ArticleHuman genetics2026
DNA methylation signatures from peripheral blood revealed epigenetic alterations in Fanconi anemia.
Article in Human genetics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
13 authors.
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Abstract
Fanconi Anemia (FA) is a rare autosomal recessive disorder; characterized by bone marrow failure, congenital malformation, and a markedly increased risk of cancers. Despite well characterized genetic defects in the FA/BRCA pathway, the mechanisms underlining variable disease severity and cancer susceptibility remains unknown. We studied the role of global DNA methylation and its implication in the cancer predisposition in FA. Chromosomal breakage analysis from peripheral blood cultures induced with Mitomycin C. Mutational analysis using NGS, MLPA and Sanger sequencing. Genome-wide DNA methylation profiling was performed using Illumina Infinium Methylation EPIC 850k Bead Chip Array and gene expression was validated by qPCR. Global DNA methylation profiling revealed a significant hyper-methylation pattern in FA patients as compared to the controls. Pathway enrichment and gene ontology analysis revealed the hyper-methylated genes were associated with the mTOR, WNT, cell adhesion and non-homologous end joining pathways, while hypo-methylated genes were enriched in NF-kb, MAPK, Calcium and JAK-STAT signalling pathways. Validation of top candidate genes showed significant downregulation of FAM65B, NKAPL, ITGAM, CDIP1 and CDKN1b genes which are involved in tumour suppression, immune regulation and cell-cycle control. Protein-Protein interaction analysis demonstrated that these genes are indirectly linked through the p53 and TNF- α signalling axes, contributing to a pro-inflammatory microenvironment that may promotes the emergence of pre-leukemic clones in FA. These results suggest that aberrant DNA methylation may play a role in cancer predisposition in FA by silencing key regulatory genes and may represent as promising candidates for prediction of cancer progression.
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