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PubMed2024

Serum proteomic profiling of patients with compensated advanced chronic liver disease with and without clinically significant portal hypertension.

INTRODUCTION: Portal hypertension (PH) drives the progression of liver cirrhosis to decompensation and death. Hepatic venous pressure gradient (HVPG) measurement is the standard of PH quantification, and HVPG≥10 mmHg defines clinically significant PH (CSPH). We performed proteomics-based serum profiling to search for a proteomic signature of CSPH in patients with compensated advanced chronic liver disease (cACLD). MATERIALS AND METHODS: Consecutive patients with histologically confirmed cACLD and results of HVPG measurements were prospectively included. Serum samples were pooled according to the presence/absence of CSPH and analysed by liquid chromatography-mass spectrometry. Gene set enrichment analysis was performed, followed by comprehensive literature review for proteins identified with the most striking difference between the groups. RESULTS: We included 48 patients (30 with, and 18 without CSPH). Protein CD44, involved in the inflammatory response, vascular endothelial growth factor C (VEGF-C) and lymphatic vessel endothelial hyaluronan receptor-1 (LYVE-1), both involved in lymphangiogenesis were found solely in the CSPH group. Although identified in both groups, proteins involved in neutrophil extracellular traps (NET) formation, as well as tenascin C, autotaxin and nephronectin which mediate vascular contractility and lymphangiogenesis were more abundant in CSPH. DISCUSSION AND CONCLUSION: We propose that altered inflammatory response, including NET formation, vascular contractility and formation of new lymph vessels are key steps in PH development. Proteins such as CD44, VEGF-C, LYVE-1, tenascin C, Plasminogen activator inhibitor 1, Nephronectin, Bactericidal permeability-increasing protein, Autotaxin, Myeloperoxidase and a disintegrin and metalloproteinase with thrombospondin motifs-like protein 4 might be considered for further validation as potential therapeutic targets and candidate biomarkers of CSPH in cACLD.

Humans↗

PubMed2026

A machine learning-based predictive model for radiosensitivity in nasopharyngeal carcinoma utilizing serum proteomics.

BACKGROUND: Nasopharyngeal carcinoma (NPC) remains highly sensitive to radiotherapy; however, radioresistance in a subset of patients leads to local recurrence and distant metastasis. Serum proteomics provides a minimally invasive approach to capturing dynamic physiological changes, and machine learning enables efficient construction of predictive models. This study aimed to develop and validate a serum proteomics–based machine-learning model for predicting radiotherapy sensitivity in nasopharyngeal carcinoma (NPC). METHODS: Pretreatment serum samples from newly diagnosed NPC patients were analyzed using SELDI-TOF-MS. Differentially expressed proteins between radiosensitive and radioresistant groups were identified using limma. GO and KEGG analyses were performed to explore functional enrichment. Twelve machine-learning algorithms were used to construct predictive models, and the top-performing models were optimized through feature selection. A Random Forest model with seven features was identified as the optimal model. External validation was performed using an independent cohort with ELISA-quantified protein levels. Model performance was assessed using Receiver operating characteristic curve (ROC), calibration analysis, decision curve analysis (DCA), and 10-fold cross-validation. SHapley Additive exPlanations (SHAP) analysis was applied for model interpretability, and the final model was deployed via a ShinyAPP. RESULTS: A total of 96 differentially expressed proteins were identified, which involved multiple function and signaling pathways. The Random Forest model demonstrated the best predictive performance, achieving an area under the curve (AUC) of 0.963 in the training set and 0.975 in the validation set. Cross-validation yielded an average AUC of 0.965. DCA indicated high clinical utility across a broad threshold range, and calibration curves showed good model agreement. Seven proteins (PLXND1, GSR, PGD, PTPRC, OR2T29, ACTG2, CHAD) were selected as final features. SHAP analysis provided global and individual-level interpretability. A web-based tool was developed to facilitate clinical application. CONCLUSION: This study establishes a robust serum proteomics–based machine-learning model capable of accurately predicting radiotherapy sensitivity in NPC. The model offers clinical interpretability and practical implementation, supporting personalized radiotherapy decision-making.

Humans↗

PubMed2026

Serum Proteomic Profiling Implicates a Dysregulated Neurohormonal-Inflammatory Axis in Post-Fontan Sinus Tachycardia.

BACKGROUND: Postoperative sinus tachycardia is a poorly understood complication following the Fontan procedure. The molecular signaling cascades triggering acute tachycardia remain uncharacterized, limiting therapeutic innovation. Here, we present a retrospective study leveraging serum proteomics and machine learning to identify the molecular drivers of postoperative Fontan sinus tachycardia. METHODS: We integrated a clinically relevant ovine Fontan model with continuous telemetric heart rate monitoring and human patient data. Serum proteomics coupled with least absolute shrinkage and selection operator and Boruta machine learning algorithms were used to identify protein panels predictive of postoperative sinus tachycardia. Cross-species validation was performed by comparing proteomic signatures from sheep and pediatric patients undergoing Glenn or Fontan surgery. RESULTS: Ovine Fontan animals demonstrated significant heart rate elevation beginning on postoperative day 1, peaking at postoperative day 3 (159.4±11.7 bpm versus preoperative, 105.3±10.5 bpm; P=0.0002), before trending toward baseline by postoperative day 10. This pattern was mirrored in human patients with a more modest magnitude. Surgical controls did not exhibit tachycardia. The principal component most correlated with heart rate (principal component 1: r=0.78, P=2.2×10-4) was enriched for inflammatory and neural pathways. The Boruta algorithm identified an 11-protein panel with strong predictive power (area under the receiver operating characteristic curve, 0.963). Cross-species comparison demonstrated that angiotensinogen, angiotensin-converting enzyme, and pentraxin 3 were similarly dysregulated in both species postoperatively. CONCLUSIONS: This study provides molecular evidence implicating a dysregulated neurohormonal-inflammatory axis in acute postoperative Fontan sinus tachycardia and establishes a foundation for developing targeted diagnostics and therapeutics for this complication.

Animals↗

PubMed2026

Identification of circulating parasite and host biomarkers in the serum proteome of Trypanosoma vivax-infected sheep under immunosuppression.

Bovine trypanosomiasis, caused by Trypanosoma vivax, presents a major threat to livestock health, primarily due to the lack of efficient field diagnostic tools. This study aimed to identify potential parasite and host-derived biomarkers through a longitudinal proteomic analysis of serum from sheep experimentally infected with a T. vivax isolate. Utilizing LC-MS/MS and bioinformatics, 154 proteins were identified, comprising 150 host (Ovis aries) and four pathogen proteins. Principal Component Analysis (PCA) demonstrated a clear separation of samples according to infection stages: Control, Infection (15 parasites/field), and Peak Infection (30-60 parasites/field) Among the parasite proteins, TvY486_0014340, TvY486_0040500, and TvY486_0042480 were identified as candidate antigens for future evaluation. In silico analysis revealed these proteins contain multiple B-cell epitopes with no cross-reactivity to related Trypanosoma species, supporting their potential for immunodiagnostic development. Additionally, three host proteins-folate receptor 3 (FOLR3) and complement components C1QA and C1QC-were significantly modulated across all infection phases. The upregulation of FOLR3 likely reflects a compensatory response to parasite-induced anemia, while the downregulation of C1Q components suggests immune evasion strategies. These findings highlight specific parasite antigens and host regulatory patterns that may serve as candidate biomarkers for the diagnosis and monitoring of T. vivax infection, facilitating the development of improved point-of-care assays.

Animals↗

PubMed2026

Potential evaluation of SULT1A3 as an early diagnostic marker for nasopharyngeal carcinoma: a study based on serum proteomics screening and ELISA validation.

BACKGROUND: Nasopharyngeal carcinoma (NPC) represents a highly prevalent and aggressive malignancy endemic to Southeast Asia. Early and accurate diagnosis is critical to improving survival outcomes; however, the absence of robust, stage-specific biomarkers remains a key obstacle to clinical implementation of early screening strategies. METHODS: We performed untargeted serum proteomic profiling using mass spectrometry in 15 treatment-naïve early-stage NPC patients and 15 VCA-IgA-positive healthy controls. Bioinformatics analyses were conducted to identify differentially expressed proteins (DEPs). Machine learning (random forest combined with recursive feature elimination) was employed to prioritize candidate biomarkers, which were subsequently verified using enzyme-linked immunosorbent assay (ELISA) in independent sample cohorts. RESULTS: In total, 1,428 serum proteins were identified, among which 1,410 were reliably quantified. We observed 31 upregulated and 189 downregulated proteins in NPC patients relative to controls. Spearman correlation analysis revealed significant associations: LTA4H (leukotriene A4 hydrolase) levels correlated with serum cell infiltration (r = 0.383, p = 0.032) and CD8 + T-cell abundance (r = 0.408, p = 0.021); both SULT1A3 (sulfotransferase family 1 A member 3) and FGL1 (fibrinogen-like protein 1) levels were positively associated with M1 macrophage infiltration (r = 0.510, p = 0.003 and r = 0.430, p = 0.015, respectively). In a preliminary validation cohort (n = 80), ELISA yielded AUC values of 0.631 (95% CI: 0.515-0.736, p = 0.04) for LTA4H, 0.787 (95% CI: 0.681-0.871, p < 0.001) for SULT1A3, and 0.688 (95% CI: 0.575-0.787, p = 0.002) for FGL1. In large-scale independent validation, SULT1A3 achieved an AUC of 0.826 (95% CI: 0.766-0.876; sensitivity = 78.89%, specificity = 75.47%) in cohort 1 (n = 196) and 0.796 (95% CI: 0.723-0.857; sensitivity = 76.67%, specificity = 76.67%) in cohort 2 (n = 150). CONCLUSIONS: Through an integrated workflow combining proteomic screening, machine learning prioritization, and multi-stage ELISA validation, we identified SULT1A3 as a candidate serum-based biomarker for early detection of NPC. Preliminary findings suggest that SULT1A3 may have potential utility in clinical screening, though further validation in independent, multi‑center cohorts is required.

Humans↗

PubMed2026

Urine and Serum Proteome and Lipidome Analysis of Naturally Aging Feline Species.

Aging in companion animals such as cats closely relates to human aging in environmental exposures and disease manifestation, providing a valuable model for identifying biomarkers of age-associated decline. This study provides a combined proteomic and lipidomic analysis of serum and urine from naturally aging domestic cats aged 3.8-16 years, grouped as adult, old, and senior, to identify age-related molecular changes across biofluids. Label-free quantitative proteomics identified 901 urinary and 238 serum proteins, with 75 urinary proteins significantly altered with age that are linked to kidney disease, hypertension, neurodegeneration, and metabolic disorders. In contrast, only six serum proteins differed significantly between adult and old/senior cats, including decreased Apolipoprotein A-I (APOA1) in seniors, a protein linked with cognitive function in aging. Untargeted lipidomics revealed increases in specific serum triacylglycerols, phosphatidylcholines (PCs), and sphingomyelins, while urinary lipid profiles showed limited age-related changes, with some PCs decreasing, and diacylglycerols increasing with age. These results demonstrate distinct systemic and renal molecular remodeling during feline aging and highlight the utility of integrated omics analyses of biological fluids for identifying molecular alterations relevant to both feline and human aging.

Animals↗

PubMed2026

Widespread Molecular Imprints in the Serum Proteome of COVID-19 Convalescents Uncovering Immune System Sequelae.

Post-COVID-19 sequelae have become an emerging global health issue, but the mechanisms for the sustained susceptibility of convalescents to the sequelae remain poorly understood. Here we report the use of a restricted open-search approach to explore the molecular imprints of SARS-CoV-2 infection left on the proteome of 412 COVID-19 patients and convalescences. A total of 827 non-standard amino acid variations, chemically modified residues as well as post-translational modifications, termed non-coded amino acids (ncAAs), are found spreading over 29,814 sites in patient's serum proteins. Markedly, widespread ncAAs are induced and sustainedly imprinted on the serum proteome predominately perturbing the immunoglobulin-mediated immune response, complement activation and coagulation regulation even 12 months after recovery. Sustained amino acid variations and chemical modifications are found in the complementary‑determining regions (CDRs) of the variable region of immunoglobulin contributing to the interactions between the emerging antibody and antigens; durable chemical amino acid modifications found in the hyper ncAA-modified regions of the constant region of immunoglobulin important for the interaction with the complement and regulatory receptors. In the complement system, inducible ncAAs are memorized in the components essential for the complement activation, amplification cascades and membrane attack processes. Thus, the workflow described in this study can be used to identify the molecular imprints of viral infection at the proteomic scale, particularly the specific antibodies and the immune targets left in COVID-19 patients and convalescents.

Humans↗

PubMed2026

Serum Proteomic Signatures of Rheumatoid Arthritis Risk and Response: Analysis of a Rheumatoid Arthritis Interception Trial.

OBJECTIVE: Our study objective was to identify serum protein signatures associated with progression to rheumatoid arthritis (RA) and response to abatacept in at-risk individuals. METHODS: A total of 440 serum samples from 118 APIPPRA (Arthritis Prevention In the Preclinical Phase of RA with Abatacept) study participants were selected from baseline to RA onset for 46 progressors of RA or to study end for 72 participants who did not develop RA. Samples were analyzed using the SomaScan 7k assay platform. Differential expression analysis was assessed by progression to RA (three pre-RA time intervals to RA, progressors of RA vs nonprogressors, baseline to RA), and by treatment allocation (abatacept vs placebo). Risk and response signatures were identified in the full 7k panel and two prespecified subpanels defined as Inflammatory Mediators and Adaptive Immune Cell panel. RESULTS: We observed significant changes in 80 proteins (68 down-regulated and 12 up-regulated) occurring between RA onset and 6 to 24 months before developing disease. Progression to RA was associated with increased levels of acute-phase reactants SAA1 and SAA2 and reductions in CTLA4, when compared to nonprogressors at the end of treatment. Two up-regulated proteins (CTLA4 and CD86) and seven down-regulated proteins (CXCL13, FCRL4, FCER2, CCL21, LTA|LTB, FDCSP, and IL22RA2) were observed in participants receiving abatacept compared to placebo regardless of RA outcome. CONCLUSION: Protein signatures dominated by acute-phase proteins define progression to RA, whereas changes associated with abatacept therapy highlight potential mechanisms of treatment response. Such signatures provide a better understanding of the immune landscape of the at-risk phase, opening up the possibility of new treatment modalities for RA prevention.

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PubMed2025

Serum proteomics reveals high-affinity and convergent antibodies by tracking SARS-CoV-2 hybrid immunity to emerging variants of concern.

The rapid spread of SARS-CoV-2 and its continuing impact on human health has prompted the need for effective and rapid development of monoclonal antibody therapeutics. In this study, we investigate polyclonal antibodies in serum and B cells from the whole blood of three donors with SARS-CoV-2 immunity to find high-affinity anti-SARS-CoV-2 antibodies to escape variants. Serum IgG antibodies were selected by their affinity to the receptor-binding domain (RBD) and non-RBD sites on the spike protein of Omicron subvariant B.1.1.529 from each donor. Antibodies were analyzed by bottom-up mass spectrometry, and matched to single- and bulk-cell sequenced repertoires for each donor. The antibodies observed in serum were recombinantly expressed, and characterized to assess domain binding, cross-reactivity between different variants, and capacity to inhibit RBD binding to host protein. Donors infected with early Omicron subvariants had serum antibodies with subnanomolar affinity to RBD that also showed binding activity to a newer Omicron subvariant BQ.1.1. The donors also showed a convergent immune response. Serum antibodies and other single- and bulk-cell sequences were similar to publicly reported anti-SARS-CoV-2 antibodies, and the characterized serum antibodies had the same variant-binding and neutralization profiles as their reported public sequences. The serum antibodies analyzed were a subset of anti-SARS-CoV-2 antibodies in the B cell repertoire, which demonstrates significant dynamics between the B cells and circulating antibodies in peripheral blood.

Humans↗

PubMed2024

Proteomic serum profiles before and after lipoprotein apheresis in patients with peripheral artery disease with ulceration.

INTRODUCTION: The efficacy of lipoprotein apheresis (LA) in peripheral arterial disease (PAD) has been primarily attributed to its anti-atherosclerotic effects through the adsorption of lipoproteins. However, the other potential effects of LA remain unknown. We evaluated changes in serum profiles before and after LA using a comprehensive analysis to explore the underlying mechanism. METHODS: Ten patients with leg ulcers were included from the LETS-PAD study, in which patients with lipoprotein-controlled PAD underwent LA. Serum samples collected at baseline and 1 month after LA were analyzed for proteomic changes. RESULTS: Six patients exhibited ulcer epithelialization and skin perfusion pressure improvement. Proteomic analysis identified 2033 proteins. Fifty-five proteins showed significant differences. B-cell lymphoma protein-2 associated X (BAX) and C-X-C motif chemokine 10 (CXCL10) were downregulated. CONCLUSION: Serum BAX and CXCL10 levels significantly decreased after LA, which may be involved in the ulcer epithelialization mechanism of LA, which potentially acts through angiogenesis promotion.

Humans↗

PubMed2026

Serum Proteomic Profiling Reveals Renin-Associated Immune and Cytoskeletal Dysregulation in Post-COVID-19 Condition Patients with Secondary Adrenal Insufficiency.

Post-COVID-19 condition (PCC) with secondary adrenal insufficiency (SAI) involves multiorgan dysfunction, potentially linked to renin-angiotensin-aldosterone system dysregulation. The molecular basis of renin-associated pathology remains unclear. Here, PCC+SAI patients were stratified by upright renin into low- (<38.8 pg/mL) and high-renin (≥38.8 pg/mL) groups. Clinical, endocrine, and proteomic analyses were performed. We found that high-renin patients showed increased BMI, lipids, renin, and aldosterone, but reduced aldosterone-to-renin ratio. Proteomic annalysis identified 20 differentially expressed proteins (DEPs), including 17 upregulated and 3 downregulated proteins in Ren-H patients. Functional annotation revealed that 15 DEPs were immune-related (e.g., APOC4, APOE, C4BPA, CFAH, CFHR3, PF4V, PLF4), while FLNA and COF1 represented cytoskeletal proteins. These DEPs were primarily involved in immune response, complement and coagulation cascades, and MAPK signaling pathways. Correlation analyses indicated that upright renin was positively correlated with complement-related proteins and platelet-derived immune factors, while cytoskeletal proteins (FLNA, COF1) showed positive associations with serum Na+ levels. Additionally, white blood cell and platelet counts were positively correlated with the majority of DEPs. In conclusion, exploratory proteomic analyses suggest that elevated upright renin in PCC+SAI may be associated with immune dysregulation, complement activation, and cytoskeletal remodeling, offering novel insights into the endocrine-immune interactions driving postviral sequelae.

Humans↗

PubMed2025

Proteomics uncovers ICAM2 (CD102) as a novel serum biomarker of proliferative lupus nephritis.

OBJECTIVES: This study aimed to identify novel, non-invasive biomarkers for lupus nephritis (LN) through serum proteomics. METHODS: Serum proteins were detected in patients with LN and healthy control (HC) groups through liquid chromatography-tandem mass spectrometry. The key networks associated with LN were screened out using Cytoscape software, followed by pathway enrichment analysis. The best candidate biomarkers were selected by machine learning models, further validated in a larger independent cohort. Finally, the expression of these candidate markers was verified in kidney tissue samples, and the mechanism was explored by knocking down the expression of intercellular adhesion molecule 2 (ICAM2) through in vitro cell transfection with siRNA. RESULTS: Following the serum proteomic screening of LN, a key network of 20 proteins was identified. Machine learning models were used to select ICAM2 (CD102), metalloproteinase inhibitor 1 (TIMP1) and thrombospondin 1 (THSB1) for validation in independent cohorts. ICAM2 exhibited the highest area under the curve (AUC) value in distinguishing LN from HC (AUC=0.92) and was significantly correlated with activity index, proteinuria, albumin and anti-dsDNA antibody levels. Particularly, ICAM2 was significantly elevated in proliferative LN and was associated with specific pathological attributes, outperforming conventional parameters in distinguishing proliferative LN from non-proliferative LN. ICAM2 expression was also elevated in renal tissue samples from patients with proliferative LN. In vitro, knockdown of ICAM2 expression can inhibit the activation of the PI3K/Akt pathway and alleviate the injury of glomerular endothelial cells. CONCLUSION: ICAM2 (CD102) may serve as a potential serum biomarker for proliferative LN that reflects renal pathology activity, potentially contributing to the progression of LN through the PI3K/Akt pathway.

Humans↗

PubMed2026

Identification of Immune Response-Related Proteomic Biomarkers in Moyamoya Disease Using Serum Olink Proteomics.

Moyamoya disease, a rare chronic cerebrovascular disorder, requires invasive digital subtraction angiography (DSA) for diagnosis. This study employed high-throughput proteomics to identify plasma biomarkers for Moyamoya disease diagnosis. We conducted immunopanel analysis using the Olink platform to evaluate 92 immune-related proteins in plasma samples from 88 Moyamoya disease patients and 88 healthy controls. Key proteins were identified through differential expression analysis, GO, and KEGG enrichment analysis. A diagnostic model was constructed using LASSO regression, Boruta algorithm, and machine learning models including random forest and XGBoost. Validation of these proteins was performed using GEO external data sets, followed by prediction of potential therapeutic drugs and molecular docking validation through pharmacogenomic databases. A total of 44 differentially expressed proteins were identified through the Olink immunopanel, with 12 downregulated and 32 upregulated. GO and KEGG analyses revealed significant enrichment of these proteins in innate immune responses and signaling pathways such as NF-kB and MAPK. Through LASSO, random forest, and protein under-area analysis, four potential biomarkers for Moyamoya disease (MGMT, SIT1, PRDX1, TRAF2) were identified. A diagnostic model using these proteins showed the highest AUC value with the XGBoost model. Additionally, TRAF2 and PRDX1 exhibited significant expression differences in Moyamoya disease patients within the GEO data set. Our study revealed the immune landscape of Moyamoya disease, identified four biomarkers, and established a variety of diagnostic models.

Humans↗

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↗

PubMed2026

How elephant host proteins fight-or fail-against EEHV: Insights from a multi-contrast proteomic enrichment study.

Elephant endotheliotropic herpesvirus hemorrhagic disease (EEHV-HD) is a rapidly fatal syndrome of juvenile Asian elephants, but the host-response programs distinguishing progression from survival and the underlying pathophysiology remain poorly defined. The serum proteome of 62 Asian elephants (Elephas maximus) was profiled using a multi-contrast design stratified by age, clinical status, and infection history; protein abundance was analyzed by empirical Bayes linear modeling and Gene Ontology enrichment with semantic similarity reduction. Clinically affected elephants showed enrichment of inflammatory and stress-associated processes-including cytokine signaling and chromatin remodeling-with suppression of type I interferon signaling and homeostatic functions, whereas asymptomatic exposed elephants showed enrichment of metabolic pathways, including fatty acid and pyruvate metabolism, vesicle-mediated transport, and protein quality control. Disease-versus-exposure comparisons distinguished a progression program (inflammatory escalation with loss of proteostasis and cell adhesion) from a resilience program (preserved metabolic and cellular homeostasis); juvenile susceptibility was further associated with impaired lipid and calcium regulation and disrupted intracellular transport. Collectively, these patterns support a pathology-centered model in which fatal EEHV-HD reflects endothelial injury coupled with maladaptive inflammation and metabolic failure. Protein-level interpretation identified candidate drivers of inflammatory amplification, endothelial barrier disruption, coagulation imbalance, and resilience-including JAK1, IL1RL2, IFI44, KCNJ15, MSN, HECW2, ITPR3, MFN2, AKT1, BMPER, and DROSHA-providing a mechanistic bridge between serum proteomic changes and the vascular lesions, thrombocytopenia, DIC-like coagulopathy, edema, and hemorrhage of EEHV-HD. These findings nominate candidate proteomic signatures for future diagnostic and risk-stratification studies; longitudinal individual-level validation is required before clinical application. Because diagnostic screening identified all PCR-positive sick cases as EEHV1A and pooled group-level serum profiles were analyzed, these signatures should be interpreted as exploratory host-response programs specifically reflecting acute EEHV1A disease requiring individual-level validation.

Animals↗

PubMed2026

Inflammatory Serum Olink Proteomics in Cancer-Related Pain Treated with Opioids: A Pilot Cross-Sectional and Longitudinal Study.

Opioid analgesia shows substantial interindividual variability in cancer patients, yet the underlying serum inflammatory alterations remain poorly characterized. This study collected plasma samples from 44 cancer pain patients before and after opioid initiation, quantifying 92 immunoinflammation proteins by Olink proteomics. Cross-sectional analysis identified nine differentially expressed proteins between responders and nonresponders. A five-protein nomogram involving TGF-α, EN-RAGE, CASP-8, ST1A1, and IL-10RA demonstrated superior predictive performance for opioid efficacy (AUC 0.902) compared to traditional CRP (AUC 0.625). Longitudinal analysis of this population revealed upregulation of β-NGF, MCP-4, IL-1alpha, and IL-13, and downregulation of CD6, IL-12beta, and SCF after treatment. STRING analysis clustered these proteins into three functional groups: efficacy-related (NGF), bowel-inflammation-related (IL-12/IL-13), and CD6-related. Notably, expression of IL-12β showed a significant efficacy-constipation interaction: constipation completely reversed the efficacy-IL-12 association, and higher IL-12 levels predicted favorable response only in nonconstipated patients. These findings established a pretreatment protein signature for predicting opioid efficacy and revealed systemic immune reprogramming following opioid therapy.

Humans↗

PubMed2026

Proteomics identify disease-associated variants in patients with rare diseases undiagnosed after genome sequencing.

Despite the introduction of genome sequencing (GS) for rare disease diagnostics, a genetic cause is not identified in most patients. Here, we explored the potential of proteomics to improve the diagnostic yield in 424 patients with rare diseases from the 100,000 Genomes Project (100kGP) without a genetic diagnosis. Serum proteomic profiling was performed using the Olink Explore 1536 assay (N = 1463 proteins). For 13 patients without genetic diagnoses, detection of lower serum protein "outliers" (z-score < -2) led to confirmed genetic diagnoses by resolving variants of uncertain significance or prioritizing genes for targeted GS reanalysis. For 23 additional patients without genetic diagnoses (64% of findings), we identified candidate gene-disease links and variants through convergent evidence from lower protein outliers and variants ranked through the variant prioritization tool Exomiser. For example, we identified a candidate heterozygous missense variant [Genome Aggregation Database (gnomAD) minor allele frequency = 0.006%] in tyrosine kinase with immunoglobulin-like and epidermal growth factor homology domains 1 (TIE1) that was only present in a patient with lower TIE1 serum abundance (z-score = -5.12) and their father, both of whom were affected by the same monogenic cardiac disorder, but in no other individuals from the 100kGP. Missense (52.5%) and splice region (27.5%) variants accounted for most diagnostic or candidate variants prioritized. This proof-of-principle study demonstrated that serum proteomics can support rare disease diagnosis and identify disease-causing genes in patients undiagnosed after GS, although successful implementation will likely depend on tissue specificity of protein expression, detectability in blood, proteomic platform coverage, and sensitivity.

Humans↗

PubMed2026

Serum Olink Proteomics Reveals Novel Biomarkers for Early Diagnosis of Hepatocellular Carcinoma.

Hepatocellular carcinoma (HCC) is a highly prevalent malignant tumor in China, and early diagnosis critically affects the prognosis. Current imaging and pathological biopsy techniques have limitations, including high invasiveness and limited accessibility, while the insufficient sensitivity of serum biomarkers (such as AFP) restricts their use in early screening. In this study, using the Olink proteomics platform based on the proximity extension assay (PEA), we screened for hepatocellular carcinoma-related differentially expressed proteins (DEPs) and constructed a multiprotein diagnostic model. In the discovery cohort, we included 15 patients with newly diagnosed HCCs and 16 healthy controls. DEPs were identified using Olink, and their diagnostic performance was analyzed to identify the candidate biomarkers. In an independent validation cohort, including 116 HCC patients (50 early stage, 66 late stage) and 83 healthy controls, we further validated the expression levels and diagnostic performance of identified proteins─C1QA and GFER. The C1QA and GFER expression levels were significantly higher in the serum of patients with early and late HCC stages compared to healthy controls. By constructing a multiprotein diagnostic model, we identified C1QA, GFER, and AFP as the optimal diagnostic combination, demonstrating a combined diagnostic AUC of 0.92 and 0.99 for early-stage and advanced-stage HCC, respectively.

Humans↗