Abstract
BACKGROUND: Recent advances in sequencing technologies have enhanced patient diagnosis; however, causal pathogenic variants remain unidentified for a significant number of patients due to limited understanding of certain variants, regulatory sequences, or sequencing challenges, such as complex rearrangements. Investigating the epigenetic landscape has become essential to improve the diagnostic yield. Diseases caused by pathogenic variants in epigenetic regulators, often associated with growth abnormalities, intellectual disability, and facial dysmorphism, are prime models for studying episignatures. Among them, Snijders Blok-Campeau syndrome (ORPHA:599082), caused by pathogenic variants in the CHD3 gene, remains largely understudied. METHODS: A European cohort of 23 patients displaying typical Snijders Blok-Campeau syndrome traits and carrying pathogenic/likely pathogenic CHD3 variants was analysed using the Illumina EPIC array, identifying 270 differentially methylated positions distinguishing patients from 62 healthy matched controls. A subset of these regions serves as diagnostic tools for complex cases or variants of uncertain significance and helps uncover deregulated pathways linked to this syndrome. Four patients carrying pathogenic/likely pathogenic variants but with atypical clinical presentation, as well as 10 patients with variants of uncertain significance, were analysed as the testing set. RESULTS: Comparing methylomes of patients carrying pathogenic variants in CHD3, CHD7 (CHARGE syndrome, ORPHA:138), and CHD8 (Intellectual developmental disorder with autism and macrocephaly, ORPHA:642675) genes allows us to identify distinct subgroups with unique methylation profiles. This CHD3 DNA methylation signature aids in reclassifying variants and diagnosing atypical cases. CONCLUSIONS: Our findings advance the field of epigenetic signatures in rare diseases. We have opened new avenues for further investigation into subtypes defined by methylome assays (such as in the context of chromatinopathies), which could refine the phenotype spectrum and help predict patient outcomes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13073-026-01639-5.