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PubMed2026

Candidate biomarkers for early Giardia duodenalis infection revealed by time-resolved secretome proteomics.

Giardia duodenalis is a zoonotic protozoan parasite that causes giardiasis in humans and other mammals. Early diagnosis remains challenging because current diagnostic methods, including microscopy and enzyme-linked immunosorbent assays (ELISAs), primarily detect established infections. Consequently, a critical diagnostic gap exists during the early stage of infection within the first 2-48 h following exposure. To address this limitation, we characterized the proteins released by in vitro-cultured G. duodenalis trophozoites under serum-free conditions and evaluated their potential as early diagnostic biomarkers. Proteomic analysis of culture supernatants collected during early trophozoite incubation identified 31,773 peptides corresponding to 2504 quantifiable proteins. Temporal profiling showed distinct secretion patterns, including proteins that peaked during the early stage, progressively accumulated over time, or remained persistently abundant throughout the incubation period. Based on their secretion characteristics and predicted immunogenic properties, five candidate biomarkers were selected for further evaluation. Polyclonal antibodies raised against selected candidates successfully detected the corresponding proteins in serum-free culture supernatants, providing preliminary evidence for their potential utility as early-stage diagnostic targets. These findings identify stage-associated candidate proteins that may serve as a resource for future early giardiasis diagnostic development, provide a valuable resource for investigating host-parasite interactions, and establish a foundation for future diagnostic assay development. However, further validation in clinical and biological samples is required to confirm their diagnostic applicability. SIGNIFICANCE: Giardiasis, caused by Giardia duodenalis, is a major diarrheal disease worldwide. Although enzyme-linked immunosorbent assays (ELISAs) provide rapid detection, their diagnostic utility is limited by the lack of biomarkers capable of identifying infection during its earliest stages, creating a critical gap in the detection of active infection within 2-48 h following exposure. Using data-independent acquisition proteomics, this study provides a time-resolved characterization of proteins released by G. duodenalis trophozoites into serum-free culture supernatants. Our findings reveal temporal secretion dynamics of protein secretion and identify candidate biomarkers with potential utility for the development of early-stage diagnostic assays pending rigorous biological and clinical validation. In addition, this proteomic resource provides a foundation for investigating host-parasite interactions and may facilitate the development of future point-of-care diagnostic strategies.

Giardiasis↗

PubMed2024

Retinal Proteome Profiling of Inherited Retinal Degeneration Across Three Different Mouse Models Suggests Common Drug Targets in Retinitis Pigmentosa.

Inherited retinal degenerations (IRDs) are a leading cause of blindness among the population of young people in the developed world. Approximately half of IRDs initially manifest as gradual loss of night vision and visual fields, characteristic of retinitis pigmentosa (RP). Due to challenges in genetic testing, and the large heterogeneity of mutations underlying RP, targeted gene therapies are an impractical largescale solution in the foreseeable future. For this reason, identifying key pathophysiological pathways in IRDs that could be targets for mutation-agnostic and disease-modifying therapies (DMTs) is warranted. In this study, we investigated the retinal proteome of three distinct IRD mouse models, in comparison to sex- and age-matched wild-type mice. Specifically, we used the Pde6βRd10 (rd10) and RhoP23H/WT (P23H) mouse models of autosomal recessive and autosomal dominant RP, respectively, as well as the Rpe65-/- mouse model of Leber's congenital amaurosis type 2 (LCA2). The mice were housed at two distinct institutions and analyzed using LC-MS in three separate facilities/instruments following data-dependent and data-independent acquisition modes. This cross-institutional and multi-methodological approach signifies the reliability and reproducibility of the results. The large-scale profiling of the retinal proteome, coupled with in vivo electroretinography recordings, provided us with a reliable basis for comparing the disease phenotypes and severity. Despite evident inflammation, cellular stress, and downscaled phototransduction observed consistently across all three models, the underlying pathologies of RP and LCA2 displayed many differences, sharing only four general KEGG pathways. The opposite is true for the two RP models in which we identify remarkable convergence in proteomic phenotype even though the mechanism of primary rod death in rd10 and P23H mice is different. Our data highlights the cAMP and cGMP second-messenger signaling pathways as potential targets for therapeutic intervention. The proteomic data is curated and made publicly available, facilitating the discovery of universal therapeutic targets for RP.

Animals↗

PubMed2026

Subcellular Proteomic Analyses Reveal REEP5 Knockdown in the Mouse Heart Disrupts Mitochondrial Networks.

Receptor Expression-Enhancing Protein 5 (REEP5) is a cardiac-enriched, membrane-shaping protein localized to the sarco(endo)plasmic reticulum (SR/ER), where it supports membrane network architecture and cardiomyocyte function. While REEP5 has been implicated in calcium handling and contractility, its role in regulating inter-organelle communication and mitochondrial homeostasis remains less well-understood. In this study, we used recombinant adeno-associated virus serotype 9-mediated shRNA knockdown of Reep5 in mouse hearts, combined with subcellular fractionation and data-independent acquisition mass spectrometry, to define proteomic remodeling across microsomal (SR/ER), mitochondrial, and cytosolic compartments. Loss of REEP5 altered the composition of SR/ER membrane-shaping proteins, including upregulation of RTN4, ATL3, and CKAP4, suggesting a partial compensatory response. Microsomal, mitochondrial and cytosolic proteomes exhibited broad reorganization, with enrichment of proteins involved in redox adaptation and proteostasis, alongside depletion of mitochondrial import machinery and antioxidant enzymes. Imaging of isolated cardiomyocytes confirmed fragmented mitochondrial networks and increased reactive oxygen species, consistent with proteomic signatures of disrupted mitochondrial dynamics and oxidative stress. Gene ontology enrichment across all fractions highlighted widespread dysregulation in organelle-specific processes, including translation, protein localization, and metabolic remodeling. Notably, several altered pathways converged on mitochondria-associated membranes, suggesting that REEP5 may support SR/ER-mitochondria tethering and functional crosstalk. These findings position REEP5 as a key regulator of organelle homeostasis in the heart and underscore how its loss disrupts mitochondrial integrity and inter-organelle communication across cellular compartments.

Animals↗

PubMed2026

High-Fat Diet and a High Amyloid Load Interact to Induce PKC-α Dependent Synaptic Insulin Resistance.

A plethora of studies suggest that a high-fat diet in combination with a high amyloid load causes synaptic insulin resistance and is a risk factor for Alzheimer's disease. Our understanding of the underlying mechanisms is still fragmented. To gain new insights, we conducted integrated proteomic and phosphoproteomic profiling of hippocampal synaptosomes from WT and a transgenic mouse line with a high amyloid load (heterozygous TBA2.1 mice) that show no overt signs of neurodegeneration and dementia. Mice were fed with a regular or high-fat diet. Data-independent acquisition quantified over 5400 proteins, revealing a stable synaptic proteome across conditions. However, the combination of high amyloid load and high-fat diet triggered coordinated remodeling of lipid metabolism pathways, particularly mitochondrial and peroxisomal fatty acid catabolism. Phosphoproteomic analysis showed pronounced activation of lipid- and stress-responsive kinases, including protein kinase C-α, along with increased inhibitory phosphorylation of insulin receptor substrates (IRS1/2). In vitro experiments indicate that blocking protein kinase C-α indeed prevents synaptic insulin resistance in primary neurons. The findings suggest that this proteomic workflow, combined with kinase pathway analysis, can reveal nodal points for interventions in a complex disease state with a trajectory to Alzheimer's disease.

Animals↗

PubMed2026

A Parallel Accumulation-Mobility Aligned Fragmentation Strategy Utilizing High-Resolution Ion Mobility for High-Performance Proteomics Analysis.

Here we present a novel data-independent acquisition (DIA) mass spectrometry (MS) operating mode termed parallel accumulation-mobility aligned fragmentation (PAMAF) that offers enhanced speed and sensitivity of ion fragmentation analysis for discovery workflows such as bottom-up proteomics. This mode of operation leverages high-resolution ion mobility (HRIM) separation capabilities of the structures for lossless ion manipulation technology to achieve HRIM-based precursor isolation in place of traditional quadrupole filtering approaches. PAMAF mode increases the number of features that can be identified per MS1/MS2 acquisition cycle by employing mobility-based time alignment to associate fragment ions with their corresponding precursor ions. By using a high-speed, lossless separation technique for precursor isolation instead of the comparatively slow and wasteful quadrupole filtering, ion losses are avoided while simultaneously increasing the rate at which precursor ions are sequentially fragmented and detected. In addition, by accumulating ions while the previous packet of ions is being analyzed, the PAMAF mode achieves ∼100% ion utilization efficiency. Benchmarking results of LC-PAMAF-MS analysis of a whole cell protein digest showed ∼6× more protein group identifications compared to a standard data-dependent acquisition analysis without HRIM on the same QTOF instrument, and >100 x improvement for low-load workflows. Quantitative evaluations demonstrated that PAMAF mode could quantify low abundance peptides, including those undetectable by data-dependent acquisition. In addition, since precursor isolation in PAMAF mode is size-based rather than m/z-based, coeluting isobars and isomers can be resolved prior to fragmentation, eliminating chimeric spectra that compromise identification accuracy. We also explored the benefits of combining HRIM and quadrupole isolation to achieve improved specificity termed DIA-PAMAF mode, which enabled the detection of over 8000 protein groups from a HeLa digest analysis. PAMAF mode brings a powerful new technique to the field of proteomics with the potential to improve the sensitivity and selectivity of mass spectrometry-based proteomics.

Proteomics↗

PubMed2026

Temporal DIA-MS proteomics reveals coordinated metabolic reprogramming associated with oil accumulation in oil palm mesocarp.

Oil palm (Elaeis guineensis Jacq.) is the most productive oil-bearing crop globally, yet the molecular basis of mesocarp development and lipid accumulation remains poorly understood. Ultra-deep data-independent acquisition mass spectrometry (DIA-MS) was applied to characterize proteome dynamics in two contrasting genotypes, seedless (KS) and thin-shelled (TS), across five developmental stages (P1-P5) spanning fruit development to mature oil accumulation. Phenotypic analysis revealed higher mesocarp proportion and oil content in KS during late maturation. A total of 137,615 peptides corresponding to 12,163 protein groups were identified, providing a temporal proteomic landscape of mesocarp development. Multivariate analysis indicated that developmental progression was the primary contributor to proteomic variation, whereas genotype-associated differences increased during lipid accumulation. Differentially abundant proteins were mainly associated with carbohydrate metabolism, photosynthesis, proteolysis, antioxidant responses, and lipid biosynthesis. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and KOG analyses suggested extensive remodeling of metabolic networks, including developmental changes in photosynthesis-associated proteins and increased representation of lipid-associated pathways during maturation. Weighted protein co-expression network analysis identified 17 modules associated with developmental progression and lipid accumulation, highlighting candidate proteins involved in carbon metabolism, energy production, and cellular protection. Genes encoding selected hub protein candidates were further examined by RT-qPCR. Biochemical analyses supported these proteomic patterns, showing increased acetyl-CoA availability, enhanced antioxidant enzyme activities (SOD, CAT, APX, and GR), improved GSH/GSSG balance, and reduced oxidative damage in KS. Together, these findings provide a temporal proteomic and biochemical framework for understanding genotype-associated differences in oil accumulation and identify candidate metabolic networks for functional studies.

Carbon metabolism↗

PubMed2026

narrowPASEF: A Sample-Aware diaPASEF Method Optimization Strategy Improving Differential Proteomics Performance on Low-Abundance Proteins.

Recent instrumental and computational innovations in mass-spectrometry-based proteomics offer new promise in biomarker discovery, thanks to unprecedented proteome coverage and depth. Data-independent acquisition (DIA) methods are very promising in this context as they allow improved proteome coverage, reduced missing value rates, and enhanced quantification precision. However, DIA methods also suffer from their own challenges, such as increased data complexity, cycle times, and background noise. In this work, we propose a sample-aware diaPASEF method optimization strategy for a timsTOF platform. Thorough method optimizations have first been conducted on standard HeLa lysates. Then, a ground-truth calibrated sample series, consisting of a range of UPS amounts spiked into a complex Arabidopsis background, was used to mimic differential analyses under controlled conditions. These benchmark experiments demonstrate clear benefits of using narrowPASEF for differential protein discovery. Finally, our strategy was applied to real use case biological samples to conduct a differential analysis of purified mouse astrocyte cells across two different conditions. narrowPASEF improved the proteome depth by 13%, considering proteins quantified with a coefficient of variation (CV) of <20%, and led to a 68% (435 vs 729) increase in differentially expressed proteins. These results provide an opportunity for a more precise and comprehensive analysis of the biological functions of biomarkers, offering a more profound understanding of the disease mechanisms. The benefits of our sample-aware narrowPASEF strategy demonstrated the most substantial impact on low-abundance proteins. Overall, these results show promise for more valuable and robust biomarker discoveries in the future.

Proteomics↗

PubMed2026

Time- and Dose-Resolved DIA-PASEF Proteomics Maps the Transition from Adaptive Stress to Apoptotic Collapse in Melittin-Treated MDA-MB-231 Cells.

Melittin, the cytolytic peptide of honeybee venom, exhibits potent anticancer activity in triple-negative breast cancer (TNBC), yet the molecular programs underlying its cytotoxic effects remain incompletely defined. To address this gap, MDA-MB-231 TNBC cells were exposed to melittin at half-maximal inhibitory concentration(half IC50) and IC50 across early(0.5, 1, and 2 h), mid(3, 4 h), and late (12, 24 h) time windows. Proteomic profiling was performed using label-free data-independent acquisition(DIA) parallel accumulation-serial fragmentation(PASEF). Approximately 5800 proteins were quantified, revealing distinct dose-dependent stress responses. An integrative exploratory framework combining time-resolved log2 fold-change trajectories, area-under-the-curve(AUC) based temporal prioritization, and independent heatmap visualization identified proteins associated with melittin-induced stress remodeling. Half IC50 exposure showed a transient stress-adaptive signature characterized by chromatin remodeling(HMGN2, H2AZ1), structural and RNA-associated buffering(LRRC7), and indirect mitochondrial quality-control signaling(CPAMD8, SPATA4), which progressively weakened over time. In contrast, IC50 treatment induced rapid chromatin remodeling dominated by histone H1 variants(H1.4, H1.2), early RNA instability(LRRC7), and late-stage cytoskeletal disassembly marked by MICAL3 induction, consistent with progression toward apoptosis. These trajectories paralleled dose-dependent apoptotic phenotypes. Overall, data suggest that melittin elicits dose- and time-dependent proteomic stress responses in TNBC cells and identify candidate trajectory-associated proteins and pathways linked to adaptive stress remodeling or progression toward cytotoxic collapse.

Melitten↗

PubMed2026

A porcine spectral assay library to quantify brain proteome by DIA-MS.

Neurological disorders are the leading cause of health loss worldwide. The growing number of patients suffering from such conditions calls for improved strategies for their prevention, diagnosis, and therapy. To better understand human pathologies, relevant models and methodologies must be made available. In this study, we focused on a biomedical model capable of recapitulating the complexity of human pathology, the pig (Sus scrofa). Brain tissue and cerebrospinal fluid samples from a transgenic minipig model of Huntington's disease were subjected to multiple extraction and fractionation steps. A proteomic mass spectrometry (MS) methodology then allowed the generation of a porcine spectral library for 8,321 proteins. Using data-independent acquisition (DIA), we demonstrated that our porcine spectral library substantially enhanced the quantitative potential of this untargeted MS approach, generating reproducible proteome-wide data. The porcine library also provides a comprehensive resource for the development of targeted MS assays, enabling the quantification of selected proteins with a key role not only in neuroscience.

Animals↗

PubMed2026

Plasma proteome profiling identifies XPNPEP3 as a novel biomarker associated with metabolic dysfunction-associated steatotic liver disease in patients with type 2 diabetes mellitus.

OBJECTIVE: To identify plasma protein differences between type 2 diabetes mellitus (T2DM) patients with and without metabolic dysfunction-associated steatotic liver disease (MASLD), and to evaluate the diagnostic potential of X-prolyl aminopeptidase 3 (XPNPEP3) for identifying MASLD in T2DM patients. METHODS: Twenty T2DM inpatients were categorized into groups with and without MASLD and their plasma samples were analyzed using data-independent acquisition mass spectrometry, followed by bioinformatics analysis to identify differentially expressed proteins. The cohort was then expanded to 84 patients, and plasma XPNPEP3 levels were validated by enzyme-linked immunosorbent assay. Correlation between XPNPEP3 and clinical indicators were evaluated, and diagnostic performance was determined via receiver operating characteristic (ROC) analysis. Immunohistochemistry was employed to compare hepatic XPNPEP3 expression between the two groups. RESULTS: Proteomic analysis identified 176 differentially expressed proteins, with XPNPEP3 exhibiting the most significant down-regulation by fold change. In the validation cohort, plasma XPNPEP3 was significantly lower in T2DM+MASLD versus T2DM alone. XPNPEP3 levels were negatively correlated with diabetes duration, liver function markers, and triglyceride levels, and was identified as an independent factor inversely associated with MASLD in T2DM.ROC analysis demonstrated strong diagnostic performance for XPNPEP3, further enhanced when combined with BMI and diabetes duration.  Immunohistochemistry confirmed reduced hepatic XPNPEP3 expression in T2DM+MASLD patients. CONCLUSIONS: Lower plasma XPNPEP3 is independently associated with MASLD in T2DM patients and demonstrates strong diagnostic potential, positioning XPNPEP3 as a promising biomarker for diagnosing MASLD in T2DM patients and a novel target for non-invasive diagnostic tool development.

Humans↗

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

Relaxin-2: Shaping the Proteomic Landscape of Skeletal Muscle Physiology, Glucose Trafficking, and Mitochondrial Function in Rat.

Relaxin-2 is a hormone with robust beneficial effects on the heart and blood vessels and potential as a therapy for cardiovascular (CV) disease. Considering the interorgan communication between skeletal muscle and heart, and the relation between muscle quality/composition and CV events, we hypothesize that relaxin-2 may regulate skeletal muscle physiology and metabolism. We aim to evaluate the impact of relaxin-2 on the proteome of skeletal muscle from healthy Sprague-Dawley rats. Animals were treated with 0.4 mg/kg/day of serelaxin (recombinant form of human relaxin-2) or vehicle (PBS) for 2 weeks employing subcutaneous osmotic minipumps. Skeletal muscle protein identification and quantification were performed by LC-MS/MS using a Data-Independent Acquisition (DIA)-Sequential Window Acquisition of All Theoretical Fragment Ion Spectra (SWATH) method. SWATH/MS quantitative analysis identified that relaxin-2 significantly decreased 95 proteins and significantly increased 32 proteins in rat skeletal muscle when compared to control rats. From these, 34 proteins were associated with muscle function, myogenesis, muscle differentiation and/or regeneration, 20 are mitochondrial proteins (six from the complexes of the electron transport chain), and 10 proteins participate in glucose metabolism. Qualitative data-dependent workflow analysis identified 35 proteins exclusive to the skeletal muscle of the relaxin-2-treated group: eight proteins related to processes of skeletal muscle function (size, ion homeostasis or organization of caveolae structures and cytoskeleton) and myogenesis, and two proteins involved in muscle differentiation. Our work highlighted for the first time the role of relaxin-2 in crucial processes of muscle physiology and energetic metabolism, which could influence several processes involved in myopathy and CV.

Animals↗

PubMed2026

SpxA1 and SpxA2 function as a stoichiometry-dependent regulatory rheostat governing virulence gene expression in group A Streptococcus.

UNLABELLED: Group A Streptococcus (GAS) is a human-restricted pathogen whose global incidence has surged in the post-COVID era. The ability of GAS to shift from a colonizing to invasive phenotype depends on coordinated virulence gene regulation in response to host-derived signals. However, the mechanisms by which individual stress-sensing systems interact to reshape the virulence gene regulatory landscape remain incompletely understood. Here, we define the regulatory programs of two conserved transcriptional regulator paralogs, SpxA1 and SpxA2, using an integrated multi-omic approach combining RNA-seq, data-independent acquisition proteomics, NanoString-based transcriptional profiling across multiple host-relevant stress conditions, and chromatin immunoprecipitation with exonuclease treatment (ChIP-exo). RNA-seq revealed functionally distinct regulons with SpxA1 governing oxidative stress defense and SpxA2 coordinating virulence-associated gene expression linked to the CovRS two-component regulatory system. Proteomic analysis established SpxA2 as a ClpXP protease substrate in GAS and identified reciprocal paralog accumulation upon loss of either SpxA1 or SpxA2, consistent with compensatory transcriptional upregulation. NanoString profiling under bacitracin and human neutrophil peptide-1 challenge identified four gene modules with distinct stoichiometry-dependent and condition-dependent regulatory logic, revealing that the SpxA1/SpxA2 ratio rather than the activity of either paralog alone determines which transcriptional programs are engaged. ChIP-exo demonstrated that SpxA2 directly modulates CovR-DNA binding occupancy in a CovR-binding motif-dependent manner, simultaneously antagonizing CovR dimer binding at an extended (25 bp) CovR motif and facilitating CovR monomer binding at the canonical ATTARA motif. These findings establish the LiaFSR-SpxA2-CovRS axis as a cross-regulatory circuit through which GAS cell envelope stress sensing is directly transduced into coordinated virulence gene regulatory changes. IMPORTANCE: Group A Streptococcus (GAS) causes millions of infections annually, including a recent global surge in invasive disease. To survive in the human host, GAS must rapidly reprogram virulence gene expression in response to host-derived stresses. This study characterizes two conserved transcriptional regulators, SpxA1 and SpxA2, that govern this response through interaction with RNA polymerase to indirectly influence the DNA-binding activity of downstream transcription factors. We show that SpxA2, activated by a cell envelope stress-sensing system responding to human antimicrobial peptides, reshapes the binding of the master virulence regulator CovR in a promoter-specific manner, coupling cell envelope stress sensing to virulence gene regulation. The stoichiometric balance between SpxA1 and SpxA2 functions as a regulatory rheostat calibrating overall virulence gene regulatory tone, providing a framework for understanding how RNA polymerase-interacting regulators coordinate stress responses and virulence gene control across Gram-positive bacterial pathogens.

Streptococcus pyogenes↗

PubMed2026

DIA proteomics of FFPE renal biopsies reveals two molecular subtypes of lupus nephritis and identifies APOL1 as candidate biomarker for stratification.

INTRODUCTION: Lupus nephritis (LN) exhibits substantial clinical and pathological heterogeneity. We aimed to define proteomics-based molecular subtypes of LN and identify candidate biomarkers for subtype discrimination. METHODS: We analysed formalin-fixed paraffin-embedded (FFPE) renal biopsy specimens from 292 patients with biopsy-proven LN from four tertiary hospitals using data-independent acquisition (DIA)-liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomics. Molecular subtypes were identified by non-negative matrix factorisation. Differential proteins, functional enrichment, immune pathway activity, protein-protein interaction networks and subtype-associated clinical/pathological features were evaluated. Extreme Gradient Boosting (XGBoost) with SHapley Additive exPlanations (SHAP) and Least Absolute Shrinkage and Selection Operator (LASSO) logistic regression were used to identify key subtype-related features and derive a protein panel distinguishing proliferative (class III/IV) from membranous (class V) LN. RESULTS: Two stable molecular subtypes were identified, with 1002 differential proteins between them. Subtype_2 was enriched for interferon-related innate immunity, complement activation, phagocytosis-endocytosis-lysosome pathways and ribosome biogenesis/RNA metabolism, whereas Subtype_1 was characterised by keratinisation and epithelial structural remodelling. Subtype_2 was associated with higher serum creatinine, lower estimated glomerular filtration rate and higher chronicity index. APOL1 showed discriminatory value between subtypes, and serum ELISA demonstrated a consistent pattern with FFPE proteomic findings. A five-protein LASSO panel achieved an area under the curve of approximately 0.76 for distinguishing class III/IV from class V LN. CONCLUSION: DIA-based proteomic profiling of FFPE renal biopsies identifies biologically and clinically relevant LN molecular subtypes and may support tissue-informed classification and risk stratification.

Humans↗

PubMed2025

Identification of Biomarkers for Right Ventricular Dysfunction in Idiopathic Dilated Cardiomyopathy Via Urinary Proteomics and Machine Learning.

BACKGROUND: Right ventricular dysfunction (RVD) is a common complication of idiopathic dilated cardiomyopathy linked to poor outcomes. However, reliable noninvasive biomarkers for RVD remain lacking. This study aimed to identify urinary proteomic markers using mass spectrometry and machine learning. METHODS: In this prospective cohort, patients with idiopathic dilated cardiomyopathy were classified by cardiac magnetic resonance imaging into groups with RVD (RV ejection fraction <45%) and without RVD groups. Baseline urine samples were profiled by data-independent acquisition mass spectrometry. Differentially expressed proteins were identified and selected by least absolute shrinkage and selection operator regression to build a diagnostic model, developed in a training set, and validated in a test set. The primary end point was a composite of cardiovascular death, heart failure rehospitalization, left ventricular assist device implantation, or heart transplantation. RESULTS: The study enrolled 147 patients with idiopathic dilated cardiomyopathy (64 with RVD, 83 without), with a median follow-up of 19.3 months. Of 3579 quantified urinary proteins, 46 were differentially expressed between groups. A 3-protein panel (RARRES1 [retinoic acid receptor responder protein 1], MVB12B [multivesicular body subunit 12B], GSK3A [glycogen synthase kinase 3 alpha]) was identified and showed excellent diagnostic accuracy (training area under the curve 0.946; validation area under the curve0.935), outperforming both NT-proBNP (N-terminal pro-brain natriuretic peptide) and tricuspid annular plane systolic excursion. The risk score derived from this panel effectively stratified patients, with the high-risk group exhibiting significantly worse outcomes than the low-risk group (hazard ratio, 3.24 [95% CI, 1.56-6.71], P=0.002). CONCLUSIONS: The urinary proteomic panel developed in this study demonstrates diagnostic and prognostic potential for identifying RVD in idiopathic dilated cardiomyopathy, providing a promising noninvasive tool for precise detection and clinical risk stratification.

Humans↗

PubMed2026

Large-scale proteomics profiling of peripheral blood of DM1 patients identifies biomarkers for disease severity and functional capacity.

BackgroundMyotonic Dystrophy Type 1 (DM1), the most common genetic neuromuscular disorder in adults, poses significant challenges for drug development due to its multisystem nature and high clinical variability in symptoms and disease progression. With a growing number of therapies entering clinical trials, this study addresses the urgent need for biomarkers that can serve as surrogate endpoints.MethodsWe profiled 437 serum samples from adult DM1 patients collected at two timepoints of the OPTIMISTIC trial using bottom-up mass spectrometry with data-independent acquisition. Associations between protein expression, the disease-causing CTG-repeat and 25 clinical outcome measures were studied using linear mixed-effect models. All key study findings were validated in an independent cohort of 69 DM1 patients and 10 healthy controls.ResultsOf the 259 identified proteins, 161 showed significant associations with the CTG-repeat length (FDR < 5%). Hypogammaglobulinemia was confirmed and shown to be worse in severely affected patients. A strong proteomic signature was associated with clinical measures of functional capacity, with the 6-Minute Walk Test showing the strongest signal (70 associations, FDR < 5%). These novel associations reveal a compelling link between chronic inflammation and reduced functional capacity. A machine learning algorithm identified a minimal set of 13 proteins robustly reflecting both the underlying genetic defect and functional capacity.ConclusionsDM1 induces a broad disease fingerprint in the serum proteome, predominantly affecting proteins of the immune system. A carefully selected panel of proteins showed the greatest potential to meet the statistical criteria required for surrogate endpoints in clinical trials.

Humans↗

PubMed2026

P1D6 inhibits FnBP-induced extracellular proteome remodeling: proteomic evidence for a novel intervention strategy in atopic dermatitis.

Atopic dermatitis (AD) is an inflammatory skin disorder characterized by skin barrier impairment, chronic inflammation, and intense pruritus. Staphylococcus aureus (S. aureus) critically contributes to its pathogenesis; however, the mechanistic role of its virulence factor fibronectin-binding protein (FnBP) in keratinocytes remains poorly understood. This study used bibliometric analysis and quantitative proteomics to examine the relationship. We first performed a bibliometric analysis, revealing a sustained increase in publications on S. aureus and AD, peaking at 99 articles in 2023, with hotspots focused on skin barrier function, immune inflammation, and pediatrics. Quantitative proteomics was employed to investigate how FnBP reshapes the extracellular proteome and whether the anti-α5 integrin antibody P1D6 exerts interventional effects. HaCaT cells were stimulated with recombinant FnBP alone or in combination with P1D6, followed by data-independent acquisition (DIA)-based proteomic analysis of secretome changes. Proteomic analysis identified FnBP-induced differentially expressed proteins enriched in immune- and barrier-related pathways, including cell adhesion, cell junctions, and VEGFA-VEGFR2 signaling. P1D6 intervention significantly inhibited the secretome profile and identified 241 core responsive proteins, of which approximately 52% returned to baseline levels after intervention (P > 0.05). These proteins were primarily enriched in pathways governing protein homeostasis, folding, proteasomal degradation, and interleukin-7 signaling. Notably, P1D6 modulated the downregulation of ATP5F1B and P4HB, key effectors within the interleukin-7 pathway. This study demonstrates that FnBP remodels the keratinocyte secretome by disrupting protein homeostasis, consequently inducing barrier injury and chronic inflammation related to AD, which can be effectively blocked by P1D6. Combined with bibliometric trends and proteomic evidence, this study focuses on FnBP, an underexplored virulence factor, and provides novel insights into AD pathogenesis and therapeutic interventions.

Humans↗

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↗