Identification of a robust DNA methylation signature for Fanconi anemia

Daria Pagliara, Andrea Ciolfi, Lucia Pedace, Sadegheh Haghshenas, Marco Ferilli, Michael A. Levy, Evelina Miele, Claudia Nardini, Camilla Cappelletti, Raissa Relator, Angela Pitisci, Rita De Vito, Simone Pizzi, Jennifer Kerkhof, Haley McConkey, Francesca Nazio, Sarina G. Kant, Maddalena Di Donato, Emanuele Agolini, Marta MatraxiaBarbara Pasini, Alessandra Pelle, Tiziana Galluccio, Antonio Novelli, Tahsin Stefan Barakat, Marco Andreani, Francesca Rossi, Cristina Mecucci, Anna Savoia, Bekim Sadikovic, Franco Locatelli*, Marco Tartaglia*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

1 Citation (Scopus)


Fanconi anemia (FA) is a clinically variable and genetically heterogeneous cancer-predisposing disorder representing the most common bone marrow failure syndrome. It is caused by inactivating predominantly biallelic mutations involving >20 genes encoding proteins with roles in the FA/BRCA DNA repair pathway. Molecular diagnosis of FA is challenging due to the wide spectrum of the contributing gene mutations and structural rearrangements. The assessment of chromosomal fragility after exposure to DNA cross-linking agents is generally required to definitively confirm diagnosis. We assessed peripheral blood genome-wide DNA methylation (DNAm) profiles in 25 subjects with molecularly confirmed clinical diagnosis of FA (FANCA complementation group) using Illumina's Infinium EPIC array. We identified 82 differentially methylated CpG sites that allow to distinguish subjects with FA from healthy individuals and subjects with other genetic disorders, defining an FA-specific DNAm signature. The episignature was validated using a second cohort of subjects with FA involving different complementation groups, documenting broader genetic sensitivity and demonstrating its specificity using the EpiSign Knowledge Database. The episignature properly classified DNA samples obtained from bone marrow aspirates, demonstrating robustness. Using the selected probes, we trained a machine-learning model able to classify EPIC DNAm profiles in molecularly unsolved cases. Finally, we show that the generated episignature includes CpG sites that do not undergo functional selective pressure, allowing diagnosis of FA in individuals with reverted phenotype due to gene conversion. These findings provide a tool to accelerate diagnostic testing in FA and broaden the clinical utility of DNAm profiling in the diagnostic setting.

Original languageEnglish
Pages (from-to)1938-1949
Number of pages12
JournalAmerican Journal of Human Genetics
Issue number11
Publication statusPublished - 2 Nov 2023

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© 2023 American Society of Human Genetics


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