Cargando…

BAFopathies’ DNA methylation epi-signatures demonstrate diagnostic utility and functional continuum of Coffin–Siris and Nicolaides–Baraitser syndromes

Coffin–Siris and Nicolaides–Baraitser syndromes (CSS and NCBRS) are Mendelian disorders caused by mutations in subunits of the BAF chromatin remodeling complex. We report overlapping peripheral blood DNA methylation epi-signatures in individuals with various subtypes of CSS (ARID1B, SMARCB1, and SMA...

Descripción completa

Detalles Bibliográficos
Autores principales: Aref-Eshghi, Erfan, Bend, Eric G., Hood, Rebecca L., Schenkel, Laila C., Carere, Deanna Alexis, Chakrabarti, Rana, Nagamani, Sandesh C. S., Cheung, Sau Wai, Campeau, Philippe M., Prasad, Chitra, Siu, Victoria Mok, Brady, Lauren, Tarnopolsky, Mark A., Callen, David J., Innes, A. Micheil, White, Susan M., Meschino, Wendy S., Shuen, Andrew Y., Paré, Guillaume, Bulman, Dennis E., Ainsworth, Peter J., Lin, Hanxin, Rodenhiser, David I., Hennekam, Raoul C., Boycott, Kym M., Schwartz, Charles E., Sadikovic, Bekim
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6244416/
https://www.ncbi.nlm.nih.gov/pubmed/30459321
http://dx.doi.org/10.1038/s41467-018-07193-y
Descripción
Sumario:Coffin–Siris and Nicolaides–Baraitser syndromes (CSS and NCBRS) are Mendelian disorders caused by mutations in subunits of the BAF chromatin remodeling complex. We report overlapping peripheral blood DNA methylation epi-signatures in individuals with various subtypes of CSS (ARID1B, SMARCB1, and SMARCA4) and NCBRS (SMARCA2). We demonstrate that the degree of similarity in the epi-signatures of some CSS subtypes and NCBRS can be greater than that within CSS, indicating a link in the functional basis of the two syndromes. We show that chromosome 6q25 microdeletion syndrome, harboring ARID1B deletions, exhibits a similar CSS/NCBRS methylation profile. Specificity of this epi-signature was confirmed across a wide range of neurodevelopmental conditions including other chromatin remodeling and epigenetic machinery disorders. We demonstrate that a machine-learning model trained on this DNA methylation profile can resolve ambiguous clinical cases, reclassify those with variants of unknown significance, and identify previously undiagnosed subjects through targeted population screening.