalamus, parahippocampus, and fusiform, and the left temporal lobe showed a more severe atrophy than the right temporal lobe. These brain structural alterations were closely related to memory and executive function deficits in CSVD-related cognitive impairment. Furthermore, a total of 1,580 genes were revealed to be significantly associated with regional change in GMV. The negatively and positively GMV-linked gene expression profiles were mainly enriched in RNA polymerase II, catalytic activity acting on a nucleic acid, aminoacyltransferase activity, axonogenesis, Golgi membrane, and cell junction organization.

Conclusion

Our findings suggest that brain morphological abnormalities in CSVD-related cognitive impairment are linked to molecular changes involving complex polygenic mechanisms, highlighting the interplay between genetic influences and structural alterations relevant to CSVD-related cognitive impairment.

Functional gradient dysfunction in drug-naïve first-episode schizophrenia and its correlation with specific transcriptional patterns and treatment predictions

BACKGROUND

First-episode schizophrenia (FES) is a progressive psychiatric disorder influenced by genetics, environmental factors, and brain function. The functional gradient deficits of drug-naïve FES and its relationship to gene expression profiles and treatment outcomes are unknown.

METHODS

In this study, we engaged a cohort of 116 FES and 100 healthy controls (HC), aged 7 to 30 years, including 15 FES over an 8-week antipsychotic medication regimen. Our examination focused on primary-to-transmodal alterations in voxel-based connection gradients in FES. Then, we employed network topology, Neurosynth, postmortem gene expression, and support vector regression to evaluate integration and segregation functions, meta-analytic cognitive terms, transcriptional patterns, and treatment predictions.

RESULTS

FES displayed diminished global connectome gradients (Cohen's d = 0.32-0.57) correlated with compensatory integration and segregation functions (Cohen's d = 0.31-0.36). Predominant alterations were observed in the default (67.6%) and sensorimotor (21.9%) network, related to high-order cognitive functions. Furthermore, we identified notable overlaps between partial least squares (PLS1) weighted genes and dysregulated genes in other psychiatric conditions. Genes linked with gradient alterations were enriched in synaptic signaling, neurodevelopment process, specific astrocytes, cortical layers (layer II and IV), and developmental phases from late/mid fetal to young adulthood. Additionally, the onset age influenced the severity of FES, with discernible differences in connection gradients between minor- and adult-FES. Moreover, the connectivity gradients of FES at baseline significantly predicted treatment outcomes.

CONCLUSIONS

These results offer significant theoretical foundations for elucidating the intricate interplay between macroscopic functional connection gradient changes and microscopic transcriptional patterns during the onset and progression of FES.

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.

Brain Morphometric Alterations in Focal to Bilateral Tonic-Clonic Seizures in Epilepsy Associated With Excitatory/Inhibitory Imbalance

BACKGROUND

Focal to bilateral tonic-clonic seizures (FBTCS) represent the most severe seizure type in temporal lobe epilepsy (TLE), associated with extensive network abnormalities. Nevertheless, the genetic and cellular factors predispose specific TLE patients to FBTCS remain poorly understood. This study aimed to elucidate the relationship between brain morphometric alterations and transcriptional profiles in TLE patients with FBTCS (FBTCS+) compared to those without FBTCS (FBTCS-).

METHODS

We enrolled 126 unilateral TLE patients (89 FBTCS+ and 37 FBTCS-) along with 60 age- and gender-matched healthy controls (HC). We assessed gray matter volume to identify morphometric differences between patients and HC. Partial least squares regression was employed to investigate the association between the morphometric disparities and human brain transcriptomic data obtained from the Allen Human Brain Atlas.

RESULTS

Compared with HC, FBTCS+ patients exhibited morphometric alterations in bilateral cortical and subcortical regions. Conversely, FBTCS- patients exhibited more localized alterations. Imaging transcriptomic analysis revealed both FBTCS- and FBTCS+ groups harbored genes that spatially correlated with morphometric alterations. Additionally, pathway enrichment analysis identified common pathways involved in neural development and synaptic function in both groups. The FBTCS- group displayed unique pathway enrichment in catabolic processes. Furthermore, mapping these genes to specific cell types indicated enrichment in excitatory and inhibitory neurons in the FBTCS- group, while FBTCS+ group only enriched in excitatory neurons. The distinct cellular expression differences between FBTCS- and FBTCS+ groups are consistent with the distribution patterns of GABAergic expression.

CONCLUSION

We applied imaging transcriptomic analysis linking the morphometric changes and neurobiology in TLE patients with and without FBTCS, including gene expression, biological pathways, cell types, and neurotransmitter receptors. Our findings revealed abnormalities in inhibitory neurons and altered distribution patterns of GABAergic receptors in FBTCS+, suggesting that an excitatory/inhibitory imbalance may contribute to the increased susceptibility of certain individuals to FBTCS.

Consistent genes associated with structural changes in clinical Alzheimer's disease spectrum

Background

Previous studies have demonstrated widespread brain neurodegeneration in Alzheimer's disease (AD). However, the neurobiological and pathogenic substrates underlying this structural atrophy across the AD spectrum remain largely understood.

Methods

In this study, we obtained structural MRI data from ADNI datasets, including 83 participants with early-stage cognitive impairments (EMCI), 83 with late-stage mild cognitive impairments (LMCI), 83 with AD, and 83 with normal controls (NC). Our goal was to explore structural atrophy across the full clinical AD spectrum and investigate the genetic mechanism using gene expression data from the Allen Human Brain Atlas.

Results

As a result, we identified significant volume atrophy in the left thalamus, left cerebellum, and bilateral middle frontal gyrus across the AD spectrum. These structural changes were positively associated with the expression levels of genes such as ABCA7, SORCS1, SORL1, PILRA, PFDN1, PLXNA4, TRIP4, and CD2AP, while they were negatively associated with the expression levels of genes such as CD33, PLCG2, APOE, and ECHDC3 across the clinical AD spectrum. Further gene enrichment analyses revealed that the positively associated genes were mainly involved in the positive regulation of cellular protein localization and the negative regulation of cellular component organization, whereas the negatively associated genes were mainly involved in the positive regulation of iron transport.

Conclusion

Overall, these results provide a deeper understanding of the biological mechanisms underlying structural changes in prodromal and clinical AD.

Population clustering of structural brain aging and its association with brain development

Structural brain aging has demonstrated strong inter-individual heterogeneity and mirroring patterns with brain development. However, due to the lack of large-scale longitudinal neuroimaging studies, most of the existing research focused on the cross-sectional changes of brain aging. In this investigation, we present a data-driven approach that incorporate both cross-sectional changes and longitudinal trajectories of structural brain aging and identified two brain aging patterns among 37,013 healthy participants from UK Biobank. Participants with accelerated brain aging also demonstrated accelerated biological aging, cognitive decline and increased genetic susceptibilities to major neuropsychiatric disorders. Further, by integrating longitudinal neuroimaging studies from a multi-center adolescent cohort, we validated the 'last in, first out' mirroring hypothesis and identified brain regions with manifested mirroring patterns between brain aging and brain development. Genomic analyses revealed risk loci and genes contributing to accelerated brain aging and delayed brain development, providing molecular basis for elucidating the biological mechanisms underlying brain aging and related disorders.

Different structural connectivity patterns in the subregions of the thalamus, hippocampus, and cingulate cortex between schizophrenia and psychotic bipolar disorder

OBJECTIVE

Schizophrenia (SCZ) and psychotic bipolar disorder (PBD) are two major psychotic disorders with similar symptoms and tight associations on the psychopathological level, posing a clinical challenge for their differentiation. This study aimed to investigate and compare the structural connectivity patterns of the limbic system between SCZ and PBD, and to identify specific regional disruptions associated with psychiatric symptoms.

METHODS

Using sMRI data from 146 SCZ, 160 PBD, and 145 healthy control (HC) participants, we employed a data-driven approach to segment the hippocampus, thalamus, hypothalamus, amygdala, and cingulate cortex into subregions. We then investigated the structural connectivity patterns between these subregions at the global and nodal levels. Additionally, we assessed psychotic symptoms by utilizing the subscales of the Brief Psychiatric Rating Scale (BPRS) to examine correlations between symptom severity and network metrics between groups.

RESULTS

Patients with SCZ and PBD had decreased global efficiency (Eglob) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.003), local efficiency (Eloc) (SCZ and PBD: adjusted P<0.001), and clustering coefficient (Cp) (SCZ and PBD: adjusted P<0.001), and increased path length (Lp) (SCZ: adjusted P<0.001; PBD: adjusted P = 0.004) compared to HC. Patients with SCZ showed more pronounced decreases in Eglob (adjusted P<0.001), Eloc (adjusted P<0.001), and Cp (adjusted P = 0.029), and increased Lp (adjusted P = 0.024) compared to patients with PBD. The most notable structural disruptions were observed in the hippocampus and thalamus, which correlated with different psychotic symptoms, respectively.

CONCLUSION

This study provides evidence of distinct structural connectivity disruptions in the limbic system of patients with SCZ and PBD. These findings might contribute to our understanding of the neuropathological basis for distinguishing SCZ and PBD.

The genetics of spatiotemporal variation in cortical thickness in youth

Prior studies have shown strong genetic effects on cortical thickness (CT), structural covariance, and neurodevelopmental trajectories in childhood and adolescence. However, the importance of genetic factors on the induction of spatiotemporal variation during neurodevelopment remains poorly understood. Here, we explore the genetics of maturational coupling by examining 308 MRI-derived regional CT measures in a longitudinal sample of 677 twins and family members. We find dynamic inter-regional genetic covariation in youth, with the emergence of regional subnetworks in late childhood and early adolescence. Three critical neurodevelopmental epochs in genetically-mediated maturational coupling were identified, with dramatic network strengthening near eleven years of age. These changes are associated with statistically-significant (empirical p-value <0.0001) increases in network strength as measured by average clustering coefficient and assortativity. We then identify genes from the Allen Human Brain Atlas with similar co-expression patterns to genetically-mediated structural covariation in children. This set was enriched for genes involved in potassium transport and dendrite formation. Genetically-mediated CT-CT covariance was also strongly correlated with expression patterns for genes located in cells of neuronal origin.

Cortical morphological changes and associated transcriptional signatures in post-traumatic stress disorder and psychological resilience

BACKGROUND

Individuals who have experienced severe traumatic events are estimated to have a post-traumatic stress disorder (PTSD) prevalence rate ranging from 10 to 50%, while those not affected by trauma exposure are often considered to possess psychological resilience. However, the neural mechanisms underlying the development of PTSD, especially resilience after trauma, remain unclear. This study aims to investigate changes of cortical morphometric similarity network (MSN) in PTSD and trauma-exposed healthy individuals (TEHI), as well as the associated molecular alterations in gene expression, providing potential targets for the prevention and intervention of PTSD.

METHODS

We recruited PTSD patients and TEHI who had experienced severe earthquakes, and healthy controls who had not experienced earthquakes. We identified alterations in the whole-brain MSN changes in PTSD and TEHI, and established associations between these changes and brain-wide gene expression patterns from the Allen Human Brain Atlas microarray dataset using partial least squares regression.

RESULTS

At the neuroimaging level, we found not only trauma-susceptible changes in TEHI same as those in PTSD, but also unique neurobiological alterations to counteract the deleterious impact of severe trauma. We identified 1444 and 2214 genes transcriptionally related to MSN changes in PTSD and TEHI, respectively. Functional enrichment analysis of weighted gene expression for PTSD and TEHI revealed distinct enrichments in Gene Ontology biological processes and Kyoto Encyclopedia of Genes and Genomes pathways. Furthermore, gene expression profiles of astrocytes, excitatory neurons, and microglial cells are highly related to MSN abnormalities in PTSD.

CONCLUSIONS

The formation of resilience may be by an active compensatory process of the brain. The combination of macroscopic neuroimaging changes and microscopic human brain transcriptomics could offer a more direct and in-depth understanding of the pathogenesis of PTSD and psychological resilience, shedding light on new targets for the prevention and treatment of PTSD.

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.

Long-term effects of childhood single-parent family structure on brain connectivity and psychological well-being

The high and increasing proportion of single-parent families is considered a risk factor associated with various childhood trauma experiences. Consequently, concerns have been raised regarding the potential long-term effects of the childhood single-parent family structure. In this study, we employed advanced magnetic resonance imaging technology, including morphometric similarity mapping, functional connectivity density, and network-based analysis, to investigate brain connectivity and behavioral differences among young adults who were raised in single-parent families. Our study also aimed to explore the relationship between these differences and childhood trauma experiences. The results showed that individuals who grew up in single-parent families exhibited higher levels of anxiety, depression, and harm-avoidant personality. The multimodal MRI analysis further showed differences in regional and network-based connectivity properties in the single-parent family group, including increased functional connectivity density in the left inferior parietal lobule, enhanced cortical structural connectivity between the left isthmus cingulate cortex and peri-calcarine cortex, and an increase in temporal functional connectivity. Moreover, elevated levels of anxiety and depression, along with heightened functional connectivity density in the left inferior parietal lobule and increased temporal functional connectivity, were found to be correlated with a greater number of childhood trauma experiences. Through analyzing multiple data patterns, our study provides objective neuropsychobiological evidence for the enduring impact of childhood single-parent family structure on psychiatric vulnerability in adulthood.

Abnormal structural‒functional coupling patterning in progressive supranuclear palsy is associated with diverse gradients and histological features

The anatomy of the brain supports inherent processes, fostering mental abilities and eventually facilitating adaptive behavior. Recent studies have shown that progressive supranuclear palsy (PSP) is accompanied by alterations in functional and structural networks. However, how the structure and function of PSP coordinates change is not clear, and the relationships between structural‒functional coupling (SFC) and the gradient of hierarchical structure and cellular histology remain largely unknown. Here, we use neuroimaging data from two independent cohorts and a public histological dataset to investigate the relationships among the cellular histology, hierarchical structure, and SFC of PSP patients. We find that the SFC of the entire cortex in PSP is severely disrupted, with higher coupling in the visual network (VN). Moreover, coupling differences in PSP follow a macroscopic organizational principle from unimodal to transmodal gradients. Finally, we elucidate greater laminar differentiation in VN regions sensitive to SFC changes in PSP, which is related mainly to the higher cellular density and smaller size of the internal-granular layer. In conclusion, our findings provide an interpretable framework for understanding SFC changes in PSP and provide new insights into the consistency of structural and functional changes in PSP regarding hierarchical structure and cellular histology.

Beyond the usual suspects: multi-factorial computational models in the search for neurodegenerative disease mechanisms

From Alzheimer's disease to amyotrophic lateral sclerosis, the molecular cascades underlying neurodegenerative disorders remain poorly understood. The clinical view of neurodegeneration is confounded by symptomatic heterogeneity and mixed pathology in almost every patient. While the underlying physiological alterations originate, proliferate, and propagate potentially decades before symptomatic onset, the complexity and inaccessibility of the living brain limit direct observation over a patient's lifespan. Consequently, there is a critical need for robust computational methods to support the search for causal mechanisms of neurodegeneration by distinguishing pathogenic processes from consequential alterations, and inter-individual variability from intra-individual progression. Recently, promising advances have been made by data-driven spatiotemporal modeling of the brain, based on in vivo neuroimaging and biospecimen markers. These methods include disease progression models comparing the temporal evolution of various biomarkers, causal models linking interacting biological processes, network propagation models reproducing the spatial spreading of pathology, and biophysical models spanning cellular- to network-scale phenomena. In this review, we discuss various computational approaches for integrating cross-sectional, longitudinal, and multi-modal data, primarily from large observational neuroimaging studies, to understand (i) the temporal ordering of physiological alterations, i(i) their spatial relationships to the brain's molecular and cellular architecture, (iii) mechanistic interactions between biological processes, and (iv) the macroscopic effects of microscopic factors. We consider the extents to which computational models can evaluate mechanistic hypotheses, explore applications such as improving treatment selection, and discuss how model-informed insights can lay the groundwork for a pathobiological redefinition of neurodegenerative disorders.

Transcriptional Patterns of Brain Structural Covariance Network Abnormalities Associated With Suicidal Thoughts and Behaviors in Major Depressive Disorder

BACKGROUND

Although brain structural covariance network (SCN) abnormalities have been associated with suicidal thoughts and behaviors (STBs) in individuals with major depressive disorder (MDD), previous studies have reported inconsistent findings based on small sample sizes, and underlying transcriptional patterns remain poorly understood.

METHODS

Using a multicenter magnetic resonance imaging dataset including 218 MDD patients with STBs, 230 MDD patients without STBs, and 263 healthy control participants, we established individualized SCNs based on regional morphometric measures and assessed network topological metrics using graph theoretical analysis. Machine learning methods were applied to explore and compare the diagnostic value of morphometric and topological features in identifying MDD and STBs at the individual level. Brainwide relationships between STBs-related connectomic alterations and gene expression were examined using partial least squares regression.

RESULTS

Group comparisons revealed that SCN topological deficits associated with STBs were identified in the prefrontal, anterior cingulate, and lateral temporal cortices. Combining morphometric and topological features allowed for individual-level characterization of MDD and STBs. Topological features made a greater contribution to distinguishing between patients with and without STBs. STBs-related connectomic alterations were spatially correlated with the expression of genes enriched for cellular metabolism and synaptic signaling.

CONCLUSIONS

These findings revealed robust brain structural deficits at the network level, highlighting the importance of SCN topological measures in characterizing individual suicidality and demonstrating its linkage to molecular function and cell types, providing novel insights into the neurobiological underpinnings and potential markers for prediction and prevention of suicide.

Brain markers of subtraction and multiplication skills in childhood: task-based functional connectivity and individualized structural similarity

Arithmetic, a high-order cognitive ability, show marked individual difference over development. Despite recent advancements in neuroimaging techniques have enabled the identification of brain markers for individual differences in high-order cognitive abilities, it remains largely unknown about the brain markers for arithmetic. This study used a data-driven connectome-based prediction model to identify brain markers of arithmetic skills from arithmetic-state functional connectivity and individualized structural similarity in 132 children aged 8 to 15 years. We found that both subtraction-state functional connectivity and individualized SS successfully predicted subtraction and multiplication skills but multiplication-state functional connectivity failed to predict either skill. Among the four successful prediction models, most predictive connections were located in frontal-parietal, default-mode, and secondary visual networks. Further computational lesion analyses revealed the essential structural role of frontal-parietal network in predicting subtraction and the essential functional roles of secondary visual, language, and ventral multimodal networks in predicting multiplication. Finally, a few shared nodes but largely nonoverlapping functional and structural connections were found to predict subtraction and multiplication skills. Altogether, our findings provide new insights into the brain markers of arithmetic skills in children and highlight the importance of studying different connectivity modalities and different arithmetic domains to advance our understanding of children's arithmetic skills.

Accelerated Cortical Thinning in Schizophrenia Is Associated With Rare and Common Predisposing Variation to Schizophrenia and Neurodevelopmental Disorders

BACKGROUND

Schizophrenia is a highly heritable disorder characterized by increased cortical thinning throughout the life span. Studies have reported a shared genetic basis between schizophrenia and cortical thickness. However, no genes whose expression is related to abnormal cortical thinning in schizophrenia have been identified.

METHODS

We conducted linear mixed models to estimate the rates of accelerated cortical thinning across 68 regions from the Desikan-Killiany atlas in individuals with schizophrenia compared with healthy control participants from a large longitudinal sample (ncases = 169 and ncontrols = 298, ages 16-70 years). We studied the correlation between gene expression data from the Allen Human Brain Atlas and accelerated thinning estimates across cortical regions. Finally, we explored the functional and genetic underpinnings of the genes that contribute most to accelerated thinning.

RESULTS

We found a global pattern of accelerated cortical thinning in individuals with schizophrenia compared with healthy control participants. Genes underexpressed in cortical regions that exhibit this accelerated thinning were downregulated in several psychiatric disorders and were enriched for both common and rare disrupting variation for schizophrenia and neurodevelopmental disorders. In contrast, none of these enrichments were observed for baseline cross-sectional cortical thickness differences.

CONCLUSIONS

Our findings suggest that accelerated cortical thinning, rather than cortical thickness alone, serves as an informative phenotype for neurodevelopmental disruptions in schizophrenia. We highlight the genetic and transcriptomic correlates of this accelerated cortical thinning, emphasizing the need for future longitudinal studies to elucidate the role of genetic variation and the temporal-spatial dynamics of gene expression in brain development and aging in schizophrenia.

Shared and distinct cortical morphometric alterations in five neuropsychiatric symptoms of Parkinson's disease

Neuropsychiatric symptoms (including anxiety, depression, apathy, impulse-compulsive behaviors and hallucinations) are among the most common non-motor features of Parkinson's disease. Whether these symptoms should be considered as a direct consequence of the pathophysiologic mechanisms of Parkinson's disease is controversial. Morphometric similarity network analysis and epicenter mapping approach were performed on T1-weighted images of 505 patients with Parkinson's disease and 167 age- and sex-matched healthy participants from Parkinson's Progression Markers Initiative database to reveal the commonalities and specificities of distinct neuropsychiatric symptoms. Abnormal cortical co-alteration pattern in patients with neuropsychiatric symptoms was in somatomotor, vision and frontoparietal regions, with epicenters in somatomotor regions. Apathy, impulse-compulsive behaviors and hallucinations shares structural abnormalities in somatomotor and vision regions, with epicenters in somatomotor regions. In contrast, the cortical abnormalities and epicenters of anxiety and depression were prominent in the default mode network regions. By embedding each symptom within their co-alteration space, we observed a cluster composed of apathy, impulse-compulsive behaviors and hallucinations, while anxiety and depression remained separate. Our findings indicate different structural mechanisms underlie the occurrence and progression of different neuropsychiatric symptoms. Based upon these results, we propose that apathy, impulse-compulsive behaviors and hallucinations are directly related to damage of motor circuit, while anxiety and depression may be the combination effects of primary pathophysiology of Parkinson's disease and psychosocial causes.

Voxel-based texture similarity networks reveal individual variability and correlate with biological ontologies

The human brain is organized as a complex, hierarchical network. However, the structural covariance patterns among brain regions and the underlying biological substrates of such covariance networks remain to be clarified. The present study proposed a novel individualized structural covariance network termed voxel-based texture similarity networks (vTSNs) based on 76 refined voxel-based textural features derived from structural magnetic resonance images. Validated in three independent longitudinal healthy cohorts (40, 23, and 60 healthy participants, respectively) with two common brain atlases, we found that the vTSN could robustly resolve inter-subject variability with high test-retest reliability. In contrast to the regional-based texture similarity networks (rTSNs) that calculate radiomic features based on region-of-interest information, vTSNs had higher inter- and intra-subject variability ratios and test-retest reliability in connectivity strength and network topological properties. Moreover, the Spearman correlation indicated a stronger association of the gene expression similarity network (GESN) with vTSNs than with rTSNs (vTSN: r = 0.600, rTSN: r = 0.433, z = 39.784, P < 0.001). Hierarchical clustering identified 3 vTSN subnets with differential association patterns with 13 coexpression modules, 16 neurotransmitters, 7 electrophysiology, 4 metabolism, and 2 large-scale structural and 4 functional organization maps. Moreover, these subnets had unique biological hierarchical organization from the subcortex-limbic system to the ventral neocortex and then to the dorsal neocortex. Based on 424 unrelated, qualified healthy subjects from the Human Connectome Project, we found that vTSNs could sensitively represent sex differences, especially for connections in the subcortex-limbic system and between the subcortex-limbic system and the ventral neocortex. Moreover, a multivariate variance component model revealed that vTSNs could explain a significant proportion of inter-subject behavioral variance in cognition (80.0 %) and motor functions (63.4 %). Finally, using 494 healthy adults (aged 19-80 years old) from the Southwest University Adult Lifespan Dataset, the Spearman correlation identified a significant association between aging and vTSN strength, especially within the subcortex-limbic system and between the subcortex-limbic system and the dorsal neocortex. In summary, our proposed vTSN is robust in uncovering individual variability and neurobiological brain processes, which can serve as biologically plausible measures for linking biological processes and human behavior.

Human adolescent brain similarity development is different for paralimbic versus neocortical zones

Adolescent development of human brain structural and functional networks is increasingly recognized as fundamental to emergence of typical and atypical adult cognitive and emotional proodal magnetic resonance imaging (MRI) data collected from N [Formula: see text] 300 healthy adolescents (51%; female; 14 to 26 y) each scanned repeatedly in an accelerated longitudinal design, to provide an analyzable dataset of 469 structural scans and 448 functional MRI scans. We estimated the morphometric similarity between each possible pair of 358 cortical areas on a feature vector comprising six macro- and microstructural MRI metrics, resulting in a morphometric similarity network (MSN) for each scan. Over the course of adolescence, we found that morphometric similarity increased in paralimbic cortical areas, e.g., insula and cingulate cortex, but generally decreased in neocortical areas, and these results were replicated in an independent developmental MRI cohort (N [Formula: see text] 304). Increasing hubness of paralimbic nodes in MSNs was associated with increased strength of coupling between their morphometric similarity and functional connectivity. Decreasing hubness of neocortical nodes in MSNs was associated with reduced strength of structure-function coupling and increasingly diverse functional connections in the corresponding fMRI networks. Neocortical areas became more structurally differentiated and more functionally integrative in a metabolically expensive process linked to cortical thinning and myelination, whereas paralimbic areas specialized for affective and interoceptive functions became less differentiated, as hypothetically predicted by a developmental transition from periallocortical to proisocortical organization of the cortex. Cytoarchitectonically distinct zones of the human cortex undergo distinct neurodevelopmental programs during typical adolescence.