Biology subjects

Wang, R.

Publications and source records attributed to Wang, R..

At least 109 records · Page 6Linked to original sources

bioRxiv2025

3D pathology-guided microdissection

Traditional micro- and macro-dissection techniques enable the extraction of localized regions in thin tissue sections for molecular analysis. Despite the growing use of 3D microscopy, analogous methods for volumetric microdissection are lacking. We have developed a 3D microdissection method based on computer numerical controlled (CNC) milling integrated with open-top light-sheet microscopy. We demonstrate the ability to study tumor evolution along convoluted 3D branching architectures, which is inaccessible to 2D methods.

bioengineering↗

bioRxiv2025

Interleukin-17A Mediates Cardiorenal Injury In Oxalate Nephropathy

AimsCardiovascular disease (CVD) is the leading cause of mortality in chronic kidney disease (CKD). While CKD is known to give rise to systemic inflammation, its inciting factors remain poorly defined. Oxalate, long implicated in rare genetic kidney disorders, accumulates with decreased kidney function and has emerged as a driver of inflammation and independent risk factor for CVD. Here, we investigate the immunological mechanisms linking oxalate nephropathy to systemic inflammation, cardiac damage and kidney injury. Methods and ResultsOxalate nephropathy was induced in C57Bl6/N mice via an oxalate-enriched diet. Oxalate induced systemic immune activation, renal fibrosis, and cardiac remodeling, including pulmonary congestion with systolic and diastolic dysfunction. Flow cytometry analysis identified interleukin (IL)-17A as a dominant inflammatory effector, with expansion of Th17 and Th17-like Treg in the kidney, intestine, and spleen. Bulk mRNA sequencing confirmed these findings. Confirming the oxalate-IL-17A relationship, plasma IL-17A was elevated in patients with primary hyperoxaluria. Gut microbiome analysis by 16S amplicon sequencing showed only mild oxalate-induced alterations in mice. However, soluble oxalate directly enhanced Th17 polarization and disrupted mitochondrial respiration in vitro. In vivo, antibody-mediated (clone: 17F3) IL-17A blockade decreased cardiac fibrosis, reduced neutrophil infiltration, and partially restored cardiac function in oxalate-fed mice. ConclusionsOur study identifies oxalate as a systemic immunometabolic stressor and IL-17A as a central mediator of oxalate-induced cardiorenal injury. These findings establish the oxalate-IL-17A axis as a mechanistic link between CKD and CVD and suggest IL-17A inhibition as a potential therapeutic strategy to reduce cardiovascular damage in CKD. Translational PerspectiveThis study advances our understanding of targetable mediators of the cardiovascular risk in chronic kidney disease (CKD). We identify the organic anion oxalate, beyond its traditional role in crystal-induced kidney damage, as a systemic immunometabolic stressor. We demonstrate that oxalate induces IL-17A-mediated inflammation and thereby contributes to maladaptive cardiac remodeling. Therapeutic blockade of IL-17A protects against oxalate-induced cardiorenal injury, highlighting the oxalate-IL-17A axis as a relevant and druggable link between CKD and cardiovascular disease.

immunology↗

bioRxiv2025

Pro4S: prediction of protein solubility by fusing sequence, structure, and surface

Protein solubility is a critical physicochemical property influencing protein stability, therapeutic efficacy, and overall developability in drug discovery. However, traditional experimental methods for assessing solubility are often resource-intensive and time-consuming. To address these limitations, computational approaches leveraging artificial intelligence have emerged, yet current models generally treat qualitative classification and quantitative regression as separate tasks and rely predominantly on sequence-based information, neglecting crucial structural and surface characteristics. Here, we introduce Pro4S, a novel multimodal predictive model that integrates protein language models, structural data, and surface descriptors using advanced contrastive learning techniques. Our unified framework achieves significant improvements in prediction accuracy, robustness, and generalizability for both qualitative and quantitative solubility assessments. Benchmark comparisons demonstrate that Pro4S consistently outperforms existing state-of-the-art predictors across diverse datasets. Furthermore, by applying Pro4S to the emerging area of de novo protein design, we validated a strong correlation between predicted solubility and experimental expression levels, reducing the proportion of non-expressed proteins by 52.7% while retaining 96.7% of highly expressed proteins. This highlights Pro4Ss potential to serve as a reliable upfront screening tool for increasing expression success rates and accelerating rational protein engineering.

bioinformatics↗

bioRxiv2025

Timing of immune checkpoint blockade shapes anti-tumor immunity via a clock-dependent chemokine axis

Circadian clocks regulate immunity, yet how they shape the tumor immune microenvironment and influence cancer immunotherapy remains unclear. Here, we show that tumor immune infiltration and immune checkpoint inhibitor efficacy vary by time of day in mice, driven by intrinsic clocks in dendritic cells and CD8+ T cells. Time-of-day modulates the abundance, spatial organization, and cytokine-chemokine production of tumor-infiltrating immune cells. Mechanistically, dendritic cell clocks control expression of Cx3cl1, driving recruitment of CX3CR1+CD8+ T cells and thereby reshaping the tumor immune microenvironment to enhance immunotherapy efficacy. Disruption of this axis abolishes time-of-day-dependent differences in treatment response. These findings identify a circadian mechanism of immune cell recruitment to tumors and provide mechanistic insight into clinical observations linking treatment timing to immunotherapy outcomes. One sentence summaryTime of day determines cancer immunotherapy efficacy through a circadian clock-dependent chemokine axis.

immunology↗

bioRxiv2025

Plasmid dependent phage eliminate pathogenic bacteria and antibiotic resistance plasmids from the chicken gut microbiome

Conjugative plasmids are a key reservoir of antimicrobial resistance (AMR) in commensal and pathogenic bacteria within the gut microbiome. Plasmid-dependent phage (PDPs) are a promising therapeutic option directly targeting AMR plasmids, but the efficacy of PDP therapy in vivo is poorly understood. Here, we show that treatment with the PRD1 phage eliminated Salmonella enterica carrying a broad-host range IncP AMR plasmid (RP4) from the chicken gut microbiome. Moreover, PRD1 treatment prevented the transfer of the RP4 plasmid to other members of the gut microbiome, whilst causing only minimal disruption to microbiome composition. Our results demonstrate that PDP therapy rapidly eliminates AMR from a natural gut microbiome by killing pathogenic bacteria and blocking AMR plasmid transmission to commensals, highlighting the conjugative pilus as a promising antimicrobial target.

microbiology↗

bioRxiv2025

Selective reduction of KCNA4 in vulnerable glutamatergic-serotonin neurons of the dorsal raphe nucleus in Alzheimers Disease

INTRODUCTIONWe previously demonstrated that htau mice recapitulate many neuropsychiatric features of early Alzheimers disease (AD), and that the dorsal raphe nucleus (DRN) contains distinct subregions. Herein, we investigate vulnerability of the centromedial DRN to pathologically-phosphorylated tau (pTau), a region composed predominantly of dually serotonergic/glutamatergic (5HT/glut) neurons. METHODSWe use computational, molecular, biophysical, and behavioral techniques to assess the centromedial DRN across preclinical and post-mortem settings. RESULTSThe centromedial DRN contains 5HT/glut neurons that differentially express ion-channel genes in the htau mouse. 5HT/glut neurons exhibit increased excitability, which we demonstrate may dually promote pTau accumulation and the severity of depressive-like behaviors in htau mice. At Braak 2, KCNA4 is reduced in 5HT/glut neurons in AD, which are especially vulnerable to pTau compared to 5HT-nonglut neurons. DISCUSSIONTau-mediated dysfunction of the DRN may be driven by changes in ion channel activity that concomitantly promote the spread of pTau in Braak progression.

neuroscience↗

bioRxiv2025

YAP1 defines an emergent, plastic population of relapsed small cell lung cancer

Small cell lung cancer (SCLC) is an aggressive neuroendocrine malignancy characterized by rapid onset of chemoresistance and poor clinical outcomes. Transcriptional heterogeneity among treatment-naive SCLC tumors underlies four transcriptional subtypes, each with distinct clinical vulnerabilities. Though previously hypothesized to delineate a distinct subtype, expression of YAP1 is largely absent from treatment-naive, pure SCLC. To characterize relapsed SCLC, circulating tumor DNA, circulating tumor cells, and core needle biopsies from SCLC patients and preclinical models following resistance to standard-of-care therapies were analyzed. In contrast to treatment-naive SCLC, these analyses reveal an emergent YAP1-positive cell population that coincides with treatment resistance. These YAP1-positive cells exhibit characteristics of drug tolerant persister cells, including senescence, stemness, and plasticity, as YAP1 positive cells largely abandon features characteristic of SCLC to adopt those of large-cell neuroendocrine carcinoma (LCNEC). As a result of this SCLC-like to LCNEC-like evolution, YAP1-positive cells lack several clinically relevant SCLC surface targets (i.e., DLL3, SEZ6), but are enriched for others (i.e., B7-H3, TROP2). We propose a model where YAP1 expressing cells emerge with SCLC treatment resistance and characterize a tenacious subpopulation capable of diverging from the treatment naive lineage and adopting features to evade therapeutic response.

cancer biology↗

bioRxiv2025

Somatic TYK2 activating mutations in tumor-infiltrating T cells promote anti-cancer immunity

Cancer cells evolve to increase fitness and evade the immune system, but it is not clear if tumor infiltrating lymphocytes (TILs) undergo selection for somatic mutations that augment anti-cancer immunity. Using single molecule whole exome sequencing in TILs, we identified somatic mutations in Tyrosine-protein kinase 2 (TYK2), several of which increased TYK2 phosphorylation, JAK-STAT signaling, and interferon gamma signaling. Among these mutations, TYK2D810V was recurrently observed in patients with diverse cancer types. In vitro, TYK2D810V enhanced T cells effector functions and cytokine production. We generated mice with a germline Tyk2D807V mutation that recapitulated the human TYK2D810Vmutation. These mice were healthy and did not develop autoimmune disorders. However, they possessed enhanced anti-tumor effects in the context of syngeneic and autochthonous cancer models. Adoptive therapy with Tyk2D807V CD8 T cells also decreased cancer growth. Thus, naturally occurring mutations in non-malignant lymphocytes can antagonize cancer and inspire new immunotherapies strategies.

cancer biology↗

bioRxiv2025

The past and potential antagonistic effects of fishing ban against nutrient loading control on eutrophication restoration in Lake Hongze

Integrated management strategies are often implemented to achieve comprehensive environmental restoration; however, the potential antagonistic effects among such measures are seldom examined. Fishing bans, aimed at enhancing fish biodiversity, may counteract the effectiveness of nutrient control measures in mitigating eutrophication. This study employs the PCLake model and structural equation modeling (SEM) to evaluate this hypothesis in Lake Hongze, the fourth largest shallow lake in China. The PCLake model was calibrated using observational data from Lake Hongze collected between 2016 and 2020. The calibrated model was subsequently applied in a hindcast analysis from 2020 to 2024 and a forecast simulation from 2025 to 2030 to assess the impacts of fishing bans. Combined with SEM path analysis, the results support the hypothesis that fishing bans can exhibit antagonistic effects on nutrient loading control by enhancing top-down regulation relative to bottom-up processes. Specifically, the fishing ban led to increased fish biomass, phytoplankton abundance, and nutrient levels over the past four years, while reducing the abundance of submerged macrophytes, zoobenthos, and zooplankton. Projections further indicate that such antagonistic effects would persist through 2030 if the fishing ban remains in place as planned. Additionally, model forecasts suggest that even with adjustments to the duration and intensity of fishing bans, antagonistic effects could be amplified under more stringent nutrient control scenarios. This study provides valuable insights into maximizing the net benefits of combined environmental management strategies through a systematic framework that evaluates both the effects and underlying processes of different interventions.

ecology↗

bioRxiv2025

Quantitative Prevalence, Chemical Speciation, and ECM-Embedded Networks of Biogenic Silicon in Animal Tissues Revealed by Refined Analytical Methods

Silicon, abundant in Earths biosphere, plays crucial roles in many organisms. However, its biological functions in animals remain inadequately characterized, primarily constrained by methodological limitations in quantifying, identifying, and visualizing biogenic silicon in tissues. Here, we refined the molybdenum blue colorimetric method (MB) for more accurate silicon quantification, developed integrated mass spectrometry techniques to delineate chemical natures of biogenic silicon, and optimized micro-X-ray fluorescence (micro-XRF) imaging for spatial mapping in animals. Employing these methodologies, we demonstrated that silicon abundance in animals substantially exceeds prior estimates--surpassing essential elements like iron. We also revealed the chemical architectures of diverse silicon compounds and visualized tissue-specific distributions in mice and humans, indicating its predominant localization within extracellular matrix (ECM) and suggesting the formation of silicified networks. These findings establish silicon as a structurally and quantitatively significant element with profound biological implications, warranting its recognition as an essential factor in human physiology and pathology.

biochemistry↗

bioRxiv2025

Theta and gamma transcranial alternating current stimulation modulate Mandarin consonant and lexical tone perception

A theta/gamma oscillatory neural mechanism has been postulated to explain the auditory sampling of hierarchical syllable-phoneme structure with corresponding speech rates or linguistic hierarchies (theta for syllable and gamma for phoneme). Yet, whether such a mechanism is generalizable to Mandarin Chinese, a language that both has suprasegmental phonemes in the form of lexical tones and contains more monosyllabic words, which may lead to higher reliance on either phonemic-level or syllabic-level perceptual representations, is unclear. In this study, we applied transcranial electric stimulation with either theta or gamma alternating currents (tACS) to bilateral auditory cortices in healthy Mandarin-speaking participants during a consonant or tone identification task in quiet or noisy environments. Results showed that theta tACS impaired consonant identification in quiet, specifically, and generally prolonged reaction times across tasks and environments. Gamma tACS, however, only delayed tone identification in quiet. Besides, both theta and gamma tACS modulated perceptual decision-making parameters, leading to increased boundary thresholds (cautiousness of decision) and altered response biases in the perceptual decision of both consonants and tones, as evidenced by the hierarchical drift-diffusion model (HDDM). These findings indicate that theta oscillations causally support the perception of Mandarin syllables, with consonants and lexical tones presumably embedded in syllable-level representations, regardless of task difficulty. Gamma activity, however, is presumably engaged in supporting fast-changing and fine-grained acoustic features in a modulatory manner. Significance StatementHow the brain samples speech features for perception is a key question in language neuroscience. Previous research has shown that theta and gamma brain activity support the perception of suprasegmental syllables and segmental phonemes, corresponding to their length or linguistic hierarchy. However, for Mandarin, the existence of suprasegmental phonemes (lexical tones) and the large number of monosyllabic words can either lead to higher reliance on gamma oscillations for phoneme perception, or higher dependence on theta oscillations for holistic syllable integration. With the combination of brain stimulation to selectively modulate theta/gamma auditory activity and phoneme identification tasks, this study reveals a causal role of theta activity in supporting holistic syllable-based Mandarin phoneme perception, yet gamma engagement is modulatory.

neuroscience↗

bioRxiv2025

Screening of a kinase library in human Huntington disease iPSC derived striatal precursor neurons reveals a neuroprotective effect of PKC alpha and PKC beta1 inhibition

The loss of striatal medium spiny neurons is a hallmark of Huntingtons disease (HD). To identify potential disease-modifying treatments, we previously developed a human neuronal model by immortalizing and differentiating HD patient-derived iPSCs into highly homogeneous striatal precursor neurons (ISPNs). Using a 96-well screening platform, and two rounds of re-screening, we tested a kinase inhibitor library and identified 5 compounds that protected HD ISPNs from mutant huntingtin (mHTT)-induced toxicity. Among these, we prioritized the PKC-/{beta}1 inhibitor GO6976, which rescued HD ISPNs from mHTT toxicity in a dose-dependent manner. Further, we found increased phosphorylation of PKC- and PKC-{beta}1 in HD cells and tissues, while their overexpression was toxic to HD ISPNs. Knockdown of PKC-/{beta}1 protected the neurons, and both isoforms interacted and colocalized with HTT. These results suggest that PKC-/{beta}1 plays a role in HD neurodegeneration, and that inhibiting their activity may offer a potential therapeutic approach for HD. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=194 SRC="FIGDIR/small/677178v2_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@256d6org.highwire.dtl.DTLVardef@1931e7borg.highwire.dtl.DTLVardef@1b6598borg.highwire.dtl.DTLVardef@b0bbb5_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIHD patient-derived iPSC-based striatal precursor neurons (ISPNs) were used to screen and identify neuroprotective compounds. C_LIO_LIThe PKC-/{beta}1 inhibitor GO6976 rescues HD ISPNs from mutant huntingtin (HTT)-induced toxicity. C_LIO_LIThe phosphorylation of PKC-/{beta}1 is elevated in HD cell and tissues, and PKC-/{beta}1 interact with both wild-type and mutant huntingtin. C_LIO_LIOverexpression of PKC-/{beta}1 is toxic to HD ISPNs, while its knockdown protects the neurons. C_LI

neuroscience↗

bioRxiv2025

Cutting Through the Artifacts: Dissecting gRNA Impurities with FUSS-seq

CRISPR-based therapeutics rely on guide RNAs (gRNAs) and the Cas9 endonuclease for precise gene editing. Ensuring gRNA purity and base-level sequence integrity is essential for clinical translation. While industry-standard practice relies on liquid chromatography-high-resolution mass spectrometry to assess oligonucleotide identity and purity, more recent FDA guidance recommends complementary base-by-base sequence analysis (FDA CBER Webinar, 2024). In this study, we evaluated next-generation sequencing (NGS) strategies for characterizing chemically synthesized gRNAs. We found that the widely used SMARTer assay, while capable of producing sequenceable libraries, introduced substantial artifacts during library preparation. These included truncated scaffold species at oligo(A) stretches in the scaffold region and 5'(n-1) deletions within the spacer sequence. Although absent in the original gRNA, these artifacts accounted for over 10% of the sequencing reads, creating the false appearance of impurities. Through experimental and computational approaches, we traced these artifacts to mispriming by template-switching oligonucleotides (TSOs). Importantly, these artifacts occur during sequencing, and although they do not reflect real gRNA impurities, they compromise assay accuracy and can obscure true sequence impurities. To overcome these limitations, we developed FUSS-seq (Full-length Uncoupled Second-strand Synthesis followed by sequencing), a novel assay that integrates principles from 5' RACE with a modified TSO bearing a 3' polymerase-blocking moiety. FUSS-seq markedly reduced artifacts and increased full-length gRNA recovery, providing a more accurate and lower-bias method for gRNA purity assessment. This approach supports improved Chemistry Manufacturing and Controls (CMC) characterization of gRNAs and strengthens the analytical toolkit needed for reliable CRISPR-based therapeutic development.

molecular biology↗

bioRxiv2025

A Generative Foundation Model for Antibody Design

Antibodies are indispensable components of the immune system, yet the design of high-affinity antibodies remains a time-consuming and experimentally intensive process. To address this challenge, we present IgGM, a novel generative foundation model designed to accelerate high-affinity antibody engineering. IgGM learns the complex relationships underlying the binding interactions between antigens and antibodies, as well as the mapping between antibody sequences and structures. By conditioning on different inputs, IgGM supports a wide range of antibody design tasks, including complex structure prediction, inverse design, affinity maturation, framework optimization, humanization, and de novo antibody design. It is compatible with both conventional antibodies and nanobodies, and allows user-defined CDR loop lengths for flexible design. To prioritize candidates, we introduce a frequency-based computational screening strategy that enhances design efficiency. Extensive evaluation through both in silico benchmarks and in vitro experiments across diverse antigens such as PD-L1, Protein A, TNF-, IL-33, SARS-CoV-2 RBD and its variants demonstrates that IgGM consistently generates antibodies or nanobodies with high measured affinity. These results underscore IgGMs versatility and effectiveness as a powerful tool for next-generation antibody discovery and optimization.

bioinformatics↗

bioRxiv2025

Fluorescent protein-based ticker tapes for multiplexed recordings of transcriptional histories in single cells in culture and in vivo

Recording and imaging of promoter activities in real time is critical for deciphering cellular states and dynamic signaling crosstalk, but technologies capable of simultaneously capturing multiple transient events in living cells are lacking. Here, we custom-design fluorescent protein-based ticker tapes (FPTT) for multiplexed and longitudinal recording of physiological activities in single cells. FPTT integrates multi-spectral monomeric fluorescent proteins with self-assembling protein fibers, enabling massively parallel analysis of signaling dynamics under varying cellular conditions. Using FPTT, we were able to log dose-dependent and reversible transcriptional histories of endogenous cFos signaling in primary hippocampus neurons at a 3-hour temporal resolution via biological timestamps and an extended recording time of over 8 days. Furthermore, we expanded the imaging toolset by engineering genetically encoded FPTT variants for human NF{kappa}B, JAK/STAT3, mTOR, NFAT and cAMP signaling, allowing for the quantification of potential crosstalk between cFos and NF{kappa}B pathways in neurons, multiplexed recording of STAT3- and cAMP-specific promoters during drug-induced liver injury in mice, as well as simultaneous analysis of up to four major signaling pathways involved in experimental T-cell activation. This platform advances single-cell analysis by providing a versatile tool to investigate transcriptional histories and signaling interplay across diverse biological contexts, with broad applications in developmental biology and disease modeling.

synthetic biology↗

bioRxiv2025

PRECOG update: An augmented resource of clinical outcome associations with gene expression for pediatric and immunotherapy cohorts

Gene expression can be used to define prognostic and predictive biomarkers across cancers and treatment modalities. PRECOG (https://precog.stanford.edu) is a compendium of datasets with gene expression and clinical outcomes that facilitates visualization of associations between genomic profiles and patient survival. Here, we augment the existing PRECOG with new datasets in previously poorly represented adult cancer types, as well as adding annotated pediatric and immunotherapy treated cohorts. Pediatric PRECOG comprises [~]4,000 patients across 12 cancers; while the immunotherapy cohort (ICI PRECOG) contains [~]4,500 patients across 20 cancer subtypes from 80 distinct datasets across 52 studies. We compute and visualize associations of gene expression with survival outcomes using Cox regression for time-to-event, or logistic regression for responder vs non-responder, across all datasets. We also estimate cell type fractions in samples via computational deconvolution using CIBERSORTx, to identify survival associations at the level of cell types. All expression data, clinical annotations, and gene and cell type survival z-scores and meta z-scores for adult, pediatric, and ICI PRECOG, are available for interactive analysis and download, along with Kaplan-Meier and boxplot visualizations. This updated resource will provide new insights into biomarkers for specific therapies, populations, and cancer types. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=80 SRC="FIGDIR/small/671849v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@13446bdorg.highwire.dtl.DTLVardef@11025fcorg.highwire.dtl.DTLVardef@12e017corg.highwire.dtl.DTLVardef@1637dba_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2025

Integrating Human Genetics and Protective Genome Editing to Enable ADGRE2-Directed AML Therapy

Acute myeloid leukemia (AML) remains a major therapeutic challenge due to extensive disease heterogeneity and lack of cancer-specific antigens. ADGRE2 has emerged as a promising AML target with broad expression in AML patient blast and leukemic stem cell-enriched populations. However, comparable expression in healthy hematopoietic stem and progenitor cells (HSPCs) and myeloid lineages suggests a high susceptibility to on-target, off-tumor myelotoxicity with ADGRE2-targeted therapies. Guided by human genetics data identifying loss-of-function variants, we evaluated whether ADGRE2 is dispensable in hematopoietic stem cells as a protective approach for transplant-based shielding from ADGRE2-directed therapies. Using CRISPR-Cas9 and adenine base editors, we achieved high-efficiency ADGRE2 knockout (>94%) in HSPCs with corresponding protein loss without impairing cell viability, differentiation, and cytokine release in vitro, or long-term engraftment, multilineage differentiation, and persistence of gene editing in mouse xenografts. We also developed novel ADGRE2-specific chimeric antigen receptor (CAR) T cells that demonstrated potent cytotoxicity against AML cells, even at low antigen levels. Together, these findings establish ADGRE2 as a compelling AML target and provide a framework for hematopoietic stem cell transplant with protective gene editing to enable ADGRE2-directed immunotherapies while minimizing myelotoxicity.

cancer biology↗

bioRxiv2025

Metabolomics-Guided Machine Learning Reveals Diagnostic and Mechanistic Biomarkers in CHB with MASLD

BackgroundMetabolic dysfunction-associated steatotic liver disease (MASLD) often coexists with chronic hepatitis B (CHB), yet early diagnosis remains challenging, particularly in non-obese patients or those with subclinical features. This study aimed to identify metabolic signatures of CHB-related MASLD and construct a predictive model using untargeted metabolomics integrated with machine learning. MethodsSerum metabolomics was performed on 160 subjects (80 CHB + MASLD and 80 healthy controls). Differential metabolites were identified and analyzed using KEGG enrichment and 4 machine learning algorithms (Random Forest, XGBoost, SVM, and LASSO). Metabolite-clinical correlations and diagnostic model performance were evaluated. ResultsA total of 924 differential metabolites were identified, with significant enrichment in pathways related to the TCA cycle, sphingolipid metabolism, and amino acid turnover. Machine learning prioritized six robust and biologically relevant metabolites: L-aspartic acid, succinic acid, caproic acid, sebacic acid, monomenthyl succinate, and glycolaldehyde, which consistently distinguished CHB + MASLD patients from controls (AUC > 0.75). These metabolites reflect key disruptions in mitochondrial function, lipid oxidation, and redox homeostasis. Integrated models combining metabolomics with clinical indices achieved perfect classification (AUC = 1.000). ConclusionCHB-associated MASLD is driven by systemic metabolic remodeling centered on mitochondrial overload, oxidative stress, and impaired amino acid metabolism. The identified metabolites provide mechanistic insights and hold promise for non-invasive MASLD screening in CHB patients. This study underscores the potential of multi-algorithmic metabolomics in advancing early diagnosis and personalized management of complex liver comorbidities.

bioinformatics↗