EBioMedicine最新文献

{"title":"Sodium glucose co-transporter 2 inhibitor prevents nephrolithiasis in non-diabetes by restoring impaired autophagic flux.","authors":"Chan-Jung Liu, Kaun-Ta Ho, Ho-Shiang Huang, Ze-Hong Lu, Miyuki Hsing-Chun Hsieh, Yu-Shan Chang, Wei-Hsuan Wang, Edward Chia-Cheng Lai, Yau-Sheng Tsai","doi":"10.1016/j.ebiom.2025.105668","DOIUrl":"https://doi.org/10.1016/j.ebiom.2025.105668","url":null,"abstract":"<p><strong>Background: </strong>Sodium-glucose cotransporter 2 inhibitors (SGLT2i) offer significant cardiovascular and kidney protection, independent of diabetes mellitus (DM). Recent cohort studies also suggest that SGLT2i can decrease the risk of nephrolithiasis in patients with DM. We aimed to use both animal models and human data to investigate whether SGLT2i can prevent nephrolithiasis and explored autophagy as a possible mechanism.</p><p><strong>Methods: </strong>We utilised SGLT2i, dapagliflozin (DAPA), on a glyoxylate (GOX)-induced calcium oxalate (CaOx) nephrolithiasis non-DM mouse model to test whether SGLT2i inhibited CaOx stone formation through modulating autophagy. Moreover, the clinical data retrieved from the National Health Insurance Research Database was analysed to confirm the findings from animal models.</p><p><strong>Findings: </strong>DAPA increased urine citrate, magnesium, pH, and decreased oxalate, effectively inhibiting CaOx stones in GOX mice. While autophagy was increased in the kidneys of GOX mice, as demonstrated by upregulated AMP-activated protein kinase (AMPK) and increased LC3B conversion; impaired autophagic flux was indicated by p62 accumulation. DAPA improved autophagy by downregulating mammalian target of rapamycin (mTOR), AMPK, and restoring autophagic flux. Rapamycin co-treatment preserved DAPA's nephrolithiasis inhibition, while hydroxychloroquine (HCQ) co-treatment abolished it. Finally, cohort data confirmed that SGLT2i reduced nephrolithiasis risk, but this protective effect disappeared if HCQ had been used within the prior year, suggesting that HCQ may compromise SGLT2i's protection against nephrolithiasis.</p><p><strong>Interpretation: </strong>SGLT2i, DAPA, inhibits nephrolithiasis by restoring impaired autophagic flux, and co-administration with autophagy inhibitor, HCQ, compromises SGLT2i's protection.</p><p><strong>Funding: </strong>This research was funded by grants from the National Science and Technology Council, Taiwan (110-2314-B-006-023, 110-2320-B-006-017MY3, and 112-2314-B-006-058) and the research grants (NCKUH-11202005, -11210020) from the National Cheng Kung University Hospital, Tainan, Taiwan.</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"114 ","pages":"105668"},"PeriodicalIF":9.7,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143728870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Prevalence, genetic variations and clinical outcomes of BRAF-V600 mutated advanced NSCLC in China: a retrospective real-world multi-centre study.","authors":"Bo Jia, Shuo Wang, Fengyuan Zhang, Ziping Wang, Tongtong An, Yuyan Wang, Minglei Zhuo, Jianjie Li, Xue Yang, Hanxiao Chen, Yujia Chi, Jingjing Wang, Xiaoyu Zhai, Reyizha Nuersulitan, Xi Wang, Yidi Tai, Yiliang Liu, Guohui Guan, Yanbin Zhao, Yudong Wang, Mengmeng Zhang, Xiuju Liu, Lin Lu, Honglin Li, Yanlei Wang, Fengqian Shen, Zhiliang Liu, Zhen Wang, Li Man, Jiwei Zhang, Minmin Shi, Yong Li, Caihong Jiang, Jingjing Yan, Xin Jin, Bo Jin, Jun Zhao","doi":"10.1016/j.ebiom.2025.105652","DOIUrl":"https://doi.org/10.1016/j.ebiom.2025.105652","url":null,"abstract":"<p><strong>Background: </strong>Due to the low incidence of BRAF mutations, limited data is available about their prevalence and clinical characteristics. Moreover, comparative real-world efficacy of dabrafenib combined with trametinib versus other treatment regimens, especially in Chinese patients, is also lacking.</p><p><strong>Methods: </strong>Patients who had BRAF genetic testing from the Lung Cancer Big Data Precise Treatment Collaboration Group (LANDSCAPE) database were included as Cohort I. The LANDSCAPE database comprises next-generation sequencing (NGS) data of 175,336 patients with lung cancer, originating from 6 Chinese genetic testing institutions. Cohort II included patients with unresectable locally advanced or metastatic NSCLC with a primary BRAF mutation from 19 centres in China from December 2015 to September 2022.</p><p><strong>Findings: </strong>In Cohort I, of patients with NSCLC, 6249 (3.56%, 95% CI: 3.48%-3.65%) were confirmed to harbour a BRAF mutation. BRAF V600E accounted for 24.6% (1539/6249) of all patients with BRAF-mutated NSCLC. In Cohort II, a total of 129 patients with locally advanced or metastatic BRAF-mutated NSCLC were included. Of 112 patients who received NGS testing, 80 (71.4%) patients had concomitant mutations. The median first-line real-world progression-free survival (rwPFS) of dabrafenib plus trametinib for patients with BRAF V600 mutations was 25.0 months (N = 37), which was numerically longer than first-line immunotherapy-based therapy (N = 12, 15.7 months), and chemotherapy (N = 17, 9.2 months).</p><p><strong>Interpretation: </strong>This study indicates that dabrafenib plus trametinib could be considered as the optimal treatment option for Chinese patients with NSCLC harbouring BRAF V600 mutations.</p><p><strong>Funding: </strong>National Natural Science Foundation of China (82072583); Beijing Municipal Administration of Hospitals Incubating Program (PX2020044); Beijing Hospitals Authority Youth Programme (QML20231113); Science Foundation of Peking University Cancer Hospital (2022-17); Peking University Cancer Hospital Inner Mongolia Hospital Public Hospital Reform and High-Quality Development Demonstration Project (Gastrointestinal Cancer + Thoracic Cancer) Research Fund (2024YNYB006).</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"114 ","pages":"105652"},"PeriodicalIF":9.7,"publicationDate":"2025-03-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143728851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A live attenuated SARS-CoV-2 vaccine constructed by dual inactivation of NSP16 and ORF3a.","authors":"Zi-Wei Ye, Chon Phin Ong, Hehe Cao, Kaiming Tang, Victor Sebastien Gray, Pak-Hin Hinson Cheung, Junjue Wang, Weixin Li, Hongzhuo Zhang, Peng Luo, Tao Ni, Chi Ping Chan, Ming Zhang, Yuntao Zhang, Guang Sheng Ling, Shuofeng Yuan, Dong-Yan Jin","doi":"10.1016/j.ebiom.2025.105662","DOIUrl":"https://doi.org/10.1016/j.ebiom.2025.105662","url":null,"abstract":"<p><strong>Background: </strong>Live attenuated vaccines against SARS-CoV-2 activate all phases of host immunity resembling a natural infection and they block viral transmission more efficiently than existing vaccines in human use. In our prior work, we characterised an attenuated SARS-CoV-2 variant, designated d16, which harbours a D130A mutation in the NSP16 protein, inactivating its 2'-O-methyltransferase function. The d16 variant has demonstrated an ability to induce both mucosal and sterilising immunity in animal models. However, further investigation is required to identify any additional modifications to d16 that could mitigate concerns regarding potential virulence reversion and the suboptimal regulation of the proinflammatory response.</p><p><strong>Methods: </strong>Mutations were introduced into molecular clone of SARS-CoV-2 and live attenuated virus was recovered from cultured cells. Virological, biochemical and immunological assays were performed in vitro and in two animal models to access the protective efficacies of the candidate vaccine strain.</p><p><strong>Findings: </strong>Here we describe evaluation of a derivative of d16. We further modified the d16 variant by inverting the open reading frame of the ORF3a accessory protein, resulting in the d16i3a strain. This modification is anticipated to enhance safety and reduce pathogenicity. d16i3a appeared to be further attenuated in hamsters and transgenic mice compared to d16. Intranasal vaccination with d16i3a stimulated humoural, cell-mediated and mucosal immune responses, conferring sterilising protection against SARS-CoV-2 Delta and Omicron variants in animals. A version of d16i3a expressing the XBB.1.16 spike protein further expanded the vaccine's protection spectrum against circulating variants. Notably, this version has demonstrated efficacy as a booster in hamsters, providing protection against Omicron subvariants and achieving inhibition of viral transmission.</p><p><strong>Interpretation: </strong>Our work established a platform for generating safe and effective live attenuated vaccines by dual inactivation of NSP16 and ORF3a of SARS-CoV-2.</p><p><strong>Funding: </strong>This work was supported by National Key Research and Development Program of China (2021YFC0866100, 2023YFC3041600, and 2023YFE0203400), Hong Kong Health and Medical Research Fund (COVID190114, CID-HKU1-9, and 23220712), Hong Kong Research Grants Council (C7142-20GF and T11-709/21-N), Hong Kong Innovation and Technology Commission grant (MHP/128/22), Guangzhou Laboratory (EKPG22-01) and Health@InnoHK (CVVT). Funding sources had no role in the writing of the manuscript or the decision to submit it for publication.</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"114 ","pages":"105662"},"PeriodicalIF":9.7,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143709437","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reporting of molecular test results from cell-free DNA analyses: expert consensus recommendations from the 2023 European Liquid Biopsy Society ctDNA Workshop.","authors":"Vincent D de Jager, Patrizio Giacomini, Jennifer A Fairley, Rodrigo A Toledo, Simon J Patton, Simon A Joosse, Claudia Koch, Zandra C Deans, Klaus Pantel, Ellen Heitzer, Ed Schuuring","doi":"10.1016/j.ebiom.2025.105636","DOIUrl":"https://doi.org/10.1016/j.ebiom.2025.105636","url":null,"abstract":"<p><p>The implementation of circulating tumor DNA (ctDNA) in the diagnostic routine may enable non-invasive predictive biomarker testing and treatment optimization in patients who lack a suitable tumor specimen, have failed previous molecular analysis or are clinically ineligible for (re-)biopsy procedures. As the interpretation and reporting are more complex for ctDNA than conventional tissue-based NGS, there is a need for specific guidelines. These will offer support for the reporting of ctDNA test results and will facilitate optimal communication of liquid biopsy findings between diagnostic laboratories and the medical oncology team. Aiming to generate guidelines based on real-world experiences and broad perspectives, we organized a European Liquid Biopsy Society (ELBS) ctDNA workshop, in which forty-four experts and key stakeholders from different molecular diagnostics laboratories, oncology and pathology departments, as well as an IVDR specialist, convened to address significant challenges associated with the reporting of liquid biopsy test results. This report delineates the resulting consensus recommendations for ctDNA test reporting with underlying rationale and background information.</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"114 ","pages":"105636"},"PeriodicalIF":9.7,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143691580","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep learning informed multimodal fusion of radiology and pathology to predict outcomes in HPV-associated oropharyngeal squamous cell carcinoma.","authors":"Bolin Song, Amaury Leroy, Kailin Yang, Tanmoy Dam, Xiangxue Wang, Himanshu Maurya, Tilak Pathak, Jonathan Lee, Sarah Stock, Xiao T Li, Pingfu Fu, Cheng Lu, Paula Toro, Deborah J Chute, Shlomo Koyfman, Nabil F Saba, Mihir R Patel, Anant Madabhushi","doi":"10.1016/j.ebiom.2025.105663","DOIUrl":"https://doi.org/10.1016/j.ebiom.2025.105663","url":null,"abstract":"<p><strong>Background: </strong>We aim to predict outcomes of human papillomavirus (HPV)-associated oropharyngeal squamous cell carcinoma (OPSCC), a subtype of head and neck cancer characterized with improved clinical outcome and better response to therapy. Pathology and radiology focused AI-based prognostic models have been independently developed for OPSCC, but their integration incorporating both primary tumour (PT) and metastatic cervical lymph node (LN) remains unexamined.</p><p><strong>Methods: </strong>We investigate the prognostic value of an AI approach termed the swintransformer-based multimodal and multi-region data fusion framework (SMuRF). SMuRF integrates features from CT corresponding to the PT and LN, as well as whole slide pathology images from the PT as a predictor of survival and tumour grade in HPV-associated OPSCC. SMuRF employs cross-modality and cross-region window based multi-head self-attention mechanisms to capture interactions between features across tumour habitats and image scales.</p><p><strong>Findings: </strong>Developed and tested on a cohort of 277 patients with OPSCC with matched radiology and pathology images, SMuRF demonstrated strong performance (C-index = 0.81 for DFS prediction and AUC = 0.75 for tumour grade classification) and emerged as an independent prognostic biomarker for DFS (hazard ratio [HR] = 17, 95% confidence interval [CI], 4.9-58, p < 0.0001) and tumour grade (odds ratio [OR] = 3.7, 95% CI, 1.4-10.5, p = 0.01) controlling for other clinical variables (i.e., T-, N-stage, age, smoking, sex and treatment modalities). Importantly, SMuRF outperformed unimodal models derived from radiology or pathology alone.</p><p><strong>Interpretation: </strong>Our findings underscore the potential of multimodal deep learning in accurately stratifying OPSCC risk, informing tailored treatment strategies and potentially refining existing treatment algorithms.</p><p><strong>Funding: </strong>The National Institutes of Health, the U.S. Department of Veterans Affairs and National Institute of Biomedical Imaging and Bioengineering.</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"114 ","pages":"105663"},"PeriodicalIF":9.7,"publicationDate":"2025-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143691579","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"AI in radiological imaging of soft-tissue and bone tumours: a systematic review evaluating against CLAIM and FUTURE-AI guidelines.","authors":"Douwe J Spaanderman, Matthew Marzetti, Xinyi Wan, Andrew F Scarsbrook, Philip Robinson, Edwin H G Oei, Jacob J Visser, Robert Hemke, Kirsten van Langevelde, David F Hanff, Geert J L H van Leenders, Cornelis Verhoef, Dirk J Grünhagen, Wiro J Niessen, Stefan Klein, Martijn P A Starmans","doi":"10.1016/j.ebiom.2025.105642","DOIUrl":"https://doi.org/10.1016/j.ebiom.2025.105642","url":null,"abstract":"<p><strong>Background: </strong>Soft-tissue and bone tumours (STBT) are rare, diagnostically challenging lesions with variable clinical behaviours and treatment approaches. This systematic review aims to provide an overview of Artificial Intelligence (AI) methods using radiological imaging for diagnosis and prognosis of these tumours, highlighting challenges in clinical translation, and evaluating study alignment with the Checklist for AI in Medical Imaging (CLAIM) and the FUTURE-AI international consensus guidelines for trustworthy and deployable AI to promote the clinical translation of AI methods.</p><p><strong>Methods: </strong>The systematic review identified literature from several bibliographic databases, covering papers published before 17/07/2024. Original research published in peer-reviewed journals, focused on radiology-based AI for diagnosis or prognosis of primary STBT was included. Exclusion criteria were animal, cadaveric, or laboratory studies, and non-English papers. Abstracts were screened by two of three independent reviewers to determine eligibility. Included papers were assessed against the two guidelines by one of three independent reviewers. The review protocol was registered with PROSPERO (CRD42023467970).</p><p><strong>Findings: </strong>The search identified 15,015 abstracts, from which 325 articles were included for evaluation. Most studies performed moderately on CLAIM, averaging a score of 28.9 ± 7.5 out of 53, but poorly on FUTURE-AI, averaging 5.1 ± 2.1 out of 30.</p><p><strong>Interpretation: </strong>Imaging-AI tools for STBT remain at the proof-of-concept stage, indicating significant room for improvement. Future efforts by AI developers should focus on design (e.g. defining unmet clinical need, intended clinical setting and how AI would be integrated in clinical workflow), development (e.g. building on previous work, training with data that reflect real-world usage, explainability), evaluation (e.g. ensuring biases are evaluated and addressed, evaluating AI against current best practices), and the awareness of data reproducibility and availability (making documented code and data publicly available). Following these recommendations could improve clinical translation of AI methods.</p><p><strong>Funding: </strong>Hanarth Fonds, ICAI Lab, NIHR, EuCanImage.</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"114 ","pages":"105642"},"PeriodicalIF":9.7,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143673608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Chromatin landscape in paired human visceral and subcutaneous adipose tissue and its impact on clinical variables in obesity.","authors":"Sadia Saeed, Lars la Cour Poulsen, Tina Visnovska, Anne Hoffmann, Adhideb Ghosh, Christian Wolfrum, Torunn Rønningen, Mai Britt Dahl, Junbai Wang, Akin Cayir, Tom Mala, Jon A Kristinsson, Marius Svanevik, Jøran Hjelmesæth, Jens Kristoffer Hertel, Matthias Blüher, Tone Gretland Valderhaug, Yvonne Böttcher","doi":"10.1016/j.ebiom.2025.105653","DOIUrl":"https://doi.org/10.1016/j.ebiom.2025.105653","url":null,"abstract":"<p><strong>Background: </strong>Obesity is a global health challenge and adipose tissue exhibits distinct depot-specific characteristics impacting differentially on the risk of metabolic comorbidities.</p><p><strong>Methods: </strong>Here, we integrate chromatin accessibility (ATAC-seq) and gene expression (RNA-seq) data from intra-individually paired human subcutaneous (SAT) and omental visceral adipose tissue (OVAT) samples to unveil depot-specific regulatory mechanisms.</p><p><strong>Findings: </strong>We identified twice as many depot-specific differentially accessible regions (DARs) in OVAT compared to SAT. SAT-specific regions showed enrichment for adipose tissue enhancers involving genes controlling extracellular matrix organization and metabolic processes. In contrast, OVAT-specific regions showed enrichment in promoters linked to genes associated with cardiomyopathies. Moreover, OVAT-specific regions were enriched for bivalent transcription start site and repressive chromatin states, suggesting a \"lingering\" regulatory state. Motif analysis identified CTCF and BACH1 as most significantly enriched motifs in SAT and OVAT-specific DARs, respectively. Distinct gene sets correlated with important clinical variables of obesity, fat distribution measures, as well as insulin, glucose, and lipid metabolism.</p><p><strong>Interpretation: </strong>We provide an integrated analysis of chromatin accessibility and transcriptional profiles in paired human SAT and OVAT samples, offering new insights into the regulatory landscape of adipose tissue and highlighting depot-specific mechanisms in obesity pathogenesis.</p><p><strong>Funding: </strong>SS received EU-Scientia postdoctoral Fellowship and project funding from the European Union's Horizon 2020 Research and Innovation program under the Marie Skłodowska-Curie Grant, (agreement No. 801133). LlCP and TR were supported by Helse Sør-Øst grants to Y.B (ID 2017079, ID 278908). MB received funding from grants from the DFG (German Research Foundation)-Projekt number 209933838-SFB 1052 (project B1) and by Deutsches Zentrum für Diabetesforschung (DZD, Grant: 82DZD00601).</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"114 ","pages":"105653"},"PeriodicalIF":9.7,"publicationDate":"2025-03-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143673610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Author response to \"A step closer to optimal paroxetine dosing: what is next?\"","authors":"Yundan Liao, Weihua Yue","doi":"10.1016/j.ebiom.2025.105651","DOIUrl":"https://doi.org/10.1016/j.ebiom.2025.105651","url":null,"abstract":"","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"114 ","pages":"105651"},"PeriodicalIF":9.7,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143669444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification of heart failure subtypes using transformer-based deep learning modelling: a population-based study of 379,108 individuals.","authors":"Zhengxian Fan, Mohammad Mamouei, Yikuan Li, Shishir Rao, Kazem Rahimi","doi":"10.1016/j.ebiom.2025.105657","DOIUrl":"https://doi.org/10.1016/j.ebiom.2025.105657","url":null,"abstract":"<p><strong>Background: </strong>Heart failure (HF) is a complex syndrome with varied presentations and progression patterns. Traditional classification systems based on left ventricular ejection fraction (LVEF) have limitations in capturing the heterogeneity of HF. We aimed to explore the application of deep learning, specifically a Transformer-based approach, to analyse electronic health records (EHR) for a refined subtyping of patients with HF.</p><p><strong>Methods: </strong>We utilised linked EHR from primary and secondary care, sourced from the Clinical Practice Research Datalink (CPRD) Aurum, which encompassed health data of over 30 million individuals in the UK. Individuals aged 35 and above with incident reports of HF between January 1, 2005, and January 1, 2018, were included. We proposed a Transformer-based approach to cluster patients based on all clinical diagnoses, procedures, and medication records in EHR. Statistical machine learning (ML) methods were used for comparative benchmarking. The models were trained on a derivation cohort and assessed for their ability to delineate distinct clusters and prognostic value by comparing one-year all-cause mortality and HF hospitalisation rates among the identified subgroups in a separate validation cohort. Association analyses were conducted to elucidate the clinical characteristics of the derived clusters.</p><p><strong>Findings: </strong>A total of 379,108 patients were included in the HF subtyping analysis. The Transformer-based approach outperformed alternative methods, delineating more distinct and prognostically valuable clusters. This approach identified seven unique HF patient clusters characterised by differing patterns of mortality, hospitalisation, and comorbidities. These clusters were labelled based on the dominant clinical features present at the initial diagnosis of HF: early-onset, hypertension, ischaemic heart disease, metabolic problems, chronic obstructive pulmonary disease (COPD), thyroid dysfunction, and late-onset clusters. The Transformer-based subtyping approach successfully captured the multifaceted nature of HF.</p><p><strong>Interpretation: </strong>This study identified seven distinct subtypes, including COPD-related and thyroid dysfunction-related subgroups, which are two high-risk subgroups not recognised in previous subtyping analyses. These insights lay the groundwork for further investigations into tailored and effective management strategies for HF.</p><p><strong>Funding: </strong>British Heart Foundation, European Union - Horizon Europe, and Novo Nordisk Research Centre Oxford.</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"114 ","pages":"105657"},"PeriodicalIF":9.7,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143669445","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unlocking the potential of circular RNA vaccines: a bioinformatics and computational biology perspective.","authors":"Xuyuan Liu, Siqi Wang, Yunan Sun, Yunxi Liao, Guangzhen Jiang, Bryan-Yu Sun, Jingyou Yu, Dongyu Zhao","doi":"10.1016/j.ebiom.2025.105638","DOIUrl":"https://doi.org/10.1016/j.ebiom.2025.105638","url":null,"abstract":"<p><p>Bioinformatics has significantly advanced RNA-based therapeutics, particularly circular RNAs (circRNAs), which outperform mRNA vaccines, by offering superior stability, sustained expression, and enhanced immunogenicity due to their covalently closed structure. This review highlights how bioinformatics and computational biology optimise circRNA vaccine design, elucidates internal ribosome entry sites (IRES) selection, open reading frame (ORF) optimisation, codon usage, RNA secondary structure prediction, and delivery system development. While circRNA vaccines may not always surpass traditional vaccines in stability, their production efficiency and therapeutic efficacy can be enhanced through computational strategies. The discussion also addresses challenges and future prospects, emphasizing the need for innovative solutions to overcome current limitations and advance circRNA vaccine applications.</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"114 ","pages":"105638"},"PeriodicalIF":9.7,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143669456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}