Frontiers in Molecular Biosciences最新文献

{"title":"Single-cell transcriptomic analysis identifies vascular smooth muscle cell transcriptional programs associated with human carotid plaque remodeling.","authors":"Yi-Jie Lu, Xue-Guang Lin, Ting Wang, Fan-Xuan Huang, Ying Deng, Shuai Jiang, Jing Dong Tang, Bo Yu","doi":"10.3389/fmolb.2026.1950061","DOIUrl":"https://doi.org/10.3389/fmolb.2026.1950061","url":null,"abstract":"<p><strong>Background: </strong>Vascular smooth muscle cells (VSMCs) contribute to plaque structure and exhibit diverse transcriptional programs in human atherosclerosis. Although human plaque single-cell studies have established substantial VSMC heterogeneity, an important unresolved question is whether discovery-defined programs remain recognizable across independent patients and sequencing platforms without forced integration, and whether those programs retain associations with plaque instability. We therefore focused on program-level reproducibility, inferred regulatory activity, continuous expression organization, and rupture-associated variation.</p><p><strong>Methods: </strong>We used three public human carotid plaque transcriptomic datasets in nonredundant analytical roles rather than merging all single-cell cohorts into a single atlas. GSE253903, a 10x Genomics single-cell cohort, was used for broad plaque mapping and focused VSMC characterization. SCENIC and transcriptional-continuum analyses were restricted to finalized VSMCs. Discovery signatures and assignment rules were frozen before independent assessment in the Smart-seq2 dataset GSE260657, with uncertain cells permitted to remain unassigned. GSE120521 supported exploratory paired comparison between relatively stable and visibly ruptured plaque regions.</p><p><strong>Results: </strong>Quality control retained 46,209 cells from 12 patients in GSE253903, including 3,784 primary VSMCs after removal of immune-like contaminants. Five descriptive VSMC programs were identified: canonical contractile, extracellular-matrix-associated/fibromyocyte-like, DLX-osteomodulated, stress-responsive, and interferon-associated. VSMC-restricted SCENIC analysis showed higher inferred <i>ATF3, JUND,</i> and <i>CREB5</i> regulon activity in the stress-responsive program and higher <i>TEAD1, KLF2,</i> and <i>XBP1</i> activity in the DLX-osteomodulated program. Pseudotime analysis described two transcriptional continua with shared canonical contractile, stress-responsive, and extracellular-matrix-associated organization. In GSE260657, 842 of 1,483 VSMC-enriched cells were confidently projected, while 641 remained unassigned. Six of seven symptomatic-versus-asymptomatic program effects had concordant directions across the single-cell datasets, although no GSE260657 module reached a false-discovery rate below 0.05. In four paired plaques, ruptured regions showed lower contractile scores and higher osteogenic, foam-cell-like, and proliferation scores. qPCR analysis of an independent paired plaque cohort provided orthogonal tissue-level RNA support for selected remodeling-associated gene patterns.</p><p><strong>Conclusion: </strong>Human carotid plaque VSMCs display heterogeneous transcriptional programs with program-associated inferred regulon activity and continuous expression organization. An uncertainty-aware, cross-platform assessment supported partial conservation of these programs and linked selected re","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"13 ","pages":"1950061"},"PeriodicalIF":4.4,"publicationDate":"2026-09-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13649385/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149165250","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Strengthening the interpretation of longitudinal EQA data through the sporadic inclusion of native human sera in general clinical chemistry.","authors":"Laura Vierbaum, Patricia Kaiser, Ingo Schellenberg, Folker Wenzel, Mario Thevis, Manfred Falck","doi":"10.3389/fmolb.2026.1869542","DOIUrl":"10.3389/fmolb.2026.1869542","url":null,"abstract":"<p><strong>Introduction: </strong>Comparative external quality assessment (EQA) surveys using native human sera alongside routinely distributed processed EQA materials (EQAMs) provide valuable information on measurement procedure (MP) trueness and the status of standardization. They also allow EQA providers to retrospectively identify critical or less critical analyte/MP pairings regarding the commutability of processed EQAMs. This study evaluates the benefit of interpreting such commutability-related indications in the context of longitudinal EQA data, for cholesterol, urea, creatinine (enzymatic), creatinine (kinetic), γ-glutamyl transferase (GGT), and sodium.</p><p><strong>Methods: </strong>In the comparative EQA, nearly 400 results were obtained for each of four native human sera and two processed EQAMs. Mixed-effects models were used to estimate analyte/MP-specific mean natural logarithm (ln) bias to reference measurement values for native and processed EQAMs, mean differences in ln bias between sample types, and based on longitudinal EQA data between 08/2023 and 10/2024, MP/batch-specific mean ln bias.</p><p><strong>Results: </strong>In the comparative EQA study, MP-specific mean differences in bias between sample types were generally small, with most meeting the analyte-specific commutability criteria. An exception among native EQAMs was observed for GGT, showing differences in bias of more than -7% and pronounced variabilities in MP-specific mean bias (standard deviation (SD) in percentage points: 3.9-10.2), likely associated with low enzyme activities. In contrast, most analyte/MP-specific bias in native EQAMs was highly consistent (SD: enzymatic assays 0.3-3.1, creatinine (kinetic) 1.7-6.6, sodium 0.21-0.42). Longitudinal data showed higher variabilities for processed EQAMs for multiple analyte/MP pairings (SD: enzymatic assays 1.0-10.0, creatinine (kinetic) 2.1-6.5, sodium 0.38-1.00), indicating higher MP susceptibilities to synthetic EQAM matrices. Substantial shifts in bias ranges between sample types were observed for cholesterol and urea across most MPs, and for individual MPs for the remaining analytes.</p><p><strong>Conclusion: </strong>In some processed EQAM batches, bias was markedly greater than observed for the batches in the comparative EQA survey, indicating that the limited number of batches in such studies do not allow generalized interpretation on commutability, and requires batch-specific assessment. However, when combined with longitudinal monitoring of MP-specific bias, a comprehensive picture emerges of MP trueness, MP susceptibility to interferences and commutability of EQAMs, thereby supporting MP and control material manufacturers in quality improvement.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"13 ","pages":"1869542"},"PeriodicalIF":4.4,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13645575/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149135373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Development and evaluation of a machine learning based risk prediction model for osteoporosis.","authors":"Lin Zhou, Qi Zhang, Haijing Wei, Jie Liu, Yongchang Yang","doi":"10.3389/fmolb.2026.1939155","DOIUrl":"10.3389/fmolb.2026.1939155","url":null,"abstract":"<p><strong>Objective: </strong>Osteoporosis is a systemic bone disease that can lead to decreased bone strength and increased susceptibility to fractures. This study aims to evaluate the level of cytokines and other common blood biomarkers, and establish a machine learning-based risk prediction model for osteoporosis patients.</p><p><strong>Methods: </strong>The clinical data of patients with osteoporosis who were hospitalized in the Seventh Medical Center of the Chinese People's Liberation Army General Hospital from January 2023 to September 2024 were retrospectively collected. 16 cytokines and other potential predictive variables were analyzed to determine the independent risk factors. Eleven machine learning models were established, and the performance of the models was evaluated using the ROC curve, the PR curve and the confusion matrix, and the optimal model was selected. SHAP to provide insights into the model's predictions and construct a visual representation of the prediction model.</p><p><strong>Results: </strong>A total of 187 patients were included, and 16 characteristics such as IL-8 were identified as risk characteristics. By comparing 11 different models, it was found that the Gradient Boost was the best model, with an AUC value of 0.91, an accuracy rate of 0.81, an F1 score of 0.80, and a relatively balanced specificity and sensitivity. And the SHAP value was used to reveal the direction and strength of each feature in predicting osteoporosis.</p><p><strong>Conclusion: </strong>This study successfully developed a risk prediction model based on 16 common variables, including IL-8, providing critical evidence for the early identification and prevention of osteoporosis patients, with potential clinical significance.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"13 ","pages":"1939155"},"PeriodicalIF":4.4,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13645573/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149135757","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preoperative CT deep learning of tumor and visceral adipose tissue combined with postoperative pathology predicts colorectal cancer recurrence: a multicenter study.","authors":"Pengfei Wei, Linhua Zhong, Yongming Tan, Jinhong Zhao, Yongjie Zhou","doi":"10.3389/fmolb.2026.1937172","DOIUrl":"10.3389/fmolb.2026.1937172","url":null,"abstract":"<p><strong>Introduction: </strong>To develop and externally validate a preoperative CT imaging model integrating primary tumour and visceral adipose tissue (VAT) features for predicting recurrence in colorectal cancer (CRC).</p><p><strong>Materials and methods: </strong>This retrospective multicentre study included 1,369 patients with CRC undergoing upfront curative-intent resection, comprising a training cohort (n = 705) and two external test cohorts (n = 425 and 239). A 3D convolutional neural network extracted tumour-centred volumetric features, while an attention-based multiple instance learning branch aggregated whole-abdominal VAT slices into patient-level representations. The two CT-derived scores constituted the preoperative imaging model. A clinicopathological component was combined with the imaging scores to construct the postoperative multimodal model; robustness to variable selection was evaluated using an all-candidate ridge-penalised Cox sensitivity model.</p><p><strong>Results: </strong>Both tumour and VAT DL scores remained independently associated with recurrence-free survival after multivariable adjustment. In external test cohorts 1 and 2, the preoperative Tumor + VAT imaging model achieved C-indices of 0.734 and 0.772, whereas the postoperative multimodal model achieved C-indices of 0.772 and 0.810 and 2-year time-dependent AUCs of 0.757 and 0.836, respectively. Training-derived tertile cut-offs from the postoperative model consistently stratified patients into low-, intermediate- and high-risk groups across all cohorts (all log-rank P < 0.001). In the two external cohorts, the clinicopathological-only model achieved C-indices of 0.709 and 0.715, compared with 0.772 and 0.810 for the postoperative multimodal model.</p><p><strong>Conclusion: </strong>The preoperative CT model non-invasively stratified recurrence risk using tumour and whole-abdominal VAT phenotypes, while postoperative clinicopathological features further improved prognostic performance.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"13 ","pages":"1937172"},"PeriodicalIF":4.4,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13646159/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149135409","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative multi-omics characterization of KLRB1/CD161 in diffuse large B-cell lymphoma: associations with immune context, subtype biology, and therapeutic response.","authors":"Erwei Li, Yingying Tang, Yuanyuan Wanyan, Yu Liang","doi":"10.3389/fmolb.2026.1903725","DOIUrl":"10.3389/fmolb.2026.1903725","url":null,"abstract":"<p><strong>Background: </strong>The tumor immune microenvironment (TME) of diffuse large B-cell lymphoma (DLBCL) displays pronounced heterogeneity, and existing immunotherapeutic approaches achieve only suboptimal outcomes for a considerable proportion of affected individuals. CD161-a C-type lectin receptor whose coding gene is KLRB1-has lately emerged as a modulator of T-cell activity in several malignancies; nonetheless, a thorough characterization of its function in DLBCL has not yet been undertaken.</p><p><strong>Methods: </strong>Transcriptomic analyses quantified KLRB1 mRNA, whereas flow cytometry and immunoblotting assessed its encoded surface protein, CD161. Transcriptomic, genomic, epigenomic (methylation), and exploratory single-cell RNA-sequencing datasets from DLBCL cohorts were integrated with <i>in vitro</i> functional assays to characterize clinical associations, immune context, and hypothesis-generating therapeutic relationships.</p><p><strong>Results: </strong>Pan-cancer analysis revealed predominantly inverse associations between KLRB1 mRNA and immunomodulatory features, whereas DLBCL bulk-tumor analyses showed positive correlations with MHC molecules, immune-cell infiltration estimates, CD8⁺ T-cell effector programs, and immune-checkpoint transcripts. KLRB1 mRNA was higher in ABC than in GCB DLBCL and was associated with vital status at last follow-up and clinical stage. Lower TIDE scores and pharmacogenomic modeling suggested exploratory, context-dependent relationships with immune-checkpoint blockade and drug response; however, the IMvigor210 urothelial carcinoma cohort showed no significant objective-response difference. Single-cell analyses from two biopsies were exploratory. In OCI-LY3 cells, CD161 manipulation altered MHC-I, phospho-mTOR, cytokine secretion, T-cell activation, and fixed-dose drug-induced apoptosis. These two-biopsy single-cell outputs were not treated as reproducible trajectories or validated intercellular signaling networks, and all functional findings remained specific to the OCI-LY3 model.</p><p><strong>Conclusion: </strong>The KLRB1 mRNA/CD161 protein axis is associated with an immune-inflamed DLBCL phenotype and ABC subtype biology. Its prognostic and treatment-predictive value remains hypothesis-generating and requires validation in multivariable survival models, DLBCL-specific immunotherapy cohorts, additional cell lines, and <i>in vivo</i> systems. Confirmation in a GCB cell line and formal dasatinib and doxorubicin dose-response experiments are specifically required.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"13 ","pages":"1903725"},"PeriodicalIF":4.4,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13645582/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149135362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI-driven multi-omics integration in breast cancer: clinical applications, immunotherapy prediction, and translational challenges.","authors":"Zi-Yao Wang, Na Liu, Min-Bin Chen","doi":"10.3389/fmolb.2026.1875788","DOIUrl":"10.3389/fmolb.2026.1875788","url":null,"abstract":"<p><p>Breast cancer remains a major global threat to women's health, and its marked molecular, spatial, and temporal heterogeneity continues to limit the accuracy of early diagnosis, risk stratification, and treatment-response prediction. Conventional single-dimensional diagnostic and therapeutic models are often insufficient to capture the dynamic complexity of the tumor microenvironment (TME). In this context, artificial intelligence (AI) provides powerful tools for high-dimensional feature extraction, multimodal data integration, and cross-scale modeling of heterogeneous biological and clinical information. AI-enabled approaches can link microscopic molecular alterations with macroscopic imaging and pathological phenotypes, while also characterizing complex cellular interactions within the TME. This review summarizes current applications of AI-driven multimodal and multi-omics integration in breast cancer, focusing on early detection, precision diagnosis, immunotherapy-response prediction, drug-sensitivity assessment, and prognostic evaluation. We also discuss key translational challenges, including data heterogeneity, batch effects, interpretability, privacy protection, regulatory considerations, and clinical workflow integration. Overall, AI-driven multi-omics strategies offer a promising framework for improving individualized treatment selection and real-time monitoring in breast cancer, although robust prospective validation and multidisciplinary implementation are still required before routine clinical adoption. Compared with previous modality-specific reviews, this article emphasizes cross-modal evidence appraisal, clinical-maturity stratification, data-quality constraints, foundation model opportunities, and regulatory requirements for translating AI-enabled multi-omics from exploratory research to clinically auditable decision support.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"13 ","pages":"1875788"},"PeriodicalIF":4.4,"publicationDate":"2026-09-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13647173/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149135814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrative oxidative stress-disulfidptosis analysis identifies <i>NPR3</i> and <i>ZNF366</i> as cell-type-associated candidate markers in clear cell renal cell carcinoma.","authors":"Ping Wang, Zhixuan Cai, Gaofeng Wu, Guangfeng Zhu","doi":"10.3389/fmolb.2026.1912537","DOIUrl":"10.3389/fmolb.2026.1912537","url":null,"abstract":"<p><p>Disulfidptosis is a regulated cell-death program that occurs in SLC7A11-high cells under glucose limitation, but its relationship with oxidative stress in clear cell renal cell carcinoma (ccRCC) remains unclear. We integrated 313 oxidative stress-related genes with 24 disulfidptosis-related genes in the original TCGA-KIRC analysis. Pearson screening (|r| ≥ 0.8 and nominal two-sided P < 0.05) identified 21 disulfidptosis-oxidative stress (DOS) genes, from which three reported DOS subtypes, 63 subtype-associated genes and a four-gene score comprising <i>ZNF366</i>, <i>EMCN</i>, <i>GRIK3</i> and <i>NPR3</i> were derived. In an updated GDC-derived TCGA-KIRC dataset, both k = 3 classifications showed method-dependent stability, with weaker stability for the available 58-of-63-gene solution. Outcome-blind centroid transfer assigned all 101 E-MTAB-1980 cases and reproduced several molecular and immune/stromal differences in GSE73731, although the hard clusters have not been independently validated for prognosis. In the atezolizumab-containing arms of IMmotion150, the within-cohort re-standardized four-gene score was lower in patients with clinical benefit and was associated with progression-free survival; the DOS21 module score was not associated with clinical benefit. The fixed four-gene score had modest internal discrimination (bootstrap optimism-corrected C-index, 0.697), and its transfer was sensitive to platform scaling and stage adjustment. Under the single 6-h glucose-deprivation condition, <i>NPR3</i> and <i>ZNF366</i> increased only in SLC7A11-high UMRC6 cells. Single-cell analyses in one VHL-related case and an independent 19-patient ccRCC cohort supported endothelial enrichment of <i>ZNF366</i> and showed that <i>NPR3</i> was not restricted to tumor cells. These findings identify <i>NPR3</i> and <i>ZNF366</i> as compartment-associated candidate markers but do not establish a functional role in disulfidptosis.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"13 ","pages":"1912537"},"PeriodicalIF":4.4,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13642137/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149126994","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The impact of zeaxanthin and lycopene on fatty acid beta-oxidation in isolated peroxisomes from frozen livers of obese rats.","authors":"Lina Baz, Mona Al-Thepyani","doi":"10.3389/fmolb.2026.1906904","DOIUrl":"10.3389/fmolb.2026.1906904","url":null,"abstract":"<p><p>Over the past decade, research has emphasized the role of organelle dysfunction in various diseases, particularly obesity and related metabolic disorders. Peroxisomes, essential for lipid metabolism and redox balance, have been associated with obesity-related complications. Although carotenoids such as zeaxanthin (Zi) and lycopene (Ly) are known for their antioxidant and anti-inflammatory properties, their effects on peroxisomal function in obesity remain unexamined. This study evaluated the effects of Zi and Ly supplementation on peroxisomal β-oxidation, oxidative stress, and inflammatory markers in rats fed a high-fat diet (HFD). Forty male Wistar rats were divided into four groups: normal diet, HFD, Zi (100 mg/kg), and Ly (25 mg/kg). After a 12-week HFD regimen, the rats received Zi and Ly for an additional 5 weeks. Peroxisome function was assessed by measuring the activity of marker enzymes such as catalase and acyl-CoA oxidase, along with evaluations of antioxidant enzyme activity, oxidative stress indicators, inflammatory biomarkers, and lipid profiles. Serum fatty acid content was analyzed using gas chromatography/mass spectrometry (GC/MS). Results showed that HFD intake resulted in significant weight gain and peroxisomal dysfunction, indicated by reduced enzyme activities and increased serum saturated fatty acids. In contrast, Zi and Ly treatments improved peroxisomal β-oxidation, altered fatty acid profiles, decreased oxidative stress and inflammation markers, and enhanced antioxidant enzyme activities. These findings suggest that Zi and Ly can restore peroxisomal function impaired by high-fat diets, highlighting peroxisomal homeostasis as a potential therapeutic target in obesity. Further research is recommended to elucidate the underlying molecular mechanisms.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"13 ","pages":"1906904"},"PeriodicalIF":4.4,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13642724/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149135487","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Plasma untargeted metabolomics reveals metabolic signatures associated with epilepsy and anti-seizure medication responsiveness.","authors":"Zijian Li, Zhen Liang, Juan Ren, Songyan Liu","doi":"10.3389/fmolb.2026.1885513","DOIUrl":"10.3389/fmolb.2026.1885513","url":null,"abstract":"<p><strong>Background: </strong>Epilepsy is a neurological disorder with heterogeneous anti-seizure medication responses and a lack of peripheral biomarkers for diagnosis and drug resistance assessment. This study aims to explore metabolic alterations and candidate metabolite panels associated with epilepsy and anti-seizure medication responsiveness.</p><p><strong>Methods: </strong>Untargeted metabolomic analysis was performed on plasma samples from 42 patients with epilepsy (PWE), including 20 patients with drug-resistant epilepsy (DRE) and 22 patients with drug-sensitive epilepsy (DSE), as well as 20 healthy controls (HCs). Multivariate and univariate statistical analyses, pathway analysis, machine-learning-based feature selection, and logistic regression modeling were conducted, with internal validation by bootstrap resampling. Transcriptomic data were analyzed and intersected with metabolomic findings at the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway level, followed by construction of a gene-metabolite-pathway network.</p><p><strong>Results: </strong>Between the PWE and HC groups, 3,329 significantly different features were identified. KEGG enrichment analysis showed that the differential metabolites were mainly enriched in the cyclic adenosine monophosphate signaling pathway, hypoxia-inducible factor-1 signaling pathway, and dopaminergic synapse pathway, and these three pathways were also enriched in the transcriptomic dataset. Three key candidate metabolites-palmitoylcarnitine, C18 (plasm)-18:1 PC, and 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine-effectively discriminated PWE from HCs. Between the DRE and DSE groups, 1,074 differential ion features were identified. Six key candidate metabolites-L-kynurenine, indolelactate, glycodeoxycholic acid, N-acetylcytidine, citric acid, and 5-hydroxyindoleacetate-showed exploratory discriminatory ability between the DRE and DSE groups.</p><p><strong>Conclusion: </strong>This study revealed plasma metabolic signatures associated with epilepsy and anti-seizure medication responsiveness. The identified candidate metabolites and pathways provide preliminary metabolic evidence that requires further validation in independent cohorts and mechanistic studies.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"13 ","pages":"1885513"},"PeriodicalIF":4.4,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13642817/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149126942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Integrated bioinformatics and single-cell transcriptomics identify mitochondrial dysfunction-driven biomarkers for preeclampsia diagnosis.","authors":"Lin Lin, Xiaowu Wang, Chengxiu Zhu, Kejun Ye, Dan Zhang, Ruohua Li, Mengjia Peng","doi":"10.3389/fmolb.2026.1922190","DOIUrl":"10.3389/fmolb.2026.1922190","url":null,"abstract":"<p><strong>Background: </strong>Preeclampsia is a complex pregnancy disorder characterized by hypertension and proteinuria that pose significant risks to maternal and fetal health. Current diagnostic and treatment methods are limited, necessitating the identification of effective biomarkers and therapeutic targets.</p><p><strong>Methods: </strong>This study utilized bioinformatics methods, including differential expression analysis, weighted gene co-expression network analysis, protein-protein interaction networks, and machine learning algorithms, to identify critical mitochondrial genes associated with preeclampsia. Enrichment analysis was performed using gene set enrichment analysis, gene set variation analysis, gene ontology, and the Kyoto Encyclopedia of Genes and Genomes. Receiver operating characteristic analysis and SHapley Additive exPlanations analysis were used to evaluate the diagnostic performance of key genes and diagnostic models. Single-cell analysis provided insights into cellular heterogeneity and interactions. The identified key genes were validated via RT-qPCR.</p><p><strong>Results: </strong>Six mitochondrial key genes (<i>SOD1</i>, <i>ACSF2</i>, <i>ABAT</i>, <i>ACSS1</i>, <i>ALDH4A1</i>, <i>PDHA1</i>) and diagnostic models were identified, demonstrating robust diagnostic accuracy. Functional enrichment implicated these genes in oxidative phosphorylation, TCA cycle, and fatty acid metabolism. Single-cell analysis revealed trophoblast subpopulations as key sites of mitochondrial dysregulation. RT-qPCR confirmed significant downregulation of <i>ABAT</i>, <i>PDHA1</i>, and <i>SOD1</i> in PE placentas.</p><p><strong>Conclusion: </strong>Genes and pathways related to preeclampsia identified based on bioinformatic analyses may have diagnostic and therapeutic utility. Future research should confirm their clinical potential in larger groups of individuals.</p>","PeriodicalId":12465,"journal":{"name":"Frontiers in Molecular Biosciences","volume":"13 ","pages":"1922190"},"PeriodicalIF":4.4,"publicationDate":"2026-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13642145/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149126986","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}