Genome Medicine最新文献

{"title":"Multi-omics and spatial proteomic profiling reveal novel AGXT2^- PYCR3^- macrophages and their phenotypes in metabolic dysfunction-associated steatotic liver disease.","authors":"Tiansu Lv, Hongshan Dai, Shihu Zhang, Ee Chang, Ming Ni, Jing Ge, Yutian Cao, Zhe Cheng, Yixian He, Jiaxuan Huai, Wenlin Ma, Yiran Zhu, Xinzi Xu, Qianhua Yan, Zhuyuan Fang, Jiangyi Yu, Feng Zhang, Xiqiao Zhou","doi":"10.1186/s13073-026-01716-9","DOIUrl":"https://doi.org/10.1186/s13073-026-01716-9","url":null,"abstract":"<p><strong>Background: </strong>Metabolic dysfunction-associated steatotic liver disease (MASLD) is a global liver disorder with a rising incidence. Early-to-middle-stage MASLD remains amenable to clinical intervention; without timely management, it may progress to fibrosis and cirrhosis. Therefore, identifying novel targets through integrated multi-technical approaches is critical for preventing and treating MASLD.</p><p><strong>Methods: </strong>We developed an integrative multi-omics and spatial proteomic strategy combined with in vitro validation. CyTOF was applied to high-dimensional immunophenotyping of the MASLD liver microenvironment. Key cell populations were then sorted accordingly for mass spectrometry to uncover their core signaling. Focusing on identified key amino acid metabolic enzymes, we performed IMC for spatial single-cell proteomic profiling to localize metabolic aberrant subsets. Finally, functional phenotypes and mechanisms were validated in cell models.</p><p><strong>Results: </strong>CyTOF revealed significant expansion of myeloid-derived cells. Thus, by targeting myeloid-derived cells, proteomic and phosphoproteomic analyses identified two severely impaired amino acid metabolic pathways: the glycine metabolic pathway regulated by AGXT2 and the proline metabolic pathway regulated by PYCR3. We then focused on AGXT2 and PYCR3 for spatial exploration via IMC and ultimately identified a macrophage subset negative for both AGXT2 and PYCR3. These macrophages were significantly elevated within MASLD and exhibited high spatial colocalization with inflammatory cells and fibrotic cells. Compared with dysregulated M1 subsets (M1-C3), dysregulated M2 subsets (M2-C1) indicated stronger pro-inflammatory and pro-fibrotic potential. In vitro models using human and murine cells confirmed that AGXT2⁻PYCR3⁻ macrophages exhibited enhanced proliferation and migration, secreted higher levels of inflammatory cytokines, chemokines, and classic fibrotic proteins, and exerted strong inductive effects on hepatic fibrotic cells, with downregulation of intercellular GSH. Mechanistically, the NF-κB and MAPK/AP-1 pathways were involved in inflammatory responses, while the p-SMAD3(T8)/TGFβ pathway contributed to the fibrotic phenotype. However, the abnormal biological functions could be effectively rescued by supplementation with corresponding amino acids, accompanied by the reversal of aberrant signaling pathway activation.</p><p><strong>Conclusions: </strong>In summary, our study explores an initial link between amino acid metabolism and early-to-middle-stage MASLD. AGXT2⁻PYCR3⁻ macrophages are significantly enriched in MASLD with pro-inflammatory and pro-fibrotic potential, and amino acid supplementation can rescue their aberrant phenotypes in vitro, warranting further validation of their treatment potential.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-07-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148436310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Combining multiplexed functional data to improve variant classification.","authors":"Jeffrey D Calhoun, Moez Dawood, Charlie F Rowlands, Shawn Fayer, Elizabeth J Radford, Abbye E McEwen, Malvika Tejura, Clare Turnbull, Amanda B Spurdle, Lea M Starita, Sujatha Jagannathan","doi":"10.1186/s13073-026-01715-w","DOIUrl":"10.1186/s13073-026-01715-w","url":null,"abstract":"<p><strong>Background: </strong>With the surge in the number of variants of uncertain significance (VUS) reported in ClinVar in recent years, there is an imperative to resolve VUS at scale. Multiplexed assays of variant effect (MAVEs), which allow the functional consequence of 100s to 1000s of genetic variants to be measured in a single experiment, are emerging as a powerful source of evidence which can be used in clinical variant classification. Increasingly, multiple published MAVEs are available for the same gene, sometimes measuring different aspects of variant impact. When multiple functional roles of a gene need to be considered, combining data from multiple MAVEs may provide a more comprehensive measure of the consequence of a genetic variant, which could impact variant classifications.</p><p><strong>Methods: </strong>We curated published datasets from five MAVEs for the gene TP53, two MAVEs for LDLR and two MAVEs for PTEN. Statistical methods (principal component analysis), unsupervised learning (k-means clustering), and supervised learning (Naïve Bayes and random forest classifiers) were used to integrate multiple MAVE datasets. The utility of MAVE integration methods were assessed using standard metrics (sensitivity, specificity, etc) as well as evidence strength in a putative variant classification framework.</p><p><strong>Results: </strong>Here, we provide guidance for combining such multiplexed functional data, incorporating a stepwise process from data curation and collection to model generation and validation. We also present a web applet that allows users to test various methods for combining score sets from multiple assays, calculate integrated functional scores for all variants, and assess whether combining data enables the application of stronger evidence for pathogenicity or benignity. In general, supervised learning methods such as random forest led to improved variant classification as compared to any individual MAVE dataset.</p><p><strong>Conclusions: </strong>By following the steps outlined herein with appropriate guardrails, researchers can maximize the value of MAVEs, strengthen the functional evidence for clinical variant classification, and potentially uncover novel mechanisms of pathogenicity for clinically relevant genes.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13644118/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148420665","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":"Metagenomic analysis of blood virome in ischemic stroke reveals an increase in herpesvirus transcripts and host immune activation.","authors":"Michael D Clarke, Sarina Falcione, Roobina Boghozian, Raluca Todoran, Yiran Zhang, Maria Guadalupe C Real, Alexis StPierre, Twinkle Joy, Glen C Jickling","doi":"10.1186/s13073-026-01707-w","DOIUrl":"10.1186/s13073-026-01707-w","url":null,"abstract":"<p><strong>Background: </strong>Viral infections may influence stroke pathophysiology. Several infections have been linked to increased risk of stroke, however our understanding of these viral interactions with immune and host tissue is limited. We performed a transcriptomic analysis of the blood virome following ischemic stroke to study these interactions.</p><p><strong>Methods: </strong>Viruses were measured by RNA sequencing of blood from 37 patients with ischemic stroke and 32 matched controls. RNA reads are aligned against a human reference genome, as well as a comprehensive database of human virus genomes. Host gene expression following stroke is examined in relation to the presence of viral transcripts.</p><p><strong>Results: </strong>Viral RNAs were detected in the blood samples of both ischemic stroke and control groups. Viral reads with a prevalence > 3% and raw counts > 2 were from a total of 6 viral families. This included several human herpesviruses (HHVs), adenoviruses, and papillomaviruses, as well as human pegivirus, respiratory syncytial virus, and human endogenous retrovirus K (HERV-K). Combined, counts from HHVs were higher in stroke compared to control by a fold change of 2.13. Coinfection with multiple HHVs was more common in stroke, with a 1.23 fold increase in the number of detected herpesviruses. Reads from two viral genes were increased in stroke, UL95 from cytomegalovirus (CMV), and EBNA2 from Epstein-Barr virus (EBV). Genes associated with stroke, including APOE, C3, PDGF, and CXCL2 were differentially expressed in stroke samples which contained high counts of one or both of UL95 and EBNA2.</p><p><strong>Conclusion: </strong>Viral RNAs from multiple families can be detected within the human blood virome. HHV transcripts were the most abundant of viral RNAs detected. Among stroke patients, HHV transcripts were more prevalent, with higher counts, and indicated a higher rate of coinfection with multiple HHV species. Expression of the EBV gene EBNA2 and the CMV gene UL95 may relate to changes in immune gene expression following stroke. Further evaluation is needed to determine the effects that the human virome have on stroke risk, immune response to stroke, and long-term outcome.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13644114/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148420637","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":"Spatial ecology of breast cancer reveals co-evolution of proliferative and dormant niches.","authors":"Cenk Celik, William A Weston, Thais de Moraes-Lacerda, Eloise Withnell, Shi Pan, Tooki Chu, John Labbadia, Alexis R Barr, Maria Secrier","doi":"10.1186/s13073-026-01711-0","DOIUrl":"10.1186/s13073-026-01711-0","url":null,"abstract":"<p><strong>Background: </strong>Cancer progression involves not only uncontrolled proliferation but also the strategic entry of tumour cells into reversible (quiescent) or irreversible (senescent) states of cell cycle arrest (G0). These states can give rise to rare persister-like cancer cells that survive hostile tumour microenvironment conditions, facilitating drug resistance, metastasis and disease relapse. Despite their importance, identifying and understanding the mechanisms regulating these cell populations remains challenging.</p><p><strong>Methods: </strong>We leveraged single-cell and spatially profiled primary breast tumours to quantify G0 arrest and proliferation decisions in cancer cells, revealing molecular and spatial features associated with proliferation-G0 dynamics.</p><p><strong>Results: </strong>We uncovered a G0 persister-like state with reduced copy number alteration burden and hallmarks of dormancy, characterised by transcriptional reprogramming of stress response pathways and increased epithelial-mesenchymal plasticity. Spatial analyses revealed distinct ecological niches: G0 cells inhabited protective niches with complement pathway activity proximal to CXCL10+ macrophages and myofibroblastic cancer-associated fibroblasts (CAFs), whereas proliferative zones were associated with CLEC9A+ dendritic cells and PERK signalling, with distinct drug sensitivities.</p><p><strong>Conclusions: </strong>Our findings highlight key principles underpinning G0-proliferation dynamics and niche specialisation in breast cancer, offering novel insights into the spatial drivers of tumour heterogeneity and evolution.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13632142/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148420654","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":"Gene expression profiling enables refined parcellation of cortical layers in the heterogeneous human cerebral cortex.","authors":"Yanrong Wei, Youzhe He, Yuyang Liu, Langjian Zhu, Tiannan Feng, Zhiming Shen, Wu Wei, Longqi Liu, Lei Han, Lifang Wang","doi":"10.1186/s13073-026-01704-z","DOIUrl":"10.1186/s13073-026-01704-z","url":null,"abstract":"<p><strong>Background: </strong>Precise delineation of cortical layers is fundamental for understanding human brain organization, cell-type architecture, and disease-related tissue alterations. However, traditional anatomy-based methods often lack molecular resolution and suffer from inter-observer subjectivity.</p><p><strong>Methods: </strong>Here, we present gene expression-defined cortical layers (GD-Ls) using the BayesSpace algorithm, a high-resolution framework for cortical parcellation based on spatial transcriptomics.</p><p><strong>Results: </strong>Compared with traditional anatomy-based approaches, GD-Ls more accurately resolve laminar boundaries and capture fine-scale laminar heterogeneity, including sublayer-like domains within L1, L3, and L6, as well as a molecularly distinct transition zone at the gray-white matter interface. Validation across diverse cortical lobes, multiple spatial platforms, and independent healthy postmortem datasets demonstrates that GD-Ls capture the intrinsic molecular architecture of the cortex irrespective of tissue source. Furthermore, cross-species analyses show that this framework is extensible to macaque and mouse cortices. Crucially, GD-Ls successfully identify subtle laminar disorganization and aberrant cellular and molecular signatures in pathologically altered tissues, which are often missed by conventional histology.</p><p><strong>Conclusions: </strong>Together, GD-Ls provide an objective and reproducible tool for standardized cortical mapping and for identifying early pathological signatures in the human brain. The source code is available on GitHub ( https://github.com/YanrongWei/GD-Ls ).</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-07-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13360882/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148411519","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":"Circadian regulation of cardiovascular function: from physiology to clinical implications.","authors":"Deeksha Malhan, Stefano Ministrini, Jesse Chih-Wei Lin, Chao-Lun Lai, Angela Relógio","doi":"10.1186/s13073-026-01710-1","DOIUrl":"10.1186/s13073-026-01710-1","url":null,"abstract":"<p><p>Circadian rhythms play a crucial role in maintaining cardiovascular homeostasis, orchestrating fluctuations in blood pressure, heart rate variability, endothelial function, and systemic vascular tone. Disruptions of the circadian clock -arising from ageing, genetic predisposition, or environmental and lifestyle factors- can significantly elevate the risk of cardiovascular diseases, including hypertension, atherosclerosis, heart failure, and arrhythmias. This review examines the role of circadian regulation in cardiovascular physiology, from molecular clock networks and clock-controlled gene regulation to systemic cardiovascular physiology and clinical translation. We discuss how circadian disruption affects blood pressure, heart rate variability, and vascular health, through mechanisms including inflammation, mitochondrial dysfunction, and metabolic dysregulation. We further position circadian biology within the broader context of cardiovascular ageing and the molecular mechanisms that drive age-associated cardiovascular decline.Special attention is given to the role of inflamm-ageing in promoting atherosclerosis and acute cardiovascular events, as well as the impact of desynchrony between central and peripheral clocks on disease severity. Additionally, we highlight the circadian regulation of genes implicated in cardiovascular ageing and disease. Finally, we explore emerging research on the clinical implications of circadian misalignment, with a focus on therapeutic strategies such as chronotherapy, time-restricted eating, and physical activity. By integrating current evidence, this review provides a comprehensive perspective on leveraging circadian rhythms for the prevention and management of cardiovascular diseases.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"18 1","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13335258/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148396327","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":"Integration of genetic evidence to identify approved drug targets.","authors":"Samuel Moix, Marie C Sadler, Zoltán Kutalik","doi":"10.1186/s13073-026-01689-9","DOIUrl":"10.1186/s13073-026-01689-9","url":null,"abstract":"<p><strong>Background: </strong>Drugs targeting genes supported by human genetic evidence are more likely to succeed in clinical trials. While previous approaches have benchmarked individual methods such as genome-wide association studies (GWAS), rare variant burden testing, and quantitative trait locus (QTL)-informed Mendelian randomization, it remains unclear how best to integrate these signals for drug target discovery.</p><p><strong>Methods: </strong>We compared gene-prioritization strategies across 30 complex traits, evaluating their ability to recover approved drug targets compiled into lenient and moderate gold-standard sets from six curated databases. Gene-level association scores from GWAS, expression QTL, protein QTL, and exome-based analyses were integrated using five unsupervised approaches. Predictive performance was assessed with area under the receiver operating characteristic curve (AUROC) and enrichment-based statistics.</p><p><strong>Results: </strong>Across traits, GWAS alone ranked known drug targets on average ∼652 ranks (3.42%) above random expectation, and the minimum-rank-based integration strategy further improved performance by approximately ∼558 positions (2.93%), achieving the best AUROC in 23 of 30 traits. Genetic correlation and drug target overlap across trait pairs showed a significant positive association ([Formula: see text]). Cross-trait analyses further revealed that prioritization scores derived from related diseases could at times equal or even surpass a trait's own performance. For instance, coronary artery disease data improved the prediction of stroke targets ([Formula: see text]), while inflammatory bowel disease data enhanced the prioritization of chronic kidney disease targets ([Formula: see text]).</p><p><strong>Conclusions: </strong>These results demonstrate that using the strongest signal from complementary genetic prioritization methods, combined with information from genetically related traits, systematically strengthens drug target identification across complex diseases.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"18 1","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13335195/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148396435","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":"Tandem repeat polymorphisms are associated with brain structure: results of two large population-based studies.","authors":"Richard Mantey, Jialu Hu, Maryam Touhidinia, Tanzeem Butt, Ahmed Mokhtar Sidky, Roohollah Sobhani, Santiago Estrada, Kristian Haendler, Elena De Domenico, Marc Daniel Beyer, Monique Maria Bernadette Breteler, Nasir Ahmad Aziz","doi":"10.1186/s13073-026-01702-1","DOIUrl":"10.1186/s13073-026-01702-1","url":null,"abstract":"<p><strong>Background: </strong>Although genome-wide association studies (GWAS) have uncovered many genetic variants linked to brain structure, much of its heritability still remains unexplained. Short tandem repeats (STRs) are rarely considered in GWAS but may account for part of this \"missing heritability\". While the causal association of large pathogenic repeat expansions with a range of brain disorders is well established, the role of non-pathogenic STR variations in the general population is largely unknown. In this study, we systematically assessed the relationship between STR variations and brain imaging-derived phenotypes across the adult lifespan in the general population.</p><p><strong>Methods: </strong>We used targeted deep sequencing to genotype approximately 3,000 polymorphic STRs across 2,958 individuals (mean age: 54.1 years, range: 30-90 years, 57.1% women) from the population-based Rhineland Study in Bonn, Germany. STR sizes at 2940 loci were estimated using ExpansionHunter v5, while 45 brain imaging-derived phenotypes were obtained from 3T T1-weighted MRI scans using the FreeSurfer processing pipeline. Associations between STR lengths and neuroimaging phenotypes were assessed using multiple linear regression models, adjusting for age, sex, population stratification, and other relevant covariates. Significant findings were independently assessed for directional consistency in the UK Biobank Imaging Substudy (N = 38,879), leveraging available whole-genome sequencing data.</p><p><strong>Results: </strong>The expansion of an intronic AC repeat in PRR14L was associated with larger thalamic volume (standardized β [95% CI] = 0.15 [0.06-0.24]), while AATG repeat polymorphisms in NADK were associated with reduced subcortical gray matter volume (-0.05 [-0.08 to - 0.01]) and thalamic volume (-0.06 [-0.08 to - 0.04]). These associations were directionally consistent in the UK Biobank cohort. Beyond single loci, higher polygenic burden of moderate STR expansions was associated with increased total brain, gray matter, supratentorial, and thalamic volumes (all multiple-testing-corrected p < 0.05).</p><p><strong>Conclusions: </strong>Our findings indicate that moderate STR expansions are region-specific determinants of brain morphology and suggest that STR variability may have evolved to enhance neuroanatomical plasticity and cognitive function. By leveraging large population-based cohorts, our study extends current understanding of how repetitive genomic elements contribute to inter-individual variation in brain structure beyond the effects of single-nucleotide variation.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"18 1","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13335240/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148396464","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":"Correction: Longitudinal analysis of genetic and environmental interplay in human metabolic profiles and the implication for metabolic health.","authors":"Jing Wang, Alberto Zenere, Xingyue Wang, Göran Bergström, Fredrik Edfors, Mathias Uhlén, Wen Zhong","doi":"10.1186/s13073-026-01705-y","DOIUrl":"10.1186/s13073-026-01705-y","url":null,"abstract":"","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":"18 1","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13335180/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148396492","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":"RankVar: machine learning-based variant ranking and reinterpretation for rare genetic diseases.","authors":"Yuan Zhang, Mian Umair Ahsan, Peng Wang, Xiaoqi Lin, Ian M Campbell, Cong Liu, Wendy K Chung, Chunhua Weng, Kai Wang","doi":"10.1186/s13073-026-01701-2","DOIUrl":"10.1186/s13073-026-01701-2","url":null,"abstract":"<p><strong>Background: </strong>Prior biological knowledge and phenotype information can help identify disease genes from whole genome/exome sequencing studies, but how best to incorporate external knowledge with variant data remains challenging. We developed a machine learning algorithm called RankVar to prioritize causative variants for rare diseases, based on clinical notes and genome/exome sequencing profiles.</p><p><strong>Methods: </strong>RankVar uses a random forest classifier trained on ~ 1 million variants from the 1000 Genomes Project with spiked-in pathogenic variants. For testing, we compiled sequencing data and phenotype information from several independent datasets: 260 subjects from the Children's Hospital of Philadelphia (CHOP) with positive genetic diagnosis of various Mendelian diseases, 135 subjects from Birth Defects Biorepository (BDB), as well as 356 and 97 subjects with candidate causal variants for autism spectrum disorders from the Simons Simplex Collection (SSC) and the Simons Foundation Powering Autism Research for Knowledge (SPARK), respectively.</p><p><strong>Results: </strong>RankVar achieves a top 10 variant accuracy of 90.0%, 81.5%, 46.1%, and 76.3% for CHOP, BDB, SSC, and SPARK, respectively, with improved performance over existing approaches. Notably, RankVar successfully identified X-linked and Y-linked disease-causal variants, such as KDM6A (p.N915Kfs5*) and SRY (p.W98X), as the top candidate variants. Moreover, we evaluated RankVar for genomic reinterpretation of 130 unsolved CHOP cases with hearing loss and successfully identified 61 candidate causal variants after manual review.</p><p><strong>Conclusions: </strong>In summary, RankVar performed favorably relative to existing methods in our evaluation, accommodated different genetic models and X/Y chromosome variants, and may provide a useful framework for prioritizing variants in monogenic or oligogenic diseases. We anticipate that RankVar may aid in primary genetic diagnosis, genome reinterpretation of previously unsolved cases, and the discovery of novel disease genes.</p>","PeriodicalId":12645,"journal":{"name":"Genome Medicine","volume":" ","pages":""},"PeriodicalIF":10.8,"publicationDate":"2026-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13617915/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148387490","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}