Selective disrupted gray matter volume covariance of amygdala subregions in schizophrenia.

Objective: Although extensive structural and functional abnormalities have been reported in schizophrenia, the gray matter volume (GMV) covariance of the amygdala remain unknown. The amygdala contains several subregions with different connection patterns and functions, but it is unclear whether the GMV covariance of these subregions are selectively affected in schizophrenia. Methods: To address this issue, we compared the GMV covariance of each amygdala subregion between 807 schizophrenia patients and 845 healthy controls from 11 centers. The amygdala was segmented into nine subregions using FreeSurfer (v7.1.1), including the lateral (La), basal (Ba), accessory-basal (AB), anterior-amygdaloid-area (AAA), central (Ce), medial (Me), cortical (Co), corticoamygdaloid-transition (CAT), and paralaminar (PL) nucleus. We developed an operational combat harmonization model for 11 centers, subsequently employing a voxel-wise general linear model to investigate the differences in GMV covariance between schizophrenia patients and healthy controls across these subregions and the entire brain, while adjusting for age, sex and TIV. Results: Our findings revealed that five amygdala subregions of schizophrenia patients, including bilateral AAA, CAT, and right Ba, demonstrated significantly increased GMV covariance with the hippocampus, striatum, orbitofrontal cortex, and so on (permutation test, P< 0.05, corrected). These findings could be replicated in most centers. Rigorous correlation analysis failed to identify relationships between the altered GMV covariance with positive and negative symptom scale, duration of illness, and antipsychotic medication measure. Conclusion: Our research is the first to discover selectively impaired GMV covariance patterns of amygdala subregion in a large multicenter sample size of patients with schizophrenia.

Identification of a novel nonsense ATP2A2 gene variant in a patient with Darier's disease flare following COVID-19 infection: A case report.

RATIONALE: Darier disease (DD) is a rare autosomal dominant disorder that primarily manifests as hyperkeratotic papules and itching. The underlying etiology of DD is pathogenic variation in the ATP2A2 gene. However, this disease has a high penetrance but variable expressivity, indicating that patients inheriting the genotype may have different manifestations due to exogenous factors. Meanwhile, a few reports have documented that COVID-19 may be implicated in the flare of DD. PATIENT CONCERNS: A 51-year-old man presented with keratotic papules and scaly erythematous rash on his trunk with pruritus after being infected with COVID-19. Laboratory test results were normal. Histological analysis revealed epidermal hyperkeratosis and intraepidermal lacunae containing dyskeratinized cells. Genetic analysis revealed a novel variant of ATP2A2 (c.815G>A, p.Trp272*), which was considered pathogenic in this case. DIAGNOSES: The patient was diagnosed as having DD. INTERVENTIONS: Oral acitretin and topical corticosteroid hormone ointments were used. OUTCOMES: The patient achieved complete resolution of symptoms during the 3-month follow-up period. LESSONS: We revealed the first novel ATP2A2 variant (c.815G>A, p.Trp272*) in the flare of DD following COVID-19 infection. Additionally, this pathogenic variant enriches the ATP2A2 gene mutation spectrum.

Identification of a novel TSC1 gene variant in a patient with atypical vitiligo-like skin lesions: Unveiling the hidden tuberous sclerosis complex.

BACKGROUND: Tuberous sclerosis complex (TSC), an autosomal-dominant disorder, is characterized by hamartomas affecting multiple organ systems. The underlying etiology of TSC is the pathogenic variations of the TSC1 or TSC2 genes. The phenotype variability of TSC could lead to missed diagnosis; therefore, the latest molecular diagnostic criteria for identifying a heterozygous pathogenic variant in either the TSC1 or TSC2 gene filled this gap. Furthermore, the pathogenicity of numerous variants remains unverified, potentially leading to misinterpretations of their functional consequences. METHODS: In this study, a single patient presenting with atypical vitiligo-like skin lesions suspected to have TSC was enrolled. Targeted next-generation sequencing and Sanger sequencing were employed to identify a pathogenic variant. Additionally, a minigene splicing assay was conducted to assess the impact of TSC1 c.1030-2A>T, located in intron 10, on RNA splicing. RESULTS: A novel TSC1: c.1030-2A>T heterozygosis variant was identified in intron 10. In vitro minigene assay revealed that the c.1030-2A>T variant caused exon 11 skipping, resulting in a frameshift in the absence of 112 base pairs of mature messenger RNA and premature termination after 174 base pairs (p.Ala344Glnfs*59). CONCLUSION: The detection of this novel pathogenic TSC1 variant in the patient with atypical vitiligo-like skin lesions enrolled in our study ultimately resulted in the diagnosis of TSC. As a result, our study contributes to expanding the mutational spectrum of the TSC1 gene and refining the genotype-phenotype map of TSC.

Identification of novel KRT5 gene variants in two Chinese patients with sporadic form of epidermolysis bullosa simplex: A case report.

Epidermolysis bullosa simplex (EBS), a rare genetic disorder characterized by fragile skin that is prone to blistering and tearing, is primarily caused by mutations in genes encoding keratin proteins, such as KRT5 and KRT14. This study aimed to identify the pathogenic gene variants responsible for the sporadic form of EBS in two Chinese patients. Blood samples were collected from patients and their parents, and next-generation sequencing (NGS) was performed for variant screening. Two novel gene variants were identified within the KRT5 gene: c.1399A>T (p.Ile467Phe) in patient 1 and c.1412G>A (p.Arg471His) in patient 2. These variants were absent in the unaffected parents and a control group of 100 healthy individuals. These two novel gene variants within the KRT5 gene may be responsible for EBS, thus improving understanding of the genetic basis of EBS.

Individualized Texture Similarity Network in Schizophrenia.

BACKGROUND: Structural covariance network disruption has been considered an important pathophysiological indicator for schizophrenia. Here, we introduced a novel individualized structural covariance network measure, referred to as a texture similarity network (TSN), and hypothesized that the TSN could reliably reveal unique intersubject heterogeneity and complex dysconnectivity patterns in schizophrenia. METHODS: The TSN was constructed by measuring the covariance of 180 three-dimensional voxelwise gray-level co-occurrence matrix feature maps between brain areas in each participant. We first tested the validity and reproducibility of the TSN in characterizing the intersubject variability in 2 longitudinal test-retest healthy cohorts. The TSN was further applied to elucidate intersubject variability and dysconnectivity patterns in 10 schizophrenia case-control datasets (609 schizophrenia cases vs. 579 controls) as well as in a first-episode depression dataset (69 patients with depression vs. 69 control participants). RESULTS: The test-retest analysis demonstrated higher TSN intersubject than intrasubject variability. Moreover, the TSN reliably revealed higher intersubject variability in both chronic and first-episode schizophrenia, but not in depression. The TSN also reproducibly detected coexistent increased and decreased TSN strength in widespread brain areas, increased global small-worldness, and the coexistence of both structural hyposynchronization in the central networks and hypersynchronization in peripheral networks in patients with schizophrenia but not in patients with depression. Finally, aberrant intersubject variability and covariance strength patterns revealed by the TSN showed a missing or weak correlation with other individualized structural covariance network measures, functional connectivity, and regional volume changes. CONCLUSIONS: These findings support the reliability of a TSN in revealing unique structural heterogeneity and complex dysconnectivity in patients with schizophrenia.

Metallic artifacts-free spectral computed tomography angiography based on renal clearable bismuth chelate.

Computed tomography angiography (CTA) is one of the most important diagnosis techniques for various vascular diseases in clinic. However, metallic artifacts caused by metal implants and calcified plaques in more and more patients severely hinder its wide applications. Herein, we propose an improved metallic artifacts-free spectral CTA technique based on renal clearable bismuth chelate (Bi-DTPA dimeglumine) for the first time. Bi-DTPA dimeglumine owns the merits of ultra-simple synthetic process, approximately 100% of yield, large-scale production capability, good biocompatibility, and favorable renal clearable ability. More importantly, Bi-DTPA dimeglumine shows superior contrast-enhanced effect in CTA compared with clinical iohexol at a wide range of X-ray energies especially in higher X-ray energy. In rabbits' model with metallic transplants, Bi-DTPA dimeglumine assisted-spectral CTA can not only effectively mitigate metallic artifacts by reducing beam hardening effect under high X-ray energy, but also enables accurate delineation of vascular structure. Our proposed strategy opens a revolutionary way to solve the bottleneck problem of metallic artifacts in CTA examinations.

A neuroimaging biomarker for Individual Brain-Related Abnormalities In Neurodegeneration (IBRAIN): a cross-sectional study.

Background: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder that poses a worldwide public health challenge. A neuroimaging biomarker would significantly improve early diagnosis and intervention, ultimately enhancing the quality of life for affected individuals and reducing the burden on healthcare systems. Methods: Cross-sectional and longitudinal data (10,099 participants with 13,380 scans) from 12 independent datasets were used in the present study (this study was performed between September 1, 2021 and February 15, 2023). The Individual Brain-Related Abnormalities In Neurodegeneration (IBRAIN) score was developed via integrated regional- and network-based measures under an ensemble machine learning model based on structural MRI data. We systematically assessed whether IBRAIN could be a neuroimaging biomarker for AD. Findings: IBRAIN accurately differentiated individuals with AD from NCs (AUC = 0.92) and other neurodegenerative diseases, including Frontotemporal dementia (FTD), Parkinson's disease (PD), Vascular dementia (VaD) and Amyotrophic Lateral Sclerosis (ALS) (AUC = 0.92). IBRAIN was significantly correlated to clinical measures and gene expression, enriched in immune process and protein metabolism. The IBRAIN score exhibited a significant ability to reveal the distinct progression of prodromal AD (i.e., Mild cognitive impairment, MCI) (Hazard Ratio (HR) = 6.52 [95% CI: 4.42∼9.62], p < 1 × 10-16), which offers similar powerful performance with Cerebrospinal Fluid (CSF) Aß (HR = 3.78 [95% CI: 2.63∼5.43], p = 2.13 × 10-14) and CSF Tau (HR = 3.77 [95% CI: 2.64∼5.39], p = 9.53 × 10-15) based on the COX and Log-rank test. Notably, the IBRAIN shows comparable sensitivity (beta = -0.70, p < 1 × 10-16) in capturing longitudinal changes in individuals with conversion to AD than CSF Aß (beta = -0.26, p = 4.40 × 10-9) and CSF Tau (beta = 0.12, p = 1.02 × 10-5). Interpretation: Our findings suggested that IBRAIN is a biologically relevant, specific, and sensitive neuroimaging biomarker that can serve as a clinical measure to uncover prodromal AD progression. It has strong potential for application in future clinical practice and treatment trials. Funding: Science and Technology Innovation 2030 Major Projects, the National Natural Science Foundation of China, Beijing Natural Science Funds, the Fundamental Research Funds for the CentralUniversity, and the Startup Funds for Talents at Beijing Normal University.

Non-invasive Diagnosis and Postoperative Evaluation of Carotid Artery Stenosis by BSA-Gd2O3 Nanoparticles-Based Magnetic Resonance Angiography.

Contrast-enhanced magnetic resonance angiography is a powerful and effective method to accurately diagnose carotid artery stenosis. Small molecular gadolinium (Gd)-based agents have reliable signal enhancement, but their short circulating time may result in a loss of image resolution due to insufficient vascular filling or contrast agent emptying. Here, we report an MRA imaging approach to diagnose carotid artery stenosis using long-circulating bovine serum albumin (BSA)-Gd2O3 nanoparticles (NPs). The BSA-Gd2O3 NPs synthesized by a simple biomineralization approach exhibit admirable monodispersity, uniform size, favorable aqueous solubility, good biocompatibility, and high relaxivity (14.86 mM-1 s-1 in water, 6.41 mM-1 s-1 in plasma). In vivo MRA imaging shows that outstanding vascular enhancement of BSA-Gd2O3 NPs (0.05 mmol Gd/kg, half the dose in the clinic) can be maintained for at least 2 h, much longer than Gd-DTPA. Vessels as small as 0.3 mm can be clearly observed in MRA images with high resolution. In a rat carotid artery stenosis model, the BSA-Gd2O3 NPs-based MRA enables the precise diagnosis of the severity and location and the therapeutic effect following the surgery of carotid artery stenosis, which provides a method for the theranostics of vascular diseases.

Genome-wide association study of hippocampal blood-oxygen-level-dependent-cerebral blood flow correlation in Chinese Han population.

Correlation between blood-oxygen-level-dependent (BOLD) and cerebral blood flow (CBF) has been used as an index of neurovascular coupling. Hippocampal BOLD-CBF correlation is associated with neurocognition, and the reduced correlation is associated with neuropsychiatric disorders. We conducted the first genome-wide association study of the hippocampal BOLD-CBF correlation in 4,832 Chinese Han subjects. The hippocampal BOLD-CBF correlation had an estimated heritability of 16.2-23.9% and showed reliable genome-wide significant association with a locus at 3q28, in which many variants have been linked to neuroimaging and cerebrospinal fluid markers of Alzheimer's disease. Gene-based association analyses showed four significant genes (GMNC, CRTC2, DENND4B, and GATAD2B) and revealed enrichment for mast cell calcium mobilization, microglial cell proliferation, and ubiquitin-related proteolysis pathways that regulate different cellular components of the neurovascular unit. This is the first unbiased identification of the association of hippocampal BOLD-CBF correlation, providing fresh insights into the genetic architecture of hippocampal neurovascular coupling.

Dissociation between neuroanatomical and symptomatic subtypes in schizophrenia.

BACKGROUND: Schizophrenia is a complex and heterogeneous syndrome with high clinical and biological stratification. Identifying distinctive subtypes can improve diagnostic accuracy and help precise therapy. A key challenge for schizophrenia subtyping is understanding the subtype-specific biological underpinnings of clinical heterogeneity. This study aimed to investigate if the machine learning (ML)-based neuroanatomical and symptomatic subtypes of schizophrenia are associated. METHODS: A total of 314 schizophrenia patients and 257 healthy controls from four sites were recruited. Gray matter volume (GMV) and Positive and Negative Syndrome Scale (PANSS) scores were employed to recognize schizophrenia neuroanatomical and symptomatic subtypes using K-means and hierarchical methods, respectively. RESULTS: Patients with ML-based neuroanatomical subtype-1 had focally increased GMV, and subtype-2 had widespread reduced GMV than the healthy controls based on either K-means or Hierarchical methods. In contrast, patients with symptomatic subtype-1 had severe PANSS scores than subtype-2. No differences in PANSS scores were shown between the two neuroanatomical subtypes; similarly, no GMV differences were found between the two symptomatic subtypes. Cohen's Kappa test further demonstrated an apparent dissociation between the ML-based neuroanatomical and symptomatic subtypes (P > 0.05). The dissociation patterns were validated in four independent sites with diverse disease progressions (chronic vs. first episodes) and ancestors (Chinese vs. Western). CONCLUSIONS: These findings revealed a replicable dissociation between ML-based neuroanatomical and symptomatic subtypes of schizophrenia, which provides a new viewpoint toward understanding the heterogeneity of schizophrenia.

MRAß: A multimodal MRI-derived amyloid-ß biomarker for Alzheimer's disease.

Florbetapir 18 F (AV45), a highly sensitive and specific positron emission tomographic (PET) molecular biomarker binding to the amyloid-ß of Alzheimer's disease (AD), is constrained by radiation and cost. We sought to combat it by combining multimodal magnetic resonance imaging (MRI) images and a collaborative generative adversarial networks model (CollaGAN) to develop a multimodal MRI-derived Amyloid-ß (MRAß) biomarker. We collected multimodal MRI and PET AV45 data of 380 qualified participants from the ADNI dataset and 64 subjects from OASIS3 dataset. A five-fold cross-validation CollaGAN were applied to generate MRAß. In the ADNI dataset, we found MRAß could characterize the subject-level AV45 spatial variations in both AD and mild cognitive impairment (MCI). Voxel-wise two-sample t-tests demonstrated amyloid-ß depositions identified by MRAß in AD and MCI were significantly higher than healthy controls (HCs) in widespread cortices (p < .05, corrected) and were much similar to those by AV45 (r > .92, p < .001). Moreover, a 3D ResNet classifier demonstrated that MRAß was comparable to AV45 in discriminating AD from HC in both the ADNI and OASIS3 datasets, and in discriminate MCI from HC in ADNI. Finally, we found MRAß could mimic cortical hyper-AV45 in HCs who later converted to MCI (r = .79, p < .001) and was comparable to AV45 in discriminating them from stable HC (p > .05). In summary, our work illustrates that MRAß synthesized by multimodal MRI could mimic the cerebral amyloid-ß depositions like AV45 and lends credence to the feasibility of advancing MRI toward molecular-explainable biomarkers.

Effects of urban living environments on mental health in adults.

Urban-living individuals are exposed to many environmental factors that may combine and interact to influence mental health. While individual factors of an urban environment have been investigated in isolation, no attempt has been made to model how complex, real-life exposure to living in the city relates to brain and mental health, and how this is moderated by genetic factors. Using the data of 156,075 participants from the UK Biobank, we carried out sparse canonical correlation analyses to investigate the relationships between urban environments and psychiatric symptoms. We found an environmental profile of social deprivation, air pollution, street network and urban land-use density that was positively correlated with an affective symptom group (r = 0.22, Pperm < 0.001), mediated by brain volume differences consistent with reward processing, and moderated by genes enriched for stress response, including CRHR1, explaining 2.01% of the variance in brain volume differences. Protective factors such as greenness and generous destination accessibility were negatively correlated with an anxiety symptom group (r = 0.10, Pperm < 0.001), mediated by brain regions necessary for emotion regulation and moderated by EXD3, explaining 1.65% of the variance. The third urban environmental profile was correlated with an emotional instability symptom group (r = 0.03, Pperm < 0.001). Our findings suggest that different environmental profiles of urban living may influence specific psychiatric symptom groups through distinct neurobiological pathways.

Cross-ancestry genome-wide association meta-analyses of hippocampal and subfield volumes.

The hippocampus is critical for memory and cognition and neuropsychiatric disorders, and its subfields differ in architecture and function. Genome-wide association studies on hippocampal and subfield volumes are mainly conducted in European populations; however, other ancestral populations are under-represented. Here we conduct cross-ancestry genome-wide association meta-analyses in 65,791 individuals for hippocampal volume and 38,977 for subfield volumes, including 7,009 individuals of East Asian ancestry. We identify 339 variant-trait associations at P < 1.13 × 10-9 for 44 hippocampal traits, including 23 new associations. Common genetic variants have similar effects on hippocampal traits across ancestries, although ancestry-specific associations exist. Cross-ancestry analysis improves the fine-mapping precision and the prediction performance of polygenic scores in under-represented populations. These genetic variants are enriched for Wnt signaling and neuron differentiation and affect cognition, emotion and neuropsychiatric disorders. These findings may provide insight into the genetic architectures of hippocampal and subfield volumes.

Characterization of the effects of outliers on ComBat harmonization for removing inter-site data heterogeneity in multisite neuroimaging studies.

Data harmonization is a key step widely used in multisite neuroimaging studies to remove inter-site heterogeneity of data distribution. However, data harmonization may even introduce additional inter-site differences in neuroimaging data if outliers are present in the data of one or more sites. It remains unclear how the presence of outliers could affect the effectiveness of data harmonization and consequently the results of analyses using harmonized data. To address this question, we generated a normal simulation dataset without outliers and a series of simulation datasets with outliers of varying properties (e.g., outlier location, outlier quantity, and outlier score) based on a real large-sample neuroimaging dataset. We first verified the effectiveness of the most commonly used ComBat harmonization method in the removal of inter-site heterogeneity using the normal simulation data, and then characterized the effects of outliers on the effectiveness of ComBat harmonization and on the results of association analyses between brain imaging-derived phenotypes and a simulated behavioral variable using the simulation datasets with outliers. We found that, although ComBat harmonization effectively removed the inter-site heterogeneity in multisite data and consequently improved the detection of the true brain-behavior relationships, the presence of outliers could damage severely the effectiveness of ComBat harmonization in the removal of data heterogeneity or even introduce extra heterogeneity in the data. Moreover, we found that the effects of outliers on the improvement of the detection of brain-behavior associations by ComBat harmonization were dependent on how such associations were assessed (i.e., by Pearson correlation or Spearman correlation), and on the outlier location, quantity, and outlier score. These findings help us better understand the influences of outliers on data harmonization and highlight the importance of detecting and removing outliers prior to data harmonization in multisite neuroimaging studies.

Abnormal cerebral blood flow in patients with Leber's hereditary optic neuropathy.

PURPOSE: The study aimed to unravel abnormal cerebral blood flow (CBF) in patients with Leber's hereditary optic neuropathy (LHON) using arterial spin labeling (ASL) and to investigate the associations among disrupted CBF, disease duration, and neuro-ophthalmological impairment. METHODS: ASL perfusion imaging data was collected from 20 patients with acute LHON, 29 patients with chronic LHON, and 37 healthy controls. We used a one-way analysis of covariance to test the intergroup differences in CBF. Linear and nonlinear curve fit models were applied to explore the associations among CBF, disease duration, and neuro-ophthalmological metrics. RESULTS: Brain regions differed in LHON patients, including the left sensorimotor and bilateral visual areas (p < 0.05, cluster-wise family-wise error correction). Acute and chronic LHON patients demonstrated lower CBF in bilateral calcarine than the healthy controls. Chronic LHON had lower CBF in the left middle frontal gyrus and sensorimotor cortex, and temporal-partial junction than the healthy controls and acute LHON. A significant logarithmic negative correlation was shown between CBF of left middle frontal gyrus and disease duration. A significant linear positive correlation was found between retinal nerve fiber layer thickness and CBF in left middle frontal gyrus, and negative correlations between loss of variance and CBF in left middle frontal gyrus and sensorimotor cortex (p < 0.05, Bonferroni correction). CONCLUSION: LHON patients exhibited reduced CBF in the visual pathway, sensorimotor and higher-tier cognitive areas. Disease duration and neuro-ophthalmological impairments can influence the metabolism of non-visual areas.

Genes associated with spontaneous brain activity changes in clinically different patients with major depressive disorder: A transcription-neuroimaging association study.

AIMS: The amplitude of low-frequency fluctuations (ALFF) of resting-state functional MRI signals is a reliable neuroimaging measure of spontaneous brain activity. Inconsistent ALFF alterations have been reported in major depressive disorder (MDD) possibly due to clinical heterogeneity. This study was designed to investigate clinically sensitive and insensitive genes associated with ALFF alterations in MDD and the potential mechanisms. METHODS: Transcription-neuroimaging association analyses of case-control ALFF differences from two independent neuroimaging datasets with gene expression data from Allen Human Brain Atlas were performed to identify the two gene sets. Various enrichment analyses were conducted to characterize their preference in biological functions, cell types, temporal stages, and shared effects with other psychiatric disorders. RESULTS: Compared with controls, first-episode and drug-naïve patients showed more extensive ALFF alterations than patients with varied clinical features. We identified 903 clinically sensitive genes and 633 clinically insensitive genes, and the former was enriched for genes with down-regulated expression in the cerebral cortex of MDD patients. Despite shared functions of cell communication, signaling, and transport, clinically sensitive genes were enriched for cell differentiation and development whereas clinically insensitive genes were for ion transport and synaptic signaling. Clinically sensitive genes showed enrichment for microglia and macrophage from childhood to young adulthood in contrast to clinically insensitive genes for neurons before early infancy. Clinically sensitive genes (15.2%) were less likely correlated with ALFF alterations in schizophrenia than clinically insensitive genes (66.8%), and both were not relevant to bipolar disorder and adult attention deficit and hyperactivity disorder based on a third independent neuroimaging dataset. CONCLUSIONS: Present results provide novel insights into the molecular mechanisms of spontaneous brain activity changes in clinically different patients with MDD.

Dynamic reorganization of cortical structure in multi-domain regions after capsular and pontine stroke.

Subcortical stroke may cause widespread structural changes to the cerebral cortex in multiple domains; however, the details of this process remain unclear. In this prospective observational study, we acquired two datasets to investigate the effect of lesion location on cortical structure. One was cross-sectional, comprising 269 patients with chronic stroke, either capsular stroke (CS) or pontine stroke (PS), and the other was longitudinal, comprising 119 patients with CS or PS. In the chronic-stage data, both CS and PS exhibited reduced cortical thickness in the precentral gyrus and increased cortical thickness and area in the frontal, temporal, occipital and insular cortices. Cortical thicknesses were correlated with motor outcomes in the precentral and lingual gyri, and early impairment of the corticospinal tract was associated with cortical thickness in the middle frontal gyrus. In the longitudinal dataset, CS showed gradually decreasing cortical thickness in the precentral gyrus, and both CS and PS showed gradually increasing cortical thickness and area in regions with significant structural reorganization. Subcortical stroke can therefore cause complex cortical structural changes in multi-domain regions involved in motor, primary and higher cognitive areas and have different evolution patterns depending on the subcortical level of the lesion affecting the motor pathways.

Cerebellar connectome alterations and associated genetic signatures in multiple sclerosis and neuromyelitis optica spectrum disorder.

BACKGROUND: The cerebellum plays key roles in the pathology of multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD), but the way in which these conditions affect how the cerebellum communicates with the rest of the brain (its connectome) and associated genetic correlates remains largely unknown. METHODS: Combining multimodal MRI data from 208 MS patients, 200 NMOSD patients and 228 healthy controls and brain-wide transcriptional data, this study characterized convergent and divergent alterations in within-cerebellar and cerebello-cerebral morphological and functional connectivity in MS and NMOSD, and further explored the association between the connectivity alterations and gene expression profiles. RESULTS: Despite numerous common alterations in the two conditions, diagnosis-specific increases in cerebellar morphological connectivity were found in MS within the cerebellar secondary motor module, and in NMOSD between cerebellar primary motor module and cerebral motor- and sensory-related areas. Both diseases also exhibited decreased functional connectivity between cerebellar motor modules and cerebral association cortices with MS-specific decreases within cerebellar secondary motor module and NMOSD-specific decreases between cerebellar motor modules and cerebral limbic and default-mode regions. Transcriptional data explained > 37.5% variance of the cerebellar functional alterations in MS with the most correlated genes enriched in signaling and ion transport-related processes and preferentially located in excitatory and inhibitory neurons. For NMOSD, similar results were found but with the most correlated genes also preferentially located in astrocytes and microglia. Finally, we showed that cerebellar connectivity can help distinguish the three groups from each other with morphological connectivity as predominant features for differentiating the patients from controls while functional connectivity for discriminating the two diseases. CONCLUSIONS: We demonstrate convergent and divergent cerebellar connectome alterations and associated transcriptomic signatures between MS and NMOSD, providing insight into shared and unique neurobiological mechanisms underlying these two diseases.

The impact of pre-adulthood urbanicity on hippocampal subfield volumes and neurocognitive abilities in young adults.

BACKGROUND: Urbanicity refers to the conditions that are particular to urban areas and is a growing environmental challenge that may affect hippocampus and neurocognition. This study aimed to investigate the effects of the average pre-adulthood urbanicity on hippocampal subfield volumes and neurocognitive abilities as well as the sensitive age windows of the urbanicity effects. PARTICIPANTS AND METHODS: We included 5,390 CHIMGEN participants (3,538 females; age: 23.69 ± 2.26 years, range: 18-30 years). Pre-adulthood urbanicity of each participant was defined as the average value of annual night-time light (NL) or built-up% from age 0-18, which were extracted from remote-sensing satellite data based on annual residential coordinates of the participants. The hippocampal subfield volumes were calculated based on structural MRI and eight neurocognitive measures were assessed. The linear regression was applied to investigate the associations of pre-adulthood NL with hippocampal subfield volumes and neurocognitive abilities, mediation models were used to find the underlying pathways among urbanicity, hippocampus and neurocognition, and distributed lag models were used to identify sensitive age windows of urbanicity effect. RESULTS: Higher pre-adulthood NL was associated with greater volumes in the left (ß = 0.100, 95%CI: [0.075, 0.125]) and right (0.078, [0.052, 0.103]) fimbria and left subiculum body (0.045, [0.020, 0.070]) and better neurocognitive abilities in information processing speed (-0.212, [-0.240, -0.183]), working memory (0.085, [0.057, 0.114]), episodic memory (0.107, [0.080, 0.135]), and immediate (0.094, [0.065, 0.123]) and delayed (0.087, [0.058, 0.116]) visuospatial recall, and hippocampal subfield volumes and visuospatial memory showed bilateral mediations for the urbanicity effects. Urbanicity effects were greatest on the fimbria in preschool and adolescence, on visuospatial memory and information processing from childhood to adolescence and on working memory after 14 years. CONCLUSION: These findings improve our understanding of the impact of urbanicity on hippocampus and neurocognitive abilities and will benefit for designing more targeted intervention for neurocognitive improvement.

Reproducible Abnormalities and Diagnostic Generalizability of White Matter in Alzheimer's Disease.

Alzheimer's disease (AD) is associated with the impairment of white matter (WM) tracts. The current study aimed to verify the utility of WM as the neuroimaging marker of AD with multisite diffusion tensor imaging datasets [321 patients with AD, 265 patients with mild cognitive impairment (MCI), 279 normal controls (NC)], a unified pipeline, and independent site cross-validation. Automated fiber quantification was used to extract diffusion profiles along tracts. Random-effects meta-analyses showed a reproducible degeneration pattern in which fractional anisotropy significantly decreased in the AD and MCI groups compared with NC. Machine learning models using tract-based features showed good generalizability among independent site cross-validation. The diffusion metrics of the altered regions and the AD probability predicted by the models were highly correlated with cognitive ability in the AD and MCI groups. We highlighted the reproducibility and generalizability of the degeneration pattern of WM tracts in AD.