Rare DiseaseNCT07839754
EpiSign International: Expanding Epigenomic Testing in Rare Disease
An observational study of Rare Disease and Undiagnosed Disease, run by University of Manchester at 1 site in United Kingdom.
Trial summary
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. Read more about this study
- Who is it for?
- Any age
- Conditions the study is for
- Rare Disease, Undiagnosed Disease, Genetic Diseases, Inborn
- What is being tested?
- Integrated EPIC/CNV microarray with EpiSign analysis and EpiSign analysis with EPIC DNA methylation microarray
- How many people
- 192 participants
- Where
- 1 siteUnited Kingdom
- Study dates
- 1 Oct 2026to 31 Dec 2029
- Phase
- Observational
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Any age
- All sexes
- No healthy volunteers
- Child, Adult, Older adult
Study population: 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/CNV microarray.
Who may be able to join
- Eligible for, or have undergone, standard-of-care first-tier genetic testing at the participating site with a negative or inconclusive result.
- No established molecular or clinical diagnosis explaining their presentation.
- No diagnostic result from subsequent/reflex genetic testing available at enrolment.
- 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.
- For Phase 2 first-tier participants: meet the Phase 1 inclusion criteria.
- For Phase 2 CNV-positive participants, priority will be given to those with VUS, pathogenic/likely pathogenic, or other CNVs where EpiSign analysis may provide clinically relevant information.
Who cannot join
- Do not meet the applicable inclusion criteria.
- Isolated, non-syndromic autism or isolated learning disability without additional features suggestive of a syndromic rare disorder.
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United Kingdom1 site
Manchester Centre for Genomic Medicine, 6th Floor, St Mary's Hospital, Oxford Road
Manchester, UK, M13 9WL
James C McConnell, PhD, +441612765403, james.mcconnell@manchester.ac.uk
About this study
Official title: EpiSign International: Health System Impact Assessment and Expanding Clinical Utilization of Epi/Genomic Testing in Rare Diseases and Beyond
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.
The 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/CNV microarrays and evaluate the technical performance of these microarrays in detecting CNVs, as part of the diagnostic assessment of individuals with suspected rare diseases.
Patients 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.
Read the detailed description
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.
Diagnostic 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.
Patients 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.
There 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.
Epigenomic 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.
Research 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.
EpiSign™ 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% (237/732) 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% (312/1,667) had a positive result.
The 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.
This 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.
The 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.
Phase 2 will assess the utility of EpiSign analysis using a newly developed integrated EPIC/CNV 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.
Together, the two phases will provide evidence regarding the clinical utility of EpiSign analysis, the technical performance of the integrated EPIC/CNV microarray, and the potential impact of incorporating these approaches into diagnostic pathways for patients with suspected rare diseases.
- Being tested
- Integrated EPIC/CNV microarray with EpiSign analysis, EpiSign analysis with EPIC DNA methylation microarray
- Keywords
- Rare Disease, DNA Methylation, Rare Diseases, Copy Number Variation, DNA methylation microarray, Epigenetics, EPIC microarray, Undiagnosed rare disease
- Medical subject headings
- Rare Diseases, Undiagnosed Diseases, Genetic Diseases, Inborn, Congenital Abnormalities
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
Integrated EPIC/CNV microarray with EpiSign analysisDiagnostic test
Participants will undergo analysis using a newly developed integrated EPIC/CNV 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.
EpiSign analysis with EPIC DNA methylation microarrayDiagnostic test
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.
| Study group | Role | What they receive |
|---|---|---|
| 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. Receives: Diagnostic Test: EpiSign analysis with EPIC DNA methylation microarray | |
| Phase 2: Integrated EPIC/CNV Array and EpiSign | Participants will undergo analysis using a newly developed integrated EPIC/CNV 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. Receives: Diagnostic Test: Integrated EPIC/CNV microarray with EpiSign analysis |
What is being measured
The primary outcome is the main question the study is designed to answer.
Additional diagnostic yield of EpiSign analysis
Proportion (%) of participants for whom EpiSign identifies a relevant episignature that contributes to a molecular or clinical diagnosis.
Measured: Following completion of relevant genetic and EpiSign testing and collection of clinical data, expected approximately 12-18 months after study initiation.
Secondary outcomes (5)
Change in clinical management following EpiSign analysis
Proportion (%) of participants with a change in clinical management.
Measured: Following completion of relevant genetic and EpiSign testing and collection of clinical data, expected approximately 12-18 months after study initiation.
Change in diagnostic pathway following EpiSign analysis
Proportion (%) of participants with a change in diagnostic pathway.
Measured: Following completion of relevant genetic and EpiSign testing and collection of clinical data, expected approximately 12-18 months after study initiation.
Time to diagnosis following EpiSign analysis
Time in months.
Measured: Following completion of relevant genetic and EpiSign testing and collection of clinical data, expected approximately 12-18 months after study initiation.
Additional diagnostic investigations prompted by EpiSign analysis
Number of additional investigations per participant.
Measured: Following completion of relevant genetic and EpiSign testing and collection of clinical data, expected approximately 12-18 months after study initiation.
Genetic findings that would otherwise have remained unidentified
Proportion (%) of participants.
Measured: Following completion of relevant genetic and EpiSign testing and collection of clinical data, expected approximately 12-18 months after study initiation.
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted24 Sep 2026
- Study start1 Oct 2026 (estimated)
- Primary completion31 Dec 2028 (estimated)
- Study completion31 Dec 2029 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (5)Papers the sponsor has linked to this study.
- Other trials for Rare DiseaseStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 192 participants (estimated)
Sponsor and investigators
- Lead sponsor
- University of Manchester
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Siddharth Banka, University of Manchester
- Investigators
- Siddharth Banka, MBBS, MRCPCH, CCT, PhD, Prof, Principal investigator, University of Manchester
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07839754
- Sponsor's protocol ID
- IRAS 353927
- Status last verified
- Sep 2026
- First submitted
- 4 Sep 2026
- Last updated
- 24 Sep 2026
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Publications
Aref-Eshghi E, Bend EG, Colaiacovo S, Caudle M, Chakrabarti R, Napier M, Brick L, Brady L, Carere DA, Levy MA, Kerkhof J, Stuart A, Saleh M, Beaudet AL, Li C, Kozenko M, Karp N, Prasad C, Siu VM, Tarnopolsky MA, Ainsworth PJ, Lin H, Rodenhiser DI, Krantz ID, Deardorff MA, Schwartz CE, Sadikovic B. Diagnostic Utility of Genome-wide DNA Methylation Testing in Genetically Unsolved Individuals with Suspected Hereditary Conditions. Am J Hum Genet. 2019 Apr 4;104(4):685-700. doi: 10.1016/j.ajhg.2019.03.008. Epub 2019 Mar 28.
PubMed 30929737Levy MA, McConkey H, Kerkhof J, Barat-Houari M, Bargiacchi S, Biamino E, Bralo MP, Cappuccio G, Ciolfi A, Clarke A, DuPont BR, Elting MW, Faivre L, Fee T, Fletcher RS, Cherik F, Foroutan A, Friez MJ, Gervasini C, Haghshenas S, Hilton BA, Jenkins Z, Kaur S, Lewis S, Louie RJ, Maitz S, Milani D, Morgan AT, Oegema R, Ostergaard E, Pallares NR, Piccione M, Pizzi S, Plomp AS, Poulton C, Reilly J, Relator R, Rius R, Robertson S, Rooney K, Rousseau J, Santen GWE, Santos-Simarro F, Schijns J, Squeo GM, St John M, Thauvin-Robinet C, Traficante G, van der Sluijs PJ, Vergano SA, Vos N, Walden KK, Azmanov D, Balci T, Banka S, Gecz J, Henneman P, Lee JA, Mannens MMAM, Roscioli T, Siu V, Amor DJ, Baynam G, Bend EG, Boycott K, Brunetti-Pierri N, Campeau PM, Christodoulou J, Dyment D, Esber N, Fahrner JA, Fleming MD, Genevieve D, Kerrnohan KD, McNeill A, Menke LA, Merla G, Prontera P, Rockman-Greenberg C, Schwartz C, Skinner SA, Stevenson RE, Vitobello A, Tartaglia M, Alders M, Tedder ML, Sadikovic B. Novel diagnostic DNA methylation episignatures expand and refine the epigenetic landscapes of Mendelian disorders. HGG Adv. 2021 Dec 3;3(1):100075. doi: 10.1016/j.xhgg.2021.100075. eCollection 2022 Jan 13.
PubMed 35047860Aref-Eshghi E, Kerkhof J, Pedro VP; Groupe DI France; Barat-Houari M, Ruiz-Pallares N, Andrau JC, Lacombe D, Van-Gils J, Fergelot P, Dubourg C, Cormier-Daire V, Rondeau S, Lecoquierre F, Saugier-Veber P, Nicolas G, Lesca G, Chatron N, Sanlaville D, Vitobello A, Faivre L, Thauvin-Robinet C, Laumonnier F, Raynaud M, Alders M, Mannens M, Henneman P, Hennekam RC, Velasco G, Francastel C, Ulveling D, Ciolfi A, Pizzi S, Tartaglia M, Heide S, Heron D, Mignot C, Keren B, Whalen S, Afenjar A, Bienvenu T, Campeau PM, Rousseau J, Levy MA, Brick L, Kozenko M, Balci TB, Siu VM, Stuart A, Kadour M, Masters J, Takano K, Kleefstra T, de Leeuw N, Field M, Shaw M, Gecz J, Ainsworth PJ, Lin H, Rodenhiser DI, Friez MJ, Tedder M, Lee JA, DuPont BR, Stevenson RE, Skinner SA, Schwartz CE, Genevieve D, Sadikovic B. Evaluation of DNA Methylation Episignatures for Diagnosis and Phenotype Correlations in 42 Mendelian Neurodevelopmental Disorders. Am J Hum Genet. 2020 Mar 5;106(3):356-370. doi: 10.1016/j.ajhg.2020.01.019. Epub 2020 Feb 27.
PubMed 32109418Sadikovic B, Levy MA, Kerkhof J, Aref-Eshghi E, Schenkel L, Stuart A, McConkey H, Henneman P, Venema A, Schwartz CE, Stevenson RE, Skinner SA, DuPont BR, Fletcher RS, Balci TB, Siu VM, Granadillo JL, Masters J, Kadour M, Friez MJ, van Haelst MM, Mannens MMAM, Louie RJ, Lee JA, Tedder ML, Alders M. Clinical epigenomics: genome-wide DNA methylation analysis for the diagnosis of Mendelian disorders. Genet Med. 2021 Jun;23(6):1065-1074. doi: 10.1038/s41436-020-01096-4. Epub 2021 Feb 5.
PubMed 33547396Kerkhof J, Rastin C, Levy MA, Relator R, McConkey H, Demain L, Dominguez-Garrido E, Kaat LD, Houge SD, DuPont BR, Fee T, Fletcher RS, Gokhale D, Haukanes BI, Henneman P, Hilton S, Hilton BA, Jenkinson S, Lee JA, Louie RJ, Motazacker MM, Rzasa J, Stevenson RE, Plomp A, van der Laan L, van der Smagt J, Walden KK, Banka S, Mannens M, Skinner SA, Friez MJ, Campbell C, Tedder ML, Alders M, Sadikovic B. Diagnostic utility and reporting recommendations for clinical DNA methylation episignature testing in genetically undiagnosed rare diseases. Genet Med. 2024 May;26(5):101075. doi: 10.1016/j.gim.2024.101075. Epub 2024 Jan 18.
PubMed 38251460
Study at a glance
From the registry record, last updated by the sponsor on 24 Sep 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- EpiSign International: Health System Impact Assessment and Expanding Clinical Utilization of Epi/Genomic Testing in Rare Diseases and Beyond
- ClinicalTrials.gov ID
- NCT07839754
- Acronym / sponsor ID
- IRAS 353927
- Keywords
- Rare Disease, DNA Methylation, Rare Diseases, Copy Number Variation, DNA methylation microarray, Epigenetics, EPIC microarray, Undiagnosed rare disease
- Study type
- Observational
- Recruitment status
- Not yet recruiting
- Enrolment
- 192 participants (estimated)
- Lead sponsor
- University of ManchesterUniversity, hospital or other
- Study start
- 1 Oct 2026 (estimated)
- Primary completion
- 31 Dec 2028 (estimated)
- Study completion
- 31 Dec 2029 (estimated)
- First posted
- 24 Sep 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
The 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/CNV microarrays and evaluate the technical performance of these microarrays in detecting CNVs, as part of the diagnostic assessment of individuals with suspected rare diseases.
Patients 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.
Detailed description
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.
Diagnostic 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.
Patients 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.
There 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.
Epigenomic 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.
Research 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.
EpiSign™ 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% (237/732) 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% (312/1,667) had a positive result.
The 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.
This 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.
The 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.
Phase 2 will assess the utility of EpiSign analysis using a newly developed integrated EPIC/CNV 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.
Together, the two phases will provide evidence regarding the clinical utility of EpiSign analysis, the technical performance of the integrated EPIC/CNV microarray, and the potential impact of incorporating these approaches into diagnostic pathways for patients with suspected rare diseases.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| Phase 1: EpiSign with EPIC DNA Methylation Array | – | Diagnostic Test: EpiSign analysis with EPIC DNA methylation microarrayParticipants 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. |
| Phase 2: Integrated EPIC/CNV Array and EpiSign | – | Diagnostic Test: Integrated EPIC/CNV microarray with EpiSign analysisParticipants will undergo analysis using a newly developed integrated EPIC/CNV 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. |
Who may qualify
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child, Adult, Older adult
- Study population
- 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/CNV microarray.
Key inclusion criteria (6 listed)
- Eligible for, or have undergone, standard-of-care first-tier genetic testing at the participating site with a negative or inconclusive result.
- No established molecular or clinical diagnosis explaining their presentation.
- No diagnostic result from subsequent/reflex genetic testing available at enrolment.
- 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.
- For Phase 2 first-tier participants: meet the Phase 1 inclusion criteria.
Key exclusion criteria (2 listed)
- Do not meet the applicable inclusion criteria.
- Isolated, non-syndromic autism or isolated learning disability without additional features suggestive of a syndromic rare disorder.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| Integrated EPIC/CNV microarray with EpiSign analysisParticipants will undergo analysis using a newly developed integrated EPIC/CNV 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. | Diagnostic test | Phase 2: Integrated EPIC/CNV Array and EpiSign |
| EpiSign analysis with EPIC DNA methylation microarrayParticipants 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. | Diagnostic test | Phase 1: EpiSign with EPIC DNA Methylation Array |
Primary outcome
Additional diagnostic yield of EpiSign analysis
Time frame: Following completion of relevant genetic and EpiSign testing and collection of clinical data, expected approximately 12-18 months after study initiation.
Proportion (%) of participants for whom EpiSign identifies a relevant episignature that contributes to a molecular or clinical diagnosis.
5 secondary outcomes
Change in clinical management following EpiSign analysis
Time frame: Following completion of relevant genetic and EpiSign testing and collection of clinical data, expected approximately 12-18 months after study initiation.
Change in diagnostic pathway following EpiSign analysis
Time frame: Following completion of relevant genetic and EpiSign testing and collection of clinical data, expected approximately 12-18 months after study initiation.
Time to diagnosis following EpiSign analysis
Time frame: Following completion of relevant genetic and EpiSign testing and collection of clinical data, expected approximately 12-18 months after study initiation.
Additional diagnostic investigations prompted by EpiSign analysis
Time frame: Following completion of relevant genetic and EpiSign testing and collection of clinical data, expected approximately 12-18 months after study initiation.
Genetic findings that would otherwise have remained unidentified
Time frame: Following completion of relevant genetic and EpiSign testing and collection of clinical data, expected approximately 12-18 months after study initiation.
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 24 Sep 2026.
- Background: PubMed 30929737Aref-Eshghi E, Bend EG, Colaiacovo S, Caudle M, Chakrabarti R, Napier M, Brick L, Brady L, Carere DA, Levy MA, Kerkhof J, Stuart A, Saleh M, Beaudet AL, Li C, Kozenko M, Karp N, Prasad C, Siu VM, Tarnopolsky MA, Ainsworth PJ, Lin H, Rodenhiser DI, Krantz ID, Deardorff MA, Schwartz CE, Sadikovic B. Diagnostic Utility of Genome-wide DNA Methylation Testing in Genetically Unsolved Individuals with Suspected Hereditary Conditions. Am J Hum Genet. 2019 Apr 4;104(4):685-700. doi: 10.1016/j.ajhg.2019.03.008. Epub 2019 Mar 28.
- Background: PubMed 35047860Levy MA, McConkey H, Kerkhof J, Barat-Houari M, Bargiacchi S, Biamino E, Bralo MP, Cappuccio G, Ciolfi A, Clarke A, DuPont BR, Elting MW, Faivre L, Fee T, Fletcher RS, Cherik F, Foroutan A, Friez MJ, Gervasini C, Haghshenas S, Hilton BA, Jenkins Z, Kaur S, Lewis S, Louie RJ, Maitz S, Milani D, Morgan AT, Oegema R, Ostergaard E, Pallares NR, Piccione M, Pizzi S, Plomp AS, Poulton C, Reilly J, Relator R, Rius R, Robertson S, Rooney K, Rousseau J, Santen GWE, Santos-Simarro F, Schijns J, Squeo GM, St John M, Thauvin-Robinet C, Traficante G, van der Sluijs PJ, Vergano SA, Vos N, Walden KK, Azmanov D, Balci T, Banka S, Gecz J, Henneman P, Lee JA, Mannens MMAM, Roscioli T, Siu V, Amor DJ, Baynam G, Bend EG, Boycott K, Brunetti-Pierri N, Campeau PM, Christodoulou J, Dyment D, Esber N, Fahrner JA, Fleming MD, Genevieve D, Kerrnohan KD, McNeill A, Menke LA, Merla G, Prontera P, Rockman-Greenberg C, Schwartz C, Skinner SA, Stevenson RE, Vitobello A, Tartaglia M, Alders M, Tedder ML, Sadikovic B. Novel diagnostic DNA methylation episignatures expand and refine the epigenetic landscapes of Mendelian disorders. HGG Adv. 2021 Dec 3;3(1):100075. doi: 10.1016/j.xhgg.2021.100075. eCollection 2022 Jan 13.
- Background: PubMed 32109418Aref-Eshghi E, Kerkhof J, Pedro VP; Groupe DI France; Barat-Houari M, Ruiz-Pallares N, Andrau JC, Lacombe D, Van-Gils J, Fergelot P, Dubourg C, Cormier-Daire V, Rondeau S, Lecoquierre F, Saugier-Veber P, Nicolas G, Lesca G, Chatron N, Sanlaville D, Vitobello A, Faivre L, Thauvin-Robinet C, Laumonnier F, Raynaud M, Alders M, Mannens M, Henneman P, Hennekam RC, Velasco G, Francastel C, Ulveling D, Ciolfi A, Pizzi S, Tartaglia M, Heide S, Heron D, Mignot C, Keren B, Whalen S, Afenjar A, Bienvenu T, Campeau PM, Rousseau J, Levy MA, Brick L, Kozenko M, Balci TB, Siu VM, Stuart A, Kadour M, Masters J, Takano K, Kleefstra T, de Leeuw N, Field M, Shaw M, Gecz J, Ainsworth PJ, Lin H, Rodenhiser DI, Friez MJ, Tedder M, Lee JA, DuPont BR, Stevenson RE, Skinner SA, Schwartz CE, Genevieve D, Sadikovic B. Evaluation of DNA Methylation Episignatures for Diagnosis and Phenotype Correlations in 42 Mendelian Neurodevelopmental Disorders. Am J Hum Genet. 2020 Mar 5;106(3):356-370. doi: 10.1016/j.ajhg.2020.01.019. Epub 2020 Feb 27.
- Background: PubMed 33547396Sadikovic B, Levy MA, Kerkhof J, Aref-Eshghi E, Schenkel L, Stuart A, McConkey H, Henneman P, Venema A, Schwartz CE, Stevenson RE, Skinner SA, DuPont BR, Fletcher RS, Balci TB, Siu VM, Granadillo JL, Masters J, Kadour M, Friez MJ, van Haelst MM, Mannens MMAM, Louie RJ, Lee JA, Tedder ML, Alders M. Clinical epigenomics: genome-wide DNA methylation analysis for the diagnosis of Mendelian disorders. Genet Med. 2021 Jun;23(6):1065-1074. doi: 10.1038/s41436-020-01096-4. Epub 2021 Feb 5.
- Background: PubMed 38251460Kerkhof J, Rastin C, Levy MA, Relator R, McConkey H, Demain L, Dominguez-Garrido E, Kaat LD, Houge SD, DuPont BR, Fee T, Fletcher RS, Gokhale D, Haukanes BI, Henneman P, Hilton S, Hilton BA, Jenkinson S, Lee JA, Louie RJ, Motazacker MM, Rzasa J, Stevenson RE, Plomp A, van der Laan L, van der Smagt J, Walden KK, Banka S, Mannens M, Skinner SA, Friez MJ, Campbell C, Tedder ML, Alders M, Sadikovic B. Diagnostic utility and reporting recommendations for clinical DNA methylation episignature testing in genetically undiagnosed rare diseases. Genet Med. 2024 May;26(5):101075. doi: 10.1016/j.gim.2024.101075. Epub 2024 Jan 18.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
Siddharth Banka, MBBS, MRCPCH, CCT, PhD, Prof principal investigator
University of Manchester
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Rare Disease and Undiagnosed Disease, run by University of Manchester at 1 site in United Kingdom.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 6 inclusion and 2 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: opening soon, as of the sponsor's last update on 24 Sep 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United Kingdom. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact James C McConnell, PhD (+441612765403, james.mcconnell@mft.nhs.uk), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
Additional diagnostic yield of EpiSign analysis (time frame: Following completion of relevant genetic and EpiSign testing and collection of clinical data, expected approximately 12-18 months after study initiation.). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT07839754, which also lists 5 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 24 Sep 2026.