Genome Medicine最新文献

{"title":"PhenoDP: leveraging deep learning for phenotype-based case reporting, disease ranking, and symptom recommendation.","authors":"Baole Wen, Sheng Shi, Yi Long, Yanan Dang, Weidong Tian","doi":"10.1186/s13073-025-01496-8","DOIUrl":"10.1186/s13073-025-01496-8","url":null,"abstract":"<p><strong>Background: </strong>Current phenotype-based diagnostic tools often struggle with accurate disease prioritization due to incomplete phenotypic data and the complexity of rare disease presentations. Additionally, they lack the ability to generate patient-centered clinical insights or recommend further symptoms for differential diagnosis.</p><p><strong>Methods: </strong>We developed PhenoDP, a deep learning-based toolkit with three modules: Summarizer, Ranker, and Recommender. The Summarizer fine-tuned a distilled large language model to create clinical summaries from a patient's Human Phenotype Ontology (HPO) terms. The Ranker prioritizes diseases by combining information content-based, phi-based, and semantic-based similarity measures. The Recommender employs contrastive learning to recommend additional HPO terms for enhanced diagnostic accuracy.</p><p><strong>Results: </strong>PhenoDP's Summarizer produces more clinically coherent and patient-centered summaries than the general-purpose language model FlanT5. The Ranker achieves state-of-the-art diagnostic performance, consistently outperforming existing phenotype-based methods across both simulated and real-world datasets. The Recommender also outperformed GPT-4o and PhenoTips in improving diagnostic accuracy when its suggested terms were incorporated into different ranking pipelines.</p><p><strong>Conclusions: </strong>PhenoDP enhances Mendelian disease diagnosis through deep learning, offering precise summarization, ranking, and symptom recommendation. Its superior performance and open-source design make it a valuable clinical tool, with potential to accelerate diagnosis and improve patient outcomes. PhenoDP is freely available at https://github.com/TianLab-Bioinfo/PhenoDP .</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"67"},"PeriodicalIF":10.4,"publicationDate":"2025-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12143081/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144247520","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations between HLA-II variation and antibody specificity are predicted by antigen properties.","authors":"Gabriel Innocenti, Sergio Andreu-Sánchez, Nicolai V Hörstke, Hesham Elabd, Iros Barozzi, Andre Franke, Máté Manczinger, Thomas Vogl","doi":"10.1186/s13073-025-01486-w","DOIUrl":"10.1186/s13073-025-01486-w","url":null,"abstract":"<p><strong>Background: </strong>Human leukocyte antigen class II (HLA-II) genes are highly polymorphic affecting the specificity of human antibody responses, as presentation of processed antigen peptides by HLA-II on B cells is essential for T helper cell dependent affinity maturation and class switching. The combination of high-throughput immunoassays and genome-wide association studies has recently revealed strong associations between HLA-II variants and antibody responses against specific antigens. However, factors underlying these associations remain incompletely understood.</p><p><strong>Methods: </strong>Here, we have leveraged paired data sets of SNP arrays and functional antibody epitope repertoires against 344,000 peptide antigens in 1940 individuals to mine for key determinants linking genetics and antibody specificity.</p><p><strong>Results: </strong>We show that secreted proteins and antigens presented in small modules (i.e., viruses) are significantly more frequently associated with HLA-II alleles, than membrane bound or intracellular proteins. This data suggests a model in which antibody responses against separate antigen units composed of single or few proteins dominate HLA-II associations. In contrast, the presence of manifold intracellular or membrane proteins (peptides of which could be bound by different HLA-II alleles) on bacterial cells dilutes potential associations to antibody specificities.</p><p><strong>Conclusions: </strong>Hence, genetic associations to antibody specificities are shaped by antigen intrinsic properties. Given the prominent role of HLA-II alleles in infection, autoimmune diseases, allergies, and cancer, our work provides a theoretical framework to study antigen/HLA-II risk factors in these disease settings and will fuel the design of improved immunogenetics screens.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"65"},"PeriodicalIF":10.4,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12131526/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144208402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pan-cancer analysis identifies CD155 as a promising target for CAR-T cell therapy.","authors":"Xiaohong Liu, Yue Sun, Boxu Lin, Hao Xiong, Xinyue Lu, Binghe Tan, Chenglin Zhang, Mingyao Liu, Juliang Qin, Na Zhang, Bing Du","doi":"10.1186/s13073-025-01490-0","DOIUrl":"10.1186/s13073-025-01490-0","url":null,"abstract":"<p><strong>Background: </strong>Chimeric antigen receptor T (CAR-T) cell therapy has shown remarkable success in treating hematologic malignancies. However, its efficacy against solid tumors remains limited. One of the major challenges is the lack of specific tumor antigens. Therefore, the exploration and rational selection of novel tumor targets is urgently needed. In this study, we investigate the therapeutic potential of targeting CD155 in cancer by CAR-T cells.</p><p><strong>Methods: </strong>The expression of CD155 was analyzed across various cancer types using data from The Cancer Genome Atlas (TCGA) and validated by tissue microarray analysis. The impact of CD155 on T cell mediated cytotoxicity was analyzed using CD155 over-expression or knockout tumor cells. Subsequently, second-generation CAR-T cells were constructed using either the extracellular domain (ECD) of TIGIT or an anti-CD155 scFv to evaluate their anti-tumor efficacy both in vitro and in vivo.</p><p><strong>Results: </strong>We demonstrated that CD155 is specifically overexpressed across various cancer types and that its high expression is strongly associated with poor prognosis, as revealed by data from TCGA. Consistently, CD155 is significantly upregulated in clinical tumor tissues and in numerous cancer cell lines, while it is rarely expressed in normal tissues. Furthermore, CD155 expression is also significantly increased in granulocytes derived from cancer patients compared to those from healthy donors. Functionally, high CD155 expression significantly inhibits the release of cytotoxic factors from T cells, thereby functioning as an immune checkpoint that mediates tumor immune evasion. After comparison, the scFv based anti-CD155 CAR-T cells demonstrated stronger anti-tumor activity than ECD of TIGIT based CAR-T cells. Moreover, the scFv based CAR-T cells exhibited effective anti-tumor activity against multiple CD155⁺ solid and hematologic tumors both in vitro and in different xenograft mouse models.</p><p><strong>Conclusions: </strong>Our study demonstrates that CD155 is selectively expressed in cancer cells while being rarely detected in normal tissues, and may serve as a promising pan-cancer target for CAR-T therapy. Targeting CD155 with CAR-T cells provides an effective approach to treating both solid and hematologic malignancies.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"64"},"PeriodicalIF":10.4,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12128359/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144208404","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 molecular impact of cigarette smoking resembles aging across tissues.","authors":"Jose Miguel Ramirez, Rogério Ribeiro, Oleksandra Soldatkina, Athos Moraes, Raquel García-Pérez, Winona Oliveros, Pedro G Ferreira, Marta Melé","doi":"10.1186/s13073-025-01485-x","DOIUrl":"10.1186/s13073-025-01485-x","url":null,"abstract":"<p><strong>Background: </strong>Tobacco smoke is the main cause of preventable mortality worldwide. Smoking increases the risk of developing many diseases and has been proposed as an aging accelerator. Yet, the molecular mechanisms driving smoking-related health decline and aging acceleration in most tissues remain unexplored.</p><p><strong>Methods: </strong>Here, we use data from the Genotype-Tissue Expression Project (GTEx) to perform a characterization of the effect of cigarette smoking across human tissues. We perform a multi-tissue analysis across 46 human tissues. Our multi-omics characterization includes analysis of gene expression, alternative splicing, DNA methylation, and histological alterations. We further analyze ex-smoker samples to assess the reversibility of these molecular alterations upon smoking cessation.</p><p><strong>Results: </strong>We show that smoking impacts tissue architecture and triggers systemic inflammation. We find that in many tissues, the effects of smoking significantly overlap those of aging. Specifically, both age and smoking upregulate inflammatory genes and drive hypomethylation at enhancers (odds ratio (OR) = 2). In addition, we observe widespread smoking-driven hypermethylation at target regions of the Polycomb repressive complex (OR = 2), which is a well-known aging effect. Smoking-induced epigenetic changes overlap causal aging CpGs, suggesting that these methylation changes may directly mediate the aging acceleration observed in smokers. Finally, we find that smoking effects that are shared with aging are more persistent over time.</p><p><strong>Conclusion: </strong>Overall, our multi-tissue and multi-omic analysis of the effects of cigarette smoking provides an extensive characterization of the impact of tobacco smoke across tissues and unravels the molecular mechanisms driving smoking-induced tissue homeostasis decline and aging acceleration.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"66"},"PeriodicalIF":10.4,"publicationDate":"2025-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12131351/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144208405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Unified high-resolution immune cell fraction estimation in blood tissue from birth to old age.","authors":"Xiaolong Guo, Mahnoor Sulaiman, Alexander Neumann, Shijie C Zheng, Charlotte A M Cecil, Andrew E Teschendorff, Bastiaan T Heijmans","doi":"10.1186/s13073-025-01489-7","DOIUrl":"10.1186/s13073-025-01489-7","url":null,"abstract":"<p><p>Variations in immune-cell fractions can confound or hamper interpretation of DNAm-based biomarkers in blood. Although cell-type deconvolution can address this challenge for cord and adult blood, currently there is no method applicable to blood from other age groups, including infants and children. Here we construct and extensively validate a DNAm reference panel, called UniLIFE, for 19 immune cell-types, applicable to blood tissue of any age. We use UniLIFE to delineate the dynamics of immune-cell fractions from birth to old age, and to infer disease associated immune cell fraction variations in newborns, infants, children and adults. In a prospective longitudinal study of type-1 diabetes in infants and children, UniLIFE identifies differentially methylated positions that precede type-1 diabetes diagnosis and that map to diabetes related signaling pathways. In summary, UniLIFE will improve the identification and interpretation of blood-based DNAm biomarkers for any age group, but specially for longitudinal studies that include infants and children. The UniLIFE panel and algorithms to estimate cell-type fractions are available from our EpiDISH Bioconductor R-package: https://bioconductor.org/packages/release/bioc/html/EpiDISH.html.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"63"},"PeriodicalIF":10.4,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12108007/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144158039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Closing the gap in the clinical adoption of computational pathology: a standardized, open-source framework to integrate deep-learning models into the laboratory information system.","authors":"Miriam Angeloni, Davide Rizzi, Simon Schoen, Alessandro Caputo, Francesco Merolla, Arndt Hartmann, Fulvia Ferrazzi, Filippo Fraggetta","doi":"10.1186/s13073-025-01484-y","DOIUrl":"10.1186/s13073-025-01484-y","url":null,"abstract":"<p><strong>Background: </strong>Digital pathology (DP) has revolutionized cancer diagnostics and enabled the development of deep-learning (DL) models aimed at supporting pathologists in their daily work and improving patient care. However, the clinical adoption of such models remains challenging. Here, we describe a proof-of-concept framework that, leveraging Health Level 7 (HL7) standard and open-source DP resources, allows a seamless integration of both publicly available and custom developed DL models in the clinical workflow.</p><p><strong>Methods: </strong>Development and testing of the framework were carried out in a fully digitized Italian pathology department. A Python-based server-client architecture was implemented to interconnect through HL7 messaging the anatomic pathology laboratory information system (AP-LIS) with an external artificial intelligence-based decision support system (AI-DSS) containing 16 pre-trained DL models. Open-source toolboxes for DL model deployment were used to run DL model inference, and QuPath was used to provide an intuitive visualization of model predictions as colored heatmaps.</p><p><strong>Results: </strong>A default deployment mode runs continuously in the background as each new slide is digitized, choosing the correct DL model(s) on the basis of the tissue type and staining. In addition, pathologists can initiate the analysis on-demand by selecting a specific DL model from the virtual slide tray. In both cases, the AP-LIS transmits an HL7 message to the AI-DSS, which processes the message, runs DL model inference, and creates the appropriate visualization style for the employed classification model. The AI-DSS transmits model inference results to the AP-LIS, where pathologists can visualize the output in QuPath and/or directly as slide description in the virtual slide tray.</p><p><strong>Conclusions: </strong>Taken together, the developed integration framework through the use of the HL7 standard and freely available DP resources offers a standardized, portable, and open-source solution that lays the groundwork for the future widespread adoption of DL models in pathology diagnostics.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"60"},"PeriodicalIF":10.4,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12107920/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149447","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"DNA repair and the contribution to chemotherapy resistance.","authors":"Ksenija Nesic, Phoebe Parker, Elizabeth M Swisher, John J Krais","doi":"10.1186/s13073-025-01488-8","DOIUrl":"10.1186/s13073-025-01488-8","url":null,"abstract":"<p><p>The DNA damage response comprises a set of imperfect pathways that maintain cell survival following exposure to DNA damaging agents. Cancers frequently exhibit DNA repair pathway alterations that contribute to their intrinsic genome instability. This, in part, facilitates a therapeutic window for many chemotherapeutic agents whose mechanisms of action often converge at the generation of a double-strand DNA break. The development of therapy resistance occurs through countless molecular mechanisms that promote tolerance to DNA damage, often by preventing break formation or increasing repair capacity. This review broadly discusses the DNA damaging mechanisms of action for different classes of chemotherapeutics, how avoidance and repair of double-strand breaks can promote resistance, and strategic directions for counteracting therapy resistance.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"62"},"PeriodicalIF":10.4,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12107761/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144149914","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"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 case for including proteomics in routine diagnostic practice for rare disease.","authors":"Elizabeth M McCormick","doi":"10.1186/s13073-025-01491-z","DOIUrl":"10.1186/s13073-025-01491-z","url":null,"abstract":"<p><p>Many people with rare diseases cannot access personalized therapies because they do not have a confirmed genetic diagnosis. Promising technologies including proteomics are underutilized in routine diagnostic practice. It is time to incorporate proteomics into the diagnostic workflow to shorten time to diagnosis and expand treatment options for rare disease.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"61"},"PeriodicalIF":10.4,"publicationDate":"2025-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12107797/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144150183","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Untargeted proteomics enables ultra-rapid variant prioritisation in mitochondrial and other rare diseases.","authors":"Daniella H Hock, Nikeisha J Caruana, Liana N Semcesen, Nicole J Lake, Luke E Formosa, Sumudu S C Amarasekera, Tegan Stait, Simone Tregoning, Leah E Frajman, Adam M Bournazos, David R L Robinson, Megan Ball, Boris Reljic, Bryony Ryder, Mathew J Wallis, Anand Vasudevan, Cara Beck, Heidi Peters, Joy Lee, Natalie B Tan, Mary-Louise Freckmann, Vasiliki Karlaftis, Chantal Attard, Paul Monagle, Amanda Samarasinghe, Rosie Brown, Weimin Bi, Monkol Lek, Robert McFarland, Robert W Taylor, Michael T Ryan, Sandra T Cooper, Zornitza Stark, John Christodoulou, Alison G Compton, David R Thorburn, David A Stroud","doi":"10.1186/s13073-025-01467-z","DOIUrl":"10.1186/s13073-025-01467-z","url":null,"abstract":"<p><strong>Background: </strong>Only half of individuals with suspected rare diseases receive a genetic diagnosis following genomic testing. A genetic diagnosis allows access to appropriate care, restores reproductive confidence and reduces the number of potentially unnecessary interventions. A major barrier is the lack of disease agnostic functional tests suitable for implementation in routine diagnostics that can provide evidence supporting pathogenicity of novel variants, especially those refractory to RNA sequencing.</p><p><strong>Methods: </strong>Focusing on mitochondrial disease, we describe an untargeted mass-spectrometry based proteomics pipeline that can quantify proteins encoded by > 50% of Mendelian disease genes and > 80% of known mitochondrial disease genes in clinically relevant sample types, including peripheral blood mononuclear cells (PBMCs). In total we profiled > 90 individuals including undiagnosed individuals suspected of mitochondrial disease and a supporting cohort of disease controls harbouring pathogenic variants in nuclear and mitochondrial genes. Proteomics data were benchmarked against pathology accredited respiratory chain enzymology to assess the performance of proteomics as a functional test. Proteomics testing was subsequently applied to individuals with suspected mitochondrial disease, including a critically ill infant with a view toward rapid interpretation of variants identified in ultra-rapid genome sequencing.</p><p><strong>Results: </strong>Proteomics testing provided evidence to support variant pathogenicity in 83% of individuals in a cohort with confirmed mitochondrial disease, outperforming clinical respiratory chain enzymology. Freely available bioinformatic tools and criteria developed for this study ( https://rdms.app/ ) allow mitochondrial dysfunction to be identified in proteomics data with high confidence. Application of proteomics to undiagnosed individuals led to 6 additional diagnoses, including a mitochondrial phenocopy disorder, highlighting the disease agnostic nature of proteomics. Use of PBMCs as a sample type allowed rapid return of proteomics data supporting pathogenicity of novel variants identified through ultra-rapid genome sequencing in as little as 54 h.</p><p><strong>Conclusions: </strong>This study provides a framework to support the integration of a single untargeted proteomics test into routine diagnostic practice for the diagnosis of mitochondrial and potentially other rare genetic disorders in clinically actionable timelines, offering a paradigm shift for the functional validation of genetic variants.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"58"},"PeriodicalIF":10.4,"publicationDate":"2025-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12096736/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144119583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Systematic analysis of genetic and phenotypic characteristics reveals antisense oligonucleotide therapy potential for one-third of neurodevelopmental disorders.","authors":"Kim N Wijnant, Nael Nadif Kasri, Lisenka E L M Vissers","doi":"10.1186/s13073-025-01477-x","DOIUrl":"10.1186/s13073-025-01477-x","url":null,"abstract":"<p><strong>Background: </strong>Neurodevelopmental disorders (NDDs) are a challenging group of disorders to treat, but promising therapeutic interventions in the form of antisense oligonucleotides (AONs) have emerged in recent years. However, the applicability of AON therapy for NDDs varies based on genetic and phenotypic traits. In this study we systematically evaluated key characteristics for AON therapy suitability in NDDs, to estimate overall therapy potential and identify, both well- and less-studied, targetable NDDs.</p><p><strong>Methods: </strong>An NDD dataset was created and evaluated to identify potentially targetable NDDs for seven AON strategies. This involved examining the presence of a combination of critical factors including disease-gene properties, such as regulatory elements, effects of pathogenic variants, and disease-associated phenotypic features.</p><p><strong>Results: </strong>Through the systematic evaluation of the presence of targetable characteristic for each NDD and AON strategy, we identified 711 NDDs (38% of the total) with characteristics favorable for at least one AON strategy and predicted that 18% of affected individuals could benefit from AON therapy.</p><p><strong>Conclusions: </strong>The results from our analysis demonstrate that there might be a more extensive potential for the use of AON therapy in NDDs than was anticipated thus far, underscoring AON therapy as a promising treatment option for NDDs while simultaneously contributing to informed therapy selection.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"17 1","pages":"59"},"PeriodicalIF":10.4,"publicationDate":"2025-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12096787/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144119582","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}