[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"health-study-detail:100657447":3},{"organization":4,"outcomesModule":7,"designInfo":30,"detailedDescription":33,"studyPopulation":34,"armGroups":35,"interventions":46,"overallOfficials":56,"centralContacts":60,"locations":66,"responsibleParty":82,"collaborators":29,"id":85,"slug":86,"hasResults":87,"nctId":88,"briefTitle":89,"officialTitle":90,"acronym":29,"eligibilityCriteria":91,"healthyVolunteers":87,"sex":92,"minAge":29,"maxAge":29,"enrollmentInfo":93,"targetDuration":29,"studyType":96,"phases":29,"briefSummary":97,"conditions":98,"keywords":103,"overallStatus":111,"whyStopped":29,"lastUpdateSubmitDate":112,"lastUpdatePostDateStruct":113,"startDateStruct":116,"completionDateStruct":118,"leadSponsor":120,"locationsCount":121},{"fullName":5,"class":6},"University of Manchester","OTHER",{"primaryOutcomes":8,"secondaryOutcomes":13,"otherOutcomes":29},[9],{"measure":10,"description":11,"timeFrame":12},"Additional diagnostic yield of EpiSign analysis","Proportion (%) of participants for whom EpiSign identifies a relevant episignature that contributes to a molecular or clinical diagnosis.","Following completion of relevant genetic and EpiSign testing and collection of clinical data, expected approximately 12-18 months after study initiation.",[14,17,20,23,26],{"measure":15,"description":16,"timeFrame":12},"Change in clinical management following EpiSign analysis","Proportion (%) of participants with a change in clinical management.",{"measure":18,"description":19,"timeFrame":12},"Change in diagnostic pathway following EpiSign analysis","Proportion (%) of participants with a change in diagnostic pathway.",{"measure":21,"description":22,"timeFrame":12},"Time to diagnosis following EpiSign analysis","Time in months.",{"measure":24,"description":25,"timeFrame":12},"Additional diagnostic investigations prompted by EpiSign analysis","Number of additional investigations per participant.",{"measure":27,"description":28,"timeFrame":12},"Genetic findings that would otherwise have remained unidentified","Proportion (%) of participants.",null,{"allocation":29,"interventionModel":29,"interventionModelDescription":29,"primaryPurpose":29,"observationalModel":31,"timePerspective":32,"maskingInfo":29},"COHORT","PROSPECTIVE","Rare diseases are conditions that affect fewer than 1 in 2,000 individuals and can be serious, chronic or life-threatening. Collectively, rare diseases affect an estimated 3.5-5.9% of the global population, corresponding to approximately 236-446 million people worldwide, with new rare disorders continuing to be identified. Prenatal environmental exposures and maternal conditions may also be considered in the differential diagnosis of rare genetic disorders, as these can affect foetal development. Such factors include exposure to drugs and medications, lifestyle factors such as alcohol consumption, infectious agents, and maternal conditions including diabetes mellitus and epilepsy.\n\nDiagnostic assessment of patients with suspected rare disorders often includes chromosomal microarray analysis (CMA) to identify large structural copy number variations (CNVs), with an average diagnostic yield of approximately 10-15%. Where initial genomic testing is negative or inconclusive, further testing may include targeted gene panels, whole-exome sequencing (WES) or whole-genome sequencing (WGS). These approaches have substantially improved the diagnosis of rare diseases, but a significant proportion of patients remain unresolved following genomic testing. Some unresolved patients may have genetic variants of uncertain significance (VUS), while others may have disease-causing variants or disease mechanisms that are not readily identifiable using current genomic approaches.\n\nPatients with rare diseases may experience prolonged diagnostic journeys, with delays of several years and, in some cases, decades. Recent studies suggest that approximately 25% of patients in the UK may wait between five and thirty years for a final diagnosis, while global estimates of diagnostic delay range from approximately five to twelve years, with some patients remaining undiagnosed for up to thirty years. This diagnostic odyssey can have significant consequences for patients and their families, as well as for healthcare systems. Establishing a molecular diagnosis can inform clinical management, particularly for patients with genetically heterogeneous disorders or atypical presentations. Earlier diagnosis may facilitate timely access to appropriate treatment, surveillance and support, including during critical periods of development, with the potential to improve patient outcomes.\n\nThere is therefore a need for additional cost-effective, sensitive and specific approaches that can support the diagnosis of patients who remain unresolved or have ambiguous findings following conventional genomic testing. Such approaches may be particularly valuable where genetic and environmental factors contribute to disease presentation, or where clinical features are atypical or overlap between multiple disorders.\n\nEpigenomic approaches, and specifically DNA methylation analysis, provide one potential avenue for addressing this diagnostic gap. DNA methylation is a reversible epigenetic modification involving the addition of a methyl group to cytosine residues within CpG dinucleotides across the genome. DNA methylation has important roles in genomic imprinting, silencing of retroviral elements, regulation of tissue-specific gene expression, X-chromosome inactivation and chromatin structure. DNA methylation is also important during development, with dynamic changes in DNA methylation and demethylation contributing to the spatiotemporal regulation of gene expression, particularly during neuronal development.\n\nResearch has demonstrated that a number of rare genetic disorders and disorders associated with environmental exposures are characterised by distinctive patterns of DNA methylation at multiple genomic locations, known as episignatures. These reproducible patterns can provide additional diagnostic information and may assist in resolving ambiguous clinical cases, including cases involving VUSs in relevant genes or where a molecular diagnosis has not been established. Episignatures have been identified in association with both genetic and environmental aetiologies and can be detected in peripheral blood, an accessible and commonly used source of DNA for clinical diagnostic testing. An episignature is a recurring and reproducible DNA methylation pattern associated with a particular disease or aetiology. Although some DNA methylation changes overlap between rare disorders, the use of large reference datasets and advanced computational approaches enables the development of disease-specific episignature biomarkers with high sensitivity and specificity.\n\nEpiSign™ is a proprietary technology developed by EpiSign Inc. that combines machine-learning approaches with reference data from the EpiSign Knowledge Database (EKD), a large and continuously expanding database of DNA methylation profiles from individuals with rare diseases. As part of a broader diagnostic assessment, EpiSign analysis may provide additional information to physicians and diagnostic laboratories when evaluating patients with suspected rare disorders. For example, a recent study of 2,399 individuals with unsolved rare disorders reported a positivity rate of 32.4% (237\u002F732) among patients undergoing targeted assessment based on a previously identified genetic VUS or a suspected clinical diagnosis without a confirmed molecular diagnosis. Among patients undergoing comprehensive EpiSign analysis as a screening assay for known episignature disorders, 18.7% (312\u002F1,667) had a positive result.\n\nThe range of disorders assessed using EpiSign continues to expand as novel episignatures are identified and validated. New versions of the EpiSign assay undergo validation to establish the analytical performance of individual classifiers, including assessment using reference samples from the EKD and prospective testing within the EpiSign Services Laboratory Network. Cross-laboratory external quality assessment (EQA) and sample exchange programmes within this international clinically licensed laboratory network provide additional mechanisms for monitoring analytical performance, reproducibility and quality.\n\nThis study will assess the clinical utility and health-system impact of EpiSign as part of the diagnostic assessment of patients with suspected rare diseases. The study will quantify EpiSign positivity rates and assess its contribution to molecular and clinical diagnosis, as well as its impact on subsequent clinical and diagnostic pathways and associated healthcare costs. The study will generate prospective real-world evidence to inform the implementation of EpiSign within diagnostic pathways and to identify optimal implementation parameters across different health-system settings.\n\nThe study comprises two phases. Phase 1 will assess the clinical utility and health-system impact of EpiSign analysis using the standard commercial EPIC DNA methylation microarray platform as part of the diagnostic assessment of individuals with suspected rare diseases.\n\nPhase 2 will assess the utility of EpiSign analysis using a newly developed integrated EPIC\u002FCNV microarray and will additionally evaluate the technical performance and analytical yield of the integrated microarray in detecting CNVs alongside disease-associated DNA methylation patterns. This phase will provide evidence on the potential utility of combining DNA methylation and CNV analysis on a single microarray platform.\n\nTogether, the two phases will provide evidence regarding the clinical utility of EpiSign analysis, the technical performance of the integrated EPIC\u002FCNV microarray, and the potential impact of incorporating these approaches into diagnostic pathways for patients with suspected rare diseases.","Individuals with suspected rare diseases undergoing diagnostic assessment at Manchester University NHS Foundation Trust. The study population includes patients who have no established molecular or clinical diagnosis explaining their presentation and who have either negative or inconclusive results from standard-of-care genetic testing or a reported copy number variant (CNV) requiring further assessment. Participants will be recruited into two study phases: Phase 1 includes individuals undergoing first-tier EpiSign assessment using a standard DNA methylation microarray, while Phase 2 includes individuals undergoing EpiSign assessment using an integrated DNA methylation\u002FCNV microarray.",[36,41],{"label":37,"type":29,"description":38,"interventionNames":39},"Phase 1: EpiSign with EPIC DNA Methylation Array","Participants undergoing standard-of-care first-tier genetic testing who remain without an established diagnosis will undergo DNA methylation analysis using the standard EPIC microarray. DNA methylation data will be analysed using EpiSign to assess for disease-associated episignatures. EpiSign results will be evaluated alongside clinical and genetic information to assess diagnostic and clinical utility.",[40],"Diagnostic Test: EpiSign analysis with EPIC DNA methylation microarray",{"label":42,"type":29,"description":43,"interventionNames":44},"Phase 2: Integrated EPIC\u002FCNV Array and EpiSign","Participants will undergo analysis using a newly developed integrated EPIC\u002FCNV microarray, which enables assessment of both genome-wide DNA methylation and copy number variation from a single array. DNA methylation data will be analysed using EpiSign to assess for disease-associated episignatures, while CNV data will be assessed to evaluate the technical performance and analytical yield of the integrated array for CNV detection.",[45],"Diagnostic Test: Integrated EPIC\u002FCNV microarray with EpiSign analysis",[47,52],{"type":48,"name":49,"description":50,"armGroupLabels":51,"otherNames":29},"DIAGNOSTIC_TEST","Integrated EPIC\u002FCNV microarray with EpiSign analysis","Participants will undergo analysis using a newly developed integrated EPIC\u002FCNV microarray capable of measuring genome-wide DNA methylation and detecting copy number variations from a single array. DNA methylation data will be analysed using EpiSign software to identify disease-associated episignatures. CNV data will be analysed to assess the technical performance and analytical yield of the integrated microarray for CNV detection. The study will also assess the potential utility of combining DNA methylation and CNV analysis within a single diagnostic assay.",[42],{"type":48,"name":53,"description":54,"armGroupLabels":55,"otherNames":29},"EpiSign analysis with EPIC DNA methylation microarray","Participants will undergo genome-wide DNA methylation analysis using the standard Illumina EPIC DNA methylation microarray. The resulting DNA methylation data will be analysed using EpiSign software to identify disease-associated DNA methylation episignatures. EpiSign results will be assessed alongside clinical and genetic information to determine the additional diagnostic yield and clinical utility of EpiSign analysis in patients with suspected rare disease.",[37],[57],{"name":58,"affiliation":5,"role":59},"Siddharth Banka, MBBS, MRCPCH, CCT, PhD, Prof","PRINCIPAL_INVESTIGATOR",[61],{"name":62,"role":63,"phone":64,"phoneExt":29,"email":65},"James C McConnell, PhD","CONTACT","+441612765403","james.mcconnell@mft.nhs.uk",[67],{"facility":68,"status":29,"city":69,"state":70,"zip":71,"country":72,"countryCode":70,"cosmosGeoPoint":73,"geoPoint":78,"contacts":79},"Manchester Centre for Genomic Medicine, 6th Floor, St Mary's Hospital, Oxford Road","Manchester","UK","M13 9WL","United Kingdom",{"type":74,"coordinates":75},"Point",[76,77],-2.23743,53.48095,{"lat":77,"lon":76},[80],{"name":62,"role":63,"phone":64,"phoneExt":29,"email":81},"james.mcconnell@manchester.ac.uk",{"type":59,"investigatorFullName":83,"investigatorTitle":84,"investigatorAffiliation":5,"oldNameTitle":29,"oldOrganization":29},"Siddharth Banka","Professor of Genomic Medicine and Rare Diseases","100657447","episign-international-expanding-epigenomic-testing-in-rare-disease-100657447",false,"NCT07839754","EpiSign International: Expanding Epigenomic Testing in Rare Disease","EpiSign International: Health System Impact Assessment and Expanding Clinical Utilization of Epi\u002FGenomic Testing in Rare Diseases and Beyond","Inclusion Criteria:\n\n* Eligible for, or have undergone, standard-of-care first-tier genetic testing at the participating site with a negative or inconclusive result.\n* No established molecular or clinical diagnosis explaining their presentation.\n* No diagnostic result from subsequent\u002Freflex genetic testing available at enrolment.\n* For Phase 2 CNV-positive participants: have undergone standard-of-care CNV testing at the participating site and have a CNV reported by standard-of-care testing.\n* For Phase 2 first-tier participants: meet the Phase 1 inclusion criteria.\n* For Phase 2 CNV-positive participants, priority will be given to those with VUS, pathogenic\u002Flikely pathogenic, or other CNVs where EpiSign analysis may provide clinically relevant information.\n\nExclusion Criteria:\n\n* Do not meet the applicable inclusion criteria.\n* Isolated, non-syndromic autism or isolated learning disability without additional features suggestive of a syndromic rare disorder.","ALL",{"count":94,"type":95},192,"ESTIMATED","OBSERVATIONAL","The purpose of this study is to assess the utility of EpiSign software and an integrated DNA methylation and copy number variant (CNV) microarray technology in helping to diagnose individuals with rare diseases. EpiSign is a proprietary technology developed by EpiSign Inc. that uses DNA methylation patterns as biomarkers for rare diseases, including genetic disorders and conditions associated with environmental exposures. DNA methylation microarrays measure DNA methylation levels at specific locations across the genome. CNV microarray technology uses a similar approach to identify gains or losses of DNA. CNV microarray analysis is an established methodology used in the diagnosis of rare diseases.\n\nThe first phase of the study will assess the utility of EpiSign analysis using standard EPIC DNA methylation microarrays as part of the diagnostic assessment of individuals with suspected rare diseases. The second phase will assess the utility of EpiSign analysis using newly developed integrated EPIC\u002FCNV microarrays and evaluate the technical performance of these microarrays in detecting CNVs, as part of the diagnostic assessment of individuals with suspected rare diseases.\n\nPatients with suspected rare diseases will be recruited from Manchester University NHS Foundation Trust. Participants will provide a blood sample, which will be used to analyse their DNA methylation profile and detect CNVs. The study is expected to last approximately 24 months from study initiation.",[99,100,101,102],"Rare Disease","Undiagnosed Disease","Genetic Diseases, Inborn","Congenital Abnormalities",[99,104,105,106,107,108,109,110],"DNA Methylation","Rare Diseases","Copy Number Variation","DNA methylation microarray","Epigenetics","EPIC microarray","Undiagnosed rare disease","NOT_YET_RECRUITING","2026-09-23",{"date":114,"type":115},"2026-09-24","ACTUAL",{"date":117,"type":95},"2026-10-01",{"date":119,"type":95},"2029-12-31",{"name":5,"class":6},1]