Science Bulletin

Profound heterogeneity in Autism Spectrum Disorder (ASD) complicates diagnosis and the development of effective treatments. In healthcare systems with limited specialist resources, the need for rapid and accessible screening tools is particularly urgent. In the present study, we developed an objective, scalable pipeline that pairs a simple two-minute video recording of a childs naturalistic behavior with a deep AI model for autism detection, representing the first such rapid, scalable framework. By analyzing a rich spectrum of childrens responses to social stimuli, such as subtle behavioral patterns, gaze dynamics, facial morphology, and dynamic facial complexity, the deep AI model provides powerful support for clinical workflows, demonstrating high accuracy in identifying ASD risk across diverse internal and external test cohorts, irrespective of sex, age, or cognitive function. Furthermore, a series of comprehensive analyses confirmed the models clinical relevance and revealed its capacity to objectively stratify ASD heterogeneity into neurobiologically distinct subtypes. This work establishes a highly efficient and objective framework for large-scale screening, providing a data-driven foundation to stratify heterogeneity and paving the way for the future development of targeted interventions.

Asthma is a long-term inflammatory disease affecting airways and lungs with usual onset in childhood. Its cause is not fully understood up to now. Here, using single-cell RNA sequencing, we profile peripheral blood mononuclear cells (PBMCs) from three pediatric patients with onset asthma and four age-matched healthy controls to investigate the cellular etiology of childhood asthma. The overall expression features among three asthma patients PBMCs demonstrate that innate immunity is commonly upregulated while adaptive immunity is commonly downregulated in childhood asthma, but each patient has different molecular phenotypes. The analyses of the expression profiles of hematopoietic stem and progenitor cells (HSPCs) further show that the HSPCs of asthma patients have heterogeneous expression backgrounds with more specific differentially expressed genes (DEGs) in each patient than common DEGs and a common feature of low S100 protein binding gene expression. S100A8, S100A9, S100A12, and RETN are universally upregulated in various cell types of asthma patients. The cell developmental trajectories in three asthma cases exhibit an abnormal immune cell development pattern compared to that in health control. The dysregulated lymphoid lineage development is observed in all 3 patients, but there is no identical abnormal pattern for each patient. The pseudo-time analyses of gene expression show that the expression dynamics of two proto-oncogenes, JUN and SPI1, and six inflammatory response related genes (S100A8, S100A9, S100A12, IL7R, IL32, CCL5) are relevant to abnormal immune cell development in asthma patients. The cell-cell communication analyses reveal the contribution of incoming annexin signal towards dendritic cells and the outgoing resistin signal from dendritic cells to asthma heterogeneity. Interestingly, the plasma blast cells of asthma patient 3 with severe symptoms exhibit dual cell identities of both plasma blast cells and T cells. Our scRNA-Seq analyses for three asthma patients reveal a complex cellular etiology for childhood asthma and provide a new research direction for the comprehensive and systematic understanding of key molecular mechanisms of childhood asthma.

Individuals with autism spectrum disorder (ASD) have a higher prevalence of social memory impairment. A series of our previous studies revealed that hippocampal ventral CA1 (vCA1) neurons possess social memory engram and that the neurophysiological representation of social memory in the vCA1 neurons is disrupted in ASD-associated Shank3 knockout mice. However, whether the dysfunction of Shank3 in vCA1 causes the social memory impairment observed in ASD remains unclear. In this study, we found that vCA1-specific Shank3 conditional knockout (cKO) by the adeno-associated virus (AAV)- or specialized extracellular vesicle (EV)-mediated in vivo gene editing was sufficient to recapitulate the social memory impairment in male mice. Furthermore, the utilization of EV-mediated Shank3-cKO allowed us to quantitatively examine the role of Shank3 in social memory. Our results suggested that there is a certain threshold for the proportion of Shank3-cKO neurons required for social memory disruption. Thus, our study provides insight into the population coding of social memory in vCA1, as well as the pathological mechanisms underlying social memory impairment in ASD.

Early life stress (ELS), such as abuse, neglect, and maltreatment, is a well-known risk factor for mental illness. However, it is unclear how ELS affects the brain and cognitive development. Identifying specific relationships of ELS with the genetic and brain-related underpinnings of cognitive development may reveal biological mechanisms responsible for the negative impact of ELS and those that lead to individual differences in sensitivity (or resilience) to ELS. In this study, to investigate the interlinked processes of cognitive development, we analyzed the multimodal data of DNA genotypes, brain imaging (MRI), and neuropsychological assessment (NIH Toolbox) outcomes of 4,276 children (ages 9 to 10 years, European ancestry) from the Adolescent Brain Cognitive Development (ABCD) study. We estimated the genetic influence on cognitive capacity using genome-wide polygenic scores (GPSs). Our regression and mediation analyses revealed significant causal relationships for the gene-brain-cognition pathway: Brain structural development significantly mediated the genetic influence on cognitive development (partial mediation effect = 0.016, PFWE<0.001). Interestingly, within the triangular relationship, we found a significant moderation effect of abuse only on the gene-to-brain pathway (Index of Moderated Mediation = -0.007; 95% CI= -0.012 [~] -0.002; PFWE<0.05). These findings indicate the negative modulatory effects of ELS on the genetic influence on brain structural development that lead to disadvantageous neurocognitive development in prepubertal children.

Keshan disease (KD), an endemic heart disease with multifocal necrosis and replacement fibrosis of the myocardium,is still a nightmare situation for human health. However, molecular mechanism in the pathogenesis of KD remains unclear. Herein, blood samples were collected from 68 KD patients and 100 controls, and we systematically analyzed mutation profiles using whole-exome sequencing (WES). Causative genes of dilated cardiomyopathy (DCM), gene-based burden analysis, disease and pathway enrichment analysis, and protein-protein interaction (PPI) network analysis were performed. Of the 98 DCM-causative genes, 106 rare variants in 28 genes were detected in KD patients with minor allele frequency (MAF) < 0.001. Gene-based burden analysis, PPI network analysis, and automated Phenolyzer analysis were performed to prioritize 199 candidate genes, which combined with 98 DCM-causative genes, and reference genes from gene microarray or proteomics in KD. Then, 19 candidate pathogenic genes were selected, and 9 candidate genes were identified using PPI analysis, including HIF1A, GART, ALAD, VCL, DTNA, NEXN, INPPL1, NOS3, and JAK2. The 199 candidate genes were further analyzed using disease enrichment with CTD database and PPI analysis, and 21 candidate genes were identified. By combining with disease enrichment and PPI analysis, 7 Selenium (Se)-related genes were further identified, including ALAD, RBM10, GSN, GGT1, ADD1, PARP1, and NOS3. Based on the gene function and data validation, NEXN, TAF1C, FUT4, ALAD, ZNF608, and STX2 were the most likely pathogenic genes in KD. Notably, ALAD is the only candidate pathogenic gene identified by four different analyses, and its homozygous mutant mice could affect heart development and cause death.

Although COVID-19 pediatric patients just account for 1% of the overall cases, they are nonnegligible invisible infection sources. We quantitatively analyzed the clinical and epidemiological features of 82 confirmed cases aged 0-16 admitted to Wuhan Childrens Hospital, which are expected to shed some lights onto the pediatric diagnosis and therapy.

Autism Spectrum Disorder (ASD) is a lifelong neurodevelopmental condition characterized by atypical brain growth. While advances in neuroimaging and openly sharing large-sample datasets such as the Autism Brain Imaging Data Exchange (ABIDE) have improved understanding of ASD, most studies focus on adolescents and adults, with early brain development-critical for diagnosis and intervention-remaining underexplored. Existing research predominantly involves Western samples, offering limited insight and generalizability into non-Caucasian populations. We introduce the China Autism Brain Imaging Consortium (CABIC) (https://php.bdnilab.com/resources/), a grassroots effort by researchers across the country to aggregate previously collected multi-site structural MRI datasets and phenotypic information from 1,451 autistic children and 1,119 typically developing children, covering an age range from early childhood to school age (1.0 - 12.92 years). Here, we present this resource and depict brain growth charts to push forward a more comprehensive understanding of the brain development in Chinese autism children. We constructed brain growth charts that reveal a developmental shift in autistic children, transitioning from early overgrowth to delayed maturation. Regional analyses identified distinct atypical trajectories across specific brain regions. Individual deviation scores quantified inter-subject variability, characterizing the heterogeneity of brain development in ASD. Comparative analyses between CABIC and ABIDE highlighted differences potentially attributable to ethnicity and culture, advancing our understanding of cross-population neurodevelopmental diversity. CABIC MRI datasets will be shared publicly to foster investigation of the potential neural mechanisms underlying ASD in non-Western populations and support efforts toward precision medicine for autistic individuals across diverse backgrounds.

A novel coronavirus (2019-nCoV) or Severe acute respiratory syndrome corona virus 2 (SARS-CoV-2) that affects humans has been discovered in Wuhan, China, in 2019. Its genome has been sequenced, and the genetic data was quickly made public. We discovered a novel proprotein convertase subtilisin kexin-9 (PCSK9) cleavage site in the Spike protein of the 2019-nCoV. The recent research also demonstrates that the previously found proprotein convertase 3 (PC3) or furin cleavage site, which was assumed to be unique, is already present in animal corona viruses. In this article, we suggest that the combination of the both proprotein convertase PC3 cleavage site and the PCSK9 site renders SARS-CoV-2 unique in terms of the pathogenicity, potential functional effects, and implications for the development of antiviral drugs.

Three-dimensional chromatin structures regulate gene expression across genome. The significance of de novo mutations (DNMs) affecting chromatin interactions in autism spectrum disorder (ASD) remains poorly understood. We generated 931 whole-genome sequences for Korean simplex families to detect DNMs and identified target genes dysregulated by noncoding DNMs via long-range chromatin interactions between regulatory elements. Notably, noncoding DNMs that affect chromatin interactions exhibited transcriptional dysregulation implicated in ASD risks. Correspondingly, target genes were significantly involved in histone modification, prenatal brain development, and pregnancy. Both noncoding and coding DNMs collectively contributed to low IQ in ASD. Indeed, noncoding DNMs resulted in alterations, via chromatin interactions, in target gene expression in primitive neural stem cells derived from human induced pluripotent stem cells from an ASD subject. The emerging neurodevelopmental genes, not previously implicated in ASD, include CTNNA2, GRB10, IKZF1, PDE3B, and BACE1. Our results were reproducible in 517 probands from MSSNG cohort. This work demonstrates that noncoding DNMs contribute to ASD via chromatin interactions.

Neuroanatomical tracing technology is fundamental for unraveling the complex network of brain connectome. Tracing tools that could spread between neurons are urgently needed, especially the rigorous trans-monosynaptic anterograde tracer is still lacking. HSV1 strain H129 was proved to be an anterograde tracer and has been used to trace neuronal networks in several reports. However, H129 has a serious defect that it was demonstrated to infect neurons via axon terminals. Thus, when using H129 to dissect output neural circuit, its terminal take up capacity should be carefully considered. Here, we report a recombinant H129 that carrying the anti-Her2 scFv in glycoprotein D to target genetically defined neurons. With the usage of helper virus complementarily expressing Her2 and gD, we can realize the elucidation of direct projection regions of either a given brain nucleus or a specific neuron type. The retargeted H129 system complements the current neural circuit tracer arsenal, which provides a rigorous and practical anterograde trans-monosynaptic tool.

While medication use is common among pregnant women, medication safety remains insufficiently characterized because studies in pregnant women are challenging due to safety concerns. The recent digitization of healthcare databases and advances in computational methods have created new opportunities for large-scale, retrospective drug safety evaluations. Here, we present PregMedNet, a platform that characterizes multifaceted maternal medication effects on neonatal outcomes during pregnancy, covering more than 27,000 drug-disease pairs across 1,152 medications and 24 outcomes. These results encompass known and novel odds ratios (ORs), adjusted ORs, and drug-drug interactions, systematically analyzed using nationwide claims data and an advanced machine learning pipeline. Notably, one of the newly discovered associations was experimentally validated in vivo. This supports the reliability of PregMedNets findings and demonstrates the utility of claims data and machine learning for perinatal medication safety studies. Additionally, potential biological mechanisms underlying the associations were explored using a graph learning method, providing candidate pathways for future mechanistic investigations. We expect that PregMedNet will contribute to advancing maternal medication safety and improving neonatal outcomes by providing extensive, multifaceted drug safety information on this previously underrepresented population.

Human pluripotent stem cell (hPSC)-derived brain organoids offer an unprecedented opportunity for various applications as an in vitro model, such as modeling virus infection and drug screening. In this study, we present an experimental brain organoid platform for modeling infection with multiple viruses (e.g., influenza virus or enterovirus). Brain organoids challenged by influenza viruses (H1N1-WSN and H3N2-HKT68) had decreased overall organoid size, similar to ZIKA virus infection, while enteroviruses (EV68 and EV71) infected brain organoids displayed the opposite result. Then, we studied the molecular events in WSN-infected organoids, and we found that WSN could widely infect multiple cell types, and preferentially infected MAP2+ neurons compared to SOX2+ neural stem cells (NSCs) and GFAP+ astrocytes in brain organoids, and induced apoptosis of NSCs and neurons, but not astrocytes. The inflammatory responses in organoids observed to occur (Tumor necrosis factor alpha, interferon gamma, and interleukin 6) after WSN infection may further facilitate brain damage. Furthermore, transcriptional profiling revealed several upregulated genes (CSAG3 and OAS2) and downregulated genes (CDC20B, KCNJ13, OTX2-AS1, CROCC2, and F5) after WSN infection for 24 hpi and 96 hpi, implicating antiviral drugs development responses to WSN. Finally, we explored neurotrophic factors (e.g., BDNF, GDNF, and NT3) and PYC-12 as antiviral and neuroprotective reagents, which could significantly suppress virus infection, apoptosis, and inflammatory responses. Collectively, we established a tractable experimental model system to investigate the impact and mechanism of virus infection on human brain development, and provide a platform for rapidly screening therapeutic compounds, advancing the development of antiviral strategies.

This study proposes a novel spatiotemporal connectome-based framework to characterize the human brains action network, namely network affinity, moving beyond traditional static temporal connectivity measures by leveraging full functional connectivity profiles on large-scale neural wave dynamics. We applied this method to map the action network for the first time in a non-Western young adult cohort from the Chinese Human Connectome Project (CHCP). Our results delineate the action networks detailed functional affinity architecture, capturing its integrative topology across the cerebral cortex, cerebellum, and subcortical nuclei, and its characteristic anticorrelation with the default network. All the findings are replicated in HCP samples. Crucially, all derived high-resolution action network affinity maps and the associated computational code are publicly shared to foster open science and reproducibility (https://ccndc.scidb.cn/en). This work provides a foundational atlas and a new analytical approach, establishing a critical resource for future basic research across diverse populations and lifespans. It also holds significant translational potential for understanding and treating neurological and psychiatric disorders affecting goal-directed behavior, such as apathy and Parkinsons disease.

The elegant functions of the brain are facilitated by sophisticated connections between neurons, the architecture of which is frequently characterized by one nucleus connecting to multiple targets via projection neurons. Delineating the sub-nucleus fine architecture of projection neurons in a certain nucleus could greatly facilitate its circuit, computational, and functional resolution. Here, we developed multi-fluorescent rabies virus to delineate the fine organization of corticothalamic projection neuron subsets in the primary visual cortex (V1). By simultaneously labeling multiple distinct subsets of corticothalamic projection neurons in V1 from their target nuclei in thalamus (dLGN, LP, LD), we observed that V1-dLGN corticothalamic neurons were densely concentrated in layer VI, except for several sparsely scattered neurons in layer V, while V1-LP and V1-LD corticothalamic neurons were localized to both layers V and VI. Meanwhile, we observed a fraction of V1 corticothalamic neurons targeting multiple thalamic nuclei, which was further confirmed by fMOST whole-brain imaging. We further conceptually proposed an upgraded sub-nucleus tracing system with higher throughput (21 subsets) for more complex architectural tracing. The multi-fluorescent RV tracing tool can be extensively applied to resolve architecture of projection neuron subsets, with a strong potential to delineate the computational and functional organization of these nuclei.

In the search for treatment schemes of COVID-19, we start by examining the general weakness of coronaviruses and then identify approved drugs attacking that weakness. The approach, if successful, should identify drugs with a specific mechanism that is at least as effective as the best drugs proposed and are ready for clinical trials. All coronaviruses translate their non-structural proteins ([~]16) in concatenation, resulting in a very large super-protein. Homo-harringtonine (HHT), which has been approved for the treatment of leukemia, blocks protein elongation very effectively. Hence, HHT can repress the replication of many coronaviruses at the nano-molar concentration. In two mouse models, HHT clears SARS-CoV-2 in 3 days, especially by nasal dripping of 40 ug per day. We also use dogs to confirm the safety of HHT delivered by nebulization. The nebulization scheme could be ready for large-scale applications at the onset of the next epidemics. For the current COVID-19, a clinical trial has been approved by the Ditan hospital of Beijing but could not be implemented for want of patients. The protocol is available to qualified medical facilities.

Understanding the differences between genomic sequences of different lives is crucial for biological classification and phylogeny. Here, we downloaded all the reliable sequences of the seven kingdoms and determined the dimensions of the genome space embedded in the Euclidean space, along with the corresponding Natural Metrics. The concept of the Grand Biological Universe is further proposed. In the grand universe, the convex hulls formed by the universes of seven kingdoms are mutually disjoint, and the convex hulls formed by different biological groups within each kingdom are mutually disjoint. This study provides a novel geometric perspective for studying molecular biology and also offers an accurate way for large-scale sequence comparison in a real-time manner. Most importantly, this study shows that, due to the space-time distortion in the biological genome space similar to Einsteins theory, it is futile to look for a single metric to measure different biological universes, as previous studies have done.

Understanding social difficulties in Autism Spectrum Disorder (ASD) remains challenging due to its neurobiological heterogeneity and the limited ecological validity of conventional neuroimaging methods in capturing dynamic social interactions. Hyperscanning analysis based on functional near-infrared spectroscopy (fNIRS), which measures inter-brain synchrony (IBS) during dyadic interaction, offers a novel avenue to address these challenges. However, prior studies on ASD have reported inconsistent findings, primarily focusing on intra-regional synchronization while overlooking cross-regional network dynamics. To bridge this gap, we proposed an interpretable graph neural network (GNN) model to systematically identify ASD-specific IBS modular network between child-caregiver dyads during naturalistic cooperative puzzle-solving and free-talking tasks. We identified distinctive key IBS sub-networks for the cooperative puzzle-solving task and free-talking task, with the frontal eye field (FEF) of caregivers, the dorsal lateral prefrontal cortex (DLPFC) and the motor region of children highlighted. Furthermore, the key IBS sub-networks were found to be able to predict multiple domains of the core ASD symptoms. By integrating hyperscanning with GNN-driven analysis, this work uncovers task-dependent inter-brain neural mechanisms underlying social difficulties in ASD. These findings advance the field by proposing a data-driven framework to identify IBS biomarkers tied to clinical profiles, paving the way for personalized interventions that integrate computational neuroscience with clinical practice.

The ongoing global monkeypox virus (MPXV) outbreak urgently needs effective medications, which be accelerated through drug repurposing. However, it is challenging to poinpoint protein targets. Here we introduce a novel method rooted in molecular evolutionary theory for quick drug target identification for MPXV. It identifies drug targets as positively selected genes of viral proteins which bind host proteins. From the identified targets, we select a top gene product OPG021 for virtural drug screening. One top-ranked drug nilotinib is experimentally shown to have a significant 69% of antiviral efficacy of the FDA-approved antiviral tecovirimat (TPOXX(R) or ST-246). Higher binding affinity but not antiviral efficacy of repursposed drugs than FDA-approved drugs suggests the complexity of drug repurposing and underscores the importance of experimental validation. This innovative drug target identification strategy will contribute to combating the ongoing MPXV outbreak and other viral acute and chronic viral diseases.

Adverse perinatal factors can disrupt the normal development of the brain, with potential long-term impacts on childrens overall development. Currently, the neuropathological mechanisms by which these factors lead to various neurodevelopmental disorders (NDDs) remain largely unknown. An open resource that integrate perinatal factors with brain and mental health development is essential for investigating NDD-related aetiology. In this Data Descriptor, we introduce a multicentre database containing information on perinatal factors that influence childrens brain-mind development, namely, periCBD, that combines neuroimaging and behavioural phenotypes with perinatal factors associated with a high incidence of NDDs at county/region/central district hospitals. PeriCBD was designed to establish a platform for the investigation of individual differences in brain-mind development among children aged 3-10 years are associated with perinatal factors. Ultimately, our goal was to develop an early prediction and screening model for NDDs that leverages normative data to facilitate NDD aetiology research. Herein, we provide a systematic overview of the data acquisition/cleaning/quality control/sharing, processes of periCBD and present preliminary brain-mind associations.

Neurotropic virus tracers, particularly those with low toxicity and high efficient tracing, are powerful tools for structural and functional dissections of neural circuits. The retrograde trans-mono-synaptic technology based on rabies virus CVS-N2c strain has reduced cytotoxicity and enhanced efficiency, attains long-term gene manipulation for functional studies, but suffers from difficult preparation and low yield. To overcome these shortcomings, an improved production system was established for rapid rescue and preparation of CVS-N2c-{Delta}G virus, CVS-N2c-{Delta}G with the same titer as SAD-B19-{Delta}G can be prepared within a short time. Meanwhile, we found that N2cG coated CVS-N2c-{Delta}G allows efficient retrograde access to projection neurons, and further expand its application in VTA/SNc to DLS pathway that unaddressed by rAAV9-Retro, and the efficiency is 6 folds higher than that of rAAV9-Retro. Then the trans-synaptic efficiency of CVS-N2c-{Delta}G virus was evaluated. Results showed that the trans-mono-synaptic efficiency of oG-mediated CVS-N2c-{Delta}G was 2-3 folds higher than that of oG-mediated SAD-B19-{Delta}G, but there was no difference between oG-mediated and N2cG-mediated CVS-N2c-{Delta}G system. In addition, codon modified N2cG (optiG) did not increase the efficiency of CVS-N2c-{Delta}G tracing. Finally, we found that the CVS-N2c-{Delta}G produced by the improved method can be used for monitoring neural activity of projection neurons, and the time window can be maintained for 3 weeks, and it can also express sufficient recombinases for efficient transgene recombination. That is, the virus produced by the improved production system does not affect its own function, paving the way for its further optimization, popularization and application in structural and functional studies of neural circuits.