Biology subjects

Guo, J.

Publications and source records attributed to Guo, J..

At least 55 records · Page 3Linked to original sources

bioRxiv2026

Nuclear Pct1 couples phosphatidylcholine synthesis with membrane biogenesis

Phosphatidylcholine (PC) is the major eukaryotic phospholipid and its synthesis must be homeostatically controlled to prevent excess membrane and organelle growth. Here we investigate how PC synthesis by the Kennedy pathway is coordinated with membrane biogenesis. In budding yeast, the rate-limiting enzyme Pct1 is nuclear and reversibly associates with the inner nuclear membrane (INM) in response to lipid packing defects caused by low PC. We show that the enzymes acting after Pct1 to generate PC remain at the endoplasmic reticulum (ER) during pathway activation. Relocating the final PC synthesis step to different endomembrane sites does not alter the kinetics of Pct1 release from the INM, indicating that newly made PC equilibrates with the INM rapidly. In contrast, elevated phosphatidic acid locks Pct1 at the INM, prevents pathway inactivation and drives nuclear/ER membrane proliferation. These results support a model in which nuclear Pct1 senses lipid imbalance while ER-localized enzymes supply PC; disrupting this homeostasis leads to uncontrolled membrane biogenesis.

cell biology↗

bioRxiv2026

Protocadherin 9 promotes cell survival of different bipolar subtypes in the developing mouse retina

Neural circuit assembly relies on different neuronal subtypes coming together to form a functional circuit. The question of how the appropriate number of each subtype is integrated into an emerging circuit remains relatively unknown. To answer this question, we used the mouse retina to uncover the molecular mechanisms responsible for neuron subtype integration in a developing circuit. In the mammalian retina, bipolar neurons are a class of interneurons that relay visual information from photoreceptors to ganglion cells. Extensive studies have shown there are 15 distinct bipolar subtypes: 6 types of OFF cone bipolars, 8 types of ON cone bipolars, and 1 type of rod bipolar. During retinal development, bipolar neurons are born in excess and through programmed cell death, a precise number of each subtype remains to give rise to the retinal circuit. Although this process has been well-described, little is known about the key molecules responsible for bipolar subtype integration in the developing retina. Our work uncovered a new role for the autism-associated risk gene, Protocadherin 9 (Pcdh9) in bipolar subtype integration. Deletion of Pcdh9 using a floxed allele leads to loss of OFF and ON cone bipolars; however, disruption in the extracellular binding of Pcdh9 leads to selective loss of ON cone bipolars but not rod bipolars. Moreover, we found this later function of Pcdh9 is mediated by homophilic interactions between ON cone bipolars and their known synaptic partners. Taken together, our work revealed a new role for Pcdh9 in bipolar subtype integration during retinal development. SUMMARY STATEMENTNeural circuits are comprised of multiple neuronal subtypes where a specific number need to come together to give rise to a functional circuit. Although this is a critical process during neurodevelopment, little is known about the molecular mechanisms that determines the precise number of each subtype during circuit development. In the present study, we identified the autism risk gene, Protocadherin 9 as a critical molecule in subtype integration of bipolar neurons within the developing mouse retina. Using newly generated mouse lines, we found distinct requirements of Pcdh9 to promote survival in different bipolar subtypes during retinal circuit assembly. The significance of this work is that it shed lights into how different neuronal subtypes are integrated in nascent neural circuits.

neuroscience↗

bioRxiv2026

eBiota: Designing microbial communities from large seed pools with desired function using rapid optimization and deep learning

Designing microbial communities to generate target products is crucial for biotechnology, agriculture, and disease treatment. However, rationally designing such communities from large seed pools has become a major challenge, as the rapidly expanding number of complete microbial genomes greatly expands the search space and sharply increases the required screening time and computational cost. Here, we introduce eBiota, a platform for ab initio design of microbial communities from a pool of 21,514 strains to generate target products. eBiota not only identifies optimal strain combinations but also simulates community behaviors, including microbial interactions and relative abundances. eBiota integrates three modules: CoreBFS, a graph-based search algorithm that rapidly screens for bacteria with complete metabolic pathways related to the target product; ProdFBA, an extended flux balance analysis that identifies microbial consortia with maximal production efficiency; and DeepCooc, a deep learning model trained on 23,323 microbiome samples across various environments to infer co-occurrence patterns. We validated eBiotas capabilities in microbial community design and production efficiency calculation using public microbiome datasets, ranging from single strains to six-member consortia. Further in vitro experiments involving 94 strains confirmed eBiotas ability to identify species that inhibit pathogen growth and to accurately model the relative abundances within complex microbial communities. As an initial digital twin, eBiota provides a powerful platform for the rational design of functional microbial communities, offering new opportunities for metabolic engineering and synthetic biology.

bioengineering↗

bioRxiv2026

KuafuPrimer: Machine learning empowers the design of 16S amplicon sequencing primers toward minimal bias for bacterial communities

Amplicon sequencing protocol targeting the 16S rRNA gene is a widely used and cost-effective method for exploring bacterial communities. However, its performance is often limited by primer bias arising from the arbitrary use of universal primers across diverse microbial communities and habitats. We propose KuafuPrimer to design the optimal 16S rRNA gene primers toward minimal bias for targeted bacterial communities, using few-shot machine learning to guide the primer design procedure based on a small number of samples. Simulations on 809 samples across 26 representative environments and habitats showed that KuafuPrimer-designed primers outperformed the universal primers in taxonomic accuracy, achieving an averaged 16.31% relative reduction in primer bias, with reductions up to 46.08% in plant samples. Notably, KuafuPrimer detected 29 rare and key taxa undetectable by the universal primers. Validation with 317 longitudinal gut microbiota samples demonstrated that KuafuPrimer-designed primers consistently outperformed the universal primers across temporal, individual, and cohort levels, with relative bias reductions of 5.03%, 3.53%, and 3.10%, respectively. Finally, in real PCR experiments on human gut samples from Clostridioides difficile-infected and healthy groups showed that polymerase chain reaction products using KuafuPrimer-designed primers correlated better with metagenomic data compared to the universal primers. More importantly, KuafuPrimer successfully detected Clostridioides difficile, the key pathogen missed by the universal primers, highlighting its potential for improving clinical diagnostics. In summary, KuafuPrimer provides a machine learning-based primer design strategy for targeted bacterial communities, with demonstrated utility in large-scale microbiome initiatives, longitudinal surveys and clinical diagnostics.

bioinformatics↗

bioRxiv2026

Neuronal overexpression of Nrf2 reduces dystrophic neurites in 5XFAD Alzheimer's disease model mice

BackgroundThe hallmark lesions of the Alzheimers disease (AD) brain are amyloid plaques consisting of the {beta}-amyloid protein and neurofibrillary tangles comprised of hyperphosphorylated, aggregated tau protein, which both cause neuronal dysfunction and loss. One goal of neuroprotective therapies is to maintain normal neuronal function and survival in the presence of toxic pathologies such as plaques and tangles. A potential neuroprotective target is nuclear factor erythroid 2-related factor 2 (Nrf2) transcription factor, which regulates the expression of many antioxidant and detoxification genes. Nrf2 mRNA is decreased in AD brains, and deletion of the Nrf2 gene causes increased BACE1 and A{beta} production and worsened cognitive deficits in amyloid pathology mouse models. Overexpression of Nrf2 in astrocytes has been shown to be protective against neurodegeneration, but the role of Nrf2 is neurons is unclear. MethodsWe overexpressed Nrf2 from birth in neurons of 5XFAD amyloid pathology model mice using AAV8, hypothesizing that neuronal Nrf2 overexpression decreases cortical neuron loss and reduces plaque load by decreasing BACE1 levels. We quantified protein levels by immunoblot and neuropathology by immunofluorescent staining, using two-way ANOVA to measure differences between genotypes and AAV treatments. To assess genetic changes, we performed bulk mRNA seq. ResultsWhile neuronal overexpression of Nrf2 in 5XFAD mice did not prevent neuronal loss as measured by NeuN labeling, decrease neuroinflammation by Iba1 or GFAP labeling, or reduce amyloid load by A{beta} antibody or methoxy-XO4 staining, we show that increased Nrf2 expression reduces BACE1 protein levels, especially in swollen axonal dystrophic neurites around amyloid plaques. Other proteins that accumulate in dystrophic neurites were also reduced, indicating decreased dystrophic neurites overall. Immunoblot analysis suggested increased autophagy was unlikely to play a role, while bulk mRNA sequencing indicated changes in lipid metabolism and microtubule stability may have contributed to reduced dystrophic neurite formation. ConclusionsDystrophic neurites impair action potential conductance and contribute to tau seeding and spreading. Their reduction by neuronal Nrf2 overexpression may protect neurons against these pathologic changes. Further study of the mechanisms by which Nrf2 reduces dystrophic neurites may lead to therapeutic strategies that can limit neuritic damage caused by cerebral amyloid accumulation.

neuroscience↗

bioRxiv2026

Functional impact of PCSK9 variants on LDL uptake in a knockout hepatic model

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a central regulator of low-density lipoprotein (LDL) cholesterol metabolism, yet the functional consequences of many clinically observed PCSK9 variants remain unknown. To establish a rigorous system for quantitative variant assessment, we generated a PCSK9 knockout (KO) HepG2 cell line through CRISPR/Cas9-mediated deletion of exons 2-8, effectively removing both the prodomain and catalytic regions required for PCSK9 function. This null background enabled systematic functional mapping of wild-type (WT) PCSK9 and multiple clinically relevant variants representing well-characterized, recurrent, and previously understudied alleles. Functional assays revealed pronounced heterogeneity among variant activities. The classical gain-of-function (GOF) variants D374Y and R496W exhibited robust suppression of LDL uptake, whereas A443T--an infrequently reported and previously uncharacterized variant--demonstrated a loss-of-function (LOF)-like phenotype with significantly enhanced LDL uptake. Additional poorly characterized variants, including V4I, R104C/V114A, and R496W/N425S, displayed minimal functional profiles, providing novel mechanistic insights. Surface LDL receptor (LDLR) levels generally correlated with LDL uptake but revealed unique patterns for specific variants. This KO-based rescue system provides a high-resolution framework for mechanistic classification of both established and poorly characterized PCSK9 variants, bridging the gap between genetic discovery and functional interpretation while supporting precision lipid-lowering strategies.

biochemistry↗

bioRxiv2026

Sex-Specific Vulnerability to Radiofrequency Electromagnetic Radiation-Induced Reproductive and Neurological Impairment in Mice

Electromagnetic radiation (EMR) constitutes a pervasive environmental stressor, yet the sex-specific vulnerabilities to its biological effects remain inadequately characterized. This study investigated the differential impacts of 3.2 GHz pulsed EMR on reproductive and neurological functions in male and female mice following a four-week exposure regimen. We identified a pronounced sexual dimorphism in systemic and organ-specific responses. Male mice exhibited a primary vulnerability in the reproductive axis, manifesting as severe spermatogenic impairment, including depletion of the spermatogonial stem cell pool, disruption of sperm chromatin remodeling, and consequent declines in sperm quality and quantity. In contrast, exposed females showed preserved ovarian function but displayed marked neurobehavioral deficits, including increased anxiety- and depressive-like behaviors, and cognitive impairment, which were correlated with neurodegeneration in the hippocampus and prefrontal cortex. Proteomic analyses revealed distinct sex-specific biomarker profiles, with serum levels of Mdk, histone H1 variants (H1-1, H1-4, H1-5), Hp1bp3, Ncf2, and Rhoc strongly associated with male testicular dysfunction, while decreased levels of the synaptic motor protein KIF13A in serum and brain tissue were linked to female neurological impairment. Our findings delineate clear sex-divergent pathological pathways that target male spermatogenesis and female neurocognitive function and propose novel circulating protein biomarkers. This work provides a critical foundation for sex-aware risk assessment and the development of targeted preventive strategies against EMR-associated health risks.

pathology↗

bioRxiv2026

Assembling a fully-dated complete tree of life

Time-scaled phylogenetic trees summarising evolutionary relationships are fundamental to many analyses in biology, from diversification rate estimation to conservation prioritisation. The most comprehensive available summary of these relationships, the Open Tree of Life, synthesises information from over two thousand studies into a supertree covering the full range of global biodiversity, but its use in downstream analyses is limited by the lack of divergence times. Previous work has mapped dates from Open Trees database of trees to certain nodes in the supertree, but for the majority of nodes no date is available. While algorithms exist to interpolate missing dates in a tree, we found that their time and memory requirements scaled quadratically with the number of nodes, which made it computationally infeasible to run them on the entire tree. In this work, we describe novel date interpolation algorithms that scale linearly with the number of nodes. These enabled us to produce a distribution of fully-dated trees containing 2.3 million extant described species, greatly expanding the scope of feasible phylogenetic analyses. We illustrate the utility of these trees by computing the most robust estimate yet of the phylogenetic diversity of the complete tree of life, incorporating both topological and temporal uncertainty.

evolutionary biology↗

bioRxiv2026

A foundation AI model enhances electron microscopy image analysis

Electron microscopy (EM) and advanced volume EM have extensive applications in deciphering cellular ultrastructures for life sciences. However, quality issues of EM images significantly impede the precise analysis and discovery of nanoscale biological structures. Here, we present an unsupervised Foundation Model for Five Tasks (DF5T) model for image enhancement through denoising, deblurring, super-resolution, two-dimensional (2D) inpainting, and three-dimensional (3D) isotropic restoration. DF5T was trained on an extensive dataset of multi-source membrane-bound organelle EM images, consisting of a total of over 2.25 million images. On unseen data, DF5T outperformed the existing state-of-the-art models in all five tasks. Furthermore, DF5T substantially compensates for missing three-dimensional structural information and reveals significant ultrastructural alterations in organelle geometry following chemical treatment. We demonstrate that DF5T significantly enhances electron microscopy images quality by improving the accuracy of downstream organelle segmentation and 3D structural restoration, thereby contributing to future advances in biological research.

cell biology↗

bioRxiv2026

Nitro Reduction-Based RNA Control and Ultrafast Release

RNA protection and controlled release are critical for both fundamental research and therapeutic applications, yet the development of simple, efficient, and reversible post-synthetic RNA modification strategies remains a significant challenge. Here, we introduce a straight forward approach based on ribose 2'-hydroxyl acylation with a nitro-functionalized carbamate, which acts as a redox-responsive center. This modification selectively inhibits native RNA function while remaining inert to endogenous biogenic reductants and common reducing agents used in biological assays. Upon treatment with low millimolar concentrations of the THDB- BIPY reducing pair, RNA function is rapidly restored on a minute timescale. This methodology is broadly applicable across diverse RNA classes and functional contexts, including synthetic RNA oligomers, fluorogenic RNA aptamers, single-guide RNAs in CRISPR-Cas9 gene-editing systems, and mRNAs in living cells for translation control and RNAi-mediated gene silencing. These results demonstrate the general utility of this approach as a chemically controllable functional switch, providing a versatile toolkit for temporal regulation of RNA activity in both research and biotechnological applications.

biochemistry↗

bioRxiv2026

Stool Metabolomics Reveals Catecholamine and Tryptophan-NAD+ Pathway Alterations in Autism Spectrum Disorder

Gut-brain axis dysregulation and microbiome-linked metabolic disturbances have been implicated in autism spectrum disorder (ASD), yet gut-derived neuroactive metabolites remain incompletely characterized. We applied targeted liquid chromatography-tandem mass spectrometry in a cross-sectional case-control study to quantify 18 stool metabolites related to catecholamine synthesis, GABAergic signaling, and tryptophan (Trp) and NAD+ metabolism in 59 participants (32 ASD, 27 non-ASD controls). Group differences were evaluated using log2 fold change and covariate-adjusted linear models. Random forest classifiers with five-fold cross-validation assessed multivariate discriminative performance, and within-group Spearman correlations examined metabolic network organization. Norepinephrine exhibited the largest elevation in ASD, while dopamine and tetrahydrobiopterin showed nominal group effects consistent with altered BH4-dependent catecholamine metabolism. Among individual metabolites, tetrahydrobiopterin, GABA, and kynurenine were the most informative, and their combination achieved an area under the receiver operating characteristic curve of 0.737 (95% confidence interval, 0.603 to 0.871). Correlation analyses revealed conserved lithocholic acid-deoxycholic acid coupling in both groups. In controls, Trp correlated with kynurenine, whereas ASD showed expanded Trp associations with GABA, norepinephrine, anandamide, and nicotinic acid, consistent with reorganization of Trp-NAD+ precursor pathways. These findings identify coordinated, gut-linked metabolic differences in ASD and define a metabolite signature reflecting altered catecholaminergic and Trp-related network structure. ImportanceAutism spectrum disorder is currently diagnosed using behavioral assessments, and objective biological measures are limited. The gut microbiome produces many small molecules that can influence brain development and function, but the specific metabolites involved in ASD remain unclear. Using targeted analysis of stool samples, we identified changes in metabolites related to neurotransmitter synthesis and tryptophan metabolism and showed that their relationships form distinct metabolic networks in individuals with ASD. A small panel of metabolites provided moderate ability to distinguish ASD from controls. These results suggest that gut-derived metabolites capture biologically meaningful variation in ASD and may help guide future studies aimed at understanding gut-brain communication and developing noninvasive biomarkers.

microbiology↗

bioRxiv2026

Distinct Biological and Biomechanical Features in TMJ and Knee Cartilages

The temporomandibular joint (TMJ) and the knee joint are two of the most frequently used joints in the body, with the mandibular condylar cartilage (MCC) and the articular cartilage (AC) covering the joint bone surfaces, respectively. Compromised MCC functions lead to various temporomandibular disorders (TMD), including TMJ osteoarthritis (TMJ OA); however, the mechanisms governing MCC homeostasis and its biomechanical properties are still poorly understood. In this study, we comprehensively compared the biological and biomechanical features of the MCC and AC in mice. Histological analysis on P1, P21, 3-month, and 10-month mice revealed the most drastic structural differences between MCC and AC at occlusion establishment (P21), with MCC found to be more susceptible to age-associated cartilage degeneration. Immunostaining revealed differentially distributed cartilage extracellular matrix components in MCC and AC, including collagen type I, II, and X, and highly enriched expression of several key transcriptional factors at the posterior region of the MCC, including sex determining region Y-box 9 (SOX9), runt-related transcription factor 2 (RUNX2), and scleraxis (SCX). The posterior MCC also houses a group of long-lasting, slow-proliferative cells, as evidenced by the BrdU/EdU incorporation assay, suggesting the presence of a potential stem/progenitor cell niche at the posterior TMJ. Unbiased nanoindentation analysis revealed distinct biomechanical features between these joint cartilages. MCC exhibits a significantly lower elastic modulus (EIT) than AC, with the highest EIT observed at the anterior TMJ, which is oppositely associated with the fibrous layer thickness, but positively correlated with the ratio of the collagen type X-positive matrix in the cartilaginous layer. Altogether, this study provides a basic understanding of the biological and biomechanical features of the cartilaginous tissues in two important joints, which may facilitate our understanding of the physiology in the TMJ and knee joint, and support the applications of mouse models to study TMJ dysfunctions.

developmental biology↗

bioRxiv2026

Machine learning-based framework for predicting human infection potential of coronavirus associated with tri-amino acid motifs, KIQ and LEP in spike protein

Assessing the human infection potential of emerging coronaviruses remains a critical challenge for global health preparedness. In this study, we developed a machine learning-based framework to predict the human infection potential of coronaviruses and to identify associated sequence motifs using spike (S) protein sequences. A total of 3,904 complete S protein sequences were collected, annotated as human or non-human infection and encoded using trimer-based k-mer features. Model benchmarking was conducted across 27 machine learning algorithms, followed by hyperparameter optimization of the selected model. Robustness and generalizability were evaluated using k-fold cross-validation and independent external validation. Feature interpretability was further assessed using SHAP analysis to identify sequence determinants associated with infection potential. The Random Forest classifier achieved the best performance, with accuracy, sensitivity, and specificity of 97.8%, 99%, and 97.4%, respectively, and demonstrated stable predictive performance across validation datasets. Notably, the KIQ and LEP motifs were strongly associated with human infection coronaviruses and mapped to the HR1 and N-terminal domain regions of the S protein. Overall, this framework provides a practical approach for risk assessment and surveillance of emerging coronaviruses. Author summaryEmerging coronaviruses continue to threaten global public health, but rapidly identifying viruses with the potential to infect humans remains challenging. Traditional experimental approaches are time-consuming and resource-intensive, limiting their use for large-scale surveillance. In this study, we developed a machine learning based workflow to assess the human infection potential of coronaviruses using spike protein sequences. By analyzing sequence patterns across a diverse set of coronaviruses, our framework enables rapid screening of coronaviruses from multiple host species. Unlike previous studies focused on limited coronavirus genera, our approach integrates all four genera and systematically evaluates multiple learning strategies. Importantly, our analysis identifies conserved sequence motifs linked to human infection potential, bridging predictive performance with biological interpretability. Our findings demonstrate computational approaches support early warning systems for identifying high risk coronaviruses, contributing to prioritize viruses for experimental validation, guide surveillance efforts, and strengthen global pandemic preparedness under a One Health perspective.

bioinformatics↗

bioRxiv2026

Tirzepatide improves pancreatic β-cell function in mice and patients with type 2 diabetes.

The dual incretin receptor agonist tirzepatide improves {beta}-cell function in T2D patients, but the underlying mechanism remains unclear. This study aimed to elucidate the molecular pathway through which tirzepatide restores {beta}-cell functional improvement. High-fat diet (HFD)-fed C57BL/6J mice were treated with vehicle, a GIP analogue, semaglutide or tirzepatide. Tirzepatide significantly reduced body weight and improved glucose tolerance in HFD-fed mice without altering {beta}-cell mass, proliferation, or apoptosis. Instead, tirzepatide reversed {beta}-cell dedifferentiation, as indicated by reduced ALDH1A3 expression and restored levels of the identity transcription factors PDX1 and MAFA. Single-cell RNA sequencing (scRNA seq) and in vitro studies revealed that tirzepatide up-regulated FOXO1, reactivating the FOXO1-PDX1/MAFA axis. In T2D patients, tirzepatide improved glycemic control, reduced insulin demand, increased HOMA-{beta}, and decreased HOMA-IR. Improvement in HOMA-{beta} correlated positively with baseline insulin resistance. Hence, our study suggested that tirzepatide restores {beta}-cell function in T2D by reprogramming stressed {beta} cells and re-establishing {beta}-cell identity through FOXO1-dependent transcriptional reactivation. These findings provide a mechanistic basis for the superior efficacy of dual incretin receptor agonism in T2D management. ARTICLE HIGHLIGHTSO_LITirzepatide restores {beta} cell identity and function without altering {beta} cell mass in HFD induced diabetic mice. C_LIO_LITirzepatide reverses {beta}-cell dedifferentiation and restores key {beta}-cell transcription factors (PDX1, MAFA) through reactivation of the AKT-FOXO1 signaling pathway. C_LIO_LITirzepatide increases HOMA-{beta} and decreases HOMA-IR in T2D patients, and improvements in HOMA-{beta} positively correlate with baseline insulin resistance. C_LIO_LIThese results demonstrate that tirzepatides therapeutic benefits are not only metabolic but also involve direct restoration of {beta}-cell identity and function. This highlights {beta}-cell reprogramming as a novel therapeutic avenue, thus supporting the broader clinical adoption of dual incretin receptor agonists. C_LI

physiology↗

bioRxiv2026

TCR signal strength determines Treg instability and discrimination of self versus non-self antigens

Regulatory T cells (Tregs) expressing autoreactive T-cell receptors (TCRs) maintain immune self-tolerance, yet their fate upon antigen encounter remains unclear. Although selected in the thymus for high-affinity self-recognition, the cross-reactive nature of the TCR repertoire allows some Tregs to also recognize foreign antigens with high affinity. Here, we identify cross-reactive destabilization, a process in which high-affinity recognition of foreign antigens erodes Treg stability and redirects lineage fate. Using a thymic-derived Treg (tTreg) TCR capable of recognizing both self and foreign antigens distinct from the self-ligand that mediated its thymic selection, we show that stimulation with high-affinity non-self agonists induces Foxp3 loss and conversion into effector-like ex-Tregs, whereas self-antigen stimulation preserves lineage stability. Treg instability also increases with age and correlates with activation, suggesting that cumulative foreign-antigen exposure drives this process. These findings reveal a signal-strength-dependent model in which strong TCR engagement induces cross-reactive destabilization to balance immune responsiveness and self-tolerance. One Sentence SummaryForeign antigen-driven destabilization of Treg cells balances immunity and tolerance

immunology↗

bioRxiv2026

Individual Brain Structure Deviations and its Gene Expression Signatures in Early-Onset Schizophrenia

BackgroundSchizophrenia is a highly heritable mental disorder associated with widespread anatomical alterations during neurodevelopment. Converging evidence suggests transcriptomic architecture underlying brain abnormalities in schizophrenia, while how individualized brain morphological deviations relate to gene expression levels remains unclear. MethodsTo investigate individual-level brain deviations and its transcriptomic signatures in schizophrenia, this study collected T1-weighted MRI data from 95 early-onset schizophrenia (EOS) patients and 99 typically developing (TD) controls. Normative modeling was used to measure individual deviations in cortical thickness and subcortical volume. Partial least squares regression was calculated to capture covarying patterns between structural deviations and whole-brain gene expression levels. Clustering analysis was performed on latent brain-gene covarying components, and the results were further functionally decoded through gene enrichment analyses. ResultsGroup-level comparisons suggested patients with EOS showed consistently decreased z-scores of cortical thickness in the frontal and temporal lobe regions, while increased inter-individual variability in the lingual gyrus. Clustering analysis of z-scores with transcriptomic signatures identified two distinct brain-gene covarying subtypes. Subtype 1 showed thickening cingulate gyrus, thinning occipital pole, and atrophic subcortical nuclei. Subtype 2 exhibited widespread cortical thinning across the frontal, parietal, temporal, and limbic regions, but enlarged subcortical nuclei. Genes underlying two subtypes were both enriched for neurodevelopmental diseases. However, subtype 1 was associated with synaptic transmission, and subtype 2 was related to cytoskeletal and neuronal connectivity. ConclusionThis study reveals individual-level anatomical deviations and transcriptomic heterogeneity in early-onset schizophrenia. The findings provide an individualized brain-gene coupling framework for understanding pathophysiology of schizophrenia during brain development.

molecular biology↗

bioRxiv2026

Inflammation in schizophrenia: Peripheral interleukin-6 levels-related disease-specific functional activity abnormalities

BackgroundPeripheral inflammation is implicated in the pathophysiology of schizophrenia, but how inflammatory signals map onto the large-scale brain organization remains incompletely understood. MethodsWe applied a supervised multimodal fusion approach guided by interleukin-6 (IL-6) to gray matter volume (GMV) and resting-state regional homogeneity (ReHo) from a population-based discovery cohort in the UK Biobank. Brain components related to IL-6 were identified and then projected onto an independent schizophrenia cohort to examine their relevance to the disease. Imaging-transcriptomic analyses using the Allen Human Brain Atlas characterize the molecular substrates underlying the disease-relevant pattern. ResultsTwo ReHo components were significantly associated with plasma IL-6, while no GMV components showed robust IL-6 correlations. One of the components (ReHo IC4) exhibited a conserved functional pattern characterized by enhanced visual synchrony and reduced synchrony in the medial prefrontal cortex. This pattern remained unchanged in both the healthy controls and patients. In contrast, another component (ReHo IC8) showed increased synchrony in the default mode network and reduced synchrony in sensorimotor networks, and its loadings were significantly elevated in patients with schizophrenia. Imaging-transcriptomic analysis revealed the molecular architecture of this disease-amplified pattern. The default mode region was enriched in synaptic signaling pathways, while the sensorimotor region was linked to mitochondrial bioenergetic processes; both patterns significantly enriched with gene sets related to schizophrenia. ConclusionsThis study identified an IL-6-associated functional brain pattern that is amplified in schizophrenia, linking peripheral inflammation to disease-specific network dysregulation. The findings provide a systems-level framework for understanding how peripheral inflammation interacts with large-scale brain network activities in schizophrenia.

neuroscience↗

bioRxiv2026

IDH-mutant inhibitors enhance the sensitivity of IDH1-mutant gliomas to cysteine-methionine deprivation and ferroptosis

Cysteine is essential for synthesizing glutathione, the brains main antioxidant, and cysteine deprivation can trigger ferroptosis. Here, using a new mouse model of IDH1-mutant glioma that recapitulates the characteristics of human IDH1-mutant low-grade gliomas, we demonstrate that IDH1-mutant glioma cells are significantly more vulnerable to cysteine deprivation alone or in combination with the ferroptosis inducer RSL3, compared to IDH1-wildtype glioma cells. In addition, treatments with the IDH-mutant inhibitors vorasidenib and ivosidenib further sensitize the cells to ferroptosis. Metabolomics analysis reveals that IDH1-mutant cells have altered cysteine and methionine metabolism with deficiency in transsulfuration, which is further exacerbated by cysteine-methionine deprivation and IDH-mutant inhibitors. Furthermore, dietary cysteine-methionine deprivation alone or in combination with convection-enhanced delivery of RSL3 or ivosidenib in vivo significantly prolongs survival of IDH1-mutant tumor-bearing mice. Our findings suggest that targeting cysteine and methionine metabolism in combination with IDH-mutant inhibition provides promising therapeutic strategies for IDH1-mutant gliomas.

cancer biology↗