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PubMed2026

Revealing potential biomarkers and metabolic mechanisms of ovarian aging in hens during late laying period based on machine learning and metabolomics.

Ovarian function decline during the late laying period represents a major bottleneck for the economic efficiency of the global poultry industry. However, the underlying metabolic mechanisms and reliable early-warning biomarkers for ovarian aging remain poorly understood. In this study, we performed the first untargeted LC-MS/MS metabolomics analysis of ovarian tissues from Taihe silky fowls at peak laying (30 weeks) and late laying (50 weeks) stages, and employed an ensemble machine learning strategy integrating LASSO, random forest, and support vector machine (SVM) algorithms to identify high-confidence core biomarkers of ovarian aging. Gene expression analysis was further conducted to validate the potential molecular mechanisms. Our results showed that the metabolic profiles of ovarian tissues differed significantly between the two groups. A total of 6 core biomarkers were identified, 4 of which were long-chain acylcarnitines. Mechanistic analysis revealed that downregulation of key genes in the carnitine shuttle system led to impaired mitochondrial fatty acid β-oxidation, which in turn triggered excessive oxidative stress and compromised ovarian endocrine function. In conclusion, this study identifies long-chain acylcarnitines as potential metabolic biomarkers for ovarian aging in Taihe silky fowls. These findings provide novel insights into the metabolic basis of poultry ovarian aging and lay a theoretical foundation for the precise regulation of reproductive performance in indigenous poultry breeds.

Animals↗

PubMed2026

A genome-wide coverage-based pipeline for the identification of host-derived candidate DNA biomarkers from cell-free blood.

We have created a new data-analysis pipeline for the discovery of host-specific candidate DNA biomarkers derived from sequencing data of cell-free blood. Unlike approaches that rely on specific molecular or genetic signatures, our method leverages the coverage distribution of cell-free DNA sequences mapped to a reference genome, applying statistical analyses to identify informative short genomic regions for biomarker discovery. The pipeline is applicable to diverse diseases and can be used to analyze cell-free DNA sequences from plasma or serum to identify candidate biomarkers that are characteristic of disease states in mammals. Core functionalities were developed in Java and integrated with open-source software tools for the preprocessing of raw sequencing data, complemented by Python scripts for the machine-learning analysis and statistical validation. The pipeline is designed for HPC use and users can access the pipeline through a Galaxy workflow, which offers a user-friendly web interface for input selection prior to execution and analysis progress monitoring. Performance tests, carried out using duplicate sets of COVID-19 samples and controls, showed linear scalability of execution time with an increasing dataset size, as well as a substantial reduction in execution time through parallelized computation, whereby each HPC node is used to process the data of one chromosome. Further statistical tests confirmed the quality of the pipeline's results by showing that the set of identified candidate biomarkers remained stable across varying dataset sizes.

Biomarkers↗

PubMed2026

Machine learning-ready genomic biomarkers: ATF3 polymorphisms predict postoperative analgesic demand through AI-compatible phenotyping.

PURPOSE: To determine whether ATF3 polymorphisms can serve as genetic biomarkers for machine learning-based precision analgesia by establishing a genotype-phenotype association suitable for predictive modeling of postoperative opioid requirements. METHODS: In a prospective cohort of 167 adults undergoing abdominal surgery, ATF3 SNPs rs3122721 and rs3125293 were genotyped. A structured dataset architecture was developed to represent genetic profiles as input features for supervised learning models, enabling translational analysis of genotype‑dependent opioid consumption over 72 h. RESULTS: Patients with homozygous genotypes of the ATF3 SNPs had significantly higher opioid requirements than non‑carriers, despite reporting similar subjective pain scores. This consistent genotype‑dependent pattern provided a clinically relevant phenotype suitable for integration into predictive algorithms. CONCLUSION: ATF3 genotyping offers a promising biomarker for computationally informed precision analgesia. By linking genomic variability to clinically meaningful outcomes within a structured clinical and genomic framework, this approach supports the future development of risk-stratified clinical decision-support systems to optimize postoperative pain management.Trial registration ChiCTR1900021991, registered 30 April 2019. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13755-026-00480-9.

ATF3↗

PubMed2026

Effects of Acute Low- and Moderate-Dose Alcohol on Chronic Disease-Related Biomarkers in Healthy Light and Heavy Drinkers.

BACKGROUND: Alcohol consumption is a major contributor to global chronic disease, with growing evidence indicating health risks even at low levels of intake. However, mechanistic understanding of these risks relies heavily on preclinical models and observational data, leaving a critical gap in controlled experimental evidence regarding how alcohol perturbs human biological systems in vivo. METHODS: The present study utilized plasma samples from a randomized, placebo-controlled trial to evaluate the effects of low-dose (0.35 g/kg) and moderate-dose (0.60 g/kg) alcohol on disease-relevant biomarkers in 32 healthy adults (mean age = 25.0 ± 3.8 years; 21 female/11 male), characterized by light (n = 15) or heavy (n = 17) drinking. This design enabled evaluation of effects across dose, timescale, and drinking history, as well as assessment of their interactions. Plasma was collected at prebeverage baseline and hourly for 4 h afterward. Immunoassays quantified 10 disease-related biomarkers: adiponectin, angiogenin, D-dimer, high-sensitivity C-reactive protein (hsCRP), Intercellular Adhesion Molecule-1 (ICAM-1), Lipocalin-2 (LCN2), Matrix Metalloproteinase-7 (MMP-7), Matrix Metalloproteinase-9 (MMP-9), soluble Receptor for Advanced Glycation End-products (sRAGE), and Triggering Receptor Expressed on Myeloid cells 2 (TREM2). RESULTS: Main effects of group indicated that even in this young healthy sample, heavy drinking status was associated with higher levels of adiponectin, angiogenin, ICAM-1, LCN2, and sRAGE, a profile suggesting altered vascular and metabolic activity. Acute alcohol administration induced changes in sRAGE and hsCRP. Specifically, moderate-dose alcohol triggered an increase in the immunoglobulin sRAGE, which may reflect an acute compensatory response to inflammation and/or oxidative stress. Compared to placebo, hsCRP was lower in the low-dose alcohol condition; however, this finding should be interpreted in light of CRP biology. MMP-7, MMP-9, and LCN2 showed time-dependent fluctuations that were independent of experimental condition, highlighting the critical importance of placebo-controlled designs to account for diurnal/postprandial variation in immune biomarkers. CONCLUSION: Findings provide translational evidence that alcohol is associated with multisystem biomarker changes relevant to chronic disease and that alcohol-related biomarker perturbations vary by dose and chronicity.

Humans↗

PubMed2026

Urinary Small Extracellular Vesicle DNA as a Biomarker for the Non-Invasive Diagnosis of Bladder Cancer.

Existing diagnostic technologies for bladder cancer (BC) suffer from low sensitivity, low specificity, or a lack of validation. Therefore, validated, non-invasive diagnostic biomarkers with high sensitivity and specificity for early detection of BC are needed to complement and improve upon the limitations of existing diagnostic methods. We used low-pass whole genome sequencing (LP-WGS) technology to detect copy number variations (CNVs) in small extracellular vesicle (sEV) DNA isolated from urine samples of patients. Based on these results, we constructed and validated a diagnostic model to differentiate between benign and malignant bladder lesions. We conducted a receiver operating characteristic analysis and calculated the area under the curve (AUC) to evaluate the performance of the diagnostic model. The urine sEV-DNA LP-WGS data revealed CNV differences between benign and malignant samples. The diagnostic model achieved an AUC of 0.953, a sensitivity of 86.7%, and a specificity of 100% in the training cohort and an AUC of 0.985, a sensitivity of 90%, and a specificity of 100% in the validation cohort. Even at the lowest coverage depth of 0.01X, the performance of the diagnostic model remained relatively robust. Notably, the performance of this diagnostic model surpassed that of the biomarker neuron-specific enolase (sensitivity: 85.7% vs. 64.3%; specificity: 100% vs. 87.5%) and urinary cytology (sensitivity: 100% vs. 66.7%; specificity: 100% vs. 94.1%). Our study demonstrates that urine sEV-DNA exhibits high discriminatory power in distinguishing between benign and malignant bladder lesions, making it a promising tool for auxiliary diagnosis of BC.

Humans↗

PubMed2026

Candidate biomarkers for early Giardia duodenalis infection revealed by time-resolved secretome proteomics.

Giardia duodenalis is a zoonotic protozoan parasite that causes giardiasis in humans and other mammals. Early diagnosis remains challenging because current diagnostic methods, including microscopy and enzyme-linked immunosorbent assays (ELISAs), primarily detect established infections. Consequently, a critical diagnostic gap exists during the early stage of infection within the first 2-48 h following exposure. To address this limitation, we characterized the proteins released by in vitro-cultured G. duodenalis trophozoites under serum-free conditions and evaluated their potential as early diagnostic biomarkers. Proteomic analysis of culture supernatants collected during early trophozoite incubation identified 31,773 peptides corresponding to 2504 quantifiable proteins. Temporal profiling showed distinct secretion patterns, including proteins that peaked during the early stage, progressively accumulated over time, or remained persistently abundant throughout the incubation period. Based on their secretion characteristics and predicted immunogenic properties, five candidate biomarkers were selected for further evaluation. Polyclonal antibodies raised against selected candidates successfully detected the corresponding proteins in serum-free culture supernatants, providing preliminary evidence for their potential utility as early-stage diagnostic targets. These findings identify stage-associated candidate proteins that may serve as a resource for future early giardiasis diagnostic development, provide a valuable resource for investigating host-parasite interactions, and establish a foundation for future diagnostic assay development. However, further validation in clinical and biological samples is required to confirm their diagnostic applicability. SIGNIFICANCE: Giardiasis, caused by Giardia duodenalis, is a major diarrheal disease worldwide. Although enzyme-linked immunosorbent assays (ELISAs) provide rapid detection, their diagnostic utility is limited by the lack of biomarkers capable of identifying infection during its earliest stages, creating a critical gap in the detection of active infection within 2-48 h following exposure. Using data-independent acquisition proteomics, this study provides a time-resolved characterization of proteins released by G. duodenalis trophozoites into serum-free culture supernatants. Our findings reveal temporal secretion dynamics of protein secretion and identify candidate biomarkers with potential utility for the development of early-stage diagnostic assays pending rigorous biological and clinical validation. In addition, this proteomic resource provides a foundation for investigating host-parasite interactions and may facilitate the development of future point-of-care diagnostic strategies.

Giardiasis↗

PubMed2026

Plasma proteome profiling identifies XPNPEP3 as a novel biomarker associated with metabolic dysfunction-associated steatotic liver disease in patients with type 2 diabetes mellitus.

OBJECTIVE: To identify plasma protein differences between type 2 diabetes mellitus (T2DM) patients with and without metabolic dysfunction-associated steatotic liver disease (MASLD), and to evaluate the diagnostic potential of X-prolyl aminopeptidase 3 (XPNPEP3) for identifying MASLD in T2DM patients. METHODS: Twenty T2DM inpatients were categorized into groups with and without MASLD and their plasma samples were analyzed using data-independent acquisition mass spectrometry, followed by bioinformatics analysis to identify differentially expressed proteins. The cohort was then expanded to 84 patients, and plasma XPNPEP3 levels were validated by enzyme-linked immunosorbent assay. Correlation between XPNPEP3 and clinical indicators were evaluated, and diagnostic performance was determined via receiver operating characteristic (ROC) analysis. Immunohistochemistry was employed to compare hepatic XPNPEP3 expression between the two groups. RESULTS: Proteomic analysis identified 176 differentially expressed proteins, with XPNPEP3 exhibiting the most significant down-regulation by fold change. In the validation cohort, plasma XPNPEP3 was significantly lower in T2DM+MASLD versus T2DM alone. XPNPEP3 levels were negatively correlated with diabetes duration, liver function markers, and triglyceride levels, and was identified as an independent factor inversely associated with MASLD in T2DM.ROC analysis demonstrated strong diagnostic performance for XPNPEP3, further enhanced when combined with BMI and diabetes duration.  Immunohistochemistry confirmed reduced hepatic XPNPEP3 expression in T2DM+MASLD patients. CONCLUSIONS: Lower plasma XPNPEP3 is independently associated with MASLD in T2DM patients and demonstrates strong diagnostic potential, positioning XPNPEP3 as a promising biomarker for diagnosing MASLD in T2DM patients and a novel target for non-invasive diagnostic tool development.

Humans↗

PubMed2026

Longitudinal Repeated Protein Measurements in a Multiethnic Cohort Identify Novel Diabetes Biomarkers That Reveal Unique Disease Pathways.

There is up to a fourfold increase in diabetes biomarkers identified with longitudinal repeated versus single time point proteomic measurements. The increase in biomarkers identified with longitudinal repeated measurements is supported by a similar proportion being nominated as causal for type 2 diabetes with Mendelian randomization. Proteins unique to the longitudinal repeated analyses highlighted biological pathways (e.g., posttranslational protein modification and cellular structure and cycle regulation) that were distinct from pathways enriched among the shared proteins (e.g., small-molecule metabolic and catabolic processes). Longitudinal protein measurements identify additional novel disease biomarkers and disparate biological pathways compared with single measurement analyses.

Journal Article↗

PubMed2026

Assay-dependent variability in peptide biomarker quantification: experimental evidence from renalase in chronic kidney disease.

BACKGROUND: Renalase is a promising biomarker for kidney disease, but published levels vary widely between studies. We hypothesised that variability in commercial enzyme-linked immunosorbent assays (ELISAs) kits and matrix effects (serum vs plasma) drive these inconsistencies. METHODS: Paired serum and plasma samples from 56 participants (28 chronic kidney disease (CKD) stages 2-5, 28 healthy controls) were tested using three commercial renalase ELISAs (BTLAB, Cloud-Clone, EIAab). We assessed intra-assay precision, inter-assay agreement (Spearman's rank correlation and Bland-Altman analysis on log10-transformed values), matrix effects, and associations with estimated glomerular filtration rate (eGFR). Diagnostic performance was evaluated by Receiver operating characteristic (ROC) analysis. RESULTS: Inter-assay renalase concentrations differed markedly (up to orders of magnitude), with weak inter-assay correlations (r ≤ 0.25). Bland-Altman analyses revealed large, systematic biases between kits. Only the BTLAB assay showed consistent serum/plasma agreement, a significant correlation with eGFR (ρ ≈ 0.32-0.42, p < 0.05), and moderate discriminatory performance for CKD in serum (AUC = 0.70) and plasma (AUC = 0.68). Cloud-Clone and EIAab produced divergent results and strong matrix-dependent biases. CONCLUSIONS: Observed variability among commercial ELISA platforms may compromise comparability between studies. Harmonisation, standardised reference materials, and cross-validation are necessary before renalase assays can be used reliably in clinical practice.

Humans↗

PubMed2026

Dealcoholized muscadine wine improved skin elasticity and oxidative stress biomarkers without affecting gut microbiome in women over 40 in a randomized controlled trial.

Muscadine wine has a unique polyphenol profile distinct from that of common wine, and limited research exists on its health benefits. This study aimed to investigate the effects of intake of dealcoholized muscadine wine (DMW) on skin health, oxidative stress, inflammatory biomarkers, and the gut microbiome. Seventeen healthy women were randomly assigned to consume 300 mL of DMW or a placebo daily for 6 weeks, separated by a 3-week washout period, in a randomized, single-blinded, crossover design. Skin health parameters were measured on the face and forearm. Oxidative stress and inflammatory biomarkers were assessed in plasma. Fecal bacterial DNA was sequenced using shotgun sequencing. DMW did not affect UVB-induced erythema compared to placebo. However, it significantly decreased transepidermal water loss and increased facial gross elasticity. Skin elasticity significantly improved on the forearm, whereas other skin parameters were not affected. DMW significantly decreased plasma levels of matrix metalloproteinase-9 and advanced glycation end products compared with placebo. However, the abundance, diversity, and functions of the gut microbiome were not affected. Polyphenol-rich DMW administered for six weeks improved certain skin health parameters and reduced oxidative and inflammatory stress, without affecting the gut microbiome in healthy women.

Humans↗

PubMed2026

Insights from changes in NDEV biomarkers of metabolism: effects of PPARγ and GLP1 receptor agonists on brain metabolism.

BACKGROUND: Insulin resistance (IR) is implicated in central nervous system disorders, including depression and Alzheimer's disease (AD). METHODS: We analyzed biological samples from two cohorts of clinical trial participants: (1) participants with unremitted depression after six months of treatment as usual who received pioglitazone (PPARγ agonist, N = 12) or placebo and (2) middle-aged participants at genetic risk for AD who received liraglutide (glucagon-like peptide 1 [GLP1] receptor agonist, N = 15) or placebo. These cohorts, which previously showed treatment-related improvements in peripheral IR, were used to assess the effects of pioglitazone and liraglutide on CNS insulin signaling using neuron-derived extracellular vesicles (NDEVs) as biomarkers. We utilized biological samples to measure biomarkers of IR in NDEVs. Eleven Akt-mTOR pathway proteins were measured before and after 12 weeks of treatment in both groups. RESULTS: Participants who received pioglitazone experienced broader changes, with significant increases in GSK3β (Ser9), mTOR (Ser2448), and RPS6 (Ser235/Ser236; all P ≤ .02) compared with placebo, and 77% of participants showed mTOR (Ser2448) response. Participants who received liraglutide demonstrated significantly increased NDEV-associated phosphorylated Akt (Ser473) and mTOR (Ser2448; P = .04 and P = .025, respectively) compared with placebo, with 40% and 30% of participants in the liraglutide group showing biomarker response in both Akt (Ser473) and mTOR (Ser2448), respectively. These effects appeared relatively independent from changes in fasting plasma insulin and glucose concentration at 120-minutes during the oral glucose tolerance test. DISCUSSION: Our findings demonstrate CNS-specific biomarker responses to both PPARγ agonists and GLP1 receptor agonists.

Humans↗

PubMed2026

Translating single-cell RNA sequencing into monocyte direct leukocyte subpopulation-transcript abundance assay ratio-based biomarkers (IFI27/PSAP or IFI27/CTSS) for clinical detection of viral infection.

A rapid method for triaging febrile patients by aetiology (e.g., viral or bacterial infection) using gene expression in peripheral blood (PB) is an intensively researched area. However, gene expression in blood represents a composite sum of gene expression of all the component cell types present in the sample. As a result, numerous genes are measured in most proposed signatures. Herein, we propose a simple ratio-based biomarker (RBB) called direct leukocyte subpopulation-transcript abundance assay (DIRECT LS-TA) that recapitulates gene expressions of a single cell type in PB (i.e., monocytes). Based on single-cell RNA sequencing (scRNAseq) data and bulk expression data, IFI27 and SIGLEC1 are found as interferon-stimulated genes (ISGs) predominantly expressed by monocytes. The DIRECT LS-TA method can use a simple ratio of two genes measured in PB as an RBB to represent the target gene expression in monocytes without the need for monocyte purification. Both scRNAseq and bulk RNA sequencing datasets were used to evaluate the correlation between ISG expression in monocytes and PB, with a particular focus on monocyte expression of IFI27. An iceberg plot of bulk transcriptome data was used to identify genes that were predominantly expressed by monocytes in PB. DIRECT LS-TA RBBs of the three genes (IFI27, IFI44L and SIGLEC1) were evaluated by group-wise comparison, receiver operating characteristic and meta-analysis. In addition, the conventional interferon (IFN) score was evaluated for comparison of diagnostic performance. In viral infection datasets, DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) was most intensely activated (p value by t test <1e-9) and had the best area under the curve (0.94) among the three potential monocyte ISGs analysed. DIRECT LS-TA SIGLEC1 was also another monocyte biomarker but showed a lower activation (p<9e-5). IFI27/PSAP showed better diagnostic performance than the conventional IFN score. On the other hand, IFI44L was not a predominant monocyte expression gene. DIRECT LS-TA of IFI27 (IFI27/PSAP or IFI27/CTSS) measured in PB was the best biomarker of viral infection and IFN activation among ISGs predominantly expressed by monocytes. It performed even better than the conventional IFN score which required quantification of eight genes. The results suggest that DIRECT LS-TA of IFI27 is a monocyte-informative biomarker which is easy to determine in PB without the need for cell sorting.

Humans↗

PubMed2026

Integrated salivary proteomic and metabolomic analyses reveal molecular characterization and novel biomarker panels of chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder characterized by chronic inflammation, oxidative stress, and metabolic dysregulation. The lack of convenient and easily-accessible non-invasive diagnostic approaches remains a major clinical challenge. This study applied an integrated saliva-based proteomic and untargeted metabolomic strategy to identify potential biomarkers for COPD classification. Comprehensive multi-omics analyses identified 225 differentially abundant proteins and 60 differentially abundant metabolites between patients with COPD and healthy controls, including 24 biologically relevant endogenous metabolites. Functional enrichment analyses revealed pronounced dysregulation of mitochondrial energy metabolism, redox homeostasis, lipid remodeling, and inflammatory-related pathways in COPD. By integrating salivary proteomic and metabolomic biomarkers, a stepwise feature selection combined with LASSO logistic regression was used to construct diagnostic models, yielding an optimized biomarker panel consisting of 11 proteins and 2 endogenous metabolites. This integrated model achieved excellent diagnostic performance, with an area under the ROC curve of 0.96. Collectively, these findings demonstrate that integrated salivary proteomic and metabolomic profiling provides a robust, non-invasive approach for COPD classification and offers a promising foundation for the development of biosensor-based diagnostic platforms and early disease detection. SIGNIFICANCE: Chronic obstructive pulmonary disease (COPD) remains a major global health burden. Current diagnostic approaches rely largely on spirometry and clinical assessment, which are limited in sensitivity for early-stage disease and unsuitable for large-scale screening. This study employs an integrated saliva-based proteomic and metabolomic strategy to identify non-invasive biomarkers for COPD classification. Our findings reveal coordinated dysregulation of mitochondrial energy metabolism, redox homeostasis, and lipid remodeling in COPD, highlighting the interconnected roles of metabolic reprogramming, oxidative stress, and inflammation in disease pathophysiology. Notably, a robust diagnostic panel comprising 11 proteins and 2 endogenous metabolites was established, achieving excellent classification performance (AUC of 0.96). To our knowledge, the integrated application of salivary proteomics and metabolomics for COPD diagnosis remains largely unexplored, underscoring the significance and translational potential of our findings.

Humans↗

PubMed2026

Multiparametric flow cytometry immune profiling of pulmonary and extra-pulmonary tuberculosis reveals distinct blood-based biomarker signatures.

This study investigated immune cell distributions, cell-specific immune markers, and selected biomarker targets in pulmonary tuberculosis (PTB) and extrapulmonary tuberculosis (EPTB) using multiparametric flow cytometry (MFC). Whole blood was collected from 45 individuals, including healthy controls (HC), EPTB, and PTB patients (n = 15/group). Peripheral blood leukocytes were analysed by MFC to characterize CD4+ and CD8+ T cells, natural killer (NK), invariant NKT (iNKT) and NKT cells, classical (CM), intermediate (IM) and non-classical monocytes (NCM), and activated monocytes (AM). Expression of GBP1, CALCOCO2, IFIT3, SNX10, ARG1, PD-1, and PD-L1 was assessed across these immune subsets. Increased frequencies of NK, NKT, and monocytes were observed in PTB and EPTB compared with HC, while CD4+, CD8+, iNKT, and AM were reduced. Monocyte-to-lymphocyte ratios were incrementally elevated in EPTB and PTB compared with HC. Despite variability of expression within groups, median biomarker fold-change expression changes were found between HC, EPTB and PTB groups; (i) (>2.0FC) for ARG1 in CD4, CD8, CM and AM, for CALCOCO2 in AM, GBP1 in CD8 and NCM, PD-1 in CD4, CD8, NK, IM and AM, PD-L1 in CD4, CD8, iNKT and NKT, NK, IM and AM and SNX10 in CD4, CD8, NCM, IM and AM (ii) (<2.0FC) in TB vs HC for CALCOCO2 in iNKT and NKT, IFIT3 in NCM, PD-1 in NK and NCM, PD-L1 in NCM, IM and AM and SNX10 in AM. Statistical significance was achieved for ARG1 (P = 0.017) in CD4 cells. Our findings highlight distinct immune cell and biomarker signatures in PTB and EPTB.

Humans↗

PubMed2026

Exploring sex differences in endocannabinoid system biomarkers and their relationship with antidepressant treatment outcomes in major depressive disorder: a CAN-BIND 1 secondary analysis.

BACKGROUND: Sex differences in major depressive disorder (MDD) are well documented, but it remains unclear whether sex-related variation in peripheral endocannabinoid system (ECS)-related biomarkers is detectable in MDD. OBJECTIVES: To examine baseline sex differences in ECS-related mRNA expression, DNA methylation, and single nucleotide polymorphisms (SNPs) in MDD, and associations between baseline ECS markers and antidepressant outcomes in sex-stratified analyses. METHODS: Among 178 participants with MDD from CAN-BIND-1, all received escitalopram for 8 weeks; non-responders then received adjunctive aripiprazole from Weeks 8-16.Response was defined as ≥ 50% reduction in MADRS score, and remission as MADRS ≤ 10. ANCOVAs examined baseline sex differences and sex-stratified biomarker associations with percent MADRS reduction at Weeks 8 and 16, as well as categorical response and remission outcomes. Covariates included site, baseline MADRS, age, and ethnicity. False discovery rate correction was applied. RESULTS: Baseline sex differences in methylation were observed for CACNA1H, GABRB2, MAGL, and GABRR2, though none survived correction. No baseline sex differences in mRNA expression or SNPs were detected after correction. Lower baseline DAGLA mRNA in males was associated with greater Week 8 symptom improvement (FDR corrected). This association was not observed in females. No associations with response or remission at Weeks 8 or 16 survived correction. IMPLICATIONS: Baseline sex differences in peripheral ECS-related markers were not detected in this sample. Larger studies are needed to verify whether ECS-related biomarkers, particularly DAGLA, contribute to antidepressant outcomes in a sex-specific manner.

Humans↗

PubMed2026

Comparative evaluation of oxidative stress biomarkers F2-isoprostanes and 8-OHdG in Parkinson's disease and Type 2 Diabetes Mellitus: a systematic review and meta-analysis of human studies.

BACKGROUND: Oxidative stress is central to type 2 diabetes mellitus (T2DM) and Parkinson's disease (PD). However, the utility of biomarkers for lipid peroxidation (F2-isoprostanes) and DNA damage (8-OHdG) in the comorbidity of PD and T2DM remains unclear. METHODS: We conducted a systematic review and meta-analysis of 54 unique studies of human subjects aged ≥ 50 years (n = 7,521: 3,522 with T2DM, 722 with PD, and 3,277 controls), measuring biomarkers in serum, plasma, or leukocytes. Mixed-effects models quantified standardized differences (Hedges' g) across subgroups. RESULTS: In T2DM, F2-isoprostanes (g = 1.60, 95% CI: 0.95-2.25) and 8-OHdG (g = 2.64, 95% CI: 2.13-3.14) were markedly elevated (p < 0.001). Stronger effects were observed in younger cohorts and serum/plasma samples, with complications like nephropathy exhibiting extreme oxidative stress (g = 5.24). In PD, 8-OHdG was moderately elevated (g = 0.78, 95% CI: 0.18-1.39; p = 0.011), particularly in randomized controlled trials and plasma samples, whereas F2-isoprostanes were not significantly elevated (g = 0.47, 95% CI: -0.43-1.38). High heterogeneity in T2DM (I2 > 90%) reflected methodological variability. CONCLUSION: Distinct profiles - both markers elevated in T2DM but only 8-OHdG in PD - underscore 8-OHdG's potential in PD-T2DM comorbidity. Future research should focus on standardized assays, multi-compartmental or multi-modal sampling, and longitudinal studies to clarify mechanisms and therapeutic targets.

Humans↗

PubMed2026

Effect of self-activating phthalocyanine gel on palatal donor site healing, inflammatory biomarkers, somatosensory and patient-centered outcomes: a randomized split-mouth clinical trial.

OBJECTIVES: To evaluate effects of self-activating phthalocyanine (PHY) gel on palatal donor site after subepithelial connective tissue graft (SCTG) harvesting, considering clinical outcomes, inflammatory biomarkers, patient-centered outcomes, and quantitative somatosensory changes. MATERIALS AND METHODS: Twenty participants were included in this randomized, crossover, split-mouth clinical trial. Donor sites received topical PHY gel (PHY group-PHYG) and placebo gel (control group-CG). Clinical parameters (residual wound area-RWA, wound epithelialization-WE, residual remodeling area-RRA and tissue thickness-TM) were assessed at baseline, 7, 14, 30, and 60 days. Patient-centered outcomes were recorded during 14 postoperative days and inflammatory biomarkers at 3 and 7 days postoperatively. Mechanical detection threshold (MDT) and mechanical pain threshold (MPT) were evaluated at baseline, 2 months, and 6 months. RESULTS: PHYG and CG exhibited similar clinical outcomes, but PHYG demonstrated superior performance in reducing RRA. Both groups presented positive postoperative progression of patient-centered outcomes. IL-10 levels showed a significant increase in PHYG, suggesting a more favorable anti-inflammatory response. MDT remained stable but, donor sites exhibited transient hypersensitivity (MPT) at 2 months. CONCLUSIONS: PHYG and CG protocols promoted satisfactory healing of palatal donor sites. Most clinical parameters and patient-centered outcomes were similar between groups. The PHYG presented reduced RRA and increased IL-10 levels. Donor sites exhibited transient hypersensitivity, which tended to resolve over time. CLINICAL RELEVANCE: Both postoperative protocols resulted in favorable healing of palatal donor sites following SCTG harvesting, with comparable clinical and patient-centered outcomes. Quantitative sensory testing indicates that hypersensitivity may occur during healing, but sensory function tends to recover progressively.

Humans↗

PubMed2026

Effects of an internet-based combined exercise and cognitive-behavioral therapy intervention on endocannabinoid system biomarkers and physical fitness in adults with mild-to-moderate depression: a SONRIE randomized controlled trial.

BACKGROUND: This SONRIE randomized controlled trial (NCT05849792) examined the effects of a 12-week combined physical exercise and internet-based cognitive-behavioral therapy (iCBT) intervention on endocannabinoid system (ES) biomarkers and physical fitness in adults with mild-to-moderate depression. METHODS: Eighty adults were randomly assigned 1:1 to an intervention (IG) or control (CG) group. Outcomes included nine ES biomarkers (2-arachidonoylglycerol, 2-AG; anandamide, AEA; seven analogues) and physical fitness, including cardiorespiratory fitness (CRF; 6-minute walking test) and muscular strength. Measurements were taken at baseline, post-intervention and 8-week follow-up. Primary analysis performed 2 × 3 repeated-measures ANOVA on completers; mixed-effects intention-to-treat model as sensitivity analysis. RESULTS: No significant time × group interaction was detected for any ES biomarker, including 2-AG (F(2,88) = 0.17, p = 0.844) and AEA (F(2,88) = 1.20, p = 0.306); both groups showed comparable within-group decreases in 2-AG, 2-LG and 2-OG. The intervention significantly improved CRF [between-group difference + 81.6 m at 12 weeks (F(2,78) = 7.88, p = 0.001)], exceeding the established minimal clinically important difference. None of the exploratory muscular fitness outcomes reached statistical significance; the arm curl test showed a borderline non-significant interaction (F(2,78) = 2.83, p = 0.065). CONCLUSION: A 12-week internet-based combined exercise and iCBT intervention significantly improved CRF in adults with mild-to-moderate depression. We did not find evidence of an intervention-specific effect on plasma ES biomarkers. These findings support the inclusion of internet-delivered exercise and psychological interventions in comprehensive treatment strategies for depression. TRIAL REGISTRATION: ClinicalTrials.gov NCT05849792 (registered 6 May 2023).

Humans↗