Structural Brain Abnormalities Research Articles

Biallelic loss-of-function variants in GON4L cause microcephaly and brain structure abnormalities

We identified two homozygous truncating variants in GON4L [NM_001282860.2:c.62_63del, p.(Gln21Argfs*12) and c.5517+1G>A] in two unrelated families who presented prenatal-onset growth impairment, microcephaly, characteristic face, situs inversus, and developmental delay. The frameshift variant is predicted to invoke nonsense-mediated mRNA decay of all five known GON4L isoforms resulting in the complete loss of GON4L function. The splice site variant located at a region specific to the longer isoforms; therefore, defects of long GON4L isoforms may explain the phenotypes observed in the three patients. Knockdown of Gon4l in rat PC12 cells suppressed neurite outgrowth in vitro. gon4lb knockdown and knockout zebrafish successfully recapitulated the patients’ phenotypes including craniofacial abnormalities. We also observed situs inversus in gon4lb-knockout zebrafish embryo. To our knowledge, the relationship between craniofacial abnormalities or situs inversus and gon4lb has not been reported before. Thus, our data provide evidence that GON4L is involved in craniofacial and left-right patterning during development.

Volumetric Integrated Classification Index: An Integrated Voxel-Based Morphometry and Machine Learning Interpretable Biomarker for Post-Traumatic Stress Disorder.

PTSD is a complex mental health condition triggered by individuals' traumatic experiences, with long-term and broad impacts on sufferers' psychological health and quality of life. Despite decades of research providing partial understanding of the pathobiological aspects of PTSD, precise neurobiological markers and imaging indicators remain challenging to pinpoint. This study employed VBM analysis and machine learning algorithms to investigate structural brain changes in PTSD patients. Data were sourced ADNI-DoD database for PTSD cases and from the ADNI database for healthy controls. Various machine learning models, including SVM, RF, and LR, were utilized for classification. Additionally, the VICI was proposed to enhance model interpretability, incorporating SHAP analysis. The association between PTSD risk genes and VICI values was also explored through gene expression data analysis. Among the tested machine learning algorithms, RF emerged as the top performer, achieving high accuracy in classifying PTSD patients. Structural brain abnormalities in PTSD patients were predominantly observed in prefrontal areas compared to healthy controls. The proposed VICI demonstrated classification efficacy comparable to the optimized RF model, indicating its potential as a simplified diagnostic tool. Analysis of gene expression data revealed significant associations between PTSD risk genes and VICI values, implicating synaptic integrity and neural development regulation. This study reveals neuroimaging and genetic characteristics of PTSD, highlighting the potential of VBM analysis and machine learning models in diagnosis and prognosis. The VICI offers a promising approach to enhance model interpretability and guide clinical decision-making. These findings contribute to a better understanding of the pathophysiological mechanisms of PTSD and provide new avenues for future diagnosis and treatment.

Maternal Immune Activation and Child Brain Development: A Longitudinal Population-based Multimodal Neuroimaging study

Maternal Immune Activation (MIA) has been hypothesized to have an adverse effect on child neurodevelopment, but only a few neuroimaging studies have been performed to date, mostly in neonates. In this population-based cohort study, we investigated the association between MIA and multiple neuroimaging modalities depicting brain development from childhood to adolescence. We used data of mother-child pairs from the Generation R Study. To define our exposure, we measured IL-1β, IL-6, IL-17a, IL-23 and IFN-γ, and CRP at two time points during pregnancy. Given that levels of these 5 cytokines were highly correlated, we were able to compute a Cytokine index. We used multiple brain imaging modalities as outcomes, encompassing global and regional measures of brain morphology (structural MRI, volume, n=3,295), white matter microstructure (diffusion MRI, FA and MD, n=3,267), and functional connectivity (functional MRI, graph theory measures and network-level connectivity, n=2,914) at child mean ages 10 and 14 years. We performed mixed-effects models using the child's age as continuous time variable. We found no significant association or time interaction between MIA and any neuroimaging outcomes in children over time. These associations were similar for the Cytokine index, CRP, and individual cytokines. We observed no evidence for differential effects of timing of prenatal MIA or child sex after multiple testing correction. This longitudinal population-based study reports no evidence for an association between MIA and child brain development in the general population. Our findings differ from prior research in neonates showing structural and functional brain abnormalities after MIA.

Structural-informed functional MRI analysis of patients with empathy impairment following stroke.

The underlying functional alterations of brain structural changes among patients with empathy impairment following stroke remain unclear. We sought to investigate functional connectivity changes informed by brain structural abnormalities in multimodal magnetic resonance imaging (MRI) among patients with empathy impairment following stroke. We enrolled people who had experienced their first ischemic stroke, along with healthy controls. We assessed empathy 3 months after stroke using the Chinese version of the Empathy Quotient (EQ). During the acute phase, all patients underwent basic magnetic resonance imaging (MRI), followed by multimodal MRI during follow-up. Our MRI analyses encompassed acute infarction segmentation, volumetric brain measurements, regional quantification of diffusion parameters, and both region-of-interest-based and seed-based functional connectivity assessments. We grouped patients based on the severity of their empathy impairment for comparative analysis. We included 84 patients who had stroke and 22 healthy controls. Patients had lower EQ scores than controls. Patients with low empathy had larger left cortical infarcts (odds ratio [OR] 4.082, 95% confidence interval [CI] 1.183-14.088), more pronounced atrophy in the right cingulate cortex (OR 1.248, 95% CI 1.038-1.502), and lower scores on the Montreal Cognitive Assessment (OR 0.873, 95% CI 0.74-0.947). In addition, the cingulate cortex served as the seed in the seed-based analysis, which showed heightened functional connectivity between the anterior cingulate gyrus and the right superior parietal lobule, specifically in the low-empathy group. We did not evaluate the relationship between specific network involvement and empathy impairment among patients following stroke. Among patients with subacute ischemic stroke, reduced empathy was strongly associated with a more severe cognitive profile and atrophy of the right cingulate cortex. Our subsequent structural-informed functional MRI analysis suggests that the enhanced connectivity between the anterior cingulate gyrus and the superior parietal lobule may function as a compensatory mechanism for this atrophy.

Assessing changes in brain structure in new-onset children with acute lymphoblastic leukemia.

Brain structure injury was presented in acute lymphoblastic leukemia (ALL) after treatment; however, its alterations in new-onset stage are still unclear. We aim to explore white matter (WM) and grey matter (GM) alterations using surface-based morphometry (SBM) and tract-based spatial statistics (TBSS) in new-onset pediatric ALL. Thirty-five ALL and 33 typically developing (TD) children were prospectively recruited and underwent three-dimensional T1-weighted and diffusion tensor (DTI) imaging. DTI metrics, cortical GM features, anddeep GM nuclei volume were compared between groups differences. In ALL, the only increased FA in the body of corpus callosum (PFWE-corrected = 0.023) and left superior corona radiata (PFWE-corrected = 0.045) were presented. Relative to TDs, pediatric ALL presented a significant decrease in cortical surface area (CSA), thickness (CT), and volume in orbital gyri, supramarginal gyrus, middle temporal gyrus, and superior temporal gyrus (all CWP = 0.01). Additionally, increased CT and CSA were found in lingual gyrus and left sulcus intermedius primus, respectively (all CWP = 0.01). Smaller volumes in pediatric ALL were observed in bilateral thalamus, caudate, hippocampus, and right putamen (PFDR-corrected < 0.05). Widespread brain structural abnormalities were found in new-onset pediatric ALL, which suggest disease itself can cause brain structural injury. This study revealed the altered white matter integrity and gray matter morphology characteristics in childhood acute lymphoblastic leukemia on new-onset stage. It is suggested that there may be structural impairment before chemotherapy. MRI is a sensitive way for early detection on brain structural damage in childhood acute lymphoblastic leukemia.

Prenatal alcohol exposure and associations with physical size, dysmorphology and neurodevelopment: a systematic review and meta-analysis

BackgroundFetal alcohol spectrum disorder (FASD) is a significant public health concern, yet there is no internationally agreed set of diagnostic criteria or summary of underlying evidence to inform diagnostic decision-making. This systematic review assesses associations of prenatal alcohol exposure (PAE) and outcomes of diagnostic assessments, providing an evidence base for the improvement of FASD diagnostic criteria.MethodsSix databases were searched (inception–February 2023). Case-controls or cohort studies examining associations between participants with/without PAE or a FASD diagnosis and the domains of physical size, dysmorphology, functional neurodevelopment and/or brain structure/neurology were included. Excluded studies were non-empirical, sample size < 10, PAE determined via biological markers only, or no suitable comparison group. Summary data were extracted and associations between outcomes and standardised levels of PAE or FASD diagnosis determined using random-effects meta-analyses. Certainty of the evidence was assessed using GRADE.ResultsOf the 306 included studies, 106 reported physical size, 43 dysmorphology, 195 functional neurodevelopment and 110 structural/neurological outcomes, with 292 different outcomes examined. There was a dose–response relationship between PAE and head circumference, as well as measures of physical size, particularly at birth. There was also an association between higher PAE levels and characteristic sentinel facial dysmorphology, as well as many of the current functional neurodevelopmental outcomes considered during diagnosis. However, data were often lacking across the full range of exposures. There was a lack of evidence from studies examining PAE to support inclusion of non-sentinel dysmorphic features, social cognition, speech-sound impairments, neurological conditions, seizures, sensory processing or structural brain abnormalities (via clinical MRI) in diagnostic criteria. GRADE ratings ranged from very low to moderate certainty of evidence.ConclusionsThis comprehensive review provides guidance on which components are most useful to consider in the diagnostic criteria for FASD. It also highlights numerous gaps in the available evidence. Future well-designed pregnancy cohort studies should specifically focus on dose–response relationships between PAE and dysmorphology, neurodevelopment and brain structure/neurological outcomes.Systematic review registrationPROSPERO: CRD42021230522.

Structural and functional whole brain changes in autism spectrum disorder at different age stages.

Autism spectrum disorder (ASD) is a developmental disorder involving regional changes and local neural disturbances. However, few studies have investigated the dysfunctional phenomenon across different age stages. This study explores the structural and functional brain changes across different developmental stages in individuals with ASD, focusing on childhood (6-12 years), adolescence (12-18 years), and adulthood (18 + years). Using a comprehensive set of neuroimaging metrics, including modulated and non-modulated voxel-based morphometry (VBM), regional homogeneity (ReHo), amplitude of low-frequency fluctuation (ALFF), and fractional ALFF (fALFF), we identified significant stage-specific alterations in both VBM and functional measurements. Our results reveal that ASD is associated with progressive and stage-specific abnormalities in brain structure and function, with distinct patterns emerging at each developmental stage. Specifically, we observed significant modulated VBM reductions in the precuneus, lentiform nucleus, and inferior parietal lobule, accompanied by increases in the midbrain and sub-gyral regions. Moreover, we observed unmodulated VBM increment in regions including lentiform nucleus and thalamus. Functionally, ReHo analyses demonstrated disrupted local synchronization in the medial frontal gyrus, while ALFF and fALFF metrics highlighted altered spontaneous brain activity in the sub-gyral and sub-lobar. Finally, correlation analyses revealed that stage-specific findings are closely linked to clinical social- and behavior-related scores, with VBM in the inferior parietal lobule and putamen as well as ReHo in supplemental motor area being significantly associated with restrictive repetitive behaviors in childhood. These findings underscore the importance of considering age-specific brain changes when studying ASD and suggest that targeted interventions may be necessary at different developmental stages.

Identification of multimodal brain imaging biomarkers in first-episode drugs-naive major depressive disorder through a multi-site large-scale MRI consortium data

BackgroundMajor depressive disorder (MDD) is a severe and common mental illness. The first-episode drugs-naive MDD (FEDN-MDD) patients, who have not undergone medication intervention, contribute to understanding the biological basis of MDD. Multimodal Magnetic Resonance Imaging can provide a comprehensive understanding of brain functional and structural abnormalities in MDD. However, most MDD studies use single-modal, small-scale MRI data. And several multimodal studies of MDD are limited to simple linear combinations of functional and structural features. MethodsWe screened a large sample of FEDN-MDD patients and healthy controlsmultimodal MRI data. Extracting the fractional amplitude of low-frequency fluctuations (fALFF) feature from functional magnetic resonance imaging and the gray matter volume (GMV) feature from structural magnetic resonance imaging. The mCCA-jICA method was used to integrate these two modal features to investigate the functional-structural co-variation abnormalities in MDD. To validate the stability of the extracted functional-structural covariant abnormalities features, we apply them to identify FEDN-MDD patients. ResultsThe results show that compared to healthy controls, FEDN-MDD patients exhibit joint group-discriminative independent component and modality-specific group-discriminative independent component, suggesting functional-structural covariant abnormalities in MDD patients. Using lightGBM classifier, we achieve a classification accuracy of 99.84 %. LimitationWe use GMV and fALFF for multimodal fusion shows promise, but requires further validation with other datasets and exploration of additional multimodal features. ConclusionsThis may indicate that multimodal fusion features can effectively explore information between different modalities and can accurately identify FEDN-MDD patients, suggesting their potential as multimodal brain imaging biomarkers for MDD.

Altered cortical functional networks in Wilson's Disease: A resting-state electroencephalogram study

The neuropsychiatric symptoms are common in Wilson's disease (WD) patients. However, it remains unclear about the associated functional brain networks. In this study, source localization-based functional connectivity analysis of close-eye resting-state electroencephalography (EEG) were implemented to assess the characteristics of functional networks in 17 WD patients with neurological involvements and 17 healthy controls (HCs). The weighted phase-lag index (wPLI) was subsequently calculated in source space across five different frequency bands and the resulting connectivity matrix was transformed into a weighted graph whose structure was measured by five graphical analysis indicators, which were finally correlated with clinical scores. Compared to HCs, WD patients revealed disconnected sub-networks in delta, theta and alpha bands. Moreover, WD patients exhibited significantly reduced global clustering coefficients and small-worldness in all five frequency bands. In WD group, the severity of neurological symptoms and structural brain abnormalities were significantly correlated with disrupted functional networks. In conclusion, our study demonstrated that functional network deficits in WD can reflect the severity of their neurological symptoms and structural brain abnormalities. Resting-state EEG may be used as a marker of brain injury in WD.

Macrostructural Brain Abnormalities in Spinal Muscular Atrophy: A Case-Control Study.

Most individuals with spinal muscular atrophy (SMA) on disease-modifying therapies continue to have chronic motor impairment. Insights into brain involvement in SMA may open new pathways for adjunctive therapies to optimize outcomes. We aimed to characterize macrostructural brain abnormalities detected by MRI in individuals with SMA compared with peer controls. We conducted a cross-sectional case-control study of children and adults with a confirmed genetic diagnosis of 5q SMA, and peer controls matched by age and sex. Brain MRIs acquired on a 3T MRI scanner through a standardized research protocol were reviewed to qualitatively assess the presence of macrostructural changes. The primary outcome was the presence of any structural brain anomaly on MRI. In addition, the total volume of each participant's lateral ventricles was quantified by volumetry using MRIcron. Genetic and clinical variables, including SMN2 copy number and motor function (Hammersmith Functional Motor Scale Expanded and Revised Upper Limb Module scores), were then correlated with neuroimaging findings. A total of 42 participants completed the study (mean age 17.4, range 7-40; 67% male). Of the 21 individuals with 5q SMA, 9 (43%) had macrostructural brain abnormalities identified on MRI compared with 2 of 21 (10%) peer controls (odds ratio 7.1, 95% confidence interval 1.4-34.0). In patients with SMA, the most common structural changes were widening of the arachnoid spaces (n = 4) and ventriculomegaly (n = 4). Individuals with SMA had larger median lateral ventricular volume than their normally developing peers (9.3 mL, interquartile range [IQR] 5.5-13.1 vs 5.3 mL, IQR 3.8-9.8; p = 0.034). Structural brain abnormalities were more frequent in those with 2 SMN2 copies (3/5, 60%) compared with 3 or 4 SMN2 copies (4/10, 40% and 2/6, 33% respectively), not reaching significance. We found no association between structural changes and motor function scores. Individuals with SMA have higher rates of macrostructural brain abnormalities than their neurotypical peers, suggesting CNS involvement in SMA. Understanding changes in the brain architecture of the SMA population can inform the development of adjunct therapies targeting the CNS and potentially guide rehabilitation strategies.

Unveiling the interplay of MAPK/NF-κB/MLKL axis in brain health: Omega-3 as a promising candidates against copper neurotoxicity

Excessive intake of copper (Cu) may lead to increased inflammatory responses in brain, which can cause damage to neurons and glial cells, thereby affecting normal brain function. Omega-3 (ω-3) is a common dietary supplement, particularly rich in DHA in the brain, known for its anti-inflammatory properties and its role in lipid balance regulation and structural maintenance. Here, ω-3 is supplemented to Cu-exposed chickens to assess its neuroprotection in vivo and in vitro. Pathologically, ω-3 significantly alleviated structural and functional abnormalities in brain under excess Cu, including barrier disruption, neuronal shrinkage necroptosis and increased release of inflammatory factors such as IL-1β. The molecular docking analyses unveiled high enrichment values of inflammation and MAPK pathway, with IL-1β gene enrichment the highest value. Mechanistically, DHA stabilized the active site of IL-1β, thereby reducing the activation of NF-κB signal and phosphorylation of MAPK/MLKL cascades, ultimately mitigating Cu-induced inflammatory effects. These mechanisms elucidate the action mode of Cu neurotoxicity from aspect of MAPK/NF-κB/MLKL axis and the promising neuroprotection of ω-3.

Structural and functional brain markers of cognitive impairment in healthcare workers following mild SARS-CoV-2 infection during the original stream.

Severe acute respiratory syndrome coronavirus 2 infection often involves the nervous system, leading to cognitive dysfunctions, fatigue and many other neurological signs that are becoming increasingly recognized. Despite mild forms of the disease accounting for most cases worldwide, research on the pathophysiology driving mild coronavirus disease 2019 (COVID-19) has received little attention. In this respect, recent evidence has pointed out that around 30-40% of non-critical, mild-to-moderate severity COVID-19 survivors may display cognitive disturbances several months post-illness. Hence, the impact of COVID-19 on the brain structure and function, through potential neuropathological mechanisms underpinning cognitive alterations in post-mild COVID-19 infections, remains largely unexplored. This retrospective multicentre observational cohort study, entirely based on a healthcare worker sample (n = 65; 55% females, aged 21-61), investigated the cognitive status and the structural and functional brain integrity among non-hospitalized individuals who developed mild COVID-19 symptoms during the occurrence of severe acute respiratory syndrome coronavirus 2 variants Alpha to Delta, compared with healthy controls tested before the pandemic onset. All evaluations were performed at an average of 9-month follow-up post-infection period. Participants completed a comprehensive neuropsychological assessment and structural and functional MRI exams. Radiological inspection sought to detect the presence of white matter hyperintensities on axial fluid-attenuated inversion recovery images. Global and regional grey matter integrity assessment, analysing changes in grey matter volumes and cortical thinning, and functional connectivity alterations of resting-state brain networks were also conducted. Regression analyses tested the relationships between the presence of specific cognitive impairments and potential structural and functional brain findings. Our results revealed that clinical, cognitive screening and neuropsychological examinations were average between both groups, except for specific impairments related to executive functions in the mild COVID-19. Compared to healthy controls, mild COVID-19 subjects exhibited increased juxtacortical white matter hyperintensities, thalamic and occipital volume loss and diminished resting-state functional connectivity involving the left precuneus and cuneus in default-mode network and affecting the right angular gyrus and left precuneus in the dorsal attentional network. Reduced thalamic volume was the only variable selected in the final model explaining the observed executive function impairment in mild COVID-19. The presence of cognitive, structural and functional brain abnormalities over time suggests that the action of widespread neurovascular and inflammatory phenomena on the nervous system might also occur in mild forms following COVID-19 infection rather than permanent brain damage linked to the direct or indirect action of the virus. Our findings emphasize the need to pay attention to the long-term brain-related consequences of mild COVID-19 infections during the original stream.

Atrophy in the supramarginal gyrus associated with impaired cognitive inhibition in grieving Chinese Shidu parents

ABSTRACT Background: The loss of an only child, known as Shidu in China, is a profoundly distressing experience, often leading to Prolonged Grief Disorder (PGD). Despite its impact, the structural brain alterations associated with PGD, potentially influencing cognitive impairments in Shidu parents, remain understudied. Objective: This study aims to identify brain structural abnormalities related to prolonged grief and their relation with cognitive inhibition in Shidu parents. Methods: The study included 40 Shidu parents and 42 non-bereaved participants. Prolonged grief was evaluated using the Prolonged Grief Questionnaire (PG-13). We employed voxel-based morphometry (VBM) and diffusion tensor imaging (DTI) to assess brain structural alterations and their correlation with cognitive inhibition, as measured by Stroop interference scores. Results: Findings suggest that greater prolonged grief intensity correlates with reduced grey matter volume in the right amygdala and the left supramarginal gyrus (SMG). Additionally, enhanced amygdala-to-whole-brain structural connectivity showed a marginal association with prolonged grief, particularly with emotional-related symptoms. Furthermore, a decrease in SMG volume was found to mediate the relation between prolonged grief and Stroop Time Inference (TI) score, indicating an indirect effect of prolonged grief on cognitive inhibition. Conclusions: The study provides insight into the neural correlates of prolonged grief in Shidu parents, highlighting the SMG’s role in cognitive inhibition. These findings emphasise the need for comprehensive grief interventions to address the complex cognitive and emotional challenges faced by this unique bereaved population.

Depression, brain structure and socioeconomic status: A UK Biobank study

BackgroundDepression results from interactions between biological, social, and psychological factors. Literature shows that depression is associated with abnormal brain structure, and that socioeconomic status (SES) is associated with depression and brain structure. However, limited research considers the interaction between each of these factors. MethodsMultivariate regression analysis was conducted using UK Biobank data on 39,995 participants to examine the relationship between depression and brain volume in 23 cortical regions for the whole sample and then separated by sex. It then examined whether SES affected this relationship. ResultsEight out of 23 brain areas had significant negative associations with depression in the whole population. However, these relationships were abolished in seven areas when SES was included in the analysis. For females, three regions had significant negative associations with depression when SES was not included, but only one when it was. For males, lower volume in six regions was significantly associated with higher depression without SES, but this relationship was abolished in four regions when SES was included. The precentral gyrus was robustly associated with depression across all analyses. LimitationsParticipants with conditions that could affect the brain were not excluded. UK Biobank is not representative of the general population which may limit generalisability. SES was made up of education and income which were not considered separately. ConclusionsSES affects the relationship between depression and cortical brain volume. Health practitioners and researchers should consider this when working with imaging data in these populations.

Structural brain characteristics of epilepsy patients with comorbid migraine without aura

Migraine is a common bi-directional comorbidity of epilepsy, indicating potential complex interactions between the two conditions. However, no previous studies have used brain morphology analysis to assess possible interactions between epilepsy and migraine. Voxel-based morphometry (VBM), surface-based morphometry (SBM), and structural covariance networks (SCNs) can be used to detect morphological changes with high accuracy. We recruited 30 individuals with epilepsy and comorbid migraine without aura (EM), along with 20 healthy controls (HC) and 30 epilepsy controls (EC) without migraine. We used VBM, SBM, and SCN analysis to compare differences in gray matter volume, cortical thickness, and global level and local level graph theory indexes between the EM, EC, and HC groups to investigate structural brain changes in the EM patients. VBM analysis showed that the EM group had gray matter atrophy in the right temporal pole compared with the HC group (p < 0.001, false discovery rate correction [FDR]). Furthermore, the headache duration in the EM group was negatively correlated with the gray matter volume of the right temporal pole (p < 0.05). SBM analysis showed cortical atrophy in the left insula, left posterior cingulate gyrus, left postcentral gyrus, left middle temporal gyrus, and left fusiform gyrus in the EM compared with the HC group (p < 0.001, family wise error correction). We found a positive correlation between headache frequency and the cortical thickness of the left middle temporal gyrus (p < 0.05). SCN analysis revealed no differences in global parameters between the three groups. The area under the curve (AUC) of the nodal betweenness centrality in the right postcentral gyrus was lower in the EM group compared with the HC group (p < 0.001, FDR correction), and the AUC of the nodal degree in the right fusiform gyrus was lower in the EM group compared with the EC group (p < 0.001, FDR correction). We found clear differences in brain structure in the EM patients compared with the HC group. Accordingly, migraine episodes may influence brain structure in epilepsy patients. Conversely, abnormal brain structure may be an important factor in the development of epilepsy with comorbid migraine without aura. Further studies are needed to investigate the role of brain structure in individuals with epilepsy and comorbid migraine without aura.

Quantitative assessment of brain structural abnormalities in children with autism spectrum disorder based on artificial intelligence automatic brain segmentation technology and machine learning methods

Rationale and objectivesTo explore the characteristics of brain structure in Chinese children with autism spectrum disorder (ASD) using artificial intelligence automatic brain segmentation technique, and to diagnose children with ASD using machine learning (ML) methods in combination with structural magnetic resonance imaging (sMRI) features. MethodsA total of 60 ASD children and 48 age- and sex-matched typically developing (TD) children were prospectively enrolled from January 2023 to April 2024. All subjects were scanned using 3D-T1 sequences. Automated brain segmentation techniques were utilized to obtain the standardized volume of each brain structure (the ratio of the absolute volume of brain structure to the whole brain volume). The standardized volumes of each brain structure in the two groups were statistically compared, and the volume data of brain areas with significant differences were combined with ML methods to diagnose and predict ASD patients. ResultsCompared with the TD group, the volumes of the right lateral orbitofrontal cortex, right medial orbitofrontal cortex, right pars opercularis, right pars triangularis, left hippocampus, bilateral parahippocampal gyrus, left fusiform gyrus, right superior temporal gyrus, bilateral insula, bilateral inferior parietal cortex, right precuneus cortex, bilateral putamen, left pallidum, and right thalamus were significantly increased in the ASD group (P< 0.05). Among six ML algorithms, support vector machine (SVM) and adaboost (AB) had better performance in differentiating subjects with ASD from those TD children, with their average area under curve (AUC) reaching 0.91 and 0.92, respectively. ConclusionAutomatic brain segmentation technology based on artificial intelligence can rapidly and directly measure and display the volume of brain structures in children with autism spectrum disorder and typically developing children. Children with ASD show abnormalities in multiple brain structures, and when paired with sMRI features, ML algorithms perform well in the diagnosis of ASD.

Complex gut–brain interactions underlying inflammatory bowel disease-related depression have translational implications in regenerative medicine: a narrative review

Inflammatory bowel diseases, including Crohn’s disease and ulcerative colitis, are chronic gastrointestinal disorders characterized by relapsing intestinal inflammation. In addition to gastrointestinal symptoms, patients with inflammatory bowel diseases experience a disproportionately high prevalence of depression and other neuropsychiatric comorbidities. The gut–brain axis, a bidirectional communication system between the gut and brain, has emerged as a potential pathogenic link underlying this aberrant mind–gut interplay. This review synthesizes the growing evidence implicating gut–brain axis dysregulation as a central mechanism bridging intestinal inflammation and the development of depression in patients with inflammatory bowel diseases. Regenerative medicine offers promising new avenues for addressing these complex conditions. By focusing on regenerative therapies that target the gut–brain axis, we explore new approaches that could repair or restore normal function in both the gut and brain. These therapies might alleviate chronic intestinal inflammation and restore proper gut–brain signaling via neural, immune-mediated, endocrine, and microbiome-related pathways, ultimately reversing the neurochemical, structural, and functional brain abnormalities implicated in depressive neuropathology. Unraveling the complex gut–brain interactions underlying inflammatory bowel disease-related depression through regenerative medicine has profound translational implications, paving the way for transformative diagnostic and therapeutic paradigms that address the multisystemic burden of these chronic debilitating conditions holistically.

Covariation of Skull and Brain Morphology in Domestic Dogs.

Despite their distinct embryonic origins, the skull and brain are highly integrated. Understanding the covariation between the skull and brain can shed light on anatomical, cognitive, and behavioral traits in extant and extinct species. Domestic dogs offer a unique opportunity to investigate skull-brain covariation due to their diverse skull morphologies and neural anatomy. To assess this question, we examined T2-weighted MRI studies of 62 dogs from 33 breeds, plus an additional 17 dogs of mixed or unknown breeds. Scans were opportunistically collected from a veterinary teaching hospital of dogs that were referred for neurological examination but did not have grossly observable structural brain abnormalities. As the neurocrania of dogs become broader and shorter, there is a significant decrease in the gray matter volume of the right olfactory bulb, frontal cortex, marginal gyrus, and cerebellum. On the other hand, as the neurocrania of dogs become narrower and longer, there is a significant decrease in the gray matter volume of the olfactory bulb, frontal cortex, temporal cortex, amygdala, hypothalamus, hippocampus, periaqueductal gray, cerebellum, and brainstem. Selective breeding for specific skull shapes may impact canine brain anatomy and function.

Altered structural node of default mode network mediated general cognitive ability in young adults with obesity

BackgroundObesity, characterized by excessive adiposity, is associated with brain structural abnormalities. Nevertheless, the relationships between altered structural nodes of default mode network (DMN), body mass index (BMI), general cognitive ability remained unclear in young adults. MethodsIn this study, we divided a large sample of young adults into three BMI-based groups. We then conducted one-way analyses of variance and post-hoc tests with Bonferroni corrections to investigate abnormal structural brain regions associated with obesity. Furthermore, mediation effects models were built to explore whether the structural alterations influenced the relationship between BMI and general cognitive ability. ResultsCompared to their lean and overweight counterparts, young adults with obesity exhibited significantly lower general cognitive ability, higher impulsivity traits, and worse sleep quality. Furthermore, compared with lean group, young adults with obesity exhibited altered cortical thickness of both the left temporal pole and right superior parietal lobule, and abnormal cortical surface area (CSA) of the left entorhinal cortex (EC), a hub within DMN. Moreover, CSA of the left EC mediated the relationship between BMI and general cognitive ability. ConclusionObesity was linked to altered structural node of DMN, which mediated general cognitive ability in young adults. These findings indicated the negative effect of obesity on DMN and general cognitive ability in young adults.

Schizophrenia and Neurodevelopment: Insights From Connectome Perspective.

Schizophrenia is conceptualized as a brain connectome disorder that can emerge as early as late childhood and adolescence. However, the underlying neurodevelopmental basis remains unclear. Recent interest has grown in children and adolescent patients who experience symptom onset during critical brain development periods. Inspired by advanced methodological theories and large patient cohorts, Chinese researchers have made significant original contributions to understanding altered brain connectome development in early-onset schizophrenia (EOS). We conducted a search of PubMed and Web of Science for studies on brain connectomes in schizophrenia and neurodevelopment. In this selective review, we first address the latest theories of brain structural and functional development. Subsequently, we synthesize Chinese findings regarding mechanisms of brain structural and functional abnormalities in EOS. Finally, we highlight several pivotal challenges and issues in this field. Typical neurodevelopment follows a trajectory characterized by gray matter volume pruning, enhanced structural and functional connectivity, improved structural connectome efficiency, and differentiated modules in the functional connectome during late childhood and adolescence. Conversely, EOS deviates with excessive gray matter volume decline, cortical thinning, reduced information processing efficiency in the structural brain network, and dysregulated maturation of the functional brain network. Additionally, common functional connectome disruptions of default mode regions were found in early- and adult-onset patients. Chinese research on brain connectomes of EOS provides crucial evidence for understanding pathological mechanisms. Further studies, utilizing standardized analyses based on large-sample multicenter datasets, have the potential to offer objective markers for early intervention and disease treatment.