EBioMedicine最新文献

{"title":"Human microbiome-derived peptide affects the development of experimental autoimmune encephalomyelitis via molecular mimicry.","authors":"Xin Ma, Jian Zhang, Qianling Jiang, Yong-Xin Li, Guan Yang","doi":"10.1016/j.ebiom.2024.105516","DOIUrl":"https://doi.org/10.1016/j.ebiom.2024.105516","url":null,"abstract":"<p><strong>Background: </strong>Gut commensal microbiota has been identified as a potential environmental risk factor for multiple sclerosis (MS), and numerous studies have linked the commensal microorganism with the onset of MS. However, little is known about the mechanisms underlying the gut microbiome and host-immune system interaction.</p><p><strong>Methods: </strong>We employed bioinformatics methodologies to identify human microbial-derived peptides by analyzing their similarity to the MHC II-TCR binding patterns of self-antigens. Subsequently, we conducted a range of in vitro and in vivo assays to assess the encephalitogenic potential of these microbial-derived peptides.</p><p><strong>Findings: </strong>We analyzed 304,246 human microbiome genomes and 103 metagenomes collected from the MS cohort and identified 731 nonredundant analogs of myelin oligodendrocyte glycoprotein peptide 35-55 (MOG_35-55). Of note, half of these analogs could bind to MHC II and interact with TCR through structural modeling of the interaction using fine-tuned AlphaFold. Among the 8 selected peptides, the peptide (P3) shows the ability to activate MOG_35-55-specific CD4⁺ T cells in vitro. Furthermore, P3 shows encephalitogenic capacity and has the potential to induce EAE in some animals. Notably, mice immunized with a combination of P3 and MOG_35-55 develop severe EAE. Additionally, dendritic cells could process and present P3 to MOG_35-55-specific CD4⁺ T cells and activate these cells.</p><p><strong>Interpretation: </strong>Our data suggests the potential involvement of a MOG_35-55-mimic peptide derived from the gut microbiota as a molecular trigger of EAE pathogenesis. Our findings offer direct evidence of how microbes can initiate the development of EAE, suggesting a potential explanation for the correlation between certain gut microorganisms and MS prevalence.</p><p><strong>Funding: </strong>National Natural Science Foundation of China (82371350 to GY).</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"111 ","pages":"105516"},"PeriodicalIF":9.7,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142892956","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":"Decoding broadly neutralizing antibodies: a milestone in SFTSV therapy.","authors":"Xiaoyu Zhao, Hin Chu","doi":"10.1016/j.ebiom.2024.105527","DOIUrl":"https://doi.org/10.1016/j.ebiom.2024.105527","url":null,"abstract":"","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"111 ","pages":"105527"},"PeriodicalIF":9.7,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142893036","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":"Robust, fully-automated assessment of cerebral perivascular spaces and white matter lesions: a multicentre MRI longitudinal study of their evolution and association with risk of dementia and accelerated brain atrophy.","authors":"Giuseppe Barisano, Michael Iv, Jeiran Choupan, Melanie Hayden-Gephart","doi":"10.1016/j.ebiom.2024.105523","DOIUrl":"https://doi.org/10.1016/j.ebiom.2024.105523","url":null,"abstract":"<p><strong>Background: </strong>Perivascular spaces (PVS) on brain MRI are surrogates for small parenchymal blood vessels and their perivascular compartment, and may relate to brain health. However, it is unknown whether PVS can predict dementia risk and brain atrophy trajectories in participants without dementia, as longitudinal studies on PVS are scarce and current methods for PVS assessment lack robustness and inter-scanner reproducibility.</p><p><strong>Methods: </strong>We developed a robust algorithm to automatically assess PVS count and size on clinical MRI, and investigated 1) their relationship with dementia risk and brain atrophy in participants without dementia, 2) their longitudinal evolution, and 3) their potential use as a screening tool in simulated clinical trials. We analysed 46,478 clinical measurements of cognitive functioning and 20,845 brain MRI scans from 10,004 participants (71.1 ± 9.7 years-old, 56.6% women) from three publicly available observational studies on ageing and dementia (the Alzheimer's Disease Neuroimaging Initiative, the National Alzheimer's Coordinating Centre database, and the Open Access Series of Imaging Studies). Clinical and MRI data collected between 2004 and 2022 were analysed with consistent methods, controlling for confounding factors, and combined using mixed-effects models.</p><p><strong>Findings: </strong>Our fully-automated method for PVS assessment showed excellent inter-scanner reproducibility (intraclass correlation coefficients >0.8). Fewer PVS and larger PVS diameter at baseline predicted higher dementia risk and accelerated brain atrophy. Longitudinal trajectories of PVS markers differed significantly in participants without dementia who converted to dementia compared with non-converters. In simulated placebo-controlled trials for treatments targeting cognitive decline, screening out participants at low risk of dementia based on our PVS markers enhanced the power of the trial independently of Alzheimer's disease biomarkers.</p><p><strong>Interpretation: </strong>These robust cerebrovascular markers predict dementia risk and brain atrophy and may improve risk-stratification of patients, potentially reducing cost and increasing throughput of clinical trials to combat dementia.</p><p><strong>Funding: </strong>US National Institutes of Health.</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"111 ","pages":"105523"},"PeriodicalIF":9.7,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142892973","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":"Simplifying coronary artery disease risk stratification: development and validation of a questionnaire-based alternative comparable to clinical risk tools.","authors":"Michail Kokkorakis, Pytrik Folkertsma, Filippos Anagnostakis, Nicole Sirotin, Manyoo Agarwal, Ronney Shantouf, Robert H Henning, Hanno Pijl, Bruce H R Wolffenbuttel, Jeroen J Bax, Douwe E Atsma, José Castela Forte, Christos S Mantzoros, Sipko van Dam","doi":"10.1016/j.ebiom.2024.105518","DOIUrl":"https://doi.org/10.1016/j.ebiom.2024.105518","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Background: &lt;/strong&gt;Coronary artery disease (CAD) comprises one of the leading causes of morbidity and mortality both in the European population and globally. All established clinical risk stratification scores and models require blood lipids and physical measurements. The latest reports of the European Commission suggest that attracting health professionals to collect these data can be challenging, both from a logistic and cost perspective, which limits the usefulness of established models and makes them unsuitable for population-wide screening in resource-limited settings, i.e., rural areas. Therefore, the aim of this study was to develop and externally validate a questionnaire-based risk stratification model on a population scale at minimal cost, i.e., the Questionnaire-Based Evaluation for Estimating Coronary Artery Disease (QUES-CAD) to stratify the 10-year incidence of coronary artery disease.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;Cox proportional hazards (CoxPH) and Cox gradient boosting (CoxGBT) models were trained with 10-fold cross-validation using combinations of ten questionnaire variables on the White population of the UK Biobank (n = 448,818) and internally validated the models in all ethnic minorities (n = 27,433). The Lifelines cohort was employed as an independent external validation population (n = 97,770). Additionally, we compared QUES-CAD's performance, containing only questionnaire variables, to clinically established risk prediction tools, i.e., Framingham Coronary Heart Disease Risk Score, American College of Cardiology/American Heart Association pooled cohort equation, World Health Organization cardiovascular disease risk charts, and Systematic Coronary Risk Estimation 2 (SCORE2). We conducted partial log-likelihood ratio (PLR) tests and C-index comparisons between QUES-CAD and established clinical prediction models.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Findings: &lt;/strong&gt;In the external validation set, QUES-CAD exhibited C-index values of CoxPH: 0.692 (95% Confidence Interval [CI]: 0.673-0.71) and CoxGBT: 0.699 (95% CI: 0.681-0.717) for the male population and CoxPH: 0.771 (95% CI: 0.748-0.794) and CoxGBT: 0.759 (95% CI: 0.736-0.783) for the female population. The addition of measurement-based variables and variables that require a prior medical examination (i.e., insulin use, number of treatments/medications taken, prevalent cardiovascular disease [other than CAD, and stroke diagnosed by a doctor]) and the further addition of biomarkers/other measurements (i.e., high-density lipoprotein [HDL] cholesterol, total cholesterol, and glycated haemoglobin) did not significantly improve QUES-CAD's performance in most instances. C-index comparisons and PLR tests showed that QUES-CAD performs and fits the data at least as well as the clinical prediction models.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Interpretation: &lt;/strong&gt;QUES-CAD performs comparably to established clinical prediction models and enables a population-wide identification of high-risk individuals for CAD.","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"111 ","pages":"105518"},"PeriodicalIF":9.7,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142892914","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":"Why implementing machine learning algorithms in the clinic is not a plug-and-play solution: a simulation study of a machine learning algorithm for acute leukaemia subtype diagnosis.","authors":"Gernot Pucher, Till Rostalski, Felix Nensa, Jens Kleesiek, Hans Christian Reinhardt, Christopher Martin Sauer","doi":"10.1016/j.ebiom.2024.105526","DOIUrl":"https://doi.org/10.1016/j.ebiom.2024.105526","url":null,"abstract":"<p><strong>Background: </strong>Artificial intelligence (AI) and machine learning (ML) algorithms have shown great promise in clinical medicine. Despite the increasing number of published algorithms, most remain unvalidated in real-world clinical settings. This study aims to simulate the practical implementation challenges of a recently developed ML algorithm, AI-PAL, designed for the diagnosis of acute leukaemia and report on its performance.</p><p><strong>Methods: </strong>We conducted a detailed simulation of the AI-PAL algorithm's implementation at the University Hospital Essen. Cohort building was performed using our Fast Healthcare Interoperability Resources (FHIR) database, identifying all initially diagnosed patients with acute leukaemia and selected differential diagnoses. The algorithm's performance was assessed by reproducing the original study's results.</p><p><strong>Findings: </strong>The AI-PAL algorithm demonstrated significantly lower performance in our simulated clinical implementation compared to prior published results. The area under the receiver operating characteristic curve for acute lymphoblastic leukaemia dropped to 0.67 (95% CI: 0.61-0.73) and for acute myeloid leukaemia to 0.71 (95% CI: 0.65-0.76). The recalibration of probability cutoffs determining confident diagnoses increased the number of confident positive diagnosis for acute leukaemia from 98 to 160, highlighting the necessity of local validation and adjustments.</p><p><strong>Interpretation: </strong>The findings underscore the challenges of implementing ML algorithms in clinical practice. Despite robust development and validation in research settings, ML models like AI-PAL may require significant adjustments and recalibration to maintain performance in different clinical settings. Our results suggest that clinical decision support algorithms should undergo local performance validation before integration into routine care to ensure reliability and safety.</p><p><strong>Funding: </strong>This study was supported by the DFG-cofounded UMEA Clinician Scientist Program and the Ministry of Culture and Science of the State of North Rhine-Westphalia.</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"111 ","pages":"105526"},"PeriodicalIF":9.7,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142892847","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":"Reducing unnecessary preoperative testing through a comprehensive EMR based digital algorithm.","authors":"Stephen A Esper, Jennifer Holder-Murray, Katie Meister, Hsing-Hua Sylvia Lin, Alison K Bauer, Jamie Artman, Michael Garver, Amy Lukanski, Brian Scott Zuckerbraun, Oscar Marroquin, Aman Mahajan","doi":"10.1016/j.ebiom.2024.105509","DOIUrl":"https://doi.org/10.1016/j.ebiom.2024.105509","url":null,"abstract":"<p><strong>Background: </strong>We hypothesised that the implementation of an electronic medical record (EMR) embedded perioperative clinical decision support (CDS) application, Anesthesia Testing Guidelines (ATG), would result in at least a 10% reduction of unnecessary perioperative testing in patients undergoing elective surgeries.</p><p><strong>Methods: </strong>The development and implementation of ATG occurred in several phases: 1) team development, 2) development of an embedded EMR application, 3) creation of ATG training and education toolkit, and 4) implementation involving promoting ATG through training and education, addressing challenges, and monitoring compliance. The proportions of patients with any overutilisation across 19 perioperative tests were compared between the baseline cohort and the ATG implementation cohort.</p><p><strong>Findings: </strong>The overutilisation of perioperative tests was observed in 77.6% of the baseline cohort (n = 59,799) and 68.1% in the ATG cohort (n = 132,131), with a significant 12.2% reduction over two years of implementation (p < 0.0001). The two tests with the greatest amount of associated cost were reduced by 46% for chest X-rays and 39% for complete metabolic panels. The health system was able to reduce overall costs by 22% from baseline. Interrupted time series analysis estimated an immediate 7.5% decrease in monthly overutilisation when ATG initially launched, and it continued to decrease by 0.24% per month.</p><p><strong>Interpretation: </strong>Our findings suggest CDS ATG is a successful tactic to reduce unnecessary preoperative testing while maintaining quality of care and improving cost avoidance. This type of CDS implementation approach transforms organisational behaviour and medical practices to follow defined guidelines, thereby improving the value of care.</p><p><strong>Funding: </strong>CDS ATG was supported by UPMC Department of Anesthesiology and Perioperative Medicine and UPMC Department of Finance.</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"111 ","pages":"105509"},"PeriodicalIF":9.7,"publicationDate":"2024-12-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142885058","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":"Combination of spatial transcriptomics analysis and retrospective study reveals liver infection of SARS-COV-2 is associated with clinical outcomes of COVID-19.","authors":"Shiqi Chen, Yi Zhang, Asha Ashuo, Shu Song, Lunzhi Yuan, Weixia Wang, Cong Wang, Zunguo Du, Yangtao Wu, Dan Tan, Chenlu Huang, Jingna Chen, Yaming Li, Jinjin Bai, Huilin Guo, Zehong Huang, Yi Guan, Ningshao Xia, Zhenghong Yuan, Jiming Zhang, Quan Yuan, Zhong Fang","doi":"10.1016/j.ebiom.2024.105517","DOIUrl":"https://doi.org/10.1016/j.ebiom.2024.105517","url":null,"abstract":"<p><strong>Background: </strong>Liver involvement is a common complication of coronavirus disease 2019 (COVID-19), especially in hospitalized patients. However, the underlying mechanisms involved are not fully understood.</p><p><strong>Methods: </strong>Immunohistochemistry (IHC) staining of SARS-CoV-2 spike (S) and nucleocapsid (N) proteins was conducted on liver tissues from six patients with COVID-19. The 10x Genomics Visium CytAssist Spatial Gene Assay was designed to analyze liver transcriptomics. TCR CDR3 sequences were analyzed in DNA from liver tissues. Liver function indicators were retrospectively studied in 650 hospitalized patients with COVID-19.</p><p><strong>Findings: </strong>SARS-CoV-2 proteins were initially detected in the livers of naturally infected golden (Syrian) hamsters, prompting us to investigate the situation in clinical cases. Thus, we collected liver tissues from patients with abnormal liver biochemical values. Viral S and N proteins were detected in the livers of severe and deceased patients but not in those of moderate patients. We further demonstrated that hepatocytes and erythroid cells in hepatic sinusoids are major cells targeted by SARS-CoV-2. Immune cells, especially T cells, were enriched in surviving severe patients, characterized by enhanced CDR3α clonality and novel CDR3β recombination of the T-cell receptor. In contrast, hepatocyte apoptosis was triggered, and the transcription of albumin (ALB) was obviously impaired in the deceased patients. We then performed a retrospective study including patients with COVID-19. Serum aspartate aminotransferase (AST) and ALB levels at baseline significantly differed in the deceased cohort. However, AST regression did not decrease the risk of death. ALB recovery indicated clinical improvement, and declining or low serum ALB concentrations were associated with death.</p><p><strong>Interpretation: </strong>This study provides clinical evidence for liver infection with SARS-CoV-2, insight into the impact of SARS-CoV-2 on the liver, and a potential way to evaluate the risk of death via assessing serum ALB concentration fluctuations in patients with COVID-19.</p><p><strong>Funding: </strong>National Key R&D Program of China (2021YFC2300602), National Natural Science Foundation of China (92369110), National Natural Science Foundation of China (U23A20474), Shanghai Municipal Science and Technology Major Project (ZD2021CY001), Shanghai Jinshan District Medical and Health Technology Innovation Fund Project (2023-WS-31).</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"111 ","pages":"105517"},"PeriodicalIF":9.7,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876650","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":"The impact of information and communication technology on immunisation and immunisation programmes in low-income and middle-income countries: a systematic review and meta-analysis.","authors":"Mohini Zarekar, Hussein Al-Shehabi, Rita Dörner, Heide Weishaar, Tessa Lennemann, Charbel El Bcheraoui, Andrea Bernasconi","doi":"10.1016/j.ebiom.2024.105520","DOIUrl":"https://doi.org/10.1016/j.ebiom.2024.105520","url":null,"abstract":"<p><strong>Background: </strong>Low-income and Middle-income Countries (LMIC) are continually working to ensure everyone can access life-saving vaccines. Recognising the considerable impact of Information and Communication Technology (ICT) in healthcare, we performed a systematic review and meta-analysis to summarise ICT effectiveness in improving vaccine delivery in LMICs.</p><p><strong>Methods: </strong>A systematic search from January 2010 to August 2023 in MEDLINE, EMBASE, Cochrane Library, BMJ Health & Care Informatics, and grey literature was performed. This search focused on randomised controlled trials (RCTs), non-RCTs, observational, and mixed-methods studies in English, examining ICT's effects on childhood immunisation in LMICs. Risk of bias in RCTs and non-RCTs was assessed using the Joanna Briggs Institute tool, and mixed-methods studies were evaluated with the Mixed Methods Appraisal Tool. A meta-analysis summarised ICT's impact on third pentavalent dose coverage and full immunisation by age one. The study is registered with PROSPERO (CRD42023446062).</p><p><strong>Findings: </strong>Of 6535 screened studies, 27 involving 354,979 children were included. All apart from one study demonstrated a positive impact on immunisation coverage and timeliness, completeness and accuracy of records, number of adverse events reporting, vaccine stockouts, and cold chain expansion. The meta-analysis demonstrated that reminders effectively improved coverage rate of the third dose of the pentavalent vaccine (OR 2.32, 95% CI 1.34-4.03) and the full immunisation at one year of age (OR 2.61, 95% CI 1.2-5.67) with significant degrees of heterogeneity, respectively I² 82% and I² 89%. Main concerns for bias in RCTs included unblinded outcome assessors and intervention providers. Interpreting quasi-experimental studies was more challenging due to the higher risk of baseline differences between study arms, statistical methods, and dropouts. Mixed-methods studies often lacked clarity in integrating qualitative and quantitative data.</p><p><strong>Interpretation: </strong>This systematic review confirms the benefits of ICT in immunisation programmes by enhancing various stages of vaccine delivery. Specifically, reminders have been shown to enhance childhood immunisation coverage rates.</p><p><strong>Funding: </strong>Deutsche Gesellschaft für Internationale Zusammenarbeit (German Corporation for International Cooperation, GIZ) as part of the Digital Innovation in Pandemic Control (DIPC) Initiative, financed by the Bundesministerium für Wirtschaftliche Zusammenarbeit (Federal Ministry for Economic Cooperation and Development, BMZ).</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"111 ","pages":"105520"},"PeriodicalIF":9.7,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876656","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":"M&M: an RNA-seq based pan-cancer classifier for paediatric tumours.","authors":"Fleur S A Wallis, John L Baker-Hernandez, Marc van Tuil, Claudia van Hamersveld, Marco J Koudijs, Eugène T P Verwiel, Alex Janse, Laura S Hiemcke-Jiwa, Ronald R de Krijger, Mariëtte E G Kranendonk, Marijn A Vermeulen, Pieter Wesseling, Uta E Flucke, Valérie de Haas, Maaike Luesink, Eelco W Hoving, Josef H Vormoor, Max M van Noesel, Jayne Y Hehir-Kwa, Bastiaan B J Tops, Patrick Kemmeren, Lennart A Kester","doi":"10.1016/j.ebiom.2024.105506","DOIUrl":"https://doi.org/10.1016/j.ebiom.2024.105506","url":null,"abstract":"<p><strong>Background: </strong>With many rare tumour types, acquiring the correct diagnosis is a challenging but crucial process in paediatric oncology. Historically, this is done based on histology and morphology of the disease. However, advances in genome wide profiling techniques such as RNA sequencing now allow the development of molecular classification tools.</p><p><strong>Methods: </strong>Here, we present M&M, a pan-paediatric cancer ensemble-based machine learning algorithm tailored towards inclusion of rare tumour types.</p><p><strong>Findings: </strong>The RNA-seq based algorithm can classify 52 different tumour types (precision ∼99%, recall ∼80%), plus the underlying 96 tumour subtypes (precision ∼96%, recall ∼70%). For low-confidence classifications, a comparable precision is achieved when including the three highest-scoring labels. We then validated M&M on an internal dataset (precision 99%, recall 76%) and an external dataset from the KidsFirst initiative (precision 98%, recall 77%). Finally, we show that M&M has similar performance as existing disease or domain specific classification algorithms based on RNA sequencing or methylation data.</p><p><strong>Interpretation: </strong>M&M's pan-cancer setup allows for easy clinical implementation, requiring only one classifier for all incoming diagnostic samples, including samples from different tumour stages and treatment statuses. Simultaneously, its performance is comparable to existing tumour- and tissue-specific classifiers. The introduction of an extensive pan-cancer classifier in diagnostics has the potential to increase diagnostic accuracy for many paediatric cancer cases, thereby contributing towards optimal patient survival and quality of life.</p><p><strong>Funding: </strong>Financial support was provided by the Foundation Children Cancer Free (KiKa core funding) and Adessium Foundation.</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"111 ","pages":"105506"},"PeriodicalIF":9.7,"publicationDate":"2024-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142876653","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":"Preimplantation genetic testing for structural rearrangements by genome-wide SNP genotyping and haplotype analysis: a prospective multicenter clinical study.","authors":"Shuo Zhang, Yuan Gao, Xiaohong Wang, Qing Li, Jichun Tan, Bo Liang, Ming Gao, Junping Wu, Xiufeng Ling, Jiayin Liu, Xiaoming Teng, Hong Li, Yun Sun, Weidong Huang, Xianhong Tong, Caixia Lei, Hongchang Li, Jun Wang, Shaoying Li, Xiaoyan Xu, Junqiang Zhang, Wei Wu, Shanshan Liang, Jian Ou, Qiongzhen Zhao, Rentao Jin, Yueping Zhang, Chenming Xu, Daru Lu, Junhao Yan, Xiaoxi Sun, Kwong Wai Choy, Congjian Xu, Zi-Jiang Chen","doi":"10.1016/j.ebiom.2024.105514","DOIUrl":"https://doi.org/10.1016/j.ebiom.2024.105514","url":null,"abstract":"<p><strong>Background: </strong>Preimplantation genetic testing for chromosomal structural rearrangements (PGT-SR) has been widely utilized to select euploid embryos in patients carrying balanced chromosomal rearrangements (BCRs) by chromosome copy number analysis. However, reliable and extensively validated PGT-SR methods for selecting embryos without BCRs in large-cohort studies are lacking.</p><p><strong>Methods: </strong>In this prospective, multicenter, cohort study, carriers with BCRs undergoing PGT-SR were recruited across 12 academic fertility centers within China. PGT-SR was performed using genome-wide SNP genotyping and haplotyping approach. Parental haplotypes were phased by available genotypes from a close relative or an unbalanced embryo. The karyotypes of embryos were inferred from the haplotypes. Only a single embryo was transferred in each cycle.</p><p><strong>Findings: </strong>Between April 2018 and March 2023, 1298 carriers we randomly enrolled. A total of 7867 blastocysts from 1603 PGT-SR cycles were biopsied, in which 7750 (98.51%) were successfully genotyped and analyzed. Overall, 75.98% (1218/1603) of cycles obtained euploid embryos and 53.15% (852/1603) generated non-carrier embryos. The proportion of carrier and non-carrier embryos was similar in different subgroups. A total of 1030 non-carrier and 439 carrier embryos were transferred, 817 healthy babies were delivered cumulatively. Our results demonstrate that SNP-haplotyping method is highly accurate (sensitivity 95% CI: 98.34%-100%, specificity 95% CI: 96.63%-100%, respectively), and can be applied universally to different BCR types. Moreover, the clinical outcomes were comparable between the carrier and non-carrier embryo groups.</p><p><strong>Interpretation: </strong>This study demonstrates the effectiveness of preimplantation genetic genome-wide SNP-genotyping and haplotyping method, resulting in the delivery of more babies with a normal karyotype.</p><p><strong>Funding: </strong>This study was funded by the National Key Research and Development Program of China (2022YFC2703200, 2021YFC2700600, 2021YFC2700500), National Natural Science Foundation of China (82201807, 82171639, 82071717). Shanghai Science and Technology Innovation Action Plan Program (18411953800), and the Municipal Human Resources Development Program for Outstanding Young Talents in Medical and Health Sciences in Shanghai (2022YQ075).</p>","PeriodicalId":11494,"journal":{"name":"EBioMedicine","volume":"111 ","pages":"105514"},"PeriodicalIF":9.7,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142871720","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}