Journal article
Artificial intelligence-driven genotype–epigenotype–phenotype approaches to resolve challenges in syndrome diagnostics
EBioMedicine, Vol.115, 105677
05/01/2025
DOI: 10.1016/j.ebiom.2025.105677
PMCID: PMC12242594
PMID: 40280028
Abstract
Background: Decisions to split two or more phenotypic manifestations related to genetic variations within the same gene can be challenging, especially during the early stages of syndrome discovery. Genotype-based diagnostics with artificial intelligence (AI)-driven approaches using next-generation phenotyping (NGP) and DNA methylation (DNAm) can be utilized to expedite syndrome delineation within a single gene. Methods: We utilized an expanded cohort of 56 patients (22 previously unpublished individuals) with truncating variants in the MN1 gene and attempted different methods to assess plausible strategies to objectively delineate phenotypic differences between the C-Terminal Truncation (CTT) and N-Terminal Truncation (NTT) groups. This involved transcriptomics analysis on available patient fibroblast samples and AI-assisted approaches, including a new statistical method of GestaltMatcher on facial photos and blood DNAm analysis using a support vector machine (SVM) model. Findings: RNA-seq analysis was unable to show a significant difference in transcript expression despite our previous hypothesis that NTT variants would induce nonsense mediated decay. DNAm analysis on nine blood DNA samples revealed an episignature for the CTT group. In parallel, the new statistical method of GestaltMatcher objectively distinguished the CTT and NTT groups with a low requirement for cohort number. Validation of this approach was performed on syndromes with known DNAm signatures of SRCAP, SMARCA2 and ADNP to demonstrate the effectiveness of this approach. Interpretation: We demonstrate the potential of using AI-based technologies to leverage genotype, phenotype and epigenetics data in facilitating splitting decisions in diagnosis of syndromes with minimal sample requirement. Funding: The specific funding of this article is provided in the acknowledgements section.
Details
- Title: Subtitle
- Artificial intelligence-driven genotype–epigenotype–phenotype approaches to resolve challenges in syndrome diagnostics
- Creators
- Christopher C.Y. Mak - University of Hong KongHannah KlinkhammerSanaa Choufani - Hospital for Sick ChildrenNikola Reko - Hospital for Sick ChildrenAngela K. Christman - University of WashingtonElise Pisan - Université Paris CitéMartin M.C. Chui - University of Hong KongMianne Lee - University of Hong KongFiona Leduc - Centre Hospitalier Universitaire de LilleJennifer C. Dempsey - University of WashingtonPedro A. Sanchez-LaraHannah M. Bombei - University of IowaJohn A. Bernat - University of IowaLaurence FaivreFrederic Tran Mau-ThemIrene Valenzuela Palafoll - Vall d'Hebron Hospital UniversitariNatalie Canham - Liverpool Women's HospitalAjoy Sarkar - Nottingham University Hospitals NHS TrustEwelina Bukowska-Olech - Poznan University of Medical SciencesYuri A. ZarateAleksander JamsheerBert CallewaertAndreas ZanklMarjolaine Willems - InsermLaura Duncan - Vanderbilt University Medical CenterBertrand Isidor - Institut du ThoraxBenjamin Cogne - Nantes UniversitéOdile Boute - Centre Hospitalier Universitaire de LilleClémence Vanlerberghe - Centre Hospitalier Universitaire de LilleAlice Goldenberg - InsermElliot Stolerman - Greenwood Genetic CenterKaren J. LowVianney Gilard - Centre Hospitalier Universitaire de RouenJeanne Amiel - Université Paris CitéAngela E. Lin - Massachusetts General HospitalChristopher T. Gordon - Université Paris CitéDan Doherty - University of WashingtonPeter M. Krawitz - University Hospital BonnRosanna WeksbergTzung-Chien HsiehBrian H.Y. Chung
- Resource Type
- Journal article
- Publication Details
- EBioMedicine, Vol.115, 105677
- DOI
- 10.1016/j.ebiom.2025.105677
- PMID
- 40280028
- PMCID
- PMC12242594
- NLM abbreviation
- EBioMedicine
- ISSN
- 2352-3964
- eISSN
- 2352-3964
- Publisher
- Elsevier
- Grant note
- Society for the Relief of Disabled Children, Commissioned Paediatric Research at HKCH under The Health and Medical Research FundAgence Nationale de la Recherche "Investissements d'Avenir" programMSDAvenirAXASimons Foundation Autism Research InitiativeNSW Genomics Collaborative GrantNIH Eunice Kennedy Shriver National Institute of Child Health and Human Development: U54HD083091 Poznan University of Medical Sciences, Poland ProScience 2022: 502-14-11261860-11962 National Institute for Health and Care Research Doctoral Research Fellowship: 302303 NIH: P50HD103524
We would like to thank the patients and families for their essential help with our work. We thank Dr Sarina Kant for her help in sample collection for DNA. This work was supported by grants from the Society for the Relief of Disabled Children, Commissioned Paediatric Research at HKCH under The Health and Medical Research Fund (PR-HKU-4), the Agence Nationale de la Recherche "Investissements d'Avenir" program (ANR-10-IAHU-01), MSDAvenir (Devo-Decode project) and AXA ("Tete et C oe ur" project). This work was supported by a Simons Foundation Autism Research Initiative (SFARI for RW) and an NSW Genomics Collaborative Grant (to AZ) and the NIH Eunice Kennedy Shriver National Institute of Child Health and Human Development (U54HD083091, Genetics Core). Bert Callewaert is a Senior Clinical Investigator of the Research Foundation-Flanders. E.B.O. was supported by the grant from Poznan University of Medical Sciences, Poland ProScience 2022 (502-14-11261860-11962). K.L. is supported by the National Institute for Health and Care Research Doctoral Research Fellowship 302303: The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. NIH P50HD103524 PI Sandra Juul, Genetics Core supported participant enrollment and clinical data collection for UW site. None of the sponsors had any role in the design and conduct of the study; collection, management, analysis and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.
- Language
- English
- Date published
- 05/01/2025
- Academic Unit
- Stead Family Department of Pediatrics; Medical Genetics and Genomics
- Record Identifier
- 9984816017502771
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