Autism Spectrum Disorder (ASD) presents a substantial global challenge, yet no pharmacological treatments effectively target its core symptoms, especially in individuals with severe cognitive or adaptive impairments. This double-blind, sham-controlled, randomized clinical trial assessed accelerated intermittent theta burst stimulation (iTBS) targeting the personalized fronto-parietal network (FPN) in ASD. Participants (6-30 years) were randomized in a 2:1 ratio to active or sham iTBS (three daily sessions, 1800 pulses/session) over 12 weeks (324k pulses) alongside behavioral training. The primary outcome was defined as the response rate, charaterized by a ≥ 1-point reduction in ADOS-2 SA at week 12. Of 132 individuals screened, 67 were randomized (mean age 10.04 ± 4.22 years; 88.1% male; all with cognitive/adaptive delays), with 59 completing the study. Active iTBS resulted in a significantly higher response rate (55% vs. 29%) and higher symptom improvement than sham (cohen's d = -0.53), with mild local pain in only 5% of iTBS group. In the profound autism subgroup, the active group exhibited language improvement alongside amelioration of core symptoms. These findings suggest that prolonged, accelerated FPN-targeted iTBS is a safe and efficacious intervention for severe ASD, offering a promising therapeutic approach.Registration ClinicalTrials.gov Identifier: NCT05890846.

Major depressive disorder (MDD) is associated with widespread alterations in functional brain networks across the lifespan. However, heterogeneity in atypical brain development among patients with MDD remains largely uncharacterized. Using a multisite resting-state functional MRI dataset consisting of 1,105 MDD patients and 1,065 healthy controls, we constructed a harmonized multicenter brain age prediction model based on individualized functional topography and identified two patient subgroups with positive or negative brain age gaps (BAGs). In patients with a positive BAG (BAG+), expansion of the salience network (SAL) into the dorsolateral prefrontal and ventrolateral prefrontal cortices, in addition to contraction of the sensorimotor and dorsal attention networks (DAN), contributes to accelerated brain aging. Conversely, in the negative BAG (BAG-) group, SAL expansion into the orbitofrontal cortex (OFC) and contraction of the visual and sensorimotor networks (SMN) were linked to delayed brain development. These subgroups also exhibited distinct neurodevelopmental trajectories. Clinically, BAG+ patients showed stronger associations between higher-order network topography and mood symptoms, whereas BAG- patients exhibited links between visual/default mode network topography and insomnia. At the molecular level, both groups showed enrichment of genes related to synaptic signaling but displayed distinct expression patterns and divergent expression trajectories in key neurodevelopmental gene sets. Notably, antidepressant treatment modulated the brain in ways that were specific to each subgroup. These findings reveal heterogeneous neurodevelopmental profiles in MDD with distinct biological and clinical signatures, offering insights into personalized precision medicine for this disorder.

Reading and mathematics are core components of children’s academic development and are linked to later educational, occupational, and psychosocial outcomes. Yet evidence on their predictors remains dispersed across biological, cognitive, behavioral, contextual, and neuroimaging traditions, and few syntheses have examined these literatures within a common developmental framework. In this systematic review, we synthesize 165 eligible studies to examine multilevel predictors of reading and mathematics achievement in children and adolescents and to distinguish shared from domain-specific patterns of prediction. We organize the evidence within a multilevel framework spanning perinatal and early-life conditions, cognitive skills, behavioral, emotional, and motivational processes, family and school contexts, and neuroimaging indicators. Across levels, the literature supports a developmental account in which early biological and contextual conditions are best understood as distal starting conditions, cognitive skills as the most proximal capacities for academic learning, and behavioral-emotional processes as regulatory pathways through which those capacities are expressed. Reading is more consistently associated with language-related and sound-symbol skills, whereas mathematics is more consistently associated with numerical concepts, symbolic processing, spatial resources, and math anxiety; executive function and general cognitive ability appear to provide a shared scaffold across both domains. We also include a worked multimodal neuroimaging illustration, explicitly framed as an illustrative application rather than an evidential extension, to show how the neural layer may be incorporated as a source of child-proximal markers. Overall, the review advances an evidence-calibrated multilevel framework for organizing shared and domain-specific predictors of reading and mathematics achievement and clarifies the interpretive limits of translating predictive evidence into intervention claims.

Ferroptosis is being increasingly implicated in the pathophysiology of major depressive disorder (MDD). Endoplasmic reticulum (ER) stress is closely linked to ferroptosis, yet the endogenous regulators connecting ER dysfunction to ferroptosis during chronic stress remain unclear. Here, we report that the expression of mesencephalic astrocyte-derived neurotrophic factor (MANF), an ER stress-inducible protein, was upregulated in the hippocampus (Hip) of male mice subjected to chronic social defeat stress (CSDS). Hippocampal MANF overexpression alleviated depressive-like behaviors and suppressed ferroptosis, whereas MANF knockdown promoted stress susceptibility and facilitated ferroptosis. Ferrostatin-1 (Fer-1) mimicked the protective effects of MANF overexpression and rescued MANF deficiency-induced phenotypes. Mechanistically, MANF inhibited PERK/ATF4 signaling, and overexpression of PERK or ATF4 partially counteracted MANF-mediated protection, whereas their knockdown rescued MANF deficiency-induced phenotypes. Furthermore, ATF4 increased the promoter activity of glutathione-specific γ-glutamylcyclotransferase 1 (CHAC1) in an ATF4-binding-site-dependent manner, thereby impairing the SLC7A11/GPX4 anti-ferroptotic defense axis and driving ferroptosis. These findings identify hippocampal MANF as an endogenous protective factor that suppresses stress-induced ferroptosis through the PERK/ATF4 pathway and position MANF as a potential therapeutic target for MDD.

Major depressive disorder (MDD) is a highly heterogeneous condition that limits the reliability of symptom-based diagnosis and treatment selection. In response, neuroimaging-based subtyping has emerged as a promising strategy to address this heterogeneity and advance precision psychiatry. Here, we provide a critical synthesis of neuroimaging-based subtyping research in MDD with 4 central contributions. First, we integrate recent methodological advances, including unsupervised and semisupervised clustering, deep learning, and normative modeling, that move the field beyond group-level averages toward individualized deviation profiles. Second, we compare convergent and divergent subtype patterns across functional, structural, diffusion, and multimodal imaging, highlighting both shared organizational principles and modality-specific dimensions of heterogeneity. Third, we evaluate emerging evidence linking neurophysiological subtypes to symptom dimensions, illness trajectories, and treatment responses and outline a translational framework for clinical implementation. Finally, we identify key challenges and actionable future directions, including the creation of large-scale harmonized datasets, rigorous validation, and integration with physiological, genetic, and environmental data. Together, this review clarifies the current state of the neuroimaging-based subtyping of MDD and delineates a road map for translating brain-based heterogeneity into clinically meaningful advances.

Plasma tau phosphorylated at threonine 217 (p-tau217) has been recommended as a biomarker for the diagnosis of Alzheimer’s disease (AD). We evaluated the diagnostic and differential performance of plasma p-tau217 levels measured with three novel assays in a Chinese population. A total of 233 participants were recruited, including 39 cognitively unimpaired controls (CUCs), 28 individuals with mild cognitive impairment (MCI) due to AD, 57 individuals with AD dementia (ADD), 70 individuals with subcortical ischemic vascular dementia (SIVD), and 39 individuals with frontotemporal lobar degeneration (FTLD). Plasma p-tau217 levels were measured using one assay based on single-molecule techniques (DiSMS), one assay based on digital ELISA (LyMedivh™ AXL), and one assay based on flow cytometry (CBA), as well as a reference assay (ALZpath Simoa). Group differences in plasma p-tau217 levels were assessed using analysis of covariance, and the diagnostic and differential performance of the assays was evaluated via receiver operating characteristic analysis. Partial correlation analysis was used to examine the correlations between the measurements of the three novel assays and those of the reference assay. We found that plasma p-tau217 levels measured with all three novel assays were higher in the ADD group than in the CUC, SIVD, and FTLD groups (all p < 0.05) and effectively discriminated ADD patients from both CUCs and non-AD dementia patients. The diagnostic and differential performances did not significantly differ among the three assays (all p > 0.05). Both the DiSMS and LyMedivh™ AXL assays also revealed elevated plasma p-tau217 levels in the MCI group compared to the CUC group. Moreover, the measurements of the three novel assays demonstrated significant correlations with the ALZpath Simoa measurements (p < 0.01). When using their optimal cutoff values, both the DiSMS and LyMedivh™ AXL assays yielded a specificity of 100% and a sensitivity of 94.4%, and the CBA assay showed a specificity of 100% and a sensitivity of 88.9%. In conclusion, our study demonstrated the diagnostic and differential abilities of plasma p-tau 217 levels measured with three novel assays that can serve as potential alternatives to the currently available testing methods for AD diagnosis.

Strong heterogeneity limits precision medicine in youth with mood disorders during major depressive episodes (MDE). Here we propose and evaluate a neurobiomarker-guided repetitive transcranial magnetic stimulation (rTMS) strategy in a double-blind randomized controlled trial. Using multicenter resting-state functional magnetic resonance imaging data (N = 2,328), we validated functional imbalance along the sensorimotor-association axis as a robust neurobiomarker distinguishing two neurosubtypes-archetypal and atypical. We then conducted a double-blind randomized controlled trial (2 August 2022-20 January 2024) in 219 youth with MDE. Participants were classified into subtypes and randomly assigned to subtype-specific active rTMS or sham stimulation. The primary outcome was depressive symptom improvement measured by the 17-item Hamilton Depression Rating Scale; secondary outcomes assessed neurobiological effects using functional magnetic resonance imaging. The trial met its prespecified primary endpoint. The active rTMS showed greater symptom improvement than sham (adjusted mean difference of -2.34, 95% confidence interval -3.80 to -0.87, P = 0.002), with significant effects observed in both subtypes. However, the clinical efficacy was moderate, with only the anxiety/somatization factor showing significantly higher rates of partial response and response. The archetypal subtype exhibited increased fluctuation amplitude in the visual cortex following active rTMS compared with sham, meeting the prespecified secondary endpoint. By contrast, no significant neurobiological effects were observed in the atypical subtype. Symptom improvement was associated with functional activity alterations along the sensorimotor-association axis. These findings provide preliminary support for biologically driven, neurosubtype-specific treatments in youth with MDE (ClinicalTrials.gov, NCT05465928).

Unraveling the heterogeneity of autism spectrum disorder (ASD) remains a major challenge yet crucial for elucidating the etiological underpinnings. Leveraging large-scale MRI data from 60,234 healthy participants and 3,117 individuals with ASD, we established lifespan brain charts of cortical thickness (CT) and surface area (SA) and derived personalized centile scores indexing deviations from typical neurodevelopment. Using a categorical multilayer community detection framework, we identified three CT-based and three SA-based neuroanatomical subtypes, each characterized by distinct spatial patterns and clinical profiles. Polygenic and plasma proteomic analyses further revealed genetic susceptibility and immune-related pathways underlying the observed heterogeneity. Moreover, the spatial patterns of these subtypes exhibited differential associations with cortical microarchitectural features and aligned closely with multimodal disease epicenters. Collectively, our findings indicate neuroanatomical heterogeneity in ASD as an integrative substrate linking molecular dysregulation to behavioral variability, providing a biologically grounded and clinically relevant framework for parsing the complex mechanisms of autism.

Neuroimaging studies have revealed altered functional connectome dynamics in autism spectrum disorder (ASD) and linked these alterations to clinical symptoms. However, most studies have emphasized population-level contrasts, leaving interindividual variability in connectome dynamics and its structural underpinnings poorly understood. To address this gap, we analyzed resting-state functional and structural MRI data from 939 male participants (440 with ASD, 499 typically developing controls) across 18 sites in the Autism Brain Imaging Data Exchange (ABIDE). Whole-brain functional state dynamics was characterized using five leading activity modes and their expressions via eigen-microstate analysis. Age-related trajectories of mode expressions were constructed for typically developing controls using normative modeling, enabling quantification of individual-level deviations in functional dynamics. Compared with controls, ASD individuals showed greater interindividual variability in functional deviation profiles. Unsupervised clustering of these profiles identified two robust ASD subtypes with distinct mode-specific dysfunctions. One subtype primarily involved the visual, default-mode, frontoparietal, and dorsal attention networks, whereas the other subtype primarily involved the somatomotor, visual, frontoparietal, and ventral attention networks. These subtypes were clinically dissociable, differing in restricted and repetitive behaviors and social impairments, and exhibited mode-specific brain-symptom associations. Furthermore, the subtypes exhibited distinct cortical thickness alterations, and individual subtype membership was predicted with high accuracy (83%) using a random forest classifier based on cortical thickness. The main findings were replicated in an independent cohort outside ABIDE. This study delineates two reproducible and clinically dissociable ASD subtypes and links functional connectome dynamics to structural substrates, offering novel insights into the neurobiological basis behind ASD heterogeneity.

The postnatal white matter connectome undergoes profound reorganization, yet the topological principles governing its spatiotemporal maturation remain largely unknown. Using connectome mapping, machine learning, and neurobiological annotation, we show hierarchical network development from birth to childhood and its association with neurobiological signatures. We identify two cardinal topological transformations that change rapidly during infancy and continue to refine into childhood, as characterized by nonlinear global increases in network efficiency and robustness to nodal attack, and regional reorganization with accelerated hub consolidation and prolonged modular reconfiguration, predominantly involving the prefrontal and insular cortices. Early developmental trajectories of these association cortices predict late childhood network architecture through local microstructural maturation of connected white matter tracts. These patterns align with well-established multiscale cortical hierarchies, including anatomical, evolutionary, and energy metabolism axes. Our findings reveal critical neurotopological milestones after postnatal development and establish a unified multiscale framework linking macroscale network dynamics to biologically constrained rules. This study reveals a hierarchical development of the brain’s structural connectome from infancy to childhood, characterized by distinct sensorimotor-association trajectories and alignment with multiple neurobiological hierarchies.

Subthreshold depression (StD) confers a high risk for major depression and is characterized by substantial individual clinical heterogeneity. However, the neurobiological substrates underlying this heterogeneity remain largely unknown. Using a large multisite resting-state functional MRI dataset including 1203 healthy participants and 197 individuals with StD, we constructed connectome-based normative models to identify individual brain deviations and biotypes in StD. We highlighted remarkable individual variability in the connectome deviations in StD, leading to the identification of two distinct biotypes. Subtype 1 exhibits severe positive deviations primarily in the default mode regions and negative deviations in the sensorimotor and ventral attention areas, while subtype 2 shows a moderate but opposite deviation pattern. The two subtypes differ significantly in depressive symptoms, gene expression profiles, and treatment responses to bright light therapy. These findings highlight the neurobiological underpinnings of the clinical diversity in StD, emphasizing the necessity for developing personalized interventions for this condition.

The human cortical functional hierarchy, spanning from primary sensorimotor to transmodal association regions, represents a fundamental principle of brain organisation. Here, we show lifespan changes in the sensorimotor-association (S-A) gradient in the cortical functional hierarchy using multimodal neuroimaging data from 33,247 participants aged 32 postmenstrual weeks to 80 years. We identify three critical neurodevelopmental milestones: initiation (third trimester to perinatal period), establishment (infancy to early childhood), and expansion-stabilisation (late childhood to adulthood). Pronounced gradient changes are predominantly observed during the first decade, with continued refinement extending into mid-adulthood. Spatiotemporally heterogeneous growth patterns in functional gradients align with evolutionary hierarchies, segregation-integration dynamics, structural maturation, and cognitive spectrum development, proceeding along a dominant S-A growth axis. These findings establish a unified neurodevelopmental framework that links connectome gradient dynamics to multifaceted functional and structural properties, advancing our understanding of cortical hierarchy maturation across the lifespan.

Despite dynamic sulcal changes during youth paralleling skill development, the link between extended postnatal development and cognition remains underexplored. This study analyzes structural MRI data from 307 children (6-14 years), with longitudinal data (inter-scan interval ~1 year) available for a subset. Results reveal widespread cortical thinning, sulcal widening, and reductions in adjusted area and depth, following a chronological gradient where earliest-forming sulci undergo the most profound change. Longitudinal remodeling, rather than baseline morphometry, predicts cognitive gains. Specifically, working memory improvements are predicted by widening of the left calcarine and posterior intralingual sulci. In contrast, attention network maturation involves global changes, though executive control is specifically linked to left intraparietal sulcus widening. Gene enrichment analysis links these changes to synaptic processes. This study advances our understanding of the association between sulcal morphometry and cognitive function, elucidating potential mechanisms underlying brain development from childhood to adolescence.

The ventromedial prefrontal cortex (VMPFC) has been repeatedly implicated in affect, valuation, and social cognition, yet how these diverse functions are organized within a single cortical territory has remained unresolved. Here, we integrate large-scale meta-analysis, individual-level task fMRI, artificial neural-network encoding models, and multimodal connectivity analyses to reveal the internal functional architecture of the human VMPFC. Across four complementary studies, we identify a robust tripartite organization along the anterior-posterior axis, comprising posterior affective, middle valuation, and anterior social functional motifs. Connectivity fingerprinting demonstrates that each motif is preferentially embedded within distinct large-scale brain networks, providing a mechanistic account of VMPFC functional specialization. This organization is reproducible at the level of individual subjects, generalizes to naturalistic stimuli, extends across development, and shows cross-species correspondence with non-human primates and multiple neurobiological markers. Together, these findings resolve a long-standing organizational question and establish a biologically grounded framework for interpreting VMPFC function.

Understanding hippocampal–cortical integration is critical for cognitive development, yet the hippocampus’ multidimensional organization and its developmental coupling with cortical systems during youth remain unclear. Here, across three large-scale developmental cohorts, we conducted a multiscale association study that revealed reproducible triple-gradient organizations of the hippocampus and their distinct maturational trajectories, which uniquely shape cortical hierarchy, most prominently within the frontoparietal and ventral-attention or action-mode systems. These gradients differentially support episodic memory and specific aspects of executive function. Mechanistically, the hippocampus exhibits a progressive relaxation of geometric constraints on its function over development. Furthermore, the maturation of hippocampal gradients mirrors regional myelination patterns, while transcriptome analyses link gradient reorganization to molecular pathways of neurodevelopment, stress-hormone regulation, and neuroactive signaling. These findings demonstrate a developmental landscape of the triple gradients in human hippocampus to orchestrate cortical hierarchy and cognitive maturation, offering a parsimonious framework for developmental neuroscience.

Neuroinflammation plays an important role in the pathophysiology of depression. Interleukin-17A (IL-17A), an inflammatory cytokine, is strongly associated with depression; however, the potential mechanisms through which IL-17A in the brain regulates depressive symptoms remain unknown. Our study aimed at finding out the potential pathway through which IL-17A in the brain regulates depressive-like behaviours. Anti-despair-like behaviours, an important index for evaluating depression in mice, are present in IL-17A knockout mice. Given that the hippocampus is a brain region that is implicated in depression, the level of IL-17A in the hippocampus was evaluated in chronic unpredictable mild stress (CUMS) mice, and the results revealed increased hippocampal IL-17A levels. The expression of IL-17A was subsequently regulated by the stereotactic injection of multivesicular liposomes loaded with IL-17A recombinant protein as a sustained release system, and the AAV-il17a or AAV-shRNA(il17a) into the hippocampus. IL-17A overexpression induced despair-like behaviour, and the anti-despair-like phenotype in IL-17A knockout mice was blocked by the restoration of IL-17A expression in the hippocampus, which demonstrated the role of IL-17A in depression. Gene microarray, UPLC‒MS/MS, Western blot and patch clamp analyses were used to determine the pathway through which IL-17A regulates despair-like behaviours. Enhanced inhibitory synaptic transmission was detected in IL-17A-knockout mice. Furthermore, reducing the expression of the GABAA receptor α2 subunit (GABRA2) abrogated antidespair-like behaviour in IL-17A knockout mice, and hippocampal GABARA2 overexpression alleviated despair-like behaviour in CUMS mice. These results proved that GABRA2-mediated inhibitory synaptic transmission participated in the regulation of depressive-like behaviours by IL-17A. Our results revealed a vital role for IL-17A in depression and suggested that GABRA2 is the key molecule involved in the regulation of depression by IL-17A, indicating its potential as a therapeutic target for depression.

Depression is a severe mental illness that poses substantial burdens on public health. Given that depression research is still challenged by its multifaceted pathogenesis, depicting the depression associated genetic regulatory networks is essential for understanding its mechanism, optimizing diagnosis, and developing targeted therapies. However, a comprehensive panoramic view of transcriptional alterations in depression remains lacking. By leveraging the available transcriptomic studies from the National Center for Biotechnology Information (NCBI), China National Center for Bioinformatics (CNCB), European Bioinformatics Institute (EBI), and our laboratory, we compiled an extensive set of depression related datasets, encompassing 4 species, 31 types of brain and peripheral tissues, 35 categories of antidepressant interventions, and 6391 samples. Furthermore, a unified pipeline for raw data preprocessing and differential expression analysis was employed to identify differentially expressed genes (DEGs). A total of 631882 molecules entries were obtained, including 190366 entries from humans, 6612 from non-human primates, 332780 from mice, and 102124 from rats. Additionally, 15 single-cell and single-nucleus transcriptomic datasets, including 164 samples, and 78536 molecular entries were also included. Notably, we developed the TranDep database ( http://www.depression-atlas.cn/ ) for the depression research community, which provided a user-friendly web interface for browsing, and searching these molecules. To demonstrate the utility of TranDep, a case study was presented to identify robust DEGs, and explore its biological functions in the prefrontal cortex of patients with depression. Overall, TranDep is a comprehensive cross-species resource developed to provide a transcriptional atlas of depression, which may shed light on the identification and validation of diagnostic and therapeutic markers for depression.

Cerebral asymmetry is a core principle of human brain organization, showing dynamic changes across the lifespan and alterations in brain disorders. However, it remains unclear whether lifespan trajectories of asymmetry differ across populations. We compared lifespan structural asymmetry normative charts of 221 cerebral imaging phenotypes from 43,037 Chinese and 56,339 Western participants aged 0–100 years. The two populations showed distinct lifespan asymmetry patterns in 26.2% of the phenotypes. Chinese-minus-Western asymmetry difference curves displayed distinct patterns across brain phenotypes: rightward (45.7%), leftward (26.2%), rightward-to-leftward (11.8%), leftward-to-rightward (10.0%), and unclassified (6.3%). Population-matched normative models outperformed population-unmatched normative models in capturing normal asymmetry variability among healthy individuals and in detecting abnormal asymmetry deviations in patients with Alzheimer’s disease, mild cognitive impairment, schizophrenia, and major depressive disorder. These findings indicate that population mismatch can bias chart-based individual-level asymmetry assessment and underscore the need for population-representative brain asymmetry normative charts.