Biology subjects

He, Y.

Publications and source records attributed to He, Y..

At least 217 records · Page 12Linked to original sources

bioRxiv2025

Ciliated cells promote high infectious potential of influenza A virus through the efficient intracellular activation of hemagglutinin

Influenza viruses utilize host proteases to activate the viral fusion protein, hemagglutinin (HA), into its fusion-competent form. Although proteolytic activation of HA is essential for virus replication, the cell-type dependence of HA activation within the airway epithelium and the subcellular location(s) in which it occurs are not well-established. To address these questions, we investigated the proteolytic activation of HA in differentiated human airway epithelial cells using contemporary and historical H1N1 and H3N2 strains. We find that activation is efficient across viral strains and subtypes but depends on cellular tropism, with ciliated cells activating HA more effectively than non-ciliated cells. Similar to prior observations in immortalized cell lines, we find that HA activation occurs intracellularly, constraining the antiviral activity of host-directed protease inhibitors. These results establish that HA activation within the airway epithelium depends on cellular tropism, and identify important considerations for the development of protease inhibitors as antivirals. ImportanceInfluenza entry requires the proteolytic activation of the viral fusion protein, hemagglutinin (HA). Activation occurs as new viruses are produced by infected cells. Efficient proteolytic activation is critical for viral pathogenesis, and inhibiting the requisite proteases could provide an effective host-directed antiviral strategy. To understand cellular constraints on HA activation and its sensitivity to inhibitors, we use complementary approaches to investigate these processes in differentiated airway epithelial cells. We find that ciliated cells activate HA with higher efficiency than non-ciliated cell types, establishing a new mechanism through which cellular tropism and virus infectious potential are connected. We also establish that HA activation begins in the Golgi, which may contribute to the limited the efficacy of inhibitors we observe despite their high in vitro potency.

microbiology↗

bioRxiv2025

FGF21 signals through KLB-expressing glutamatergic neurons in the hindbrain to mediate the effects of dietary protein restriction

Animals adaptively respond to protein restriction by altering both behavior and metabolism. Previous work demonstrated that the metabolic hormone FGF21 acted in the brain to coordinate these adaptive responses, but the exact site of action remains unclear. Here, we identify a discrete population of glutamatergic, Klb-expressing neurons in the nucleus of the solitary tract (NTS), demonstrating that these neurons are key to mediating FGF21 action during protein restriction. Using a novel Klb-Flp mouse line combined with intersectional genetics, we demonstrate that these neurons are directly activated by FGF21. While previous work implicated the SCN, PVN, and VMH in FGF21 action, we find that these areas do not impact the response to protein restriction. Instead, selective ablation of NTS-KLB neurons prevents metabolic adaptations to protein restriction (food intake, food choice, and energy expenditure), while their chemogenetic activation is sufficient to drive these responses. These findings establish NTS-KLB neurons as a critical node for detecting protein status and coordinating whole-body metabolic responses, providing new insight into how the brain monitors and maintains protein homeostasis.

neuroscience↗

bioRxiv2025

Auto-downregulation of the florigen FT production prevents precocious flowering in plants

In many flowering plants, the developmental switch from vegetative growth to reproduction (flowering) is timed by seasonal changes in the length of daylight (photoperiod). Under inductive day lengths, the photoperiod pathway typically generates rhythmic expression of a transcriptional activator for florigen production. In the facultative long-day plant Arabidopsis thaliana, long-day exposure results in increasing buildup of the CONSTANS (CO) protein towards the end of daylight, and CO activates the expression of the major florigen gene FLOWERING LOCUS T (FT) to confer long-day induction of flowering. CO-mediated FT activation must be properly controlled to prevent an excessive florigen production and precocious flowering under inductive long days, but the underlying mechanism remains elusive. Here, we report an auto-repression mechanism to prevent excessive FT production in inductive photoperiods. We show that the transcription factor FD is expressed in leaf veins and complexes with FT to recognize several cis-regulatory DNA motifs in FT promoter. FT-FD antagonizes CO-mediated FT activation to feedback down-regulate FT expression and thus prevent its excessive induction by long-day signals, thereby precluding precocious transition to flowering. Furthermore, we found that in the facultative short-day plant soybean, an FT homolog directly represses its own expression. Thus, the auto-repression of FT or an FT homolog is a conserved mechanism to prevent excessive production of this potent floral regulator in plants, ensuring the floral transition at a proper time to balance vegetative growth with reproductive success and maximize plant production.

plant biology↗

bioRxiv2025

Ontology-based Protein-Protein Interaction Explanation Using Large Language Models

Protein-protein interactions (PPIs) play a crucial role in various biological processes, and understanding these interactions is essential for advancing biomedical research. Automated extraction and analysis of PPI information from the rapidly growing scientific literature remains an important challenge. We present a novel ontology-based approach to analyze protein-protein interactions using Large Language Models (LLMs). We applied different learning strategies, namely in-context learning and parameter-efficient instruction fine-tuning for the Llama-2 chat models, to identify keywords in the text that indicate an interaction between a pair of proteins. Our results show that parameter-efficient fine-tuning leads to a performance gain even when the domain is new. The smaller fine-tuned models outperformed the zero-shot performance of much larger models. The keywords identified by the Llama-2 models were mapped to the ontology terms in the Interaction Network Ontology (INO). Our study suggests that a pipeline of an LLM and an ontology is an effective strategy for explaining relations between biomedical entities. This work demonstrates the potential of leveraging ontologies and advanced language models to advance automated PPI analysis from the scientific literature.

bioinformatics↗

bioRxiv2025

SpatialAgent: An Autonomous AI Agent for Spatial Biology

Advances in AI are transforming scientific discovery, yet spatial biology, a field that deciphers the molecular organization within tissues, remains constrained by labor-intensive workflows. Here, we present SpatialAgent, an autonomous AI agent for spatial biology research. SpatialAgent couples large language models with a Plan-Act-Conclude architecture, dynamic tool and skill retrieval, multimodal interpretation, and verification modules that audit generated claims. It supports the full discovery loop, from gene-panel design and multimodal annotation to trajectory inference, cell-cell communication analysis, imputation, and hypothesis generation. Across human and mouse brain, heart, tonsil, colon, and prostate datasets, SpatialAgent outperformed established computational baselines and matched or surpassed expert scientists in key tasks. In open-ended case studies, it recovered known tissue organization and generated spatially grounded hypotheses. In a prospective mouse prostate cancer Xenium study, it designed a compact 100-gene add-on panel that profiled 4.2 million cells across 21 samples, improved cell-type and malignant-state prediction, and captured spatially structured tumor and microenvironment programs. SpatialAgent establishes a framework for autonomous and collaborative discovery in spatial biology.

bioinformatics↗

bioRxiv2025

Excitation Spectral Phasor Microscopy (ExSPM) unveils spatiotemporal heterogeneities in polarity of intracellular lipid droplets

Spatiotemporal heterogeneities in intracellular LD polarity are central to cellular homeostasis but remain largely unexplored. Here, we introduce Excitation Spectral Phasor Microscopy (ExSPM), which integrates high-throughput excitation spectral imaging with phasor analysis to map LD polarity with exceptional sensitivity and spatiotemporal resolution. Using the lipophilic dye Nile Red, ExSPM revealed extensive heterogeneity and dynamics of LD polarity within single cells, reflecting lipid metabolism and energy status. Notably, high-polarity LDs emerged dynamically at lysosome- and mitochondria-contact sites, revealing pathway-specific kinetics of LD catabolism that distinguish lipophagy from neutral lipolysis. ExSPM further uncovered a tightly interconnected regulatory network among lipolytic pathways, in which perturbation of one pathway reshapes others while preserving overall energy supply. ExSPM thus provides a versatile platform to dissect intracellular compositional heterogeneity and the coordinated regulation of lipid metabolism, offering new insights into organelle function and cellular homeostasis.

cell biology↗

bioRxiv2025

Spatial transcriptomics AI agent charts hPSC-pancreas maturation in vivo

Spatial transcriptomics has revolutionized our understanding of tissue organization by simultaneously capturing gene expression and spatial localization within intact tissues. However, analyzing these increasingly complex datasets requires specialized expertise across computational biology, statistics, and biological context. To address this challenge, we introduce the Spatial Transcriptomics AI Agent (STAgent), an autonomous multimodal agentic AI that integrates multimodal large language models (LLMs) with specialized computational tools to transform weeks-long analysis tasks into minutes of automated processing. Unlike conventional machine learning approaches that are limited to narrow, predefined tasks, STAgent leverages the emergent capabilities of multimodal LLMs - such as flexible reasoning, contextual understanding, and cross-modal integration - which allow it to adapt to novel data, execute multi-step analyses, and generate biologically meaningful insights with minimal human input. STAgent enables autonomous deep research through integrated capabilities, including dynamic code generation for complex analytical workflows, visual reasoning for interpreting spatial patterns, real-time retrieval of relevant peer-reviewd scientific literature, and synthesis of comprehensive, actionable reports. We applied STAgent to investigate the in vivo maturation of human stem cell-derived pancreatic cells (SC-pancreas) transplanted into immunodeficient mice. We generated single-cell spatial transcriptomics data spanning multiple developmental timepoints. STAgent autonomously (1) identified the maturation of initially scattered endocrine cells into well-defined islet-like structures, with predominantly peripheral -cells surrounding {beta}-cell cores supported by an expanding mesenchymal network; (2) revealed strengthening endocrine-endocrine cell interactions over time and, through context-aware gene set analysis, uncovered spatially resolved biological processes driving maturation; (3) unlike traditional analytical approaches, STAgent offers mechanistic explanations of spatial patterns, contextualizing findings with relevant literatures and developing cohesive insights into human pancreatic development. This agentic approach establishes a new paradigm in spatial transcriptomics analysis by substantially lowering the expertise barrier and reducing analysis time, accelerating biological and biomedical discovery.

genomics↗

bioRxiv2025

Goblet cells mechanically breach the epithelial barrier in gut homeostasis

The intestinal epithelium has to maintain a tight barrier against the harsh luminal environment. Absorptive enterocytes have a polygonal and columnar shape, while mucus-producing goblet cells exhibit a round apical cell shape and a bulky body, raising the question of how epithelial integrity is maintained around these cells. Here, we show that goblet cells induce tight junction fractures between neighboring enterocytes under homeostatic conditions in vivo, which are exacerbated during goblet cell hypertrophy, increasing gut permeability. We demonstrate that these fractures arise from a two-component mechanical interaction: goblet cells push and deform adjacent enterocytes, which rupture depending on tissue rheology controlled by myosin II. These findings reveal that the mechanical interplay between goblet cells and neighboring enterocytes is critical for maintaining intestinal epithelial barrier integrity.

cell biology↗

bioRxiv2025

Response to Tabin et al-Concerns about ancient DNA sequences reported from a Late Pleistocene individual from Southeast Asia

Tabin et al1 suspect a high error rate and abnormal error content in the MZR genome data from our published study2, from which they raised concerns about the reliability and useability of our published sequences. Given the poor environmental conditions (such as warm climate and acidic soil in the low latitude area of Southwest China), as well as the non-ideal fossil material (cranium) for DNA extraction, we argue that a relatively high level of aDNA damage, as well as possible artefacts from extraction, library construction and sequencing better explain the observed pattern by Tabin et al in MZR rather than modern DNA contamination. Particularly, we think the mutation motif of the MZR mtDNA, derived from our careful manual check, should be reliable. In addition, we provide additional analyses showing how we minimize the effect of aDNA damage in population analyses.

genomics↗

bioRxiv2025

A humanized 16A antibody conjugated with DNA topoisomerase I inhibitors, targeting a GSTA glycosite-signature epitope.

BackgroundWe previously reported the 16A antibody, which binds to the abnormally glycosylated tandem repeat region of the MUC1 glycoprotein, and developed 16A-MMAE as an antibody-drug conjugate. However, its antitumor efficacy as an antibody-drug conjugate with DNA topoisomerase Iinhibitors remains unknown. MethodsWe humanized the 16A antibody and conjugated it to DXd and MF6, two DNA topoisomerase I inhibitors. The antitumor efficacy of the conjugates was evaluated in vitro and in vivo. ResultsThe humanized 16A-DXd conjugate showed potent antitumoral efficacy, with an IC50 in the nM range against CFPAC1 cells. In vivo, h16A-DXd and h16A-MF6 inhibited tumor growth in asubcutaneous mouse tumor transplantation model using CT26-COSMC KO-hMUC1 cells, administered at a dose of 10 mg/kg. ConclusionsThe high antitumor efficacy of h16A-conjugated DNA topoisomerase I inhibitors supports further clinical development. The relatively low toxicity of h16A-DXd and h16A-MF6 may enable a higher therapeutic window, since MUC1-positive cells internalize the antibody-drug conjugate more efficiently.

pharmacology and toxicology↗

bioRxiv2025

Altered Interpersonal Neural Synchronization during Social Interaction After Shared Excluded Experiences in Depressed Adolescents

BackgroundMajor depressive disorder (MDD) is common in adolescents, and the special development stage, during which adolescents brain and neuroendocrine system develop intensively, makes it subtly difficult to develop prevention and treatment strategies for depressed adolescents compared with depressed adults. Meanwhile, public psychosocial stressors significantly influence adolescents mental health and social interaction, rendering it essential to explore how a shared psychosocial stressor, i.e., shared excluded experiences, influences social interaction in depressed adolescents. MethodsWe designed a 4-player cyberball game to probe adolescents responses to shared excluded experiences and explore the underlying interpersonal neural synchronization (INS) with functional near-infrared spectroscopy (fNIRS). ResultsWe found that shared excluded experiences could enhance adolescents social interaction preferences but decreased INS in each pair of excluded adolescents, which indicates a reduced willingness to interact with others after the exclusion. However, no significantly different behavioral responses to the shared excluded experiences were found in depressed adolescents compared to adolescents as healthy controls (HC). Further analyses revealed that adolescents with MDD experienced more negative feelings than HC after exclusion. Of note, adolescents with MDD demonstrated stronger INS than HC, indicating the potential empathic stress in depressed adolescents. In addition, there existed altered brain-behavioral association patterns in responses to shared excluded experiences in depressed adolescents. ConclusionsIn summary, our study gives us deeper insights into how a shared psychosocial stressor impacts the INS in depressed adolescents, and it might be demonstrated that INS could be more sensitive than behavioral responses to detect social interaction deficits in depressed adolescents.

neuroscience↗

bioRxiv2025

Towards a unified molecular mechanism for ligand-dependent activation of NR4A-RXR heterodimers

A subset of nuclear receptors (NRs) function as permissive heterodimers with retinoid X receptor (RXR), defined by transcriptional activation in response to RXR agonist ligands. Permissive NR-RXR activation is generally understood to operate through a classical pharmacological mechanism in which RXR agonist binding enhances coactivator recruitment to the heterodimer. However, we previously demonstrated that transcriptional activation of permissive Nurr1-RXR (NR4A2-NR2B1) heterodimers by an RXR ligand set, which included pharmacological RXR agonists and selective Nurr1-RXR agonists that function as antagonists of RXR homodimers, is explained by a non-classical activation mechanism involving ligand-binding domain (LBD) heterodimer dissociation (Yu et al., 2023). Here, we extend mechanistic ligand profiling of the same RXR ligand set to the evolutionarily related Nur77-RXR{gamma} (NR4A1-NR2B3) heterodimer. Biochemical and NMR protein-protein interaction profiling, together with cellular transcription studies, indicate that activation of Nur77-RXR{gamma} transcription by the RXR ligand set, which lacks selective Nur77-RXR{gamma} agonists, is consistent with contributions from both classical pharmacological activation and LBD heterodimer dissociation. However, reanalysis of our previously published data for Nurr1-RXR revealed that inclusion of selective Nurr1-RXR agonists was essential for elucidating the LBD heterodimer dissociation mechanism. Together, our findings highlight the importance of using a more functionally diverse RXR ligand set to define the mechanism of Nur77-RXR{gamma} activation and to further evaluate whether LBD heterodimer dissociation represents a shared activation mechanism among NR4A-RXR heterodimers relevant to neurodegenerative and inflammatory diseases.

biochemistry↗

bioRxiv2025

Resilience and vulnerabilities of tumor cells under purine shortage stress

Purine metabolism is a promising therapeutic target in cancer; however how cancer cells respond to purine shortage,particularly their adaptation and vulnerabilities, remains unclear. Using the recently developed purine shortage-inducing prodrug DRP-104 and genetic approaches, we investigated these responses in prostate, lung and glioma cancer models. We demonstrate that when de novo purine biosynthesis is compromised, cancer cells employ microtubules to assemble purinosomes, multi-protein complexes of de novo purine biosynthesis enzymes that enhance purine biosynthesis efficiency. While this process enables tumor cells to adapt to purine shortage stress, it also renders them more susceptible to the microtubule-stabilizing chemotherapeutic drug Docetaxel. Furthermore, we show that although cancer cells primarily rely on de novo purine biosynthesis, they also exploit Methylthioadenosine Phosphorylase (MTAP)-mediated purine salvage as a crucial alternative source of purine supply, especially under purine shortage stress. In support of this finding, combining DRP-104 with an MTAP inhibitor significantly enhances tumor suppression in prostate cancer (PCa) models in vivo. Finally, despite the resilience of the purine supply machinery, purine shortage-stressed tumor cells exhibit increased DNA damage and activation of the cGAS-STING pathway, which may contribute to impaired immunoevasion and provide a molecular basis of the previously observed DRP-104-induced anti-tumor immunity. Together, these findings reveal purinosome assembly and purine salvage as key mechanisms of cancer cell adaptation and resilience to purine shortage while identifying microtubules, MTAP, and immunoevasion deficits as therapeutic vulnerabilities.

cancer biology↗

bioRxiv2025

Molecular Insights into Cell Wall Architecture and Xylan-Bound Cellulose Fibrils in the Wheat Straw

The plant cell wall, a highly abundant renewable resource, remains insufficiently understood in terms of its structure, particularly the architecture of cellulose microfibrils and their interactions with hemicellulose and lignin, which impede the development of efficient downstream conversion. Here we present an alternative model of xylan-bound cellulose microfibril architecture in the cell wall of intact wheat straw, using solid-state nuclear magnetic resonance (ssNMR) coupled with X-ray scattering techniques. We show that the spectroscopic and scattering data can be fit to a simple elementary microfibril consisting of 18 glucan chains, with additional contributions from 0 to 4 tightly bound flat-ribbon xylan chains across the cellulose fibril axis. These xylan-bound cellulose microfibrils are found to serve as the secondary interaction site with lignin, following the non-flat xylan domains. The loose packing of these xylan-bound cellulose fibrils results in a heterogenous hydration landscape within the cell wall, allowing water penetration while maintaining structural integrity through numerous physical contacts between the polymers. This study provides a potential framework to reconcile the mounting biochemical evidence supporting the 18-chain elementary cellulose microfibril model and cellulose synthase complex with the oversized observations from characterization techniques, which report averaged structures influenced by microfibril coalescence and hemicellulose binding. The structural insights also offer valuable information regarding recalcitrance and the potential applications of biomass in biorefinery operations.

biochemistry↗

bioRxiv2025

RamEx: An R package for high-throughput microbial ramanome analyses with accurate quality assessment

Microbial single-cell Raman spectroscopy (SCRS) has emerged as a powerful tool for label-free phenotyping, enabling rapid characterization of microbial diversity, metabolic states, and functional interactions within complex communities. However, high-throughput SCRS datasets often contain spectral anomalies from noise and fluorescence interference, which obscure microbial signatures and hinder accurate classification. Robust algorithms for outlier detection and microbial ramanome analysis remain underdeveloped. Here, we introduce RamEx, an R package specifically designed for high-throughput microbial ramanome analyses with robust quality control and phenotypic classification. At the core of RamEx is the Iterative Convolutional Outlier Detection (ICOD) algorithm, which dynamically detects spectral anomalies without requiring predefined thresholds. Benchmarking on both simulated and real microbial datasets--including pathogenic bacteria, probiotic strains, and yeast fermentation populations--demonstrated that ICOD achieves an F1 score of 0.97 on simulated datasets and 0.74 on real datasets, outperforming existing approaches by at least 19.8%. Beyond anomaly detection, RamEx provides a modular and scalable workflow for microbial phenotype differentiation, taxonomic marker identification, metabolic fingerprinting, and intra-population heterogeneity analysis. It integrates Raman-based species-specific biomarkers, enabling precise classification of microbial communities and facilitating functional trait mapping at the single-cell level. To support large-scale studies, RamEx incorporates C++ acceleration, GPU parallelization, and optimized memory management, enabling the rapid processing of over one million microbial spectra within an hour. By bridging the gap between high-throughput Raman-based microbial phenotyping and computational analysis, RamEx provides a comprehensive toolkit for exploring microbial ecology, metabolic interactions, and antibiotic susceptibility at the single-cell resolution. RamEx is freely available under the MIT license at https://github.com/qibebt-bioinfo/RamEx.

bioinformatics↗

bioRxiv2025

Auditory efferents facilitate intensity change detection in humans: evidence from concurrent ear, brain, and behavior measures

Feedback mechanisms in the brain, such as the medial olivocochlear reflex (MOCR), can aid signal detection and discrimination in noise in animals. Extrapolating these findings in elementary perception to speech understanding in noise abilities in humans has been inconclusive. To investigate the functional role of the MOCR in elementary auditory perception in humans, we concurrently measured ear (otoacoustic emissions) and brain (N1-P2 acoustic change complex [ACC]) responses while participants performed a behavioral intensity change detection task. The intensity change was imposed on a triad of deviant clicks that occurred at early-, middle-, or late-temporal positions of a click train commensurate with null-, partial-, and full activation of the MOCR, respectively. We found faster behavioral detection and shorter ACC latencies for the middle- and late-occurring deviants relative to the early deviant. The improved behavioral detection of later-occurring deviants correlated significantly with the degree of MOCR activation and ACC latency. These mutual correlations suggest a direct involvement of the MOCR in human signal detection, underscored by earlier cortical detection. These novel findings advance our understanding of the mechanisms involved in speech perception in noise and aid in developing hearing assistive technologies.

physiology↗

bioRxiv2025

Synergistic neuroprotective and cognitive-enhancing effects of Walnut Peptide and Theanine in human brain organoid and mouse stress models

Stress is a prevalent mental health concern emerging predominantly in late adolescence or early adulthood. Since 2007, the Food and Drug Administration (FDA) has not approved any novel anxiolytic pharmaceuticals, fueling interest in nutritional supplements as alternative therapies for stress management. Building on prior zebrafish research, this study investigates the synergistic effects of Theanine (Th) and Walnut Peptide (WP) on stress mitigation and cognitive enhancement. Utilizing the human brain organoid stress (BO-stress) model, WP+ Th were observed to reduce stress and regulate expression of neurotransmitters, including Gamma-Aminobutyric Acid (GABA), serotonin (5-HT), dopamine (DA), and acetylcholine (Ach), as well as brain-derived neurotrophic factor (BDNF) and serotonin transporter (SERT). Subsequent in vivo study using C57BL/6J mouse-stress model demonstrated that the treatment (Th 85 mg/mL + WP 200 mg/mL), or administrated with vehicles, significantly improved their performance in stress and cognitive assessments, partially normalized neurotransmitter imbalances by modulating SERT and BDNF expression. These findings highlighted the potential of using WP + Th, particularly when delivered with vehicles (eg: powder/yogurt/milk), as a novel combined therapeutic approach for stress management and cognitive enhancement. We performed a correlation analysis between BO-stress model and mouse-stress model, revealing a alignement in the SERT levels.In addition, SERT was highly correlated with other markers in the mouse hippocampus and may represent a key target for modulating the balance between stress and cognition. Significance StatementThis study established an innovative human brain organoid-stress model and, in conjunction with mouse-stress model, elucidated the synergistic actions of Theanine and Walnut Peptide in mitigating stress and augmenting cognitive function. Their beneficial effects were mediated through the regulation of SERT and BDNF, presenting a promising non-pharmacological avenue for mental health care. In addition, species differences between humans and mice were also examined through correlation analysis of brain organoids and mouse models. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/640260v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@1a81886org.highwire.dtl.DTLVardef@e2281dorg.highwire.dtl.DTLVardef@1b7b167org.highwire.dtl.DTLVardef@dff9aa_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2025

Profiling brain morphology for autism spectrum disorder with two cross-culture large-scale consortia

We explore neurodevelopmental heterogeneity in Autism Spectrum Disorder (ASD) through normative modeling of cross-cultural cohorts. By leveraging large-scale datasets from Autism Brain Imaging Data Exchange (ABIDE) and China Autism Brain Imaging Consortium (CABIC), our model identifies two ASD subgroups with distinct brain morphological abnormalities: subgroup "L" is characterized by generally smaller brain region volumes and higher rates of abnormality, while subgroup "H" exhibits larger volumes with less pronounced deviations in specific areas. Key areas, such as the isthmus cingulate and transverse temporal gyrus, were identified as critical for subgroup differentiation and ASD trait correlations. In subgroup H, the regional volume of the isthmus cingulate cortex showed a direct correlation with individuals autistic mannerisms, potentially corresponding to its slower post-peak volumetric declines during development. These findings offer insights into the biological mechanisms underlying ASD and support the advancement of subgroup-driven precision clinical practices.

neuroscience↗