Clinical proteomics最新文献

{"title":"Clinic-first sepsis recognition in the ICU: a proteomics-guided, parsimonious model with independent validation.","authors":"A Khaleghi Ardabili, S Rice, A Samuelsen, Ruth-Ann Brown, Anthony S Bonavia","doi":"10.1186/s12014-026-09597-1","DOIUrl":"10.1186/s12014-026-09597-1","url":null,"abstract":"<p><strong>Background: </strong>Sepsis recognition in the ICU remains variable and relies on consensus clinical criteria rather than biomarker-defined rules. Routine laboratory and physiologic data often overlap with noninfectious critical illness, obscuring early identification. We evaluated whether discovery proteomics could prioritize a concise set of routinely obtainable clinical variables, yielding a practical, clinic-first model that distinguishes sepsis from other critical illness.</p><p><strong>Methods: </strong>In a prospective, single-center pilot at an academic medical center, we enrolled adults within 48 h of critical illness onset (sepsis and non-sepsis comparators). Plasma proteomics by LC-MS/MS with diaPASEF identified proteins differentiating groups and guided selection of proteome-enriched routine variables for modeling. A Random Forest classifier was trained in a Discovery cohort (n = 55) and evaluated in an independent Validation cohort (n = 59), with prespecified attention to discrimination, parsimony, and feasibility for electronic health record (EHR) deployment.</p><p><strong>Results: </strong>Twelve plasma proteins differed between groups at FDR < 0.10, supporting biological separation. A parsimonious model using routine predictors ± CCL3 achieved AUC 0.73 in Discovery and AUC 0.76 in the independent Validation cohort. Recursive feature elimination demonstrated a parsimony plateau at ~ 9 variables; beyond this threshold, further reduction degraded accuracy. Notably, blood urea nitrogen, CCL3 (measured by multiplex immunoassay), and creatinine were the final features retained before performance declined, aligning with renal stress and inflammatory signaling. Figures present ROC curves and the parsimony profile, highlighting a minimal variable set compatible with typical ICU workflows and decision-support systems.</p><p><strong>Conclusions: </strong>A proteomics-informed, clinic-first strategy produced a parsimonious set of routine variables that discriminated sepsis from other ICU critical illness with clinically meaningful accuracy and an immediately actionable footprint. Because most predictors are routinely captured in the EHR, the model is EHR-compatible; CCL3 is readily measurable on standard immunoassay platforms if adopted locally. These findings justify multicenter studies to confirm generalizability and calibration, evaluate real-time integration into ICU workflows, and test whether an early recognition adjunct improves timeliness of sepsis care and patient outcomes.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13101166/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147456119","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of the relationship between inflammation and typical chest pain in ST-elevation myocardial infarction.","authors":"Sophia Wolfermann, Timo Schmitz, Philip Raake, Jakob Linseisen, Christa Meisinger","doi":"10.1186/s12014-026-09596-2","DOIUrl":"10.1186/s12014-026-09596-2","url":null,"abstract":"<p><strong>Background: </strong>Previous investigations have shown that the absence of typical breast symptoms is associated with unfavorable outcomes after an acute myocardial infarction (AMI). Delayed diagnosis and therapy could not explain these results, so other causes seem to be involved. Therefore, in the present analysis the association between inflammatory plasma proteins and typical chest pain symptoms in hospitalized patients with acute ST-elevation myocardial infarction (STEMI) was investigated.</p><p><strong>Methods: </strong>Data from 395 STEMI patients registered by the population-based Myocardial Infarction Registry Augsburg between 2009 and 2013 were used for analysis. The OLINK inflammatory panel including a total of 92 cytokines was measured in arterial blood samples, which were obtained immediately after hospital admission within the scope of cardiac catheterization. The associations between the inflammation markers and typical chest pain were examined by multiple logistic regression analyses.</p><p><strong>Results: </strong>Altogether, 10.9% of the STEMI patients did not present with typical chest pain. The inflammatory markers IL8, IL6, FGF-21, CD40, CST5, ADA, OPG, PD-L1, TNFRSF9 and STAMBP were significantly inversely associated with typical chest pain after FDR-adjustment. The strongest associations were found for FGF-21, CST5 and CD40.</p><p><strong>Conclusions: </strong>These results suggest that a dysregulated inflammatory status is associated with a lack of typical chest pain in AMI patients. Beyond acute-phase inflammatory interleukins elevated within the early phase of an AMI, such as IL-6, hepatokines and transmembrane proteins seem to be associated with AMI symptoms. Further research into the causal mechanisms of these associations is necessary.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13063605/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147431220","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Distinct proteomic profiles of clinical isolates show diversity of Pseudomonas aeruginosa colistin-resistance.","authors":"Telma de Sousa, Thierry Sayd, Didier Viala, Christophe Chambon, Manuela Caniça, Miguel J N Ramos, Patrícia Poeta, Michel Hébraud, Gilberto Igrejas","doi":"10.1186/s12014-026-09592-6","DOIUrl":"10.1186/s12014-026-09592-6","url":null,"abstract":"<p><strong>Background: </strong>Pseudomonas aeruginosa is a multidrug-resistant pathogenic bacterium that poses a substantial threat to global public health because of its resistance to antibiotics, and especially to last-resort colistin. The aim of this study is to perform a comparative analysis between the antibiotic-sensitive isolate A and the resistant isolate C (8 µg/mL for isolate A and 128 µg/mL for isolate C), with the intent of elucidating the discrete molecular mechanisms underpinning resistance. This investigation seeks to distinguish between pathways inherently expressed in the absence of antibiotic exposure (acquired resistance) and those activated in response to antibiotic challenge (induced resistance), thereby providing deeper insights into the multifaceted nature of antimicrobial resistance in P. aeruginosa.</p><p><strong>Results: </strong>Proteomic analysis, performed under basal conditions and after exposure to increasing doses of colistin, revealed that, although both isolates have intrinsic resistance to several antimicrobials, the mechanisms underlying colistin resistance diverge significantly. While isolate A showed a stable proteomic response, characterized by the overexpression of proteins related to membrane remodeling and efflux systems, isolate C demonstrated a more dynamic response, evidenced by metabolic adaptations and oxidative stress mitigation mechanisms. These differences suggest that each isolate employs specific strategies to cope with antimicrobial pressure, which has direct implications for the choice of alternative therapies and the development of optimized dosing regimens.</p><p><strong>Conclusions: </strong>The findings have direct implications for the choice of alternative therapies and the development of optimized dosing regimen. In summary, the results reinforce the complexity of resistance mechanisms in P. aeruginosa and highlight the importance of personalized therapeutic approaches for the management of infections caused by multidrug-resistant isolates.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13085265/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147431214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proximity extension assay-based serum proteomic profiling identifies shared protein signatures in hypermobile Ehlers-Danlos syndrome and hypermobility spectrum disorders.","authors":"Valeria Cinquina, Giulia Carini, Nicola Chiarelli, Marika Vezzoli, Valeria Bertini, Marina Venturini, Woodrow Gandy, Marina Colombi, Marco Ritelli","doi":"10.1186/s12014-026-09588-2","DOIUrl":"10.1186/s12014-026-09588-2","url":null,"abstract":"<p><strong>Background: </strong>Hypermobile Ehlers-Danlos syndrome (hEDS) and hypermobility spectrum disorders (HSD) are prevalent conditions characterized by symptomatic joint hypermobility and a substantial public health burden, for which no causal treatment is currently available. In the absence of a defined molecular basis or validated diagnostic biomarkers, diagnosis of hEDS relies solely on the 2017 clinical criteria, with individuals who do not meet these criteria classified as HSD. Although currently categorized as distinct entities, the biological relationship between hEDS and HSD remains a subject of active debate within the scientific community.</p><p><strong>Methods: </strong>We performed targeted serum proteomic profiling using the proximity extension assay technology, quantifying 458 proteins in large cohorts of hEDS (n = 88) and HSD (n = 88) patients, alongside healthy controls (n = 176).</p><p><strong>Results: </strong>Compared to controls, 54 proteins were differentially expressed in hEDS patients and 49 in HSD patients. No statistically significant differences were observed between hEDS and HSD groups. When the combined patient cohort was analyzed, 69 proteins showed differential expression relative to controls. The proteins were distributed across the predefined PEA panels, which include proteins involved in inflammatory, cardiometabolic, neurological, organ damage, and developmental processes.</p><p><strong>Conclusions: </strong>This targeted serum proteomic analysis identified overlapping protein expression changes in hEDS and HSD relative to controls, while revealing no detectable differences between the two conditions. These findings suggest the presence of shared molecular features across the hEDS/HSD spectrum and identify a set of candidate circulating proteins that warrant further investigation and independent validation in larger, well-characterized cohorts.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13081554/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147372244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IL3RA identified as novel biomarker and therapeutic target for ER⁺ breast cancer through plasma proteome-wide mendelian randomization and TCGA database analysis.","authors":"Heting Mei, Zehan Zhang, Nan Jiang, Wenping Lu, Lei Chang, Qingya Song, Feng Li","doi":"10.1186/s12014-026-09594-4","DOIUrl":"10.1186/s12014-026-09594-4","url":null,"abstract":"<p><strong>Background: </strong>Estrogen receptor-positive (ER⁺) breast cancer, a leading cause of female cancer mortality, faces therapeutic challenges due to endocrine resistance. Plasma proteins, bridging genetic variation and disease phenotypes, offer potential biomarkers and therapeutic targets, yet their causal roles in the pathogenesis of ER⁺ breast cancer remain underexplored.</p><p><strong>Methods: </strong>Using two-sample Mendelian randomization (TSMR) and Bayesian colocalization, we analyzed associations between plasma protein quantitative trait loci from deCODE/Fenland cohorts and ER⁺ breast cancer. DSigDB predicted drugs targeting identified protein, while TCGA assessed the prognostic value.</p><p><strong>Results: </strong>TSMR identified 38 causal plasma proteins (deCODE), with Bayesian analysis prioritizing 12 candidates. IL3RA emerged as stable and novel protective factor, validated in Fenland data. TCGA revealed reduced IL3RA expression in ER⁺ tumors, with higher levels correlating with improved survival and favorable clinicopathological features, particularly in ER⁺/PR⁺ cases. Tumor microenvironment analysis revealed that IL3RA expression levels significantly correlated with immune landscape alterations in ER⁺ breast cancer. Immune infiltration analysis demonstrated significant associations between IL3RA expression levels and multiple immune cell populations in ER⁺ breast cancer, particularly CD8⁺ T cells, neutrophils, M0 macrophages, and M2 macrophages. DSigDB identified panobinostat, arbutin, clindamycin, cimetidine, and chlorzoxazone as IL3RA-targeting drugs.</p><p><strong>Conclusions: </strong>Our study identified IL3RA as novel biomarker and therapeutic target for ER⁺ breast cancer. Further validation and mechanistic studies are warranted to advance precision oncology strategies for ER⁺ breast cancer management.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13072662/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147364304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Inflammatory protein expression patterns in Hashimoto's thyroiditis: a cross-sectional observational study.","authors":"Vanna Žnidar, Dean Kaličanin, Zvonimir Boban, Ana Barić Žižić, Marko Vuletić, Sanda Sladić, Ivana Novak, Vesela Torlak Lovrić, Maja Cvek, Ante Punda, Vesna Boraska Perica","doi":"10.1186/s12014-026-09593-5","DOIUrl":"10.1186/s12014-026-09593-5","url":null,"abstract":"","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-03-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13059616/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147343917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Comparative proteomic analysis of gingival crevicular fluid and periodontal tissue: revealing clinical potential.","authors":"Jeong-Hun Mok, Ji-Youn Hong, MinJoong Joo, Won Seok Bang, Do-Young Ahn, Jeong-Ho Yun, Jong-Moon Park","doi":"10.1186/s12014-026-09587-3","DOIUrl":"10.1186/s12014-026-09587-3","url":null,"abstract":"<p><strong>Background: </strong>Periodontitis is a chronic inflammatory disease characterized by tissue destruction and immune dysregulation. While gingival crevicular fluid (GCF) serves as a non-invasive biomarker source, its molecular distinctions from periodontal tissue remain underexplored. This study conducted a comparative proteomic analysis of GCF and tissue samples from patients with Stage III-IV periodontitis, integrating differential expression, weighted gene co-expression network analysis, and protein-protein interaction networks to delineate compartment-specific molecular profiles and clarify their respective biological roles in periodontal pathophysiology.</p><p><strong>Methods: </strong>Proteomic data were acquired from GCF and periodontal tissue using label-free LC-MS analysis. Differentially expressed proteins (DEPs) were identified using independent samples t-test (p < 0.05, |fold-change| > 2). WGCNA was performed to construct co-expression modules and identify functionally related protein clusters, followed by GO enrichment and protein-protein interaction (PPI) analyses using STRING and Cytoscape. Hub proteins were determined through CytoHubba according to centrality measures. Comparative analyses were conducted between tissue and GCF to define inflammation- and repair-related modules and to assess potential molecular interconnections between the two sample types.</p><p><strong>Results: </strong>A total of 4,¹04 proteins were identified in periodontal tissue and 1,546 in GCF. Among these, 1,292 DEPs were detected in tissue and 280 in GCF. Periodontal tissue displayed coordinated upregulation of ribosomal proteins and collagen networks alongside mitochondrial components, indicating repair-oriented structural remodeling and metabolic activation. Conversely, GCF exhibited enrichment of neutrophil-derived immune effectors including MPO, ELANE, CTSG, S100A8, and apolipoproteins, representing innate immune activation. Network integration revealed that GCF and tissue maintained largely distinct molecular profiles with limited cross-compartment connectivity.</p><p><strong>Conclusions: </strong>This comparative proteomic analysis demonstrates that periodontal tissue and GCF represent functionally distinct but complementary biological environments in periodontitis. Periodontal tissue exhibits enhanced structural and metabolic processes, whereas GCF predominantly reflects neutrophil-mediated immune responses. These molecular distinctions provide a basis for developing clinical, compartment-specific biomarker candidates that warrant analytical validation, thereby supporting precision-medicine-relevant diagnostic strategies in periodontal research.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13037294/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147282589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Impact of preanalytical factors on plasma extracellular vesicles and human plasma proteome.","authors":"Patil Shivprasad Suresh, Qibin Zhang","doi":"10.1186/s12014-026-09590-8","DOIUrl":"10.1186/s12014-026-09590-8","url":null,"abstract":"<p><p>Using human plasma and its protein-rich extracellular vesicles (EVs) for proteomic biomarker discovery requires an in-depth understanding of the influences of pre-analytical procedures. This study systematically investigates the ramifications of high-speed centrifugation, freeze-thaw cycles, and prolonged storage on the plasma proteome and abundance of plasma EVs. Employing a Mag-Net-assisted workflow for high-throughput EV-based plasma proteomics, we find that high-speed centrifuging plasma samples at 8,000 g prior to analysis reduces both EV and protein numbers to only 30% of the original plasma, rendering numerous established EV markers undetectable. In contrast, multiple freeze-thaw cycles within a week have very minimal effect on proteome coverage, albeit with a reduced number of EVs and subtle shifts in the enrichment and depletion patterns of specific proteins. Long-term storage of plasma in freezer for years gradually and significantly diminishes proteome coverage with reduced EV counts and altered size distributions. These results caution the use of biobank samples for retrospective studies, particularly longitudinally collected blood specimens that have been preserved for years for EV-focused biomarker research, and underscore the imperative for stringent standardization of pre-analytical protocols to enhance the reliability and reproducibility of plasma EV proteomics.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13032548/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146776235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Shake and bake: a robust and cost-effective proteomic sample preparation workflow for plasma and cerebrospinal fluid.","authors":"John Rönnholm, Sophia Weiner, Johannes Fuchs, Annika Thorsell, Carina Sihlbom, Laura Dugom, Amy Easton, Henrik Zetterberg, Johan Gobom","doi":"10.1186/s12014-026-09589-1","DOIUrl":"10.1186/s12014-026-09589-1","url":null,"abstract":"","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12927225/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146200298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Plasma-targeted proteomic and lipidomic profiling of MASLD, MASH, and hepatitis C virus infection.","authors":"Suzumi M Tokuoka, Fumie Hamano, Ayako Kobayashi, Masaya Sugiyama, Hirokazu Takahashi, Masashi Mizokami, Yoshiya Oda","doi":"10.1186/s12014-026-09586-4","DOIUrl":"https://doi.org/10.1186/s12014-026-09586-4","url":null,"abstract":"<p><strong>Background: </strong>Metabolic dysfunction-associated steatotic liver disease (MASLD) and metabolic dysfunction-associated steatohepatitis (MASH) are chronic liver diseases characterized by lipid accumulation and persistent inflammation, often progressing to fibrosis or hepatocellular carcinoma (HCC). Hepatitis C virus (HCV) infection shares overlapping pathological features, including chronic inflammation and fibrogenesis. Despite their prevalence, reproducible plasma-level molecular data that capture disease-associated systemic alterations remain limited.</p><p><strong>Methods: </strong>We conducted targeted proteomic and targeted lipidomic profiling of several hundred plasma samples from Japanese patients diagnosed with MASLD, MASH, or HCV infection. Targeted proteomics quantified 184 plasma proteins using the Olink Proximity Extension Assay, and targeted lipidomics quantified approximately 500 phospholipid and triglyceride species using LC/MS-based selected reaction monitoring. Reproducibility was assessed across three independent cohorts.</p><p><strong>Results: </strong>Seven proteins (CASP-8, CCL20, CTSD, SCF, MMP-3, TRAIL, and TWEAK) consistently differed between MASLD and MASH across all cohorts, reflecting coordinated changes related to apoptosis, inflammation, and immune signaling. Similar alterations were observed in HCV (Hepatitis C virus), indicating shared immune dysregulation. Lipidomic analysis revealed reproducible remodeling characterized by decreased ether-linked phosphatidylethanolamine (PE), increased ester-linked PE, and elevated saturated sphingomyelin (SM) in MASH. Correlation analyses indicate coordinated relationships between selected protein and lipid alterations, including relationships between CTSD and PE and triglyceride (TG) species containing linoleic acid (18:2).</p><p><strong>Conclusions: </strong>The results of this research provide value to the field of proteomics as a large-scale, reproducible, and hypothesis-generating plasma dual-omics reference dataset. This study was not designed to establish diagnostic biomarkers, to assess clinical discriminative performance, or to imply causal mechanisms. Instead, by emphasizing reproduciblilty across independent cohorts, we provide a plasma dual-omics reference dataset that captures coordinated immune and lipid metabolic alterations associated with chronic liver disease severity. These data provide a framework and resource for future studies researching risk stratification, therapeutic monitoring, and mechanistic validation in chronic liver disease.</p>","PeriodicalId":10468,"journal":{"name":"Clinical proteomics","volume":" ","pages":""},"PeriodicalIF":3.3,"publicationDate":"2026-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146164389","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}