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PubMed2003

Proteomics of bacterial pathogens.

The rapid growth of proteomics that has been built upon the available bacterial genome sequences has opened provided new approaches to the analysis of bacterial functional genomics. In the study of pathogenic bacteria the combined technologies of genomics, proteomics and bioinformatics has provided valuable tools for the study of complex phenomena determined by the action of multiple gene sets. The review considers some of the recent developments in the establishment of proteomic databases as well as attempts to define pathogenic determinants at the level of the proteome for some of the major human pathogens. Proteomics can also provide practical applications through the identification of immunogenic proteins that may be potential vaccine targets as well as in extending our understanding of antibiotic action. There is little doubt that proteomics has provided us with new and valuable information on bacterial pathogens and will continue to be an important source of information in the coming years.

Animals↗
PubMed2006

Applications and current challenges of proteomic approaches, focusing on two-dimensional electrophoresis.

Since the formulation of the concept of "proteomics" in 1995, a plethora of proteomic technologies have been developed in order to study proteomes of tissues, cells and organelles. The powerful new technologies enabled by proteomic approaches have lead to the application of these methods to an exponentially increasing variety of biological questions for highly complex protein mixtures. Continuous technical optimization allows for an ever-increasing sensitivity of proteomic techniques. In this review, a brief overview of currently available proteomic techniques and their applications is given, followed by a more detailed description of advantages and technical challenges of two-dimensional electrophoresis (2-DE). Some solutions to circumvent currently encountered technical difficulties for 2-DE analyses are proposed.

Animals↗
PubMed2005

Proteome profiling of human epithelial ovarian cancer cell line TOV-112D.

A proteome profiling of the epithelial ovarian cancer cell line TOV-112D was initiated as a protein expression reference in the study of ovarian cancer. Two complementary proteomic approaches were used in order to maximise protein identification: two-dimensional gel electrophoresis (2DE) protein separation coupled to matrix assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI-TOF MS) and one-dimensional gel electrophoresis (1DE) coupled to liquid-chromatography tandem mass spectrometry (LC MS/MS). One hundred and seventy-two proteins have been identified among 288 spots selected on two-dimensional gels and a total of 579 proteins were identified with the 1DE LC MS/MS approach. This proteome profiling covers a wide range of protein expression and identifies several proteins known for their oncogenic properties. Bioinformatics tools were used to mine databases in order to determine whether the identified proteins have previously been implicated in pathways associated with carcinogenesis or cell proliferation. Indeed, several of the proteins have been reported to be specific ovarian cancer markers while others are common to many tumorigenic tissues or proliferating cells. The diversity of proteins found and their association with known oncogenic pathways validate this proteomic approach. The proteome 2D map of the TOV-112D cell line will provide a valuable resource in studies on differential protein expression of human ovarian carcinomas while the 1DE LC MS/MS approach gives a picture of the actual protein profile of the TOV-112D cell line. This work represents one of the most complete ovarian protein expression analysis reports to date and the first comparative study of gene expression profiling and proteomic patterns in ovarian cancer.

Cell Line, Transformed↗
PubMed2004

Proteomic analysis of rat atrial secretory granules: a platform for testable hypotheses.

The recent development of powerful proteomic tools has enabled investigators to directly examine the population of proteins present in defined biological systems. We report here the first proteomic analysis of atrial secretory granules. Approximately 100 distinct protein components of the atrial secretory granule proteome were detected using subcellular fractionation and one-dimensional SDS-PAGE in conjunction with peptide mass fingerprinting by MALDI-TOF mass spectrometry. Of this number, 61 proteins were clearly identified by high probability data matches and repeated observation. The majority of the proteome was found to be membrane-associated with the most prominent proteins being peptidylglycine alpha-amidating monooxygenase (PAM) and pro-atrial natriuretic peptide (pro-ANP). This proteomic analysis of the rat atrium secretory granule produced an assembly of proteins with a diverse array of reported functions. The identified proteins fall into seven functional categories: (1) granular transport, docking and fusion; (2) signal transduction; (3) calcium-binding/calcium-dependent; (4) cellular architecture/chaperoning; (5) peptide/protein processing; (6) hormone; (7) proton transport. The novel finding of several protein processing enzymes and signal transduction proteins offer new perspectives on how pro-ANP is stored and processed to ANP during release. Accordingly, defining the proteome of the atrial secretory granule provides a framework for the development of new hypotheses that address key mechanisms governing granule function and ANP secretion.

Animals↗
PubMed2005

Proteomic resources: integrating biomedical information in humans.

Recent improvements in high-throughput proteomic technologies have unleashed the potential for generating vast amounts of data. Managing and sharing proteomic data is not an easy task. In this article, we will discuss some of the high-throughput proteomic techniques that are commonly used today. We will also review the major issues in sharing and dissemination of proteomic data and the recent community initiatives to standardize data formats and ontologies. An overview of the web-based resources and databases for analysis of proteomic data is also provided. Integration of disparate proteomic data sources with genomic and transcriptomic data should make systems biology type of approaches feasible in the near future.

Amino Acid Sequence↗
PubMed2005

Proteome analyses of Staphylococcus aureus in growing and non-growing cells: a physiological approach.

Staphylococcus aureus is a versatile human pathogen causing a wide variety of diseases ranging from wound infection to endocarditis, osteomyelitis, and sepsis. In order to investigate this pathogen, we sought to analyze the cytoplasmic proteome of S. aureus COL by using two different approaches: two-dimensional (2D) gel analyses combined with matrix-assisted laser ionization-time of flight mass spectrometry and a gel-free system using multidimensional liquid chromatography followed by mass spectrometry. By combining both analyses we identified 1123 cytoplasmic proteins that represent two-thirds of the cytoplasmic proteome of the organism. With our standard 2D gel setup (pI 4-7) we identified 473 proteins that cover about 40% of the cytoplasmic proteome predicted for this proteomic window. The identified proteins belong to a variety of cellular functions ranging from the transcriptional and translational machinery, tricarboxylic acid cycle (TCC), glycolysis, and fermentation pathways to biosynthetic pathways of nucleotides, fatty acids, and cell wall components. While most of the metabolic pathways predicted for S. aureus were covered by this gel-based proteomics 650 additional proteins were identified by the gel-free approach, among them alkaline or hydrophobic proteins. In our work, we established a master 2D gel that enabled us to study the regulation of core carbon metabolism in S. aureus cells grown in a complex medium. Our comparison of the protein pattern of exponentially growing cells with that of stationary-phase cells revealed a higher amount of enzymes involved in protein synthesis, transcription, and glycolysis in exponentially growing cells. In contrast, enzymes of the TCC and gluconeogenesis are increased at the stationary phase. With this comprehensive proteome map we have an essential tool for a better understanding of cell physiology of the human pathogen, S. aureus.

Adaptation, Physiological↗
PubMed2026

Proteome-level evidence that tebuconazole, both alone and in interaction with thiacloprid, affects epigenetic events in bumblebee heads.

Tebuconazole, a widely used ergosterol biosynthesis-inhibiting fungicide, can affect nontargets, especially when combined with insecticides. We employed label-free quantitative proteomics to investigate the effects of long-term exposure to sublethal concentrations (100 μg/L) of tebuconazole, either by itself or alongside the neonicotinoid thiacloprid (100 μg/L), on the heads of Bombus terrestris workers. A Bayesian factor power analysis revealed that the experiment produced conclusive proteomic results. Tebuconazole treatment revealed eleven differentially abundant proteins, which increased elevenfold with thiacloprid. The proteins that changed in the same direction in both treatments suggest the occurrence of epigenetic events because they are involved in histone trimethylation (H3K4me3), pre-mRNA processing, and folate (vitamin B9) metabolism. Following co-exposure, the abundance of histone H2A.V and its associated proteins was affected. Two important detoxification-related proteins, CYP6BE1 and CYP6AQ1 (honey bee homologs), were identified, as well as proteins that suggest hormonal and neurotoxic effects. Overall, this study suggests that tebuconazole affects key epigenetic processes in bumblebee heads at the proteome level, though this was not confirmed at the biological level or through orthogonal methods. The tested chemicals were previously found to affect trimethylations, but not H3K4me3. We suggest analyzing the different trimethylations, their interplay, and associated hallmarks, such as folate levels. SIGNIFICANCE: The effects of pesticides and their combinations on organisms can be unexpected until they are examined using modern, complex methods. High-throughput proteomics can provide data on important biochemical processes affected by pesticides, offering a different perspective to that at the expression level. Despite their low acute toxicity, a group of fungicides that inhibit (ergo)sterol biosynthesis (EBI or SBI) are considered dangerous to pollinators, including bumblebees. This is due to the increasing toxicity of insecticides through the inhibition of cytochrome P450 detoxification enzymes. We found that tebuconazole had a similar effect on epigenetic events when used alone or in combination with the insecticide thiacloprid. Key proteins suggest that H3K4 histone trimethylation (H3K4me3) was impacted. To our knowledge, this expands the existing evidence suggesting that tebuconazole/triazole fungicides affect histone trimethylation H3K27me3. Since literature shows that thiacloprid affects H3K9me3, it is possible that thiacloprid and tebuconazole interact in these epigenetic events that affect each other. Overall, our results suggest that tebuconazole affects proteins involved in histone trimethylation, pre-mRNA processing, and folate metabolism. These are all hallmarks of epigenetic processes and were further extended by the co-exposure of tebuconazole and thiacloprid to more differently abundant proteins. Additionally, the results provide data on cytochrome P450s of the CYP6 family, which act as detoxifying proteins, as well as proteins that indicate hormonal and neurotoxic effects in bumblebee heads. Finally, the results of the Bayesian power analysis confirmed the meaningfulness of the proteomic data analyzed in this study. If the new findings obtained at the proteome level are verified by different methods, the full extent of the side effects of tebuconazole can be revealed.

Animals↗
PubMed2026

Evaluation of pilocarpine effects on sweat proteome.

BACKGROUND: Sweat is increasingly recognized as a valuable, non-invasive biofluid for biomarker discovery, yet its composition depends on the stimulation method. This study aimed to determine how pharmacological induction with pilocarpine compares to physiologically induced sweat through exercise in shaping the sweat proteome. RESULTS: We analyzed thermoregulatory sweat from exercise, pilocarpine-induced sweat, and combined pilocarpine plus exercise sweat. Total protein concentrations were similar across conditions, but pilocarpine markedly increased proteomic diversity, with combined pilocarpine plus exercise sweat showing the highest number of identifications. The core sweat proteome remained stable, while pilocarpine selectively enriched low-abundance proteins involved in vesicular trafficking, cytoskeletal remodelling, and metabolism. Proteins linked to the canonical M3-Gq-PLC-Ca2+ pathway, including AQP5, CALML5, and CLIC1, were consistently enriched, confirming cholinergic activation. Pilocarpine-induced sweat also contained plasma-derived and immune-related proteins, reflecting enhanced secretion and reduced ductal reabsorption. CONCLUSIONS: Exercise yields a physiologically relevant but less complex proteome, pilocarpine-induced sweat produces a pharmacologically enriched yet biased profile, and combined pilocarpine plus exercise sweat maximizes protein detection at the expense of interpretability. These findings highlight the critical impact of stimulation paradigm on sweat proteomics and provide a reference framework for biomarker research. SIGNIFICANCE: This study employed LC-MS/MS to systematically characterize eccrine sweat and delineate how stimulation paradigms-exercise, pilocarpine, and their combination-shape its proteomic landscape. By demonstrating that pharmacological induction profoundly alters protein diversity and composition compared to physiologically induced sweat, these findings establish a critical benchmark for sweat-based biomarker research and highlight the need for paradigm-aware sampling strategies in clinical and translational contexts. Nonetheless, several methodological constraints warrant consideration: the limited sample size (five individuals per group), the exclusive inclusion of women under combined oral contraceptive treatment (21 active pills followed by 7 pill-free days), which restricts extrapolation to naturally cycling women, and the focus on healthy young adults (18-25 years), limiting generalizability to older or clinically heterogeneous populations. Despite these limitations, this work provides a foundational framework for optimizing sweat collection protocols and advancing precision approaches in non-invasive diagnostics.

Pilocarpine↗
PubMed2005

Development and application of proteomics technologies in Saccharomyces cerevisiae.

Proteomics research focuses on the identification and quantification of "all" proteins present in cells, organisms or tissue. Proteomics is technically complicated because it encompasses the characterization and functional analysis of all proteins that are expressed by a genome. Moreover, because the expression levels of proteins strongly depend on complex regulatory systems, the proteome is highly dynamic. This review focuses on the two major proteomics methodologies, one based on 2D gel electrophoresis and the other based on liquid chromatography coupled to mass spectrometry. The recent developments of these methodologies and their application to quantitative proteomics are described. The model system Saccharomyces cerevisiae is considered to be the optimal vehicle for proteomics and we review studies investigating yeast adaptation to changes in (nutritional) environment.

Chromatography, Liquid↗
PubMedDate not supplied

Liquid chromatography MALDI MS/MS for membrane proteome analysis.

Membrane proteins play critical roles in many biological functions and are often the molecular targets for drug discovery. However, their analysis presents a special challenge largely due to their highly hydrophobic nature. We present a surfactant-aided shotgun proteomics approach for membrane proteome analysis. In this approach, membrane proteins were solubilized and digested in the presence of SDS followed by newly developed auto-offline liquid chromatography/matrix-assisted laser desorption ionization (LC/MALDI) tandem MS analysis. Because of high tolerance of MALDI to SDS, one-dimensional (1D) LC separation can be combined with MALDI for direct analysis of protein digests containing SDS, without the need for extensive sample cleanup. In addition, the heated droplet interface used in LC/MALDI can work with high flow LC separations, allowing a relatively large amount of protein digest to be used for 1D LC/MALDI which facilitates the detection of low abundance proteins. The proteome identification results obtained by LC/MALDI are compared to the gel electrophoresis/MS method as well as the shotgun proteomics method using 2D LC/electrospray ionization MS. It is demonstrated that, while LC/MALDI provides more extensive proteome coverage compared to the other two methods, these three methods are complementary to each other and a combination of these methods should provide a more comprehensive membrane proteome analysis.

Chromatography, High Pressure Liquid↗
PubMed2006

A chick retinal proteome database and differential retinal protein expressions during early ocular development.

Proteomics approach as a research tool has gained popularity in a growing number of basic and clinical researches. However, proteomic research has yet to gain significant momentum in eye research. Hence, we decided to build a retinal proteome database using postnatal retinal tissue from chick, a commonly used animal model in eye research. Employing 2-D gels with the coverage of 3-10 pH gradients, we were able to resolve hundreds of proteins from young chick retinae. Among them, 155 high abundant proteins were identified by Peptide Mass Fingerprinting (PMF) after the Matrix-Assisted Laser Desorption Ionization-Time-of-Flight Mass Spectrometry (MALDI-TOF MS). These proteins were then classified according to their functions. Making use of the retinal database, we were able to identify several differentially expressed proteins that might be involved in early retinal development by comparing the 2-DE maps of chick retinal tissues (3, 10, and 20 days after hatching). With the current proteomics approach, we not only documented the most abundant soluble proteins in the chick retinal tissue, but also demonstrated the dynamic protein expression changes during early ocular development. This represents one of the first steps in building a complete protein database in chick retinae which is applicable to the study of eye diseases from a few selected protein candidates to the whole proteome. Proteomic technology may provide a high throughput platform for advancing eye research in the feasible future.

Animals↗
PubMed2006

Proteome-on-a-chip: mirage, or on the horizon?

Proteomics has emerged as the next great scientific challenge in the post-genome era. But even the most basic form of proteomics, proteome profiling, i.e., identifying all of the proteins expressed in a given sample, has proven to be a demanding task. The proteome presents unique analytical challenges, including significant molecular diversity, an extremely wide concentration range, and a tendency to adsorb to solid surfaces. Microfluidics has been touted as being a useful tool for developing new methods to solve complex analytical challenges, and, as such, seems a natural fit for application to proteome profiling. In this review, we summarize the recent progress in the field of microfluidics in four key areas related to this application: chemical processing, sample preconcentration and cleanup, chemical separations, and interfaces with mass spectrometry. We identify the bright spots and challenges for the marriage of microfluidics and proteomics, and speculate on the outlook for progress.

Animals↗
PubMed2024

MACSPI enables tissue-selective proteomic and interactomic analyses in multicellular organisms.

Multicellular organisms are composed of many tissue types that have distinct morphologies and functions, which are largely driven by specialized proteomes and interactomes. To define the proteome and interactome of a specific type of tissue in an intact animal, we developed a localized proteomics approach called Methionine Analog-based Cell-Specific Proteomics and Interactomics (MACSPI). This method uses the tissue-specific expression of an engineered methionyl-tRNA synthetase to label proteins with a bifunctional amino acid 2-amino-5-diazirinylnonynoic acid in selected cells. We applied MACSPI in Caenorhabditis elegans, a model multicellular organism, to selectively label, capture, and profile the proteomes of the body wall muscle and the nervous system, which led to the identification of tissue-specific proteins. Using the photo-cross-linker, we successfully profiled HSP90 interactors in muscles and neurons and identified tissue-specific interactors and stress-related interactors. Our study demonstrates that MACSPI can be used to profile tissue-specific proteomes and interactomes in intact multicellular organisms.

Animals↗
PubMed2004

Comparative proteome analysis of Saccharomyces cerevisiae grown in chemostat cultures limited for glucose or ethanol.

The use of chemostat culturing enables investigation of steady-state physiological characteristics and adaptations to nutrient-limited growth, while all other relevant growth conditions are kept constant. We examined and compared the proteomic response of wild-type Saccharomyces cerevisiae CEN.PK113-7D to growth in aerobic chemostat cultures limited for carbon sources being either glucose or ethanol. To obtain a global overview of changes in the proteome, we performed triplicate analyses using two-dimensional gel electrophoresis and identified proteins of interest using MS. Relative quantities of about 400 proteins were obtained and analyzed statistically to determine which protein steady-state expression levels changed significantly under glucose- or ethanol-limited conditions. Interestingly, only enzymes involved in central carbon metabolism showed a significant change in steady-state expression, whereas expression was only detected in one of both carbon source-limiting conditions for 15 of these enzymes. Side effects that were previously reported for batch cultivation conditions, such as responses to continuous variation of specific growth rate, to carbon-catabolite repression, and to accumulation of toxic substrates, were not observed. Moreover, by comparing our proteome data with corresponding mRNA data, we were able to unravel which processes in the central carbon metabolism were regulated at the level of the proteome, and which processes at the level of transcriptome. Importantly, we show here that the combined approach of chemostat cultivation and comprehensive proteome analysis allowed us to study the primary effect of single limiting conditions on the yeast proteome.

Aerobiosis↗
PubMed2005

New data analysis and mining approaches identify unique proteome and transcriptome markers of susceptibility to autoimmune diabetes.

Non-obese diabetic (NOD) mice spontaneously develop autoimmunity to the insulin producing beta cells leading to insulin-dependent diabetes. In this study we developed and used new data analysis and mining approaches on combined proteome and transcriptome (molecular phenotype) data to define pathways affected by abnormalities in peripheral leukocytes of young NOD female mice. Cells were collected before mice show signs of autoimmunity (age, 2-4 weeks). We extracted both protein and RNA from NOD and C57BL/6 control mice to conduct both proteome analysis by two-dimensional gel electrophoresis and transcriptome analysis on Affymetrix expression arrays. We developed a new approach to analyze the two-dimensional gel proteome data that included two-way analysis of variance, cluster analysis, and principal component analysis. Lists of differentially expressed proteins and transcripts were subjected to pathway analysis using a commercial service. From the list of 24 proteins differentially expressed between strains we identified two highly significant and interconnected networks centered around oncogenes (Myc and Mycn) and apoptosis-related genes (Bcl2 and Casp3). The 273 genes with significant strain differences in RNA expression levels created six interconnected networks with a significant over-representation of genes related to cancer, cell cycle, and cell death. They contained many of the same genes found in the proteome networks (including Myc and Mycn). The combination of the eight, highly significant networks created one large network of 272 genes of which 82 had differential expression between strains either at the protein or the RNA level. We conclude that new proteome data analysis strategies and combined information from proteome and transcriptome can enhance the insights gained from either type of data alone. The overall systems biology of prediabetic NOD mice points toward abnormalities in regulation of the opposing processes of cell renewal and cell death even before there are any clear signatures of immune system activation.

Analysis of Variance↗
PubMed2003

Tumor antigens and proteomics from the point of view of the major histocompatibility complex peptides.

The major histocompatibility complex (MHC) peptide repertoire of cancer cells serves both as a source for new tumor antigens for development of cancer immunotherapy and as a rich information resource about the protein content of the cancer cells (their proteome). Thousands of different MHC peptides are normally displayed by each cell, where most of them are derived from different proteins and thus represent most of the cellular proteome. However, in contrast to standard proteomics, which surveys the cellular protein contents, analyses of the MHC peptide repertoire correspond more to the rapidly degrading proteins in the cells (i.e. the transient proteome). MHC peptides can be efficiently purified by affinity chromatography from membranal MHC molecules, or preferably following transfection of vectors for expression of recombinant soluble MHC molecules. The purified peptides are resolved and analyzed by capillary high-pressure liquid chromatography-electrospray ionization-tandem mass spectrometry, and the data are deciphered with new software tools enabling the creation of large databanks of MHC peptides displayed by different cell types and by different MHC haplotypes. These lists of identified MHC peptides can now be used for searching new tumor antigens, and for identification of proteins whose rapid degradation is significant to cancer progression and metastasis. These lists can also be used for identification of new proteins of yet unknown function that are not detected by standard proteomics approaches. This review focuses on the presentation, identification and analysis of MHC peptides significant for cancer immunotherapy. It is also concerned with the aspects of human proteomics observed through large-scale analyses of MHC peptides.

Antigens, Neoplasm↗
PubMed2006

PRIDE: a public repository of protein and peptide identifications for the proteomics community.

PRIDE, the 'PRoteomics IDEntifications database' (http://www.ebi.ac.uk/pride) is a database of protein and peptide identifications that have been described in the scientific literature. These identifications will typically be from specific species, tissues and sub-cellular locations, perhaps under specific disease conditions. Any post-translational modifications that have been identified on individual peptides can be described. These identifications may be annotated with supporting mass spectra. At the time of writing, PRIDE includes the full set of identifications as submitted by individual laboratories participating in the HUPO Plasma Proteome Project and a profile of the human platelet proteome submitted by the University of Ghent in Belgium. By late 2005 PRIDE is expected to contain the identifications and spectra generated by the HUPO Brain Proteome Project. Proteomics laboratories are encouraged to submit their identifications and spectra to PRIDE to support their manuscript submissions to proteomics journals. Data can be submitted in PRIDE XML format if identifications are included or mzData format if the submitter is depositing mass spectra without identifications. PRIDE is a web application, so submission, searching and data retrieval can all be performed using an internet browser. PRIDE can be searched by experiment accession number, protein accession number, literature reference and sample parameters including species, tissue, sub-cellular location and disease state. Data can be retrieved as machine-readable PRIDE or mzData XML (the latter for mass spectra without identifications), or as human-readable HTML.

Databases, Protein↗
PubMed2026

Proteomic analysis identifies pathways related to immune dysregulation in patients with hematologic malignancies after COVID-19 infection.

Patients with hematologic malignancies (HMs) are particularly vulnerable to coronavirus disease 2019 (COVID-19) because of underlying immune dysfunction and treatment-related immunosuppression. However, proteomic features associated with different clinical trajectories in this population remain insufficiently characterized. We performed serum proteomic analysis in 40 HM patients with COVID-19 and 15 healthy controls. Compared with controls, HM patients showed impaired immune-related responses during the acute phase of COVID-19. Acute-phase proteomic patterns differed across outcome groups; however, because outcome groups were closely intertwined with initial COVID-19 severity, ICU admission, and systemic illness, and because multivariable adjustment was not performed due to the limited sample size, these patterns should be interpreted as severity- and outcome-associated profiles rather than independent trajectory-specific markers. Fatal cases showed evidence of dysregulated immune activation, whereas patients later classified as having long COVID exhibited broader suppression of immune-related pathways. In addition to immune alterations, pathways related to platelet activation and cardiac-related dysfunction were associated with adverse clinical trajectories. Enzyme-linked immunosorbent assay validation supported the association of selected proteins with outcome groups during acute infection. These findings provide a proteomic overview of COVID-19 in HM patients and offer a basis for future mechanistic studies and larger external validation cohorts.IMPORTANCEPatients with hematologic malignancies are highly vulnerable to severe coronavirus disease 2019 (COVID-19), acute death, and long COVID due to preexisting immune dysfunction. However, the proteomic signatures linked to adverse clinical trajectories remain poorly understood. Our serum proteomic study identifies distinct acute-phase immune profiles associated with different outcomes: broad immune suppression characterizes long COVID, while dysregulated immune activation is associated with fatal cases. Platelet activation and cardiac-related pathways are also linked to poor outcomes. These findings provide key molecular insights for this high-risk population, supporting future biomarker development, risk stratification, and targeted clinical management.CLINICAL TRIALSThis study is registered with ClinicalTrials.gov as NCT05683353.

Humans↗