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PubMed2026

A Comprehensive Analysis of Differential Protein Expression in the Plasma of Rheumatoid Arthritis Patients Utilizing Data-Independent Acquisition (DIA) Proteomics Technology.

BACKGROUND: Rheumatoid Arthritis (RA) is a Prevalent Autoimmune Disorder Affecting Millions of People Worldwide. A Thorough Understanding of Its Clinical and Pathological Features Is Essential to Improve Patient Outcomes. METHODS: This Study Combined Data-Independent Acquisition Proteomics and Enzyme-Linked Immunosorbent Assay (ELISA) to Identify and Validate Potential Plasma Protein Biomarkers for the Early Diagnosis of RA. RESULTS: Differential Proteomic Analysis Identified Differentially Expressed Proteins Between Patients With RA and Healthy Controls and Characterized Their Functions. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes Enrichment Analyses Were Performed to Explore Protein Functions and Associated Biological Pathways. The STRING Database and the Metascape Platform Were Used to Conduct an in-Depth Analysis of the Protein-Protein Interaction Network, Highlighting the Functional Attributes and Interconnections of Upregulated Proteins and Identifying Key Protein Complexes Involved in RA. ELISA Analysis of Plasma Samples Revealed Significantly Elevated SERPINA3 Levels in Patients With RA, Which Were Positively Correlated With Disease Activity Indicators-Including Erythrocyte Sedimentation Rate, C-Reactive Protein, and Disease Activity Score 28-But Were Not Correlated With Rheumatoid Factor or Its Subtypes. CONCLUSIONS: This Study Provides New Insights and Identifies Potential Biomarkers for the Early Diagnosis of RA.

Humans↗

PubMed2026

Machine learning-assisted plasma PEA proteomics enables differential diagnosis of melancholic depression and bipolar disorder.

Differentiating bipolar disorder (BD) from major depressive disorder (MDD) remains a critical unmet need in psychiatry due to overlapping clinical presentations and the absence of reliable biological markers. In this study, we assessed the capacity of multivariate machine learning models to accurately differentiate BD from MDD with melancholic features using plasma proteomic profiles obtained via Proximity Extension Assay (PEA) technology. A total of 67 participants were included (23 BD, 20 MDD, and 24 HC), and plasma protein expression was assessed using the Olink Target 96 Neurology panel. Differential proteomic analysis revealed distinct disorder-specific expression patterns, identifying 21 differentially expressed proteins in BD versus MDD, 18 in BD versus healthy controls, and 7 in MDD versus healthy controls. Using a stepwise feature reduction strategy, machine learning models were trained on three feature sets comprising all proteins, the top 20 most informative proteins, and the top 5 most beneficial proteins, and evaluated across BD-MDD, BD-HC, and MDD-HC classification tasks using five algorithms. For BD-MDD discrimination, the Random Forest model achieved the highest performance when trained on the top 5 protein set (LXN, HAGH, MATN3, PLXNB1, and CTSC), yielding an AUC of 0.905, with similarly strong performance observed using the top 20 protein set. Feature importance analysis highlighted proteins involved in neurodevelopmental processes, immune regulation, and extracellular matrix organization. Overall, these findings demonstrate that integrating plasma proteomics with machine learning enables robust differentiation between BD and MDD with melancholic features, supporting the development of scalable and biologically informed diagnostic tools for precision psychiatry.

Bipolar disorder↗

PubMed2025

HEPARIN AND DNase I TREAT MYOCARDIAL INJURY IN SEPTIC MICE.

Background: Sepsis is a life-threatening clinical condition often seen in intensive care units, leading to multi-organ dysfunction. Myocardial injury is a prevalent complication, significantly increasing mortality among sepsis patients. Although heparin is used in sepsis management, its specific effects on myocardial injury and the role of neutrophil extracellular traps (NETs) in this context remain insufficiently understood. Aim: This study investigates the role of unfractionated heparin (UFH) combined with DNase I in reducing myocardial injury in a septic mouse model. Methods: A cecal ligation and puncture (CLP)-induced sepsis model was established in C57BL/6 mice to study myocardial injury. The experimental groups included treatments with UFH, UFH with DNase I, and NETs introduction. Myocardial injury was assessed using hematoxylin and eosin staining, enzyme linked immunosorbent assay for injury markers (creatine kinase MB [CK-MB] and lactate dehydrogenase [LDH]), and Western blotting for inflammatory proteins (TNF-α and IL-6). Differential proteomic analysis using data independent acquisition mass spectrometry and pathway enrichment analysis (Gene Ontology and Kyoto Encyclopedia of Genes and Genomes) were conducted to identify molecular pathways and key proteins affected by the treatments. Results: Single UFH treatment increased the formation of NETs, upregulated TNF-α and IL-6, and increased CK-MB and LDH, worsening myocardial injury. The combination of UFH and DNase I significantly reduced myocardial injury, suppressing NETs formation and inflammation. Proteomic analysis identified crucial pathways related to NETs, metabolism, and complement and coagulation cascades, with proteins Ccn1 and Tagln highlighted as potential therapeutic targets. Conclusion: UFH combined with DNase I effectively alleviates myocardial injury in septic mice by modulating NETs formation and associated inflammatory processes. This study may provide new insights and options for the early use of heparin in the treatment of septic patients, particularly in cases with a higher risk of myocardial injury.

Animals↗

PubMed2026

DiaReport: reproducible workflow for differential expression analysis and interactive reporting in DIA-based proteomics.

MOTIVATION: Data-independent acquisition (DIA) has become the preferred data acquisition method for mass spectrometry-based proteomics, yet, reproducible workflows for differential expression (DE) analysis and results reporting remain limited. We present DiaReport, an R package that performs precursor- and protein-level DE analysis from DIA-NN output using MSqRob and QFeatures, while generating high-quality, interactive HTML reports through Quarto. DiaReport integrates precursor data, filtering of missing values, normalization, protein summarization and statistical modeling within a single function, supporting both simple pairwise as well as complex experimental designs. The package provides structured outputs and configuration files to ensure computational reproducibility across different studies. To accommodate diverse research needs, DiaReport includes multiple reporting templates tailored to different proteomic applications. Applying DiaReport to an extracellular vesicle (EV) proteomics dataset demonstrates its ability to efficiently analyze DIA data and provide rapid insights into sample quality and protein level differences. AVAILABILITY: DiaReport is an open-source R package available at https://github.com/Gevaert-Lab/diareport (DOI: 10.5281/zenodo.20120604). The package is platform-independent and distributed under the MIT license. Reports are generated using Quarto and require only standard R dependencies. Detailed documentation, installation guides and usage vignettes are provided within the repository. The interactive HTML reports discussed in this study, including the UPS2 benchmark and EV case study, are archived on Zenodo (10.5281/zenodo.20122506 and 10.5281/zenodo.20123378).

Proteomics↗

PubMed2026

Single-Cell Proteomics Reveals Proteome Remodeling and Cellular Heterogeneity During NGF-Induced PC12 Neuronal Differentiation.

Single-cell proteomics enables direct measurement of cellular heterogeneity during dynamic biological processes, but its application to fragile and highly adherent neuronal models remains challenging. Here, we developed and applied an optimized single-cell proteomics workflow to characterize proteome remodeling during nerve growth factor (NGF)-induced differentiation of PC12 cells. To enable reliable single-cell analysis, we implemented gentle dissociation, antiaggregation strategies, and thermal inkjet-based cell dispensing, achieving high accuracy in single-cell isolation. Inclusion of n-dodecyl-β-d-maltoside (DDM) improved recovery of membrane-associated and low-solubility proteins. Coupled with LC-ion mobility-mass spectrometry, this workflow enabled quantification of 2,000-3,000 proteins per cell across the differentiation time course. Single-cell proteomic analysis revealed progressive and heterogeneous proteome remodeling during differentiation. While undifferentiated cells formed a relatively homogeneous population, later stages (Days 4-6) exhibited increased variability, including multimodal protein abundance distributions and separation into distinct subpopulations. Dimensionality reduction, clustering, and non-negative matrix factorization identified multiple coexisting proteomic states within the same time points, reflecting asynchronous differentiation trajectories. These subpopulations were characterized by coordinated differences in pathways related to intracellular trafficking, protein translation, cytoskeletal organization, and neuronal maturation. Comparison with bulk proteomics demonstrated that proteins associated with differentiated neuronal states, including those involved in neurite formation and structural remodeling, are underrepresented in population-averaged measurements but are enriched within specific single-cell subpopulations. Temporal and cluster-resolved analyses further revealed distinct protein expression trajectories, including early decreases in cell cycle and metabolic pathways and later increases in neuronal structural and regulatory proteins. Together, this study establishes an optimized workflow for single-cell proteomics of neuronal systems and demonstrates that NGF-induced PC12 differentiation proceeds through heterogeneous and divergent proteomic states that are not resolved by bulk analysis.

Animals↗

PubMed2026

Beyond ion channel dysfunction: Integration of the transcriptome and proteome from patient-specific re-engineered cardiac cells, and population-level QT genome-wide association study reveals broad cellular dysfunction.

BACKGROUND: Congenital long QT syndrome (LQTS) is a cardiac channelopathy with increased risk of cardiac-triggered syncope/seizures, sudden cardiac arrest, and sudden cardiac death. OBJECTIVE: This study aimed to describe the transcriptomic and proteomic profiles in patient-derived inducible pluripotent stem cell-derived cardiomyocyte (iPSC-CM) models of the 3 canonical genotypes of congenital LQTS: LQT1, LQT2, and LQT3 and integrate these omics-level findings with each other and with population/clinical level QT-genome-wide association study (GWAS) data. METHODS: LQT1, LQT2, LQT3 and respective isogenic control iPSC-CMs were cultured, and RNA and protein samples were collected. RNA sequencing and mass spectrometry-enabled proteomic analysis was performed. PrediXcan analysis was performed using QT GWAS summary statistics and transcriptome expression data. Differential gene and protein expression and ingenuity pathway analysis (IPA) was performed comparing each LQT genotype with its respective isogenic control. RESULTS: 1645 differentially expressed genes (DEGs) were identified; 13 were altered in all 3 LQTS genotypes. IPA analysis of DEGs revealed 301 altered pathways; 47 were altered in all LQTS genotypes. Proteomic analysis identified 2561 differentially expressed proteins (DEPs); 30 were altered in all 3 genotypes. IPA analysis of DEPs identified 646 altered pathways. 306 genes/proteins were identified as significantly altered in both the transcriptome and proteome; pathway analysis of these 301 genes identified 201 altered pathways. 7 pathways were altered in all 3 LQTS genotypes in both the transcriptome and proteome. Integration of the population-level PrediXcan results and the cardiomyocyte-derived omics results identified multiple shared pathways. CONCLUSION: Multi-omics analysis of LQTS and integration of omics results with QT GWAS data reveals that primary LQTS-causative ion channel defects precipitate secondary alterations in a wide range of cellular pathways. Our findings suggest more broad molecular level changes throughout the cell. This study lays the foundation for further exploration of broad cellular changes resulting from ion channel disturbances and how they contribute to disease mechanism.

Humans↗

PubMed2026

Integration of metabolomics and proteomics reveals the toxicological mechanisms of environmentally relevant concentrations of cadmium on juvenile rockfish (Sebastes schlegelii).

As a highly toxic heavy metal, cadmium (Cd) is widely distributed in the coastal environments of the Bohai Sea, posing significant ecological and health risks. This is of particular concern for Sebastes schlegelii, a rockfish species commonly found along the Bohai coast and consumed by local populations. In this study, juvenile S. schlegelii were randomly assigned to three groups (control, 5 and 50 μg/L Cd) for a 14-day exposure period, followed by analysis of Cd bioaccumulation, as well as metabolomic and proteomic profiling. ICP-MS analysis indicated dose-dependent Cd bioaccumulation in the whole body, with 0.11 ± 0.07 μg/g dry weight in the 5 μg/L group and 0.38 ± 0.09 μg/g dry weight in the 50 μg/L group (9.5-fold higher than the control, p < 0.05). An iTRAQ-based proteomic analysis determined 168 differentially expressed proteins, while 1H NMR-based metabolomic profiling identified 34 metabolites with significant alterations. Integrated analysis of the proteomic and metabolomic data provided insights into the molecular responses of juvenile rockfish to Cd exposure. Specifically, metabolomic results indicated significant alterations in key metabolites, including lactate, phosphocholine, adenosine triphosphate, alanine, and inosine in the Cd-treated groups. Proteomic analysis further suggested that Cd exposure was associated with immune and oxidative stress responses, neurotoxicity, cellular damage, and disruptions in critical metabolic pathways, such as glycolysis, the tricarboxylic acid cycle, amino acid and lipid metabolism. Overall, this study demonstrates the utility of integrating proteomics and metabolomics to characterize molecular responses to Cd stress in juvenile S. schlegelii.

Animals↗

PubMed2026

Free polyphenols and multi-omics traits underlying antioxidant variation across Paeonia lactiflora leaf cultivars.

Leaves of Paeonia lactiflora are underutilized by-products with potential as natural antioxidant sources. In this study, 18 cultivars were evaluated for phytochemical composition and in vitro antioxidant capacity. Total phenolic content correlated strongly with DPPH and ABTS activities, and the comprehensive antioxidant index identified 'Coral Charm' and 'Hangshao' as representative high- and low-antioxidant cultivars, respectively. Untargeted metabolomics detected 2677 metabolites and identified 908 differential metabolites between the two cultivars. Targeted phenolic profiling quantified 27 compounds, among which 11 differed significantly between the two cultivars. Catechin and epicatechin were enriched in 'Coral Charm', with contents of 6.62 and 0.397 ng/mg, respectively, compared with 0.012 and 0.002 ng/mg in 'Hangshao'. (+)-Dihydroquercetin was also more abundant in 'Coral Charm', while caffeic acid showed an upward trend. Proteomic analysis identified 423 differentially expressed proteins, mainly associated with secondary metabolite biosynthesis, redox homeostasis, and central carbon metabolism. Integrated analysis identified pyruvate metabolism as the only pathway significantly enriched in both metabolomic and proteomic datasets. Molecular docking predicted favorable binding between representative phenolics and selected proteins. These findings link cultivar-dependent antioxidant variation in peony leaves with free-phenolic accumulation and pathway-level metabolic differences, supporting the selection and utilization of antioxidant-rich peony leaf resources.

Antioxidants↗

PubMed2025

TGF-β Receptor-dependent Tissue Factor Release and Proteomic Profiling of Extracellular Vesicles from Mechanically Compressed Human Bronchial Epithelial Cells.

In asthma, tissue factor (TF) concentrations are elevated in the lung. In our previous studies using mechanically compressed human bronchial epithelial (HBE) cells, which are a well-defined in vitro model of bronchoconstriction during asthma exacerbations, we detected TF within extracellular vesicles (EVs) released from compressed HBE cells. Here, to better characterize the potential role of this mechanism in asthma, we tested the extent to which the transcriptional regulation of epithelial cell-derived TF varied between donors with and without asthma. Using RNA in situ hybridization, we detected epithelial expression of F3, the TF protein-encoding gene, in human airways. Next, to determine the role of TGF-β receptor (TGF-βR) in the regulation of TF, we exposed well-differentiated HBE cells to mechanical compression in the presence or absence of a pharmacological inhibitor of TGF-βR. Furthermore, to identify the protein cargo of EVs released from HBE cells, we used tandem mass tag mass spectrometry. Our findings revealed significantly higher F3 expression in the airways of patients with asthma compared with healthy control subjects. However, we observed no differences in F3 expression or TF release between asthmatic and nonasthmatic HBE cells, both at baseline and after compression. Mechanistically, compression-induced F3 expression in HBE cells depended on TGF-βR. Our proteomic analysis identified 22 differentially released proteins in EVs, with higher concentrations in compressed cells compared with controls. Gene Ontology analysis indicates that these proteins are involved in diverse biological processes, highlighting a potential role for epithelial cell-derived EVs during asthma exacerbations.

Humans↗

PubMed2026

Multi-Omics Analysis Reveals Molecular Networks and Key Pathways Associated with Cysteine- and Methionine-Mediated Biosynthesis of Sulfur-Containing Flavor Metabolites in Lentinula edodes.

Lentinula edodes is renowned for its unique aroma, which is characterized by various volatile sulfur-containing flavor metabolites (SCFMs). Cysteine and methionine could enhance the SCFMs biosynthesis in L. edodes; however, the underlying metabolic pathways remain unclear. To bridge this gap, integrated proteomic and metabolomic analysis were performed to decipher pathways through which cysteine and methionine regulate SCFM biosynthesis. Results showed that exogenous cysteine and methionine supplementation significantly increased the content of lenthionine, the key aroma compound of shiitake mushrooms. Both treatments induced substantial changes in the proteomic and metabolomic profiles. Proteomic analysis revealed that differentially expressed proteins were predominantly enriched in cysteine and methionine metabolism and sulfur metabolism following cysteine treatment, whereas methionine treatment mainly affected proteins associated with tryptophan metabolism and sulfur metabolism. Metabolomic analysis showed that differentially accumulated metabolites were significantly enriched in D-amino acid metabolism and cysteine and methionine metabolism, with glutathione metabolism specifically enriched under cysteine treatment. Integrated omics analysis further uncovered distinct sulfur metabolite-protein regulatory networks under different sulfur nutrition and identified treatment-specific hub proteins. These findings establish a molecular regulatory framework linking SCFM biosynthesis with broader primary metabolic pathways involved in sulfur intermediate generation and regulation, providing new insights into the potential regulatory networks underlying SCFM formation in L. edodes.

Methionine↗

PubMed2026

Proteomic Analysis of Extracellular Vesicles Reveals Vitronectin and Laminin Subunit Alpha-3 as Candidate Biomarkers for Gastric Cancer.

BACKGROUND/AIMS: Clinically useful noninvasive biomarkers for gastric cancer remain limited. Extracellular vesicles (EVs) carry a molecular cargo reflective of their cells of origin and have emerged as promising candidates for blood-based cancer biomarkers. We aimed to identify EV-associated protein biomarkers for gastric cancer via a proteomic approach. METHODS: Proteomic profiling of EVs was performed using one normal gastric cell line (Hs738st/int) and two gastric cancer cell lines (AGS and NCI-N87). Selected proteins were validated in blood-derived EVs isolated from plasma samples of 10 healthy controls and 36 patients with gastric cancer. RESULTS: Proteomic analysis identified 224 differentially expressed proteins whose expression was consistently altered in gastric cancer cell line-derived EVs. Among these, vitronectin (VTN) and laminin subunit alpha-3 (LAMA3) were selected based on their consistent upregulation. EV-associated LAMA3 levels were significantly higher in patients with gastric cancer than in healthy controls (p=0.003), with significant elevations observed from stage II onward (p=0.041, p=0.017, and p=0.004 for stages II, III, and IV, respectively). EV-associated VTN levels were not significantly different overall (p=0.089); however, stage-specific analysis demonstrated significant increases in VTN levels in patients with stage III (p=0.036) and stage IV (p=0.005) gastric cancer. Both EV-associated VTN and LAMA3 levels showed significant positive correlations with the cancer stage (ρ=0.564 and ρ=0.611, respectively; both p<0.001). CONCLUSIONS: The levels of EV-associated VTN and LAMA3 appear to be more closely associated with disease progression than with early-stage detection of gastric cancer. These findings suggest that EV-based proteomic biomarkers may have clinical utility for monitoring tumor progression in patients with clinically advanced gastric cancer.

Humans↗

PubMed2026

11-O-galloylbergenin alleviates LPS-stimulated inflammation in RAW 264.7 macrophages by targeting Grb2, RhoA, and Cdc42 in the RAS signaling pathway.

OBJECTIVE: This study aimed to explore the anti-inflammatory mechanism of 11-O-galloylbergenin in macrophages. METHODS: Lipopolysaccharide (LPS)-stimulated RAW 264.7 macrophages were treated with 11-O-galloylbergenin. Cytotoxicity was assessed by 3-(4,5-Dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay, and cytokine secretion was measured by enzyme-linked immunosorbent (ELISA) assay. Data-independent acquisition (DIA)-based proteomics, Gene Ontology (GO)/Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, western blotting, and molecular docking were also performed. RESULTS: 11-O-Galloylbergenin (≤50 μg/mL) was non-cytotoxic and significantly suppressed tumor necrosis factor-alpha (TNF-α) and interleukin-6 (IL-6) secretion. Proteomics analysis identified 209 differentially expressed proteins (DEPs) that showed opposite expression trends before and after 11-O-galloylbergenin treatment. Seven of these DEPs were enriched in the RAS pathway: RhoA, Cdc42, Grb2, RalB, Calm3, Gnb2, and Pla2g4a. Western blotting confirmed that 11-O-galloylbergenin downregulated RhoA, Cdc42, and Grb2 expression. Molecular docking revealed good binding affinity of 11-O-galloylbergenin to RhoA, Cdc42, and Grb2. CONCLUSION: 11-O-Galloylbergenin alleviates LPS-stimulated inflammation in RAW 264.7 macrophages by inhibiting the RAS signaling pathway.

Animals↗

PubMed2025

Protective effects of liver-derived apolipoprotein A1 against heat stress-induced hypothalamic lipid metabolism and blood-brain barrier integrity.

Heat stress (HS), a prevalent occupational and environmental hazard, has increasingly been recognized as a major contributor to multiple physiological disorders. The hypothalamus, a key regulator of thermoregulation and endocrine signaling, is especially susceptible to metabolic and inflammatory disturbances induced by HS. This study investigates the interplay among lipid metabolism, blood-brain barrier (BBB) integrity, and neuroinflammation in the hypothalamus under HS conditions, with a specific focus on apolipoprotein A1 (APOA1) as a potential protective factor. To achieve this, we integrated proteomic and lipidomic analyses with experimental validation in porcine and murine models. Proteomic analysis identified 266 differentially expressed proteins (DEPs) in the hypothalamus following HS, with significant enrichment in lipid metabolism pathways-especially glycerophospholipid (GP) metabolism-in which APOA1 displayed a marked increase. Lipidomic profiling further revealed HS-induced disruptions in phosphatidylcholine (PC), phosphatidylethanolamine (PE), and cardiolipin (CL) metabolism. Additionally, blood-brain barrier integrity was compromised, as evidenced by increased perivascular IgG extravasation, reduced pericyte coverage, and decreased expression of tight junction proteins ZO-1 and Occludin. HS also triggered pronounced neuroinflammation, characterized by elevated levels of iNOS, GFAP, and pro-inflammatory cytokines (TNF-α, IL-1β, and IL-6). Notably, administration of D-4F, an APOA1 mimetic peptide, alleviated blood-brain barrier damage, reduced neuroinflammation, and preserved synaptic integrity, thereby suggesting a neuroprotective role for APOA1 in HS-induced hypothalamic dysfunction. These findings underscore the critical role of lipid metabolism in maintaining hypothalamic homeostasis under HS conditions and position APOA1 as a key regulator with potential therapeutic implications for mitigating HS-related neuroinflammatory and metabolic disturbances.

Blood-Brain Barrier↗

PubMed2025

Gain-of-function PPM1D mutations attenuate ischemic stroke.

Identification of genetic aberrations in stroke, the second leading cause of death worldwide, is of paramount importance for understanding the disease pathogenesis and generating new therapies. Whole-genome sequencing from 10,241 ischemic stroke patients identified eight patients carrying gain-of-function mutations on coding variants in the protein phosphatase magnesium-dependent 1 δ (PPM1D) gene. Patients carrying PPM1D mutations exhibit better stroke-related clinical phenotypes, including improvements in peripheral inflammation, fibrinogen, low-density lipoprotein, cholesterol and plateletcrit level. Experimental brain ischemia in Ppm1d-deficient (Ppm1d-/-) mice resulted in enlarged lesions and pronounced neurological impairments. Spatial transcriptomics revealed a distinct Ppm1d-associated gene expression pattern, indicating disrupted endothelial homeostasis during ischemic brain injury. Proteomic analysis demonstrated that differentially expressed proteins in primary brain endothelial cells from Ppm1d-/- mice were significantly enriched in the peroxisome proliferator-activated receptors (PPARs)-mediated metabolic signaling. Mechanistically, Ppm1d deficiency promoted aberrant fatty acid β-oxidation and increased oxidative stress, which impaired endothelial cell function through the PPARα pathway. A small molecule, T2755, was identified to engage Trp427 and stabilize PPM1D, thereby mitigating ischemic brain injury in mice. Collectively, we find that PPM1D protects against ischemic brain injury and validates its pharmacological stabilizer T2755 as a promising therapy for ischemic stroke. Gain-of-function PPM1D mutations attenuate ischemic cerebral injury. Whole-genome sequencing data of 10,241 ischemic stroke patients from the Third Chinese National Stroke Registry (CNSR-III) identified eight patients with gain-of-function mutations in the protein phosphatase magnesium-dependent 1 δ (PPM1D) gene (17q23.2). These mutation carriers displayed improved peripheral inflammation, decreased fibrinogen, low-density lipoprotein, cholesterol and plateletcrit level. Ppm1d-deficient (Ppm1d-/-) mice exhibited exacerbated stroke outcomes, characterized by enlarged infarct volumes, disrupted cerebrovascular architecture, and enhanced neuro-inflammation. Mechanistically, Ppm1d deficiency induced the disturbance of endothelial fatty acid metabolism involving the PPARα pathway. Through integrated computational modeling, virtual screening, and in vitro validation, T2755 was identified as a small molecule PPM1D stabilizer. Pharmacological PPM1D stabilization with T2755 significantly attenuated ischemic brain injury in murine models.

Aged↗

PubMed2026

Hepatic metabolic adaptation to endurance exercise: temporal and sex differences by multiomics integration and validation.

BACKGROUND: Although endurance exercise benefits liver health, sex-specific adaptive trajectories remain unclear. This study mapped dynamic liver adaptation in males and females during prolonged training and identified underlying molecular programs. METHODS: Using publicly available time-resolved liver multi-omics data generated by the Molecular Transducers of Physical Activity Consortium (MoTrPAC), we established a computational pipeline for differential analysis of transcriptomic, proteomic, phosphoproteomic, and metabolomic data with FDR correction, followed by FGSEA pathway enrichment. Kinase activities were inferred through ortholog mapping and PhosphoSitePlus. Cross-omics co-expression networks were constructed using WGCNA and topological overlap to link omics features with physiological phenotypes. For experimental validation, liver tissues were collected from endurance-trained Sprague-Dawley rats, and key nodes were confirmed by Western blotting, qRT-PCR, and immunofluorescence/immunohistochemical staining. Public scRNA-seq data were further integrated to map multi-omics signals to single-cell resolution and assess functional changes in specific cell types. RESULTS: The hepatic response to exercise stress was stage-specific, shifting from early transcriptional activation to later proteomic and metabolic remodeling. Multi-omics integration revealed distinct sex-associated adaptive trajectories: males were more strongly associated with energy metabolism, redox-related programs, and amino acid/organic acid catabolism, whereas females showed prominent membrane lipid remodeling, proteostasis -related programs, and mitochondrial/ribosomal translational features. Single-cell analysis showed that tissue remodeling occurred without major lineage turnover, instead involving altered communication among pre-existing cell communities. Validation of PPP1R3G identified a protein-dominant exercise-responsive marker, supporting the contribution of post-transcriptional or protein-level regulation. CONCLUSIONS: Hepatic adaptation to endurance stress follows a cross-omics evolutionary pattern with sex-specific reprogramming of energy supply and homeostatic maintenance. This time-resolved framework clarifies how exercise improves liver function and supports sex-oriented metabolic interventions and therapeutic target discovery.

Animals↗

PubMed2026

Systemic Proteomic Alterations and Predictive Biomarkers of Paroxetine Response in Refractory Rosacea: A Secondary Analysis of a Randomized Clinical Trial.

IMPORTANCE: Rosacea is a chronic inflammatory cutaneous disorder characterized by persistent erythema and vascular dysregulation. While paroxetine has shown clinical efficacy in reducing these symptoms, the systemic molecular mechanisms underlying its therapeutic response remain poorly characterized. OBJECTIVE: To investigate systemic proteomic alterations and identify potential predictive biomarkers in patients with refractory erythematous rosacea following paroxetine treatment. DESIGN, SETTING, AND PARTICIPANTS: This prospective plasma proteomic analysis was nested within a multicenter, randomized, double-blind, placebo-controlled clinical trial (Prospective Rosacea Refractory Erythema Randomized Clinical Trial [PRRERCT]). Participants included patients aged 18 to 65 years with refractory rosacea (Clinician's Erythema Assessment [CEA] score ≥3). Plasma samples were collected at baseline and after 12 weeks of treatment. The data for this study were analyzed between September 2025 and November 2025. INTERVENTIONS: Participants received oral paroxetine, 25 mg per day, for a 12-week treatment period. MAIN OUTCOMES AND MEASURES: Systemic protein expression profiles were analyzed using data-independent acquisition liquid chromatography-tandem mass spectrometry. Clinical response was evaluated using CEA and the Flushing Assessment Tool. Correlations between proteomic changes and clinical improvements were assessed, and predictive biomarkers were identified using receiver operating characteristic curve analysis. RESULTS: Among 24 participants (mean [SD] age, 35 [11] years; 24 [100%] female), paroxetine treatment significantly reduced mean (SD) CEA scores from 3.1 (0.3) to 2.3 (0.7) and Flushing Assessment Tool scores from 3.1 (0.6) to 2.0 (0.9) (P < .001). Exploratory proteomic analysis revealed 497 candidate differentially expressed proteins after treatment. Downregulated proteins showed preliminary enrichment in pathways related to immune response activation, insulin receptor signaling, and neuronal remodeling. A subset of 98 reversed-response proteins was observed, primarily linked to synaptic vesicle cycles and vascular smooth muscle contraction. Proteomic alterations were associated with clinical improvement (65 proteins for erythema; 73 for flushing). Candidate biomarkers, notably OLFML3 (area under the receiver operating characteristic curve [AUC], 0.87 [95% CI, 0.70-1.00]) and IGFBP2 (AUC, 0.80 [95% CI 0.55-1.00]), demonstrated high predictive value for clinical response. CONCLUSIONS AND RELEVANCE: In this secondary analysis of a randomized clinical trial, paroxetine treatment was associated with modulation of systemic neuro-vascular-immune networks in patients with rosacea. These exploratory findings provide preliminary mechanistic clues regarding the possible disease-modifying potential of paroxetine and point to circulating protein signatures that may facilitate personalized therapeutic strategies for rosacea management. TRIAL REGISTRATION: Chinese Clinical Trial Registry Identifier: ChiCTR2000031479.

Humans↗

PubMed2026

Proteomics-Based Identification of the Pyroptosis-Related Biomarker PCSK9 and Its Association With the Pathogenesis of Rheumatoid Arthritis.

Rheumatoid arthritis (RA) is a common autoimmune disease, and early diagnosis is critical for effective treatment. This study aims to identify potential biomarkers related to pyroptosis through serum proteomics analysis, offering new insights for the early diagnosis of RA. We enrolled 100 participants, including 50 patients with RA and 50 healthy controls. Serum samples were collected and analyzed using high-resolution liquid chromatography-tandem mass spectrometry (LC-MS/MS) for proteomics profiling. Differential protein expression analysis and functional annotation revealed significant upregulation of pyroptosis-related proteins in the serum of patients with RA. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, along with protein-protein interaction (PPI) network analysis, showed that these proteins are involved in inflammation and immune pathways, particularly the activation of the NOD-like receptor protein 3 (NLRP3) inflammasome. Enzyme-linked immunosorbent assay (ELISA) validation confirmed a significant increase in PCSK9 levels in patients with RA, suggesting that PCSK9 may play a key role in the pathogenesis of RA. This study provides new directions for biomarker research in RA, particularly regarding the potential involvement of the pyroptosis pathway, with significant clinical application prospects.

Humans↗

PubMed2026

A proteomic analysis of the PHF-forming tau fragment (tau297-391) following uptake into differentiated human neuronal SHSY5Y cells.

Tau self-assembly and intracellular deposition are associated with a group of neurodegenerative diseases called tauopathies, which include Alzheimer's disease (AD) and Pick's disease. Here, we measured the proteome response in human neuronal cells (differentiated SH-SY5Y) following the addition of a spontaneously amyloidogenic region of tau known as dGAE (tau297-391), which forms AD-like paired helical filaments in vitro, and proteomic analysis showed increased endogenous tau expression. Further interactome analysis uncovered increased association between tau and proteins associated with nuclear chromatin, the nucleolus, and the spliceosome, as well as the thiol-peroxidase, PRDX6, alongside an increase in reactive oxygen species. The present work highlights a method to identify proteome pathways that may play an important role in the development of tau pathology and reveals an oxidative stress response to dGAE.

Humans↗