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PubMed2026

Diagnostic value of blood p-tau subtypes in Alzheimer's disease progression and pathology: systematic review and meta-analysis.

BACKGROUND: Alzheimer's disease (AD) is the most common neurodegenerative disease and the most likely to lead to dementia. With the availability of the latest therapies, the need for Alzheimer's disease diagnosis is now gradually increasing. Whereas blood phosphorylated-tau (p-tau) has demonstrated excellent performance in the prediction and diagnosis of disease progression and Aβ positivity in AD, there are differences between different p-tau subtypes. Therefore, a pooled analysis of different blood p-tau subtypes is of more important clinical value. METHOD: Relevant literature was screened by complete search in four databases, Pubmed, Embase, Cochrane Library and Scopus. Relevant data and AUC and their confidence intervals of the included literature were extracted and analyzed by classification according to p-tau subtypes. Quality assessment was performed using the QUADAS-2 tool. RESULT: Our results reveal that p-tau217 performs better in the diagnostic performance in most stages of AD, which is consistent with the guidelines. However, our results concluded that p-tau217 has poorer diagnostic performance in the stages of cognitive unimpaired or less cognitively impaired, especially in the Aβ positivity diagnosis of SCD and CU. Head-to-head meta-analyses formally confirmed that p-tau217 significantly outperforms p-tau181 across AD dementia, Aβ positivity, tau positivity, and biological staging (all P < 0.05), whereas no significant difference was observed between p-tau231 and p-tau181. CONCLUSION: By integrating single-arm pooled AUC estimates with formal head-to-head statistical comparisons, our study provides evidence-based support for plasma p-tau217 as the subtype with the most robust diagnostic performance across AD pathology and biological staging. Head-to-head analyses formally confirmed that p-tau217 significantly outperforms p-tau181 in Aβ positivity, Tau positivity, and biological staging.

Humans↗

PubMed2026

MET-Aberrant non-small cell lung cancer: from kinase dependence to cell-surface targetability-mechanistic basis and biomarker framework for bispecific antibodies and antibody-drug conjugates.

MET-aberrant non-small cell lung cancer (NSCLC) is not a uniform therapeutic entity. Its biology, diagnostic pathways, and treatment sensitivity differ across MET exon 14 skipping alteration (METex14), MET amplification, and MET overexpression. This heterogeneity cannot be fully explained by conventional event-based classification and is reflected in the distinct clinical activity of MET tyrosine kinase inhibitors (MET-TKIs), bispecific antibodies (BsAbs), and antibody-drug conjugates (ADCs). With the emergence of antibody-based therapies, MET has evolved from a signaling driver to a cell-surface target for receptor modulation and payload delivery. We therefore propose a clinically anchored two-dimensional framework for interpreting therapeutic relevance in MET-aberrant NSCLC: kinase dependence and cell-surface targetability. Neither dimension should be regarded as a directly measurable binary variable. Kinase dependence is inferred from genomic and treatment-contextual proxies, most strongly METex14 and, more conditionally, high-level focal MET amplification. Cell-surface targetability is approximated by drug-specific IHC assessment of assay-defined c-MET protein expression; however, receptor internalization, intracellular trafficking, and payload delivery capacity remain incompletely measurable in routine clinical practice. Within this framework, MET-TKIs have the most evidence-supported established role in tumors with evidence of MET-driven kinase dependence. EGFR × MET BsAbs have demonstrated clinical activity in broad post-osimertinib EGFR-mutant NSCLC, while EGFR/MET co-dependence or MET-mediated bypass activation provides a mechanistic rationale for their use; MET-defined preferential benefit remains to be prospectively established. MET-directed antibody-drug conjugates (MET-ADCs) are supported in drug- and assay-defined populations with high c-MET protein overexpression, although the predictive relevance of delivery-related factors remains hypothesis-generating. Accordingly, MET testing should shift from single-event detection to platform-oriented stratification: next-generation sequencing (NGS) for driver alterations and resistance profiles, fluorescence in situ hybridization (FISH) for high-level focal amplification, and immunohistochemistry (IHC) for surface expression relevant to antibody-based therapies. This framework is intended to organize current biological and clinical evidence rather than to replace drug-specific companion diagnostics, regulatory indications, or prospectively validated treatment-selection algorithms. Precision treatment of MET-aberrant NSCLC is thus moving from event-based drug selection toward mechanism-based therapeutic matching. Future priorities include standardizing biomarkers, defining optimal target populations, and aligning biological subtypes, diagnostic strategies, and therapeutic platforms.

Antibody-drug conjugate↗

PubMed2026

Omics in hereditary optic neuropathies: A systematic review of clinical studies with an integrated point of view.

Hereditary optic neuropathies are characterized by bilateral visual loss due to the degeneration of retinal ganglion cells, resulting in optic nerve degeneration and atrophy. Although the genetic origin of the main isolated and syndromic hereditary optic neuropathies has been characterized, the clinical phenotypes exhibit significant and poorly understood variability in both penetrance and expressivity. Additionally, the genetic and environmental factors that influence the onset of these optic neuropathies remain poorly understood, with limited biomarkers to predict disease progression or as readouts for therapeutic trials. Data-driven omics strategies allow deep phenotyping to improve our understanding of pathophysiological mechanisms and to search for new biomarkers and therapeutic targets. We explore whether the omics strategies applied to patients with hereditary optic neuropathies have provided such new insights. MEDLINE, Web of Science and EMBASE databases were screened for studies with terms relating to hereditary optic neuropathies, transcriptomics, epigenomics, proteomics, metabolomics and lipidomics in clinical studies exploring patients' samples. Out of 1244 references identified, 22 articles were included after double-masked data curation. These articles focused only on the 3 main forms of hereditary optic neuropathies, namely, OPA1-related dominant optic atrophy (n = 4), Leber hereditary optic neuropathy (n = 13), and Wolfram syndrome (n = 5). While the methodological designs and results of these studies were highly heterogeneous, they revealed molecular alterations that we have attempted to discuss at the integrated multi-omics level. This data integration highlighted several common pathophysiological mechanisms such as energetic impairment, endoplasmic reticulum stress, proteotoxic and oxidative stresses, lipid remodeling and altered amino acid and purine metabolisms, while suggesting potential new biomarkers and therapeutic targets. These findings underscore the potential of integrated multi-omics approaches to deepen our understanding of the phenotypic complexity of hereditary optic neuropathies and to support the development of innovative diagnostic and therapeutic strategies.

Humans↗

PubMed2026

The mighty microproteins: from versatile cellular regulators to precision medicine therapeutics.

Microproteins, are tiny proteins encoded by small open reading frame (sORF), translation of these non-canonical open reading frames (ncORFs) has been implicated in diverse biological processes and diseases. This review summarizes recent developments in the discovery, biogenesis, and functional characterization of microproteins, and their involvement in various disease, with special focus on their roles in cancer, cardiovascular, metabolic, neurodegenerative and immune-related disorders. We emphasize the regulation of key cellular pathways by microproteins, including mitochondrial homeostasis, apoptosis, metabolic reprogramming, and immune signaling, all of which affect disease initiation and progression. Emerging evidence also supports their potential as disease biomarkers and therapeutic candidates for precision medicine. Finally, the review critically discusses the current challenges including discrepancies in microprotein annotation, the limitations of ribosome profiling and proteogenomic approaches, the gap between computationally predicted and experimentally validated microproteins, and the need for rigorous orthogonal validation by means of CRISPR-based genome editing, ribosome release assays, mutational analysis, high-resolution mass spectrometry, and functional studies. Finally, we review recent development of AI-assisted ORF prediction, single-cell translatomics, spatial proteomics, and integrated multi-omics as emerging technologies reshaping. Microprotein discovery and functional annotation. Finally, we discuss the translational potential of microproteins and highlight the remaining challenges to clinical application, including peptide stability, pharmacokinetics, tissue-specific delivery, immunogenicity, and the need for rigorous preclinical and clinical validation. Together, this review provides an updated and critical overview of the rapidly evolving microprotein field and highlights future research priorities for translating these molecules into clinically useful biomarkers and precision therapeutics.

Microproteins↗

PubMed2026

Prevalence of Claudin 18.2 Expression in Gastric and Gastroesophageal Junction Adenocarcinoma: A Systematic Review and Meta-Analysis.

BACKGROUND: Claudin 18 isoform 2 (CLDN18.2) has emerged as a clinically validated therapeutic target in gastric and gastroesophageal junction (GEJ) adenocarcinoma following the regulatory approval of zolbetuximab in combination with first-line chemotherapy. Accurate prevalence data at the clinically validated immunohistochemical threshold are essential for patient selection, healthcare resource planning, and treatment strategy. Reported prevalence estimates vary widely across studies due to differences in populations, methodologies, and immunohistochemical protocols. This systematic review and meta-analysis aimed to generate a robust pooled prevalence estimate of CLDN18.2 expression at the threshold used in pivotal phase III trials. METHODS: PubMed, Embase, and the Cochrane Library were searched from database inception through March 12th, 2026. Studies reporting CLDN18.2 expression in gastric or gastroesophageal junction adenocarcinoma using the ≥ 75% moderate-to-strong membranous staining threshold were included. Prevalence proportions were pooled using a random-effects model with logit transformation and restricted maximum-likelihood estimation of between-study variance. Heterogeneity was assessed using the I² statistic and Cochran's Q test, and a 95% prediction interval was calculated. Pre-specified subgroup analyses assessed antibody clone and geographic region, with additional exploratory analyses according to disease setting and specimen type. Sensitivity analyses were performed to assess the robustness of the pooled estimate. RESULTS: Twenty-two predominantly retrospective cohort studies comprising 12,173 patients were included. The pooled prevalence of CLDN18.2 positivity using a random-effects model was 33.99% (95% CI: 30.13%-38.07%; 95% prediction interval: approximately 18%-55%), with high between-study heterogeneity (I² = 92.4%). Subgroup analysis by antibody clone showed no statistically significant difference between studies using the 43-14 A clone (32.79%, 95% CI: 28.86%-36.97%) and those using other reported antibody clones (41.74%, 95% CI: 26.76%-58.42%; p = 0.281). One study with an unreported antibody clone was excluded from this subgroup analysis. Geographic subgroup analysis excluding the multinational Shitara et al. cohort demonstrated a non-significant trend toward higher prevalence in non-Asian populations (37.85%, 95% CI: 31.59%-44.54%) compared with Asian populations (32.10%, 95% CI: 27.28%-37.34%; p = 0.169). All three sensitivity analyses confirmed robustness of the pooled estimate. No significant evidence of publication bias was detected (Egger's test p = 0.56). CONCLUSIONS: Approximately one-third of patients with gastric and GEJ adenocarcinoma express CLDN18.2 at the clinically validated ≥ 75% threshold. However, because the included studies encompassed heterogeneous disease settings and were predominantly HER2-unselected, the pooled estimate should not be interpreted directly as the proportion of patients eligible for zolbetuximab. The estimate was robust across sensitivity analyses and provides an evidence base for understanding CLDN18.2 prevalence and biomarker-testing requirements. Standardisation of immunohistochemical assessment methods is warranted to reduce between-study heterogeneity in future research.

Humans↗

PubMed2026

Bi-compartmental CSF-serum analysis of NfL and GFAP differentiates central and peripheral pathology in neuroinfectious diseases: A monocentric real-world cohort study.

Neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP), established biomarkers of neuroaxonal injury and astroglial pathology, are frequently only assessed in blood, which limits conclusions regarding their origin. Bi-compartmental analyses of CSF and serum may help differentiate central or peripheral origin of biomarker elevation. Moreover, studies on NfL and GFAP in distinct neuroinfectious disease (NID) phenotypes, particularly those based on real-world cohorts, are limited. This retrospective monocentric study analyzed CSF and serum from patients with (meningo-)encephalitis/myelitis (TI+; n = 48), meningitis (TI-; n = 80), (cranial) nerve palsies/polyradiculitis (PND; n = 61), and 113 non-neuroinflammatory/non-neurodegenerative controls. A bi-compartmental model using scatter plots and simple linear regression was applied to assess the origin of blood biomarker levels and discriminate between central and peripheral pathology. CSF and serum NfL and GFAP z-scores were significantly higher in TI+ compared with TI- (CSF-GFAP p < 0.001/sGFAP p = 0.0083; CSF-NfL p = 0.003/sNfL p = 0.0004). TI+ and PND differed only in GFAP levels, which were higher in TI+ (CSF-GFAP p = 0.0049/sGFAP p = 0.003). The overall group effect (p ≤ 0.003) and principal findings remained significant after adjustment for age, sex, QAlb, and time since (symptom) onset to LP. Bi-compartmental analysis revealed simultaneous elevation of CSF and serum NfL in TI+, indicating predominantly central origin, whereas PND demonstrated a shift toward higher sNfL levels suggesting peripheral origin. Higher clinical severity (modified Rankin Scale 3-5) was associated with elevated serum and CSF GFAP and NfL (sGFAP p = 0.012/sNfL p = 0.002; CSF-GFAP p < 0.0001/CSF-NfL p = 0.0001), which also predicted unfavorable outcome at discharge (sGFAP p = 0.006/sNfL p = 0.004; CSF-GFAP p = 0.003/CSF-NfL p = 0.012). NfL and GFAP were associated with brain/myelon involvement in NID, predominantly reflecting central pathology. Despite strong CSF-serum correlations, bi-compartmental approaches provide additional insight into biomarker origin and disease compartment.

Humans↗

PubMed2026

Imaging‑based models for predicting cerebrovascular complications of carotid stenosis.

This is a protocol for a Cochrane review (prognosis). The objectives are as follows: Primary objective To systematically review and critically appraise multivariable prognostic models developed for adults (≥ 18 years) with carotid stenosis in which imaging biomarkers (e.g. plaque characteristics derived from magnetic resonance imaging (MRI), computed tomography (CT), or ultrasound) constitute the core predictors. The primary focus is to evaluate the predictive performance of these models for cerebrovascular complications - specifically ipsilateral ischaemic stroke and transient ischaemic attack (TIA) - which are the clinical outcomes to be predicted. Where feasible, we will summarise and compare the models' discrimination (C‑statistic/area under the curve (AUC)) and calibration (calibration‑in‑the‑large, calibration slope, observed‑to‑expected ratio) across studies, and assess their potential for clinical application and external validation. For the purpose of defining symptomatic carotid stenosis as an eligibility criterion and subgroup variable, we will include studies that also considered retinal ischaemia (e.g. retinal embolism, amaurosis fugax) as a qualifying event. Secondary objectives To describe the combinations of imaging markers, modelling techniques, sample sizes, and variable‑selection strategies used in the development of the included models To evaluate the performance of these models for additional secondary clinical outcomes: plaque progression or regression, incident high‑risk imaging features, and the transition from asymptomatic to symptomatic disease To explore whether predictive performance differs according to imaging modality (MRI versus CT versus contrast‑enhanced ultrasound (CEUS)) or technical protocol (e.g. 3 T versus 1.5 T, spectral CT versus conventional CT) For studies that report both cerebrovascular and broader cardiovascular outcomes (major adverse cardiovascular events, myocardial infarction, etc.), we will only extract the performance metrics relating to cerebrovascular events for the primary analysis. Performance metrics for cardiovascular outcomes will be considered exploratory and will not form part of the main synthesis.

Humans↗

PubMed2026

Serum Albumin on Admission: A Prognostic Marker of Morbidity and Mortality in Burns? A Systematic Review and Meta-Analysis.

Albumin is essential for maintaining oncotic pressure and vascular integrity. In burn injuries, increased capillary permeability leads to hypoalbuminemia, which is a recognized marker of poor outcomes in critical illness. However, its prognostic value in acute burn care remains underexplored. This study evaluated the prognostic value of admission serum albumin in predicting mortality, acute kidney injury (AKI), hospital and intensive care unit length of stay, ventilatory requirements, sepsis, and pulmonary infection in patients with burn injuries. A systematic search of PubMed, Scopus, Cochrane Library, Web of Science, MEDLINE, and Embase was conducted. Of 5587 studies screened, 19 were included in the systematic review and 9 in the meta-analysis. Statistical analysis was performed using RStudio, with pooled outcomes reported as odds ratios (ORs), standardized mean differences, and hierarchical summary receiver operating characteristic curves. Heterogeneity was assessed using Cochran's Q, I2, and tau2. Hypoalbuminemia on admission was significantly associated with increased mortality during admission (OR 9.51; 95% CI, 3.04-29.78; I2 49.3%). Admission hypoalbuminemia was also associated with an increased risk of AKI (OR 2.83; 95% CI, 2.49-3.22; I2 0%). Evidence for other outcomes was limited and heterogeneous. Admission serum albumin appears to be a valuable prognostic marker in patients with burn injuries, particularly for mortality and AKI. Further research is required to support its integration into burn-specific risk models, characterize albumin trends within the first 24 h postinjury, and establish optimal cut-off values.

Humans↗

PubMed2026

Longitudinal Prediction of Retinal Sensitivity Based on Disease Progression Quantified From Optical Coherence Tomography in Geographic Atrophy.

PURPOSE: The purpose of this study was to analyze the association between disease progression of geographic atrophy (GA) from optical coherence tomography (OCT) with retinal sensitivity (RS) in microperimetry (MP) over a 2-year follow-up period. METHODS: This is a longitudinal analysis of the OAKS Phase-III clinical trial. Both study and fellow eyes with GA that underwent imaging with the Spectralis OCT and consecutive MP examination were eligible. Pointwise quantification of ellipsoid zone (EZ) thickness, EZ and retinal pigment epithelium (RPE) loss from OCT volumes was correlated with localized RS. A longitudinal predictive model using a Markov Chain framework was implemented to predict RS change over time based on OCT biomarkers. The modeling of morphological and functional progression was based on the fellow-eye cohort. RESULTS: A total of 39,681 MP points from 406 patients were analyzed. In the fellow eye cohort, baseline (BSL) EZ thickness was positively associated with RS (0.3 decibel [dB]/µm, P < 0.001). Decrease in EZ thickness between visits during follow-up was significantly associated with decrease in RS (0.1 dB / 1 µm change). RS was significantly lower in MP points within EZ loss during follow-up compared with MP points within the retina with measurable EZ (P < 0.001). The largest functional decline was observed within RPE loss, also associated with the highest probability of absolute scotoma (P < 0.001). Morphological progression to EZ and RPE loss was influenced by EZ thickness and the morphology of adjacent MP points (P < 0.001). CONCLUSIONS: Two exploratory endpoints were developed, namely quantification of EZ thickness and loss, and localized RS within high-risk OCT areas. RS decline during follow-up is associated with automatically quantified disease progression in OCT.

Humans↗

PubMed2026

Novel environmental contaminant 6PPD-quinone promotes malignant phenotypes in colorectal cancer cells and identifies candidate response-associated genes.

6PPD-quinone (6PPDQ), an oxidative transformation product of the widely used tire antioxidant 6PPD, is a ubiquitous environmental contaminant with bioaccumulation potential and widespread human exposure. Recent epidemiological evidence indicates a positive association between urinary 6PPDQ levels and colorectal cancer (CRC) risk; however, its biological effects on CRC-related phenotypes and associated molecular responses remain unclear. We integrated bioinformatics analysis, prognostic modeling, molecular docking and dynamics simulations, and in vitro experiments to investigate cellular and molecular responses to 6PPDQ in CRC models. Predicted 6PPDQ targets were intersected with CRC prognosis-related genes from The Cancer Genome Atlas, followed by functional enrichment and LASSO regression to construct a prognostic risk model, with 1-, 3-, and 5-year AUC values of 0.727, 0.754, and 0.778, respectively. Molecular docking and 100-ns molecular dynamics simulations suggested interactions between 6PPDQ and candidate proteins, including CPT2, SHC2, SRMS, and STK35. Functional assays showed that 6PPDQ exposure altered proliferation, wound-closure capacity, and invasion in Caco-2 and HCT116 cells across the nanomolar concentration range, with non-monotonic and cell-line-dependent responses. In contrast, NCM460 cells showed no increase in EdU incorporation at 10 or 100 nM, whereas reduced proliferation at higher concentrations was accompanied by increased LDH release. 6PPDQ also altered the expression of several prognosis-associated candidate genes. These findings identify cellular phenotypes and candidate molecular responses associated with 6PPDQ exposure under the tested in vitro conditions, but do not establish their causal roles or in vivo relevance. Further mechanistic and in vivo studies are required.

Humans↗

PubMed2026

Stage-specific ROMO1 in rheumatoid arthritis: predictive immune insights into the MIF pathway and HLA-DR/IL2RA axis via integrated GWAS, transcriptomic, single-cell, and spatial profiling.

Emerging evidence links reactive oxygen species modulator 1 (ROMO1), a key mitochondrial ROS regulator, to rheumatoid arthritis (RA) pathogenesis. However, its exact mechanism remains elusive given the conflicting evidence about its specific function. We used a four-level integrative framework combining multi-omics data and literature‑supported mechanistic inference. At the genetic level, Mendelian randomization (MR) was performed to explore potential causal relationships between ROMO1, IL2RA, HLA-DR, MIF, and RA risk, followed by differential expression analysis and machine learning-based feature selection to identify key mROS genes. The temporal expression dynamics of ROMO1 were assessed in RA progression. At the cellular and tissue levels, we integrated single-cell RNA sequencing and spatial transcriptomics to map cell-type-specific expression and synovial localization of ROMO1-related immune cells and pathways. Finally, our multi-omics findings were contextualized with literature-supported mechanistic inference. (1) MR results were consistent with a potential protective effect of ROMO1 on RA (OR = 0.52) and its potential regulation of risk factors IL2RA (OR = 0.46) and HLA-DR (OR = 0.40). Conversely, IL2RA (OR = 1.42), HLA-DR (OR = 1.88), and MIF (OR = 1.17) were positively associated with RA risk. Additionally, ROMO1 was identified as a top candidate diagnostic predictor with stage-specific dynamics: downregulated in the early but upregulated in the late/remission stages. (2) Single-cell RNA sequencing showed ROMO1's cell-specific expression in CD14+ HLA-DR+ CD74+ monocytes and CD4+ IL2RA+ T cells. Cell communication analysis further suggested that these cells may participate in MIF pathway regulation. Spatial transcriptomics subsequently identified that ROMO1-related cells localized to synovial pathological regions, with MIF pathway changes correlated with RA progression. (3) Finally, literature-supported mechanistic inference suggests that ROMO1 may modulate mROS levels to promote anti-inflammatory M2 macrophage polarization, which could theoretically contribute to reduced systemic inflammation and the alleviation of multi-organ decline in RA. This integrated multi-omics investigation, supported by literature-based mechanistic inference, suggests ROMO1 as a stage-dependent biomarker candidate and potential immune regulator in RA.

Humans↗

PubMed2026

Promoter Methylation of HOXA5 and NDRG2 in Multiple Myeloma Patients with Renal Impairment.

Renal impairment (RI) is frequently caused by multiple myeloma (MM), which makes clinical care more difficult if renal function deteriorates or renal failure develops. Thus, in this investigation, we looked at the relationship between HOXA5&NDRG2 promoter methylation in MM patients and evaluated their prognostic potential in predicting RI risk in MM patients. This study included 60 control volunteers and 120 MM patients. The promoter methylations of HOXA5&NDRG2 were quantitatively evaluated by real-time PCR (qPCR) after the extraction of gDNA from whole blood and then treated with bisulfite. The promoter methylation percentages of HOXA5&NDRG2 were significantly increased in MM patients (77.16 ± 2.43&45.49 ± 2.16;p < 0.05) when compared to controls (4.47 ± 0.61&3.33 ± 0.31,respectively), in stage II&III patients when compared to stage I patients and in patients with age ≥ 60 years when compared to patients with age < 60 years. While only the methylation percentage of NDRG2 promoter was significantly increased in MM patients with RI (53.61 ± 3.21,p < 0.05) when compared to MM patients without RI (37.37 ± 2.04). Results obtained from ROC curve revealed that both HOXA5&NDRG2 promoter methylation were good diagnostic tools for MM. The NDRG2 promoter methylation was good prognostic biomarker could predict renal while HOXA5 promoter in the prediction of MM staging. The Kaplan-Meier survival test showed that patients with higher HOXA5&NDRG2 promoter methylation had a shorter OS and a worse prognosis. Only NDRG2 promoter hypermethylation was significantly associated with the risk of RI development in MM patients. HOXA5&NDRG2 promoter hypermethylation may have roles in the molecular etiology of MM and could be used as a treatment regimen.

Humans↗

PubMed2026

Plasma proteomic profiling characterizes candidate biomarkers of perimesencephalic non-aneurysmal subarachnoid hemorrhage.

OBJECT: This study aims to explore the plasma proteomic profiles of angiographically confirmed pmSAH and aSAH, and to identify candidate protein biomarkers for discriminating these subtypes on a biological level. METHODS: The differentially abundant proteins of plasma samples from patients with pmSAH (n = 30) and aSAH (n = 30) were analyzed by data-independent acquisition proteomics, and candidate biomarkers were screened. RESULTS: 291 candidate biomarkers were obtained that could be used to distinguish pmSAH patients from aSAH patients, among which 76 were upregulated and 215 were downregulated in pmSAH. Subsequently, the 10 candidate biomarkers were validated by enzyme-linked immunosorbent assay in a validation cohort of 72 subjects. ORM1, ORM2, HP and NMNAT1 were specifically down-regulated in the pmSAH group, while ANP32A was specifically up-regulated in the pmSAH group. FGL2 was specifically up-regulated in the aSAH group. The combined model of ORM2, HP and ANP32A had the best discriminative power (AUC = 0.880). CONCLUSIONS: This study identified ORM2, HP, and ANP32A as candidate biomarkers reflecting biological differences between pmSAH and aSAH. SIGNIFICANCE: Although some proteomic studies have analyzed aneurysmal subarachnoid hemorrhage, to date, there have been no reports on the circulating proteomic analysis of pmSAH. Comparative analysis of the circulating proteomic differences between pmSAH and aSAH may not only help understand the causes of pmSAH, but also contribute to a deeper understanding of mechanisms showing how pmSAH differs from the formation and rupture mechanisms of intracranial aneurysms.

Humans↗

PubMed2026

Making waves: toward systems-level interpretation of hormonal and endogenous biomarkers in wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) has proven invaluable for population health monitoring, most notably during the COVID-19 pandemic. Yet current WBE largely relies on exogenous markers such as drugs, pathogens, and their metabolites, limiting surveillance to what communities are exposed to. We argue for expanding WBE towards endogenous biomarkers, particularly hormones, which provide insights into physiological stress, metabolic function, and endocrine activity. Hormone-based WBE offers new opportunities to capture population-level biological responses to societal and environmental stressors, disasters, and chronic disease burdens at the community scale. This perspective outlines a systems-level framework for integrating hormonal signals in wastewater with clinical data, behavioral indicators, environmental factors, and digital markers to support more robust and context-aware public health surveillance. We highlight key technical considerations, interpretive challenges, and opportunities for translational pilot studies. By moving beyond exposure tracking toward more integrated interpretation of biological responses, hormone-informed WBE may contribute to more resilient, inclusive, and actionable public health infrastructure.

Humans↗

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.

Humans↗

PubMed2026

Decoding tumor immune microenvironment heterogeneity by single-cell and spatial multi-omics: From immunotherapy resistance to translational biomarkers.

Immune checkpoint blockade has transformed cancer therapy, yet primary and acquired resistance remain major clinical challenges. Increasing evidence indicates that immunotherapy resistance cannot be fully explained by tumor-intrinsic alterations or conventional biomarkers such as PD-L1 expression, tumor mutational burden, or microsatellite instability. Instead, therapeutic response is shaped by the tumor immune microenvironment (TIME) as a heterogeneous, spatially organized, and dynamically evolving ecosystem. Single-cell omics has revealed diverse immune and stromal cell states, including progenitor and terminally exhausted T cells, suppressive myeloid programs, B-cell/TLS-associated immune-reactive states, and CAF-mediated exclusion phenotypes. Spatial transcriptomics, spatial proteomics, and imaging-based approaches further demonstrate that these cell states assemble into distinct immune niches, including immune-inflamed, T-cell-excluded, myeloid-suppressive, metabolic/hypoxic, and TLS-associated niches. These spatial ecosystems determine whether antitumor immune cells can access malignant cells, receive antigen-presenting support, or become restrained by stromal, vascular, metabolic, and myeloid barriers. In this review, we summarize how single-cell and spatial multi-omics redefine TIME heterogeneity in immunotherapy resistance, highlight ligand-receptor communication networks linking cell states to spatial immune dysfunction, and discuss emerging translational biomarkers for patient stratification. We further propose that future immunotherapy biomarkers should evolve from static single-marker assays toward longitudinal, spatially resolved, and interpretable multi-omics models that guide precision combination immunotherapy.

Humans↗

PubMed2026

Multi-omics panorama of glaucoma: Pathogenesis, biomarkers, and novel therapeutic strategies.

Glaucoma is a group of irreversible, blinding eye diseases characterized by progressive loss of retinal ganglion cells, leading to gradual visual field defects that severely impact patients' quality of life. Its complex pathophysiological mechanisms remain incompletely understood, limiting the development of early diagnostic and effective therapeutic strategies. Advances in omics technologies have provided new insights into elucidating the pathophysiology of glaucoma. We summarize specific alterations in genomics, transcriptomics, proteomics, metabolomics, epigenomics, and microbiomics associated with glaucoma. We emphasize the systematic analysis of disease mechanisms, identification of clinically applicable biomarkers, and discovery of novel therapeutic targets through the integration of these data. This approach paves new pathways for glaucoma subtype diagnosis and personalized treatment, while also outlining future research directions and challenges.

Humans↗

PubMed2026

From host response to genomic targets: electrochemical biosensing of tuberculosis biomarkers.

Tuberculosis (TB) remains one of the leading causes of death from a single infectious agent worldwide, with timely diagnosis continuing to be a major challenge, particularly in resource-limited settings. Conventional TB diagnostic methods are limited by low sensitivity, long turnaround times, and an inability to reliably differentiate latent from active disease. Biomarker-based diagnostic strategies have therefore gained increasing attention as they offer the potential to improve early detection, disease differentiation, and treatment monitoring. Herein, we examine electrochemical biosensing strategies for TB diagnostics using a biomarker-class-driven framework, covering host-response biomarkers (IFN-γ and TNF-α), pathogen-derived antigens (ESAT6, CFP10, CFP10-ESAT6, MPT64, Ag85, HspX and LpqH), cell-wall signatures and whole-cell markers (LAM and whole cell Mtb), and genomic markers (Mtb DNA and IS6110). Through structured comparison of recognition elements, biointerface designs, signal amplification strategies, electrochemical techniques, matrices, and validation levels, this review identifies the most promising technical approaches for different TB biomarker classes. It further highlights key translational bottlenecks, including limited clinical validation, buffer-based testing, complex multistep amplification, redox-probe dependence, matrix fouling, and insufficient evidence of manufacturability. This review therefore provides practical guidance for developing electrochemical TB biosensors that are analytically sensitive, clinically relevant, and suitable for decentralized diagnostic applications.

Biosensing Techniques↗