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Results for “Gut metabolome”

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PubMed2026

Integrated analysis of gut microbiota, serum metabolomics, and proteomics reveals novel associations with clinical symptoms in patients with cerebral infarction.

BACKGROUND: Cerebral infarction (CI) is a major cause of adult disability and mortality worldwide. Mounting evidence supports the critical role of the gut-brain axis in cerebrovascular disease progression. This study aimed to characterize the alterations in gut microbiota, serum metabolome, and serum proteome in patients with CI, and to identify multi-omics signatures associated with clinical symptoms. METHODS: A total of 20 CI patients and 20 healthy controls (HC) were enrolled. Fecal microbiota was profiled using 16 S rRNA gene high-throughput sequencing. Serum metabolomics and proteomics were analyzed using ultra-high-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and data-independent acquisition (DIA) proteomics, respectively. Spearman correlation and multi-omics integration were applied to explore the associations among microbiota, metabolites, proteins, and clinical indicators. RESULTS: CI patients displayed significant gut microbiota dysbiosis, with a markedly lower gut microbiota health index (GMHI) and higher microbiota disorder index (MDI) compared with HC (P < 0.001). The genera g_norank_o_RF39 and Oxalobacter were significantly enriched in CI patients, whereas Clostridium_sensu_stricto_1 and Agathobacter were enriched in HC. Metabolomic analysis identified 445 differential metabolites, mainly involved in glycerophospholipid metabolism, phenylalanine metabolism, and caffeine metabolism. Proteomic analysis revealed 140 differentially expressed proteins linked to inflammatory responses, calcium signaling, and NF-κB signaling. Multi-omics integration showed that signature gut microbiota was strongly correlated (P < 0.005) with key serum metabolites and proteins implicated in CI pathogenesis. CONCLUSIONS: This integrated multi-omics study revealed distinct gut microbiota, serum metabolomic, and proteomic alterations in CI patients. The microbiota-metabolite-protein regulatory axes provide novel insights into the gut-brain axis in CI and may serve as potential diagnostic biomarkers or therapeutic targets.

Humans↗

PubMed2026

Characterization of age-related changes in the gut microbiome and metabolome of Kunming dogs and their associations with police performance.

BACKGROUND: Gut microbiota plays a pivotal role in regulating the host's central nervous system (CNS) activity and behavior. However, its influence on the police performance of Kunming dogs and the underlying mechanisms remain largely unexplored. This study was the first to apply multi-omics technologies to investigate the dynamic variations in gut microbiota and their metabolic profiles across different ages of Kunming dogs. Furthermore, we systematically examined the associations between these microbial alterations and police performance metrics, providing a theoretical foundation for enhancing the working capabilities of Kunming dogs through targeted modulation of intestinal microecology. RESULTS: The study showed that puppies, young dogs and adult dogs had significantly better police performance than elderly dogs, with young dogs exhibiting the highest scores. Analysis of 16S rRNA sequencing demonstrated that gut microbial diversity and stability were highest during the young dog stage, gradually declining with age. Metagenomic analysis revealed that the abundance of Lactobacillus acidophilus, Lactobacillus johnsonii, Limosilactobacillus reuteri, Ligilactobacillus animalis and Muribaculum gordoncarteri were strongly correlated with police performance. The results of metagenome-assembled genomes (MAGs) indicated that the above species have functional genes involved in GABAergic and glutamatergic synapse pathways. Furthermore, metabolomic analysis showed that differential metabolites were enriched in the neuroactive ligand-receptor interaction pathway, in which GABA (γ-aminobutyric acid), histamine and tyramine metabolites were positively correlated with the above species and police performance. CONCLUSION: The species L. acidophilus, L. johnsonii, L. reuteri, L. animalis, and M. gordoncarteri, which were enriched in the gut of puppies and young Kunming dogs, may potentially influence the nervous system through the production of neurotransmitters and neuromodulators, suggesting a possible association with police performance. Video Abstract.

Animals↗

PubMed2026

Interconnected influences of diet, gut microbiome, and metabolome on cognition across three metabolomics platforms.

Cognitive impairment is increasing with global aging, yet mechanisms linking diet, the gut microbiome, and metabolism to cognitive function remain unclear. To investigate a diet-microbiome-metabolome axis associated with cognition, we integrated fecal metagenomics, diet, and multi-platform plasma metabolomics in 505 older adults from four ADRCs. Several microbes broadly associated with circulating metabolites were also linked to multiple measures of cognitive performance. These taxa exhibited coordinated metabolic signatures, with cognition-positive microbes associated with antioxidant, lipid, and microbial-host co-metabolites, and microbes negatively associated with cognition were linked to inflammatory and aromatic amino acid-derived metabolites. Dietary patterns, particularly the Healthy Eating Index Greens and Beans component, were associated with microbial composition and metabolomic structure. Mediation analyses supported a diet-microbe-metabolite-cognition pathway, while metabolites remained associated with cognition after accounting for microbial features. These findings highlight the metabolome as a central integrator of diet, microbial activity, and cognitive function.

Journal Article↗

PubMed2025

Gut metagenome and plasma metabolome profiles in older adults suggest pyruvate metabolism as a link between sleep quality and frailty.

Poor sleep quality is associated with increased frailty in older adults, but the role of the gut microbiome in this relationship remains unclear. Here, gut metagenome and plasma metabolome were profiled in 1,225 individuals aged 62-96 years. Poor sleep quality was associated with reduced abundances of potential probiotics such as Faecalibacterium prausnitzii and elevated abundances of pathobionts. A gut microbiome sleep quality index (GMSI) was developed to quantify microbial balance related to better sleep quality; higher GMSI scores were inversely associated with frailty and related clinical traits. Pyruvate metabolism emerged as a key microbial pathway linking sleep quality to frailty, with features such as F. prausnitzii abundance and microbial pyridoxal 5'-phosphate biosynthesis implicated in this connection. These findings deepen our understanding of microbiome-metabolome pathways related to sleep quality and frailty in aging and provide a valuable resource for future longitudinal and interventional studies.

Humans↗

PubMed2022

Characterizing the metabolic effects of the selective inhibition of gut microbial β-glucuronidases in mice.

The hydrolysis of xenobiotic glucuronides by gut bacterial glucuronidases reactivates previously detoxified compounds resulting in severe gut toxicity for the host. Selective bacterial β-glucuronidase inhibitors can mitigate this toxicity but their impact on wider host metabolic processes has not been studied. To investigate this the inhibitor 4-(8-(piperazin-1-yl)-1,2,3,4-tetrahydro-[1,2,3]triazino[4',5':4,5]thieno[2,3-c]isoquinolin-5-yl)morpholine (UNC10201652, Inh 9) was administered to mice to selectively inhibit a narrow range of bacterial β-glucuronidases in the gut. The metabolomic profiles of the intestinal contents, biofluids, and several tissues involved in the enterohepatic circulation were measured and compared to control animals. No biochemical perturbations were observed in the plasma, liver or gall bladder. In contrast, the metabolite profiles of urine, colon contents, feces and gut wall were altered compared to the controls. Changes were largely restricted to compounds derived from gut microbial metabolism. This work establishes that inhibitors targeted towards bacterial β-glucuronidases modulate the functionality of the intestinal microbiota without adversely impacting the host metabolic system.

Mice↗

PubMed2025

Characterization of gut microbiota and metabolites in renal transplant recipients during COVID-19 and prediction of one-year allograft function.

BACKGROUND: The gut-lung-kidney axis is pivotal in immune-related kidney diseases, with gut dysbiosis potentially exacerbating the severity of Coronavirus disease 2019 (COVID-19) in recipients of kidney transplant. This study aimed to characterize the gut microbiome and metabolome in renal transplant recipients with COVID-19 pneumonia over a one-year follow-up period. METHODS: A total of 30 renal transplant recipients were enrolled, comprising 17 with COVID-19 pneumonia, six with mild COVID-19, and seven without COVID-19. Fecal samples were collected at the onset of infection for gut microbiome and metabolome analysis. Generalized Estimating Equations (GEE) model and Latent Class Growth Mixed Model (LCGMM) were employed to dissect the relationships among clinical characteristics, laboratory tests, and gut microbiota and metabolites. RESULTS: Four microbial phyla (Deferribacteres, TM7, Fusobacteria, and Gemmatimonadetes) and 13 genera were significantly enriched across three recipients groups, correlating with baseline inflammatory response and allograft function. Additionally, 52 differentially expressed metabolites were identified, with seven significantly correlating with eight altered microbiota genera. LCGMM revealed two distinct classes of recipients, with those suffering from COVID-19 pneumonia exhibiting significantly elevated serum creatinine (Scr) trajectories over the one-year period. GEE further identified 12 genera and 181 metabolites closely associated with these trajectories; a multivariable model incorporating gut metabolites of 1-Caffeoylquinic Acid and PMK was found to effectively predict one-year allograft function. CONCLUSIONS: Our study indicates a possible interaction between the composition of the gut microbiota and metabolites community and COVID-19 in renal transplant recipients, particularly in relation to disease severity and the prediction of one-year allograft function.

Humans↗

PubMed2025

Uncovering potential biomarkers and metabolic pathways in systemic lupus erythematosus and lupus nephritis through integrated microbiome and metabolome analysis.

OBJECTIVE: This study aims to explore the relationship between gut microbiota and fecal metabolomic profiles in patients with systemic lupus erythematosus (SLE), with and without lupus nephritis (LN), in order to identify potentially relevant biomarkers and better understand their association with disease progression. METHODS: Fecal samples from 15 healthy controls (HC) and 36 SLE patients (18 SLE-nonLN and 18 SLE-LN) were analyzed using 16S rRNA gene sequencing and untargeted metabolomics. Differential microbial taxa and metabolites were identified using Linear Discriminant Analysis Effect Size (LEfSe) and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA). Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Receiver Operating Characteristic (ROC) curve analyses were used to assess the potential clinical relevance of selected metabolites. RESULTS: Beta diversity analysis demonstrated distinct microbial clustering between groups (p < 0.05). SLE-LN samples showed an increased relative abundance of Proteobacteria and decreased Firmicutes compared to SLE-nonLN. Metabolomic profiling identified multiple differentially abundant metabolites, with notable enrichment in primary bile acid biosynthesis pathways (e.g., Glycocholic acid, AUC = 0.951). In the SLE-nonLN group, increased Glycoursodeoxycholic acid levels (AUC = 0.922) were observed in pathways related to taurine and hypotaurine metabolism. Correlation analysis indicated a negative association between Escherichia-Shigella and bile acid levels (p < 0.01). CONCLUSION: This integrative analysis suggests that patients with SLE and LN harbor distinct gut microbiota and metabolomic profiles. The identified microbial taxa and metabolites may have potential as non-invasive biomarkers and could contribute to a better understanding of SLE pathogenesis and progression.

Humans↗

PubMed2026

Effects of aerobic exercise on inflammation and gut microbiota in obese mice: a metagenomic and metabolomic analysis.

BACKGROUND: Aerobic exercise can ameliorate insulin resistance (IR). However, the mechanism by which aerobic exercise regulates the gut microbiome to ameliorate IR and obesity remains unexplored. METHODS: Obese models were established by feeding C57BL/6 male mice a high-fat diet. A total of 26 mice were randomly divided into control group (group A, N = 8) and high-fat diet group (HFD group, N = 18). Successfully modeled mice were further assigned to model group (group B, N = 8) and exercise group (group C, N = 8). Group C underwent a 6-week treadmill exercise program (12 m/min, 60 min per day, 5 days per week). After intervention, colon tissue morphology was observed through hematoxylin-eosin staining, serum lipids and inflammatory indicators levels were detected by ELISA. The changes in the intestinal microbiota of the mice were also examined using metagenomic sequencing and UPLC-MS non-targeted metabolomics. RESULTS: Compared with the group A, the body weight, TC, TG, LDL-C, blood glucose, insulin, and IR in the group B significantly increased (P < 0.01), while the levels of pro-inflammatory cytokines TXNIP, TNF-α, NLRP3, IL-1β, and IL-18 significantly increased (P < 0.05 or P < 0.01). Compared with the group B, aerobic exercise reduced the body weight, TC, blood glucose, insulin, IR, TXNIP, TNF-α and other indicators in obese mice (P < 0.05 or P < 0.01). Moreover, aerobic exercise can regulate the imbalance of the intestinal flora in obese mice and ameliorate the disorder of metabolites. The metabolic pathways including arachidonic acid metabolism and histidine metabolism showed the most significant differences after the intervention of aerobic exercise. CONCLUSIONS: In conclusion, aerobic exercise can ameliorate glucose and lipid metabolism, IR, inflammatory response, and regulate the intestinal microecology and metabolic disorders in obese mice. The mechanism may be closely related to enhancing the diversity of intestinal flora, regulating the metabolism of arachidonic acid and histidine.

Animals↗

PubMed2025

Deciphering microbial and metabolic influences in gastrointestinal diseases-unveiling their roles in gastric cancer, colorectal cancer, and inflammatory bowel disease.

INTRODUCTION: Gastrointestinal disorders (GIDs) affect nearly 40% of the global population, with gut microbiome-metabolome interactions playing a crucial role in gastric cancer (GC), colorectal cancer (CRC), and inflammatory bowel disease (IBD). This study aims to investigate how microbial and metabolic alterations contribute to disease development and assess whether biomarkers identified in one disease could potentially be used to predict another, highlighting cross-disease applicability. METHODS: Microbiome and metabolome datasets from Erawijantari et al. (GC: n = 42, Healthy: n = 54), Franzosa et al. (IBD: n = 164, Healthy: n = 56), and Yachida et al. (CRC: n = 150, Healthy: n = 127) were subjected to three machine learning algorithms, eXtreme gradient boosting (XGBoost), Random Forest, and Least Absolute Shrinkage and Selection Operator (LASSO). Feature selection identified microbial and metabolite biomarkers unique to each disease and shared across conditions. A microbial community (MICOM) model simulated gut microbial growth and metabolite fluxes, revealing metabolic differences between healthy and diseased states. Finally, network analysis uncovered metabolite clusters associated with disease traits. RESULTS: Combined machine learning models demonstrated strong predictive performance, with Random Forest achieving the highest Area Under the Curve(AUC) scores for GC(0.94[0.83-1.00]), CRC (0.75[0.62-0.86]), and IBD (0.93[0.86-0.98]). These models were then employed for cross-disease analysis, revealing that models trained on GC data successfully predicted IBD biomarkers, while CRC models predicted GC biomarkers with optimal performance scores. CONCLUSION: These findings emphasize the potential of microbial and metabolic profiling in cross-disease characterization particularly for GIDs, advancing biomarker discovery for improved diagnostics and targeted therapies.

Humans↗

PubMed2026

Untargeted metabolomics and proteomics reveals cocoa-mediated mitigation of valproic acid-induced dysregulation in a zebrafish model of autism: pilot study.

INTRODUCTION: Autism spectrum disorder (ASD) is a neurodevelopmental condition characterized by behavioral impairments and limited therapeutic options. Emerging evidence suggests that plant-derived polyphenols may offer neuroprotective benefits. OBJECTIVES: This pilot study aimed to investigate the therapeutic potential of polyphenol-rich cocoa extract in a valproic acid (VPA)-induced zebrafish model of ASD. METHODS: Zebrafish were exposed to 3 μM VPA, cocoa powder providing 2.5 μM (-)-epicatechin, a combination of both, or left untreated. Behavioral phenotyping was conducted using DanioVision and gut morphology was assessed. Untargeted metabolomic and proteomic profiling was performed followed by univariate and multivariate analyses. RESULTS: VPA exposure induced ASD-like behavioral hyperactivity, and severe gastrointestinal abnormalities. Cocoa co-treatment ameliorated both behavioral performance and gut architecture. Metabolomic profiling revealed VPA-associated disruptions in neurotransmission, methylation, mitochondrial function and redox homeostasis. Proteomic profiling showed elevated levels of trafficking protein particle complex subunit 11, proteasomal ubiquitin receptor, betaine-homocysteine S-methyltransferase 1 (BHMT-1), and desmoplakin-A, consistent with genotoxic stress and impaired protein trafficking. Cocoa co-treatment normalized BHMT-1 and desmoplakin-A expression and mitigated broader metabolic dysregulation. CONCLUSION: Collectively, these results suggest that polyphenol-rich cocoa may represent a promising multi-targeted nutraceutical approach for mitigating ASD-related neurodevelopmental and metabolic disturbances.

Animals↗

PubMed2026

Gut microbiota dysbiosis and host metabolite-immune crosstalk drives the pathogenesis of neonatal lupus erythematosus: a multi-omics analysis.

BACKGROUND: Neonatal lupus erythematosus (NLE) is a rare autoimmune condition triggered by the transplacental transfer of maternal antibodies. Despite its recognized clinical manifestations, the underlying pathogenesis remains incompletely understood. This study seeks to explore the disruption of the gut microbiota-host metabolism-immune axis in anti-Ro/La-positive neonates, and to assess its potential role in the development of NLE. METHODS: This multicenter, cross-sectional study included 90 neonates, divided into three groups: 30 with neonatal lupus erythematosus (NLE), 30 with positive antibodies but without clinical manifestations (No-NLE), and 30 healthy controls. We performed 16 S rRNA sequencing to analyze gut microbiota composition, untargeted plasma metabolomic profiling, and proteomic analysis to identify alterations associated with the pathogenesis of NLE. RESULTS: We identified significant alterations in the gut microbiota, plasma metabolome, and proteome profiles of anti-Ro/La-positive neonates. NLE infants exhibited marked enrichment of Enterobacteriaceae and depletion of Bifidobacterium and Clostridium butyricum. Metabolomic analysis revealed hyperactivation of β-alanine and purine metabolism, along with impaired α-linolenic acid metabolism and endocannabinoid signaling. Proteomic profiling indicated aberrant protein expression that modulated IFN signaling, particularly within the C-type lectin receptor pathway. Dysregulation of the spleen tyrosine kinase (SYK) and high-affinity immunoglobulin epsilon receptor subunit gamma (FCER1G) decoupling was observed, correlating with elevated IFN-α and NF-κB p65 levels. Integrated correlation analysis revealed significant associations among differential microbial taxa, plasma metabolites, and proteins. Notably, E. coli-associated metabolites and proteins displayed inverse relationships with those associated with C. butyricum. CONCLUSIONS: These findings represent comprehensive evidence of dysregulation along the "gut microbiota-host metabolism-immune" axis in neonatal lupus erythematosus (NLE), providing novel insights into the disease's underlying heterogeneity.

Humans↗

PubMed2025

AI-driven multi-omics modeling of myalgic encephalomyelitis/chronic fatigue syndrome.

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a chronic illness with a multifactorial etiology and heterogeneous symptomatology, posing major challenges for diagnosis and treatment. Here we present BioMapAI, a supervised deep neural network trained on a 4-year, longitudinal, multi-omics dataset from 249 participants, which integrates gut metagenomics, plasma metabolomics, immune cell profiling, blood laboratory data and detailed clinical symptoms. By simultaneously modeling these diverse data types to predict clinical severity, BioMapAI identifies disease- and symptom-specific biomarkers and classifies ME/CFS in both held-out and independent external cohorts. Using an explainable AI approach, we construct a unique connectivity map spanning the microbiome, immune system and plasma metabolome in health and ME/CFS adjusted for age, gender and additional clinical factors. This map uncovers altered associations between microbial metabolism (for example, short-chain fatty acids, branched-chain amino acids, tryptophan, benzoate), plasma lipids and bile acids, and heightened inflammatory responses in mucosal and inflammatory T cell subsets (MAIT, γδT) secreting IFN-γ and GzA. Overall, BioMapAI provides unprecedented systems-level insights into ME/CFS, refining existing hypotheses and hypothesizing unique mechanisms-specifically, how multi-omics dynamics are associated to the disease's heterogeneous symptoms.

Humans↗

PubMed2026

Toxoplasma gondii infection disrupts secondary bile acid transformation in feline gut microbiota.

UNLABELLED: Bile acid (BA) transformation relies on gut microbiota and is vulnerable to Toxoplasma gondii infection, yet feline microbial BA-transforming capacity upon toxoplasmosis remains unclear. Here, we constructed a catalog of 2,474 nonredundant feline gut microbial genomes and integrated serum metabolomic data to verify BA transformation alterations. The results revealed that the feline gut microbiome harbored widespread genetic potential for BA transformation but lacked a complete 7α-dehydroxylation pathway due to the absence of the key gene baiE. The BA transformation-related genomes (2,045 in total) were predominantly from the phyla Bacillota_A and Actinomycetota, among which only 37 encoded baiB, all belonging to Bacillota_A. The distribution of BA transformation-related genes varied across intestinal regions: genes encoding 7α-HSDH were primarily enriched in the small intestine, whereas genes encoding 3α-HSDH, baiCD, and baiH were more abundant in the large intestine. Additionally, the abundance of genes encoding BSH and 3α-HSDH increased significantly in the small intestine on day 3 post-infection, accompanied by increases in the phylum Bacillota_C and genera such as Blautia_A, Enterococcus_E, and Ligilactobacillus. Serum metabolomics revealed a significant increase in cholesterol levels post-infection, supporting the impact of T. gondii infection on intestinal BA transformation. These findings illustrated that the feline gut microbiota played an important role in BA transformation and that T. gondii infection disrupted the microbial potential for secondary BA transformation. This study provided new insights into gut microbiota-associated metabolic perturbations during feline toxoplasmosis. IMPORTANCE: Bile acid (BA) transformation plays a critical role in host metabolism and immune regulation. Although studies on BA transformation are increasing, the capacity for BA transformation within the feline gut microbiota and the impact of Toxoplasma gondii infection on this capacity remain unclear. To bridge this gap, we constructed a catalog of 2,474 nonredundant feline gut microbial genomes and integrated serum metabolomic data to verify BA transformation alterations. Our findings revealed that the feline gut microbiome lacked a complete 7α-dehydroxylation pathway, and the specific functions involved in BA transformation may differ between the small and large intestines. Furthermore, integrated metagenomic and serum metabolomic analyses suggested that T. gondii infection disrupted BA transformation capacity in the small intestine. This study provided new insights into gut microbiota-associated metabolic perturbations during feline toxoplasmosis.

Toxoplasma gondii↗

PubMed2025

Leveraging chemical synthesis to discover metabolites from the gut microbiome.

The gut microbiome has the biosynthetic potential to make a variety of secondary metabolites or natural products, which serve as molecular messages between cells and organisms. These chemical signals are capable of affecting physiology and behavior in real time, and are, therefore, bioactive and can exhibit medicinal properties including anticancer, antimicrobial, or immunomodulating activities. It is clearly important to identify signaling molecules in the human gut, but elucidating their chemical structures can be challenging since traditional isolation methods are typically not available. The discovery of microbiome-related metabolites requires multidisciplinary collaboration, where chemical synthesis often plays an essential role. This review highlights examples where synthetic chemistry was used to study novel metabolites produced by the gut microbiota. In the first part, we describe examples where organic synthesis was utilized in traditional contexts, as a last step for validating structures and sourcing material for biological testing. The final section of this review discusses next-generation applications for chemical synthesis, where integration with metabolomic or genomic analysis simultaneously uncovers both structural and biological information about small molecules from the gut.

Gastrointestinal Microbiome↗

PubMed2025

Bacterial metabolite patterns of infants receiving multi-strain probiotics and risk of late-onset sepsis.

The effect of multi-strain probiotics containing Bifidobacterium longum (B. longum) on late-onset sepsis (LOS) risk in very-low-birth-weight infants (VLBWIs; birth weight < 1,500 g) remains uncertain. In a single-center study, we analyzed intestinal metagenome and metabolome data in VLBWIs during the period of highest vulnerability of LOS. Using a unit's policy change to routinely administer B. longum subspecies infantis plus Lactobacillus acidophilus as natural experiment, we compared 97 infants (including 38 LOS cases) after change with 78 infants (including 32 LOS cases) before. Probiotic supplementation was associated with more beneficial bacteria and reduced abundance of nosocomial pathobionts, such as Klebsiella spp. Infants in the probiotic group had significantly lower concentrations of B. longum fermentation products prior to sepsis diagnosis than matched non-LOS cases (acetate: padj = 0.0049; lactate: padj = 0.048). Modulation of the gut metabolic milieu is an interesting target for LOS prevention.

Humans↗

PubMed2026

Longitudinal Clinical, Physiological, and Molecular Profiling of Female Patients With Metastatic Cancer: Protocol and Feasibility of a Multicenter High-Definition Oncology Study.

PURPOSE: A substantial proportion of patients receiving genomically matched therapies do not achieve clinical benefit, underscoring the influence of nongenetic factors on cancer outcomes. High-Definition Oncology (HDO) proposes integrating longitudinal, multimodal patient data-spanning clinical, molecular, physiological, and behavioral domains-to enable truly individualized cancer care. This manuscript describes the HDO study design, framework, and feasibility results in women with metastatic cancer. METHODS: We initiated a prospective, multicenter observational study (HDO study; ClinicalTrials.gov identifier: NCT06590506) enrolling 300 female patients with newly diagnosed metastatic breast, lung, or colorectal cancer. Here, we report the study design, standardized workflows, prespecified feasibility criteria, and early internal pilot results. Eleven data modalities are collected longitudinally, including tumor and germline genomics, germline epigenomics, gut microbiome, blood and stool metabolomics and proteomics, exposome characterization, wearable-derived physiological monitoring, digital footprint assessment, medical imaging, and patient-reported outcomes. Standardized workflows govern clinical procedures, data acquisition, biospecimen processing, and quality control across all participating sites. RESULTS: Feasibility was evaluated in the first 30 participants (10% of planned accrual). Patients completed 100% of scheduled clinical visits, 97.4% of planned plasma collections, 80.7% of stool samples, and all tumor biopsies. Wearable devices captured activity, heart rate, sleep, and blood oxygen saturation data during 95.0%, 84.2%, 90.6%, and 70.7% of total patient-days, respectively. Biospecimens met predefined quality control metrics across all molecular modalities. Engagement with mobile applications for pain and emotion reporting exceeded 80%. CONCLUSION: The HDO study demonstrates the feasibility of comprehensive, longitudinal, multimodal data collection in women with metastatic cancer. This internal pilot establishes an integrated framework for future analyses aimed at characterizing disease trajectories, defining molecular and physiological determinants of outcomes, and developing patient-specific computational models.

Humans↗

PubMed2026

The mechanism by which long-term exposure to TDCIPP promotes cognitive impairment in 3 ×Tg-AD mice: Insights from multi-omics studies.

Tri(1,3-dichloro-2-propyl) phosphate (TDCIPP) is a commonly used organophosphate ester that has the potential to adversely affect human health. Although previous studies have closely associated TDCIPP with cognitive impairment, the underlying mechanisms remain unclear. To elucidate the neurotoxic effects of TDCIPP and its mechanistic contribution to cognitive impairment in 3 ×Tg-AD mice, a multi-omics approach incorporating proteomics, untargeted metabolomics, and 16S ribosomal RNA (rRNA) gene sequencing was employed to evaluate the impact of TDCIPP exposure on neurobehavioral function. TDCIPP exposure promoted cognitive impairment in 3 ×Tg-AD mice. Proteomic analyses revealed that this promotion is associated with disturbances in the hippocampal mitochondrial autophagy pathway. Furthermore, TDCIPP may interfere with the PINK1/Parkin-mediated mitophagy pathway at the functional level, without altering PINK1 protein abundance. Untargeted metabolomic analysis of urine samples demonstrated that TDCIPP exposure altered the metabolic profile of 3 ×Tg-AD mice, with 58 metabolites upregulated and 11 downregulated. Additionally, 16S rRNA sequencing revealed substantial modifications in gut microbiome composition following exposure to TDCIPP. Notably, significant correlations were identified between the perturbed bacterial genera and the differential metabolites. In conclusion, exposure to TDCIPP promotes cognitive impairment in 3 ×Tg-AD mice, which is associated with the interference with the PINK1/Parkin-mediated mitophagy pathway, as well as alterations in the urinary metabolome and gut microbiota. These findings suggest the potential to mitigate such cognitive impairment by targeting the microbiota-gut-brain axis.

Animals↗

PubMed2026

Microplastics as vectors for microbial pollutants: Biofilm-associated transfer of pathogens and antibiotic resistance genes in zebrafish intestine.

As composite carriers of microorganisms and pollutants, biofilm-attached microplastics (MPs) serve as potential vectors for the environmental migration and biotransmission of antibiotic resistance genes (ARGs) and pathogens. In this study, traditional polypropylene (PP) and biodegradable polylactic acid (PLA) MPs were used to investigate the interference effects of biofilms-attached MPs on gut microbiota and ARGs transmission, through a combination of laboratory biofilm cultivation, zebrafish (Danio rerio) exposure simulations, metagenomic sequencing, and metabolomic profiling. Results showed that MP biofilms likely induced gut dysbiosis and were associated with altered diversity and abundance of pathogens and ARGs. At the phylum level, Nitrospira was transferred from PP biofilms to the gut. At the genus level, 23 genera were transferred from MP biofilms, with PLA (23 genera) showing higher transfer capacity than PP (4 genera). Notably, two human pathogens, one opportunistic pathogen, and two ARGs (adeF and oqxB) were specifically transferred from PLA biofilms, highlighting the unique dissemination risk of biodegradable MPs. Mechanistically, MPs may activate mobile genetic elements (e.g., Tn916 transposon) through metabolic remodeling and quorum sensing, thereby promoting horizontal gene transfer and ARGs dissemination within the gut. Our findings highlight the potential role of MPs as carriers of microorganisms and ARGs, underscoring the biotransmission risks of antibiotic resistance caused by composite pollution.

Animals↗