: 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.

Identification of a robust DNA methylation signature for Fanconi anemia / Pagliara, Daria; Ciolfi, Andrea; Pedace, Lucia; Haghshenas, Sadegheh; Ferilli, Marco; Levy, Michael A; Miele, Evelina; Nardini, Claudia; Cappelletti, Camilla; Relator, Raissa; Pitisci, Angela; De Vito, Rita; Pizzi, Simone; Kerkhof, Jennifer; Mcconkey, Haley; Nazio, Francesca; Kant, Sarina G; Di Donato, Maddalena; Agolini, Emanuele; Matraxia, Marta; Pasini, Barbara; Pelle, Alessandra; Galluccio, Tiziana; Novelli, Antonio; Barakat, Tahsin Stefan; Andreani, Marco; Rossi, Francesca; Mecucci, Cristina; Savoia, Anna; Sadikovic, Bekim; Locatelli, Franco; Tartaglia, Marco. - In: AMERICAN JOURNAL OF HUMAN GENETICS. - ISSN 1537-6605. - 110:11(2023), pp. 1938-1949. [10.1016/j.ajhg.2023.09.014]

Identification of a robust DNA methylation signature for Fanconi anemia

Ciolfi, Andrea;Pedace, Lucia;Ferilli, Marco;Miele, Evelina;Pizzi, Simone;Agolini, Emanuele;Novelli, Antonio;Savoia, Anna;
2023

Abstract

: 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.
2023
DNA methylation profiling; Fanconi anemia; classifier; diagnostic tool; episignature; gene conversion; hematological disorders; machine learning; mosaicism; variant classification
01 Pubblicazione su rivista::01a Articolo in rivista
Identification of a robust DNA methylation signature for Fanconi anemia / Pagliara, Daria; Ciolfi, Andrea; Pedace, Lucia; Haghshenas, Sadegheh; Ferilli, Marco; Levy, Michael A; Miele, Evelina; Nardini, Claudia; Cappelletti, Camilla; Relator, Raissa; Pitisci, Angela; De Vito, Rita; Pizzi, Simone; Kerkhof, Jennifer; Mcconkey, Haley; Nazio, Francesca; Kant, Sarina G; Di Donato, Maddalena; Agolini, Emanuele; Matraxia, Marta; Pasini, Barbara; Pelle, Alessandra; Galluccio, Tiziana; Novelli, Antonio; Barakat, Tahsin Stefan; Andreani, Marco; Rossi, Francesca; Mecucci, Cristina; Savoia, Anna; Sadikovic, Bekim; Locatelli, Franco; Tartaglia, Marco. - In: AMERICAN JOURNAL OF HUMAN GENETICS. - ISSN 1537-6605. - 110:11(2023), pp. 1938-1949. [10.1016/j.ajhg.2023.09.014]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1696213
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