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Results for “plasma biomarkers”

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PubMed2026

Cross-Platform Proteomics and Machine Learning Algorithms Nominate Plasma Biomarkers of Stroke Diagnosis.

BACKGROUND: Blood-based biomarkers for stroke subtyping could improve triage in emergency settings. We used cross-platform proteomics to identify plasma biomarkers differentiating major stroke diagnostic groups. METHODS: We conducted a case-control study using 2 biorepositories. Plasma was collected in the emergency department from adults with suspected stroke before therapeutic intervention. Differentially enriched proteins were identified across acute ischemic stroke, intracerebral hemorrhage, transient ischemic attack, and stroke mimics using SomaScan discovery proteomics (Grady). Differentially enriched proteins were nominated using pairwise and multigroup comparisons and adjusted for clinical covariates. Protein panels were created using least absolute shrinkage and selection operator logistic regression. Internal validation used repeated nested cross-validation (rCV) and targeted mass spectrometry (MS), while external validation used data-independent acquisition  mass spectrometry in an independent cohort (Yale). RESULTS: We included 100 subjects (40 with acute ischemic stroke, 20 with intracerebral hemorrhage, 20 with transient ischemic attack, 20 with stroke mimics) in discovery and 80 subjects (20 per group) in external validation cohorts. SomaScan quantified 7307 proteins, of which 61 differentiated stroke subtypes. We identified 7 protein classifiers for acute ischemic stroke (rCV-area under the curve, 0.82 [95% CI, 0.78-0.86]), 6 for intracerebral hemorrhage (rCV-area under the curve, 0.70 [95% CI, 0.64-0.76]), 8 for transient ischemic attack (rCV-area under the curve, 0.78 [95% CI, 0.73-0.84]), and 7 for stroke mimics (rCV-area under the curve, 0.81 [95% CI, 0.77-0.86]). Targeted proteomics internally validated 11 proteins, and data-independent acquisition-mass spectrometry externally validated 32 proteins, including VTN (vitronectin), PLG (plasminogen), and S100A9 as top stroke mimics, transient ischemic attack, and intracerebral hemorrhage classifiers. CONCLUSIONS: This study highlights plasma proteomics as a valuable tool for discovering protein biomarkers of stroke diagnosis. These findings support further validation in larger, multicenter cohorts to facilitate biomarker-guided stroke diagnosis in acute care.

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PubMed2026

Depression and amyloid-β across CSF, PET, and plasma biomarkers: a systematic review and meta-analysis.

Alzheimer's disease is increasingly defined by biomarker evidence of amyloid-β and tau pathology, sharpening questions about whether late-life depression contributes to, or instead reflects, this pathology. We conducted a systematic review and meta-analysis of studies published between 2000 and 2025 that compared amyloid-β biomarkers in adults with and without depression, with depression defined by validated clinical diagnoses or symptom rating scales. Twenty-four studies were included, spanning three biomarker sources: cerebrospinal fluid, positron emission tomography imaging, and plasma. Across all sources, the pooled difference in amyloid-β burden between depressed and non-depressed individuals was small and clustered near zero, indicating only a weak, statistically non-significant tendency toward higher amyloid in depression. When the three sources were examined separately, each yielded a similar near-null result, although between-study heterogeneity was considerable for cerebrospinal fluid and plasma and moderate for imaging. Importantly, a prespecified subgroup analysis showed that imaging results diverged by quantification method: studies using the simpler standardized uptake value ratio clustered around zero, whereas the smaller group of studies using kinetic distribution volume ratio modelling showed a significant positive association, suggesting that methodological choices critically influence the observed relationship. Taken together, these findings indicate that depression is not consistently accompanied by greater amyloid-β burden across widely used biomarker platforms. The distribution volume ratio signal nonetheless raises the possibility of subtle associations that cruder methods may obscure, and suggests that depression may shape Alzheimer's disease trajectories more by modifying the clinical impact of amyloid than by altering its amount.

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PubMed2026

Tau proteoforms as plasma biomarkers in Alzheimer's disease: mechanisms, measurement, and medicine.

INTRODUCTION: Blood-based tau proteoforms have emerged as specific, scalable biomarkers of Alzheimer's pathology, addressing the limitations of symptom-based diagnosis, neuroimaging, and invasive cerebrospinal fluid (CSF) testing. This review synthesizes advances in tau phosphorylation and truncation biology, evaluates translation from CSF to plasma with state-of-the-art proteomics, and outlines the analytical standards and cross-matrix calibration needed for clinical adoption. AREAS COVERED: We conducted a literature search in PubMed and Google Scholar. We reviewed studies published between January 2005 and September 2025 investigating tau proteoforms in Alzheimer's disease. EXPERT OPINION: Blood-based tau proteoforms are poised to move Alzheimer's diagnostics from specialized imaging to accessible frontline testing, with plasma p-tau217 approaching positron emission tomography (PET) and CSF performance and multi-analyte panels with glial fibrillary acidic protein (GFAP) or neurofilament light (NfL) improving differential diagnosis while reducing invasiveness and cost. Building on the first FDA-cleared plasma assay (Lumipulse G p-tau217/Aβ1-42 Ratio) in May 2025, we anticipate a dual pathway over the next decade in which referral centers use high-plex mass spectrometry (MS) panels for phosphoforms and truncations, while primary care adopts automated high-throughput immunoassays (e.g. chemiluminescent enzyme immunoassay (CLEIA)) for triage, supported by harmonized standard operating procedures (SOPs), cross-matrix calibration, and robust reference materials.

Humans↗

PubMed2026

Discovery and validation of novel plasma protein biomarkers for severe tuberculosis patients.

OBJECTIVE: Severe tuberculosis (STB) imposes a substantial disease burden, yet reliable biomarkers for distinguishing STB from mild/moderate tuberculosis (MTB) remain scarce. This study aimed to identify and independently validate plasma protein biomarkers associated with tuberculosis severity. METHODS: In this multicenter prospective study, 298 adults with confirmed pulmonary tuberculosis were enrolled into screening (n = 128) and independent validation (n = 170) cohorts. Plasma samples were analysed using data-independent acquisition proteomics. Differentially expressed proteins were screened via Limma and four machine-learning algorithms, with candidate proteins measured by enzyme-linked immunosorbent assays. Receiver operating characteristic analysis assessed individual and combined diagnostic performance. RESULTS: STB patients were older and presented with lymphopenia, hypoalbuminemia, neutrophilia, and elevated lactate dehydrogenase. Among 166 differentially expressed proteins, HSPA5, HSP90B1, EEF1D, and SULT1A1 were selected for validation. In STB patients, HSPA5, HSP90B1, and EEF1D were upregulated, whereas SULT1A1 was downregulated. The four-protein panel achieved an AUC of 0.908 (95% CI 0.864-0.952), with 87.5% sensitivity and 83.8% specificity, modestly outperforming HSPA5 alone (AUC = 0.894). Functional enrichment implicated cholesterol metabolism, immune-inflammatory pathways, and endoplasmic reticulum stress. CONCLUSIONS: The four-protein panel effectively discriminated STB from MTB; however, its marginal improvement over HSPA5 alone suggests that an HSPA5-based assay may offer a simpler, more practical, and potentially cost-effective strategy for severity stratification.

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PubMed2025

Impact of sodium-glucose cotransporter-2 inhibitors on aging biomarkers and plasma ceramide levels in type 2 diabetes: beyond glycemic control.

BACKGROUND: Aging is a complex biological process marked by the decline of physiological functions and heightened susceptibility to chronic illnesses, notably cardiometabolic disorders. Ceramides (Cer) are lipid derivatives linked to aging and metabolic diseases. Sodium-Glucose Cotransporter-2 inhibitors (SGLT2i), widely used in managing type 2 diabetes, have an unclear impact on aging biomarkers and Cer profiles. OBJECTIVE: This study explored the association between SGLT2i use, plasma Cer levels (CerC16:0, CerC18:0, CerC22:0, CerC24:0, and CerC24:1), and aging biomarkers-Human Insulin-Like Growth Factor 1 (IGF-1), mammalian target of rapamycin (mTOR), 5-Methylcytosine (5MC), and Human H2AFX (Histone H2AX) in patients with type 2 diabetes mellitus (T2DM). METHODS: In this retrospective study, 95 participants were divided into three groups: patients on SGLT2i (n = 34), patients on non-SGLT2i anti-diabetic treatments (n = 36), and healthy controls (n = 25). Plasma Cer and aging biomarkers were quantified using Liquid Chromatography with tandem mass spectrometry (LC-MS-MS) and ELISA, respectively. Principal component analysis (PCA) assessed group-based clustering, while ANCOVA evaluated group differences with confounder adjustment. RESULTS: SGLT2i-treated patients showed significantly lower CerC16:0, CerC22:0, and CerC24:1 levels (p < 0.01) and decreased 5MC and H2AX (p < 0.05) compared to non-SGLT2i patients. IGF-1 was significantly elevated in the SGLT2i group (p < 0.01), suggesting a possible protective effect on metabolic health. PCA distinguished control from diabetic groups but revealed overlap between SGLT2i and non-SGLT2i groups. CONCLUSION: Beyond glucose control, SGLT2i may improve plasma Cer and aging markers in diabetic patients, supporting their broader therapeutic potential in aging and age-related diseases. Further large-scale studies are warranted to confirm these effects and underlying mechanisms.

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PubMed2025

The Effect of APOE ε4 Allele on Dynamic Local Spontaneous Brain Activity and Functional Integration in Alzheimer's Disease.

The apolipoprotein E (APOE) ε4 allele is the most important genetic risk factor for sporadic Alzheimer's disease (AD), yet its mechanisms in AD pathology and cognitive decline remain unclear. Using a sliding-time window approach to directly quantify the instantaneous fluctuations of various local metrics based on continuous time series and calculate voxel-wise concordance of these metrics, we explored the impact of APOE ε4 on dynamic local brain activity and functional integration in AD, and its interrelations with plasma biomarkers and cognition. Results showed that APOE ε4 widely affected dALFF, dReHo, dGSCorr, and voxel-wise concordance. For AD patients, APOE ε4 carriers uniquely exhibited correlations between dALFF in the right angular gyrus/supramarginal gyrus and MoCA scores and orientation function, and between voxel-wise concordance in the right caudate nucleus (CAU) and general cognition, attention, language function, orientation function, plasma Aβ42. Critically, APOE ε4-related altered voxel-wise concordance in the right CAU mediated the relationship between plasma Aβ and language cognition in AD. Moreover, the combined model incorporating dynamic metrics, plasma AD biomarkers, and demographic data effectively distinguished AD from NC (AUC = 0.94, sensitivity = 87.69%, specificity = 86.84%). In conclusion, the APOE ε4 allele might play a pivotal role in modulating brain dynamic functional activities in AD, which may contribute to the association between Aβ pathology and cognitive decline. Our findings may provide imaging markers and targets for the diagnosis and treatment of AD.

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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.

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PubMed2025

The Consortium for Clarity in ADRD Research Through Imaging (CLARiTI): Overview of consortium sites and anticipated enrollment.

INTRODUCTION: The Consortium for Clarity in Alzheimer's disease related dementias (ADRD) Research Through Imaging (CLARiTI) is a study that aims to collect standardized imaging and plasma biomarkers on 2000 Clinical Core participants enrolled across all Alzheimer's Disease Research Centers (ADRC) sites. We sought to summarize the known heterogeneity across centers regarding scientific focus and initial enrollment plans for CLARiTI. METHODS: We developed and distributed a survey capturing information on the 36 CLARiTI site's theme/expertise, recruitment plans, and the intersection of CLARiTI with other ADRC imaging efforts. RESULTS: Anticipated CLARiTI enrollees spanned 11 different categories of suspected etiologies underlying impairment. A wide range of risk factors were endorsed across sites regarding the enrollment of unimpaired individuals. Variability also existed regarding site-level strategies in enrollment into CLARiTI versus other imaging efforts. DISCUSSION: We anticipate that the 2000 individuals that will enroll into CLARiTI will reflect the clinical heterogeneity already in place across the ADRC network. HIGHLIGHTS: The ADRC Consortium for Clarity in ADRD Research Through Imaging (CLARiTI) will leverage and contribute to the existing Alzheimer's Disease Research Centers (ADRC) program by supporting standardized imaging and plasma collection across all centers. We summarize the variation in scientific focus and enrollment plans across ADRC sites participating in CLARiTI. The anticipated CLARiTI cohort will reflect the clinical heterogeneity that already exists across the ADRC network. CLARiTI will contribute to scientific goals related to the detection of multi-etiological signatures relevant for Alzheimer's disease and related disorders (ADRDs).

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PubMed2025

Elevated plasma GFAP levels in MCI link APOE ε4 allele with impaired gait speed.

The presence of at least one copy of the apolipoprotein ε4 allele (APOE ε4) is a known predictor of gait impairment risk among older adults. However, the mechanisms by which APOE ε4 affects gait performance remain unclear. This cross-sectional study aimed to reveal underlying pathological mechanisms linking APOE ε4 carriage to slow gait. This secondary analysis used baseline assessments from the J-MINT multicenter intervention trial, focusing on older adults with mild cognitive impairment. Gait speed was measured at baseline, with slow gait (SG) defined as speeds one standard deviation below the age- and sex-specific mean. APOE phenotype and plasma biomarkers related to Alzheimer's disease (AD), including amyloid-β composite biomarker, phosphorylated Tau 181, neurofilament light, and glial fibrillary acidic protein (GFAP), were also measured. The analysis included 236 non-APOE ε4 carriers and 84 carriers of at least one APOE ε4. APOE ε4 carriers exhibited significantly slower gait speed than non-carriers (1.20 m/s [SD = 0.22] vs 1.26 m/s [SD = 0.23], p = 0.042). Significant interaction between APOE ε4 carriage and SG was observed only in plasma GFAP levels (F1, 312 = 7.17, p = 0.008), indicating that individuals with APOE ε4 and SG had significantly higher plasma GFAP levels. Elevated plasma GFAP levels fully mediated the association between APOE ε4 carriage and gait speed (partially standardized indirect effect = -0.059: -0.12 to -0.013]). No other AD-related biomarkers mediated this association. Our results suggest that APOE ε4-related gait changes may reflect AD pathology, as indicated by elevated GFAP levels, and could potentially accelerate dementia symptoms.

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PubMed2025

Association of Lung Quantitative CT Scan Textures With Systemic Inflammation and Mortality in COPD.

BACKGROUND: COPD is characterized by persistent inflammation that is responsible for remodeling the bronchovascular bundles (BVBs), which may lead to poor quality of life. Quantitative CT (QCT) scan textures of the lung can capture local disease patterns of inflammation and related respiratory morbidity. RESEARCH QUESTION: Are BVB textures, obtained from the adaptive multiple feature method, associated with systemic inflammation, morbidity, and mortality in COPD? STUDY DESIGN AND METHODS: We analyzed data from the Subpopulations and Intermediate Outcome Measures in COPD Study (SPIROMICS; n = 2,981) and the Genetic Epidemiology of COPD (COPDGene) study (n = 10,305). The predictors included 2 QCT scan biomarkers, the BVB and CT density gradient (CTDG) textures, age, sex, BMI, race, smoking status, pack-years of smoking, CT scan-detected emphysema, and square root of the wall area of a hypothetical airway with a 10-mm lumen perimeter (Pi10). Outcomes included plasma biomarker concentrations from Meso Scale Discovery proteomics assays and CBC counts, both as markers of inflammation, along with FEV1, FEV1 to FVC ratio, St. George's Respiratory Questionnaire score, 6-minute walk distance, and modified Medical Research Council dyspnea scale score. Associations of these QCT scan textures with FEV1 decline and all-cause mortality also were investigated. RESULTS: Increased BVB texture was associated significantly with elevated neutrophil and monocyte counts and the neutrophil to lymphocyte ratio, independent of clinical covariates, CT scan-detected emphysema, and Pi10. Elevated CTDG was associated with increased neutrophil count, NLR, and tumor necrosis factor α. Increased CTDG and BVB textures also were associated with a lower FEV1 and 6-minute walk distance. CTDG at baseline was also associated with decline in FEV1 at the 5-year follow-up in the COPDGene study. We observed a significant association of both BVB texture (SPIROMICS: hazard ratio [HR], 1.084 [95% CI, 1.035-1.135; P < .001]; COPDGene: HR, 1.106 [95% CI, 1.080-1.131; P < .001]) and CTDG texture (SPIROMICS: HR, 1.033 [95% CI, 1.003-1.064; P = .03]; COPDGene: HR, 1.079 [95% CI, 1.061-1.096; P < .001]) with all-cause mortality independent of CT scan-detected emphysema and Pi10. INTERPRETATION: QCT scan textures may provide imaging evidence of the spatial heterogeneity of lung inflammation and overall disease burden in COPD. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov; Nos.: NCT01969344 (SPIROMICS) and NCT00608764 (COPDGene); URL: www. CLINICALTRIALS: gov.

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PubMed2026

Obesity-Related Coagulation Activation in Adolescents and Children: A Systematic Review and Meta-Analysis.

UNLABELLED: Obesity is recognized as a pro-thrombotic condition, yet the extent of coagulation activation across biomarkers remains unclear. This meta-analysis evaluates the impact of obesity on parameters-D-dimer, fibrinogen, plasminogen activator inhibitor-1 (PAI-1), von Willebrand factor (vWF), factor VIII (FVIII), and endogenous thrombin potential (ETP)-in children and adults. METHODS: Sixty-four studies comprising 59,503 individuals were analyzed. Plasma biomarker levels were compared between non-obese and obese groups using standardized mean differences (SMDs), with subgroup analyses. RESULTS: D-dimer was significantly elevated in adults with obesity (SMD 1.36, 95% CI 0.47-2.25, p = 0.003) and children with obesity (SMD 0.77, 95% CI 0.19-1.36, p = 0.009), indicating increased fibrin turnover. Fibrinogen levels were markedly higher in both adults (SMD 1.17, 95% CI 0.14-2.20, p = 0.03) and children (SMD 1.43, 95% CI 0.93-1.92, p < 0.0001). PAI-1 showed the most pronounced increase in adults (SMD 2.30, 95% CI 0.1.51-3.09, p < 0.0001) and children (SMD 3.54, 95% CI 1.65-5.43, p = 0.0002). FVIII levels were modestly elevated (SMD 0.52, 95% CI 0.10-0.94, p = 0.02), whereas vWF levels showed inconsistent changes. ETP was significantly higher in obesity, in children (SMD 1.06, 95% CI 0.24-1.88, p = 0.01) and adults (SMD 0.71, 95% CI 0.46-0.97, p < 0.0001). Gender-stratified data indicated higher PAI-1, fibrinogen, and ETP levels in females. CONCLUSION: Obesity is associated with increased coagulation activation, suggesting a pro-thrombotic shift. These findings support the need for age- and gender-specific research into obesity-related hemostatic alterations.

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PubMed2026

Omics Profiling of Patients with Obstructive Sleep Apnoea Reveals Risks of Diabetes Mellitus and Cardiovascular Diseases.

Obstructive sleep apnoea (OSA) constitutes a multisystemic disorder often associated with cardiovascular and metabolic disorders. Thus, far, the underlying pathophysiological processes are not fully understood. In total, 142 plasma samples were acquired: 50 from controls (CON), 45 from mild/moderate OSA (M-OSA) patients, and 47 from severe OSA (S-OSA) patients. Proteomic and metabolic signatures significantly differed among S-OSA, M-OSA, and CON samples. A novel plasma biomarker panel including two proteins (ACTR2 and ENO1) and three metabolites (2-aminobicyclo[2 2·1], heptane-2-carboxylic acid, 1-O-[2r-hydroxy-hexadecyl]-sn-glycerol, and 1-pentadecene) was developed to identify S-OSA (AUC: 1.000) and distinguish severe cases from nonsevere cases (AUC: 0.813). An independent cohort was used to validate the model by distinguishing S-OSA samples from M-OSA (AUC: 0.729) and CON (AUC: 0.990) samples. Glycolysis pathway activation was identified as a characteristic of OSA; it may contribute to diabetes mellitus onset in OSA patients. Dyslipidaemia, foamy macrophage formation, platelet activation, and actin cytoskeleton might collectively play a key role in vascular damage in OSA patients, contributing to the development of atherosclerosis. These findings reveal molecular bases for OSA-related cardiometabolic complications and provide new diagnostic biomarkers for OSA and the identification of severe cases.

Humans↗

PubMed2026

Plasma von Willebrand Factor and ADAMTS13 Interact With APOE-ε4 in Predicting Longitudinal Brain Atrophy and Cognitive Decline Over a 9-Year Follow-Up.

BACKGROUND: Von Willebrand factor (VWF) and ADAMTS13 (a disintegrin and metalloproteinase with thrombospondin type 1 motif, 13) are linked to dementia risk, and limited evidence suggests apolipoprotein E (APOE)-ε4 alters VWF release. This study assessed whether baseline VWF and ADAMTS13 levels predict neurodegeneration and cognitive decline and evaluated effect modification by APOE-ε4 carriership. METHODS: Vanderbilt Memory and Aging Project cohort participants (n=332, 73±7 years, 59% male) completed serial blood draw, neuropsychological assessment, and brain magnetic resonance imaging over 6.4 years (range 1.4-9.7 years). Baseline plasma VWF and ADAMTS13 levels were quantified using mass spectrometry and Olink. Fully adjusted linear mixed-effects models related protein×time and protein×APOE-ε4×time interaction terms to longitudinal brain magnetic resonance imaging and neuropsychological outcomes. RESULTS: Lower baseline ADAMTS13 predicted faster declines in language (β=0.11, P=0.01), information processing speed (β=0.27, P=0.001), executive function (β=0.01, P=0.03), episodic memory (β=0.01, P=0.03), and visuospatial ability (β=0.11, P=0.001) and faster increases in global (β=-0.29, P=0.01) and frontal (β=-0.17, P=0.01) white matter hyperintensity volumes. Associations between ADAMTS13 and faster rates of cognitive decline and white matter injury were driven by APOE-ε4 carriers. Models relating VWF to longitudinal outcomes were null. APOE-ε4 interacted with VWF on longitudinal gray matter volumetric outcomes, such that faster rates of global gray matter atrophy were observed with higher baseline VWF levels among APOE-ε4 noncarriers only (β=-1530.5, P<0.001). CONCLUSIONS: ADAMTS13 shows promise as a potential plasma biomarker for brain aging outcomes, but additional research is warranted to understand the performance of VWF in the presence versus absence of an APOE-ε4 allele.

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PubMed2026

Downregulated lysyl oxidase in plasma extracellular vesicles: a biomarker linked to brain metastasis risk in lung adenocarcinoma.

BACKGROUND: Brain metastasis (BrM) is a leading cause of mortality in patients with lung adenocarcinoma (LUAD). Extracellular vesicles (EVs), which carry bioactive molecules, play a critical role in tumor microenvironment remodeling and exhibit metastatic organotropism, holding promise as liquid biopsy biomarkers. This study aims to identify plasma EV-derived proteins associated with LUAD-BrM. METHODS: A multi-omics framework was applied. Plasma EVs from 59 stage IV LUAD patients (30 BrM vs 29 non-BrM) were profiled using data-independent acquisition mass spectrometry proteomics. Candidate proteins were screened via bioinformatics and machine learning (LASSO/RF/SVM). Initial validation included tissue proteomics (n = 13), single-cell transcriptomics (TISCH2), and Western blot analysis of a subset of the discovery samples. Functional experiments were conducted in vitro. The lead candidate was ultimately validated in an independent plasma cohort (n = 158) through ELISA. RESULTS: Proteomic analysis implicated collagen-containing extracellular matrix (ECM) pathways. Lysyl oxidase (LOX), a key ECM cross-linking enzyme, was identified as a lead candidate. LOX and its family member LOXL1 were consistently downregulated in BrM tissues and plasma EVs. Single-cell analysis revealed decreased LOX expression specifically in BrM-associated fibroblasts, which showed suppressed ECM-related pathways. In vitro experiments supported a PI3K/AKT-LOX-ECM regulatory axis. Plasma EV-derived LOX demonstrated strong diagnostic performance in the independent cohort, with an AUC of 0.786 (95% CI 0.713iated fi. CONCLUSIONS: Our study establishes plasma EV-derived LOX as a promising non-invasive biomarker for LUAD-BrM through a comprehensive multi-omics validation strategy. We propose a model wherein downregulation of LOX, potentially driven by PI3K/AKT signaling in tumor-associated fibroblasts, contributes to ECM degradation and may promote brain-tropic metastasis. This finding offers new insights for risk stratification and timely intervention in LUAD patients.

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PubMed2026

Development and validation of a plasma miRNA-CEA biomarker panel for early detection of lung cancer.

Lung cancer remains a leading cause of cancer-related mortality worldwide, underscoring the critical need for early detection to improve patient outcomes. This study aimed to develop and validate a plasma microRNA biomarker panel for the early detection of non-small cell lung cancer in a Japanese cohort. We enrolled 525 participants, comprising 261 LC cases and 264 non-LC controls, divided into optimization and validation cohorts. A 12-miRNA panel was optimized and further combined with CEA to enhance diagnostic performance. The miRNA-alone model demonstrated robust performance in both the optimization (AUC = 77.0%) and validation cohorts (AUC = 77.9%). Integration with CEA significantly improved accuracy, achieving AUCs of 86.2% in optimization and 84.9% in validation, with particularly high performance in late-stage cancers (AUC = 94.4%) and squamous cell carcinoma (AUC = 90.7%). Sensitivity and specificity thresholds were evaluated, enabling model customization for diverse clinical scenarios. These findings highlight the potential of the miRNA-CEA panel as a minimally invasive tool for early LC detection, especially in non-smoking populations.

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PubMed2025

Untargeted metabolomics in a prospective cross-sectional observational study reveals differences in plasma and cerebrospinal fluid between asymptomatic neurosyphilis and serofast syphilis.

Asymptomatic neurosyphilis (ANS), a diagnostically elusive complication of Treponema pallidum infection, necessitates invasive cerebrospinal fluid (CSF) analysis for detection. This study investigated metabolic differences between patients with ANS and those with serofast syphilis. Using untargeted metabolomics, we analyzed plasma and CSF from 15 patients with ANS, 15 patients with serofast syphilis, and 16 healthy controls via liquid chromatography-mass spectrometry. Univariate statistical analyses identified differential metabolites, followed by pathway enrichment through Kyoto encyclopedia of genes and genomes enrichment analysis and biomarker evaluation. Plasma analysis identified dysregulated tryptophan metabolism as a central feature in ANS, with key alterations in 4-(2-aminophenyl)-2,4-dioxobutanoic acid and 2-formylaminobezaldehyde. Comparative analysis further distinguished ANS through perturbations in inositol phosphate metabolism in both plasma and CSF. Spearman correlation analysis identified positive associations of the plasma biomarkers 1D-myo-inositol-1,3,4,6-tetrakisphosphate, inositol-1,3-bisphosphate, 4-(2-aminophenyl)-2,4-dioxobutanoic acid, and 2-formylaminobezaldehyde with CSF total protein. Our findings suggest that dysregulation in tryptophan and inositol phosphate metabolism may play an important role in ANS pathogenesis, warranting further confirmatory studies.

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PubMed2025

Identifying novel protein biomarkers with cross-psychiatric disorders effects and potential intervention targets: Evidence from proteomic-Mendelian randomization.

Plasma proteins are the potential therapeutic targets for psychiatric disorders due to their important roles in signal transduction. We aimed to explore the plasma protein biomarkers with cross-psychiatric disorders effects. Proteome-wide Mendelian randomization (MR) and colocalization analyses were performed to investigate the potential causal relationship between plasma protein biomarkers and 12 psychiatric disorders and further identify the potential proteins with cross-effects. To assess the directionality and exclude potential reverse causation, Steiger directionality tests and reverse MR analyses were additionally conducted. Then, validation analysis was performed by employing summary data from cross-psychiatric disorder GWAS to validate the cross-psychiatric effects of proteins. Protein-protein interactions were conducted to evaluate the interaction between candidate proteins and druggability assessment was used to prioritize potential drug targets for psychiatric disorders. We identified novel plasma proteins that possessed cross-psychiatric disorder effects, especially BTN2A1 and BTN3A2 associated with major depressive disorder (MDD), schizophrenia (SCZ), and bipolar disorder (BIP); ITIH1, ITIH3, ITIH4 and FES associated with SCZ and BIP, and the cross-effects of these proteins on SCZ and BIP were confirmed by validation analyses. Steiger tests and reverse MR supported causal directionality. Besides, the protein-protein interactions (PPI) analysis indicated cross-effects proteins had significant interaction, especially ITIH1-ITIH3. The druggability assessment prioritized eight proteins, two of which (ITIH3 and NCAM1) has been targeted by antipsychotic drugs. Our findings provided insights into shared biological mechanisms underlying these conditions.

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PubMed2026

Plasma Proteomic Profiling Identifies Candidate Biomarkers for Pancreatic Ductal Adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy that is often diagnosed after curative treatment is no longer feasible. Existing biomarkers, particularly CA19-9, have limited sensitivity and specificity. Plasma proteins that capture tumor-associated biological alterations may therefore provide useful signals for earlier detection. METHODS: Plasma samples from 99 patients with PDAC and 30 healthy controls were analyzed using data-independent acquisition (DIA) proteomics. Differentially expressed proteins were identified using predefined statistical thresholds and further examined by functional enrichment analysis. Selected candidate biomarkers were validated by ELISA in an independent subset. RESULTS: Among 565 quantified plasma proteins, 52 were differentially expressed between PDAC and controls. These proteins were enriched in extracellular processes, cholesterol metabolism, complement and coagulation cascades, and pancreatic secretion pathways. ELISA validation confirmed higher plasma levels of Cathepsin S, CTRB2, MARCO, PIGR, PRDX6, REG1A, Trypsin-2, and PEP-FAP in patients with PDAC compared with healthy controls. ROC analyses showed moderate-to-good discriminatory performance for several candidates, and the MARCO + PEP-FAP model improved classification compared with either marker alone. CONCLUSION: These findings reveal circulating proteins linked to key PDAC-related biological processes and identify eight candidates for further evaluation in multi-protein diagnostic panels. Larger validation studies incorporating clinically relevant disease control groups are warranted to determine their diagnostic specificity and clinical utility.

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