Evaluation of DNA Methylation Episignatures for Diagnosis and Phenotype Correlations in 42 Mendelian Neurodevelopmental Disorders.

Fiche publication

Date publication

février 2020

Journal

American journal of human genetics

Auteurs

Membres identifiés du Cancéropôle Est :
Pr FAIVRE Laurence , Pr THAUVIN-ROBINET Christel

Tous les auteurs :
Aref-Eshghi E, Kerkhof J, Pedro VP, ,Barat-Houari M, Ruiz-Pallares N, Andrau JC, Lacombe D, Van-Gils J, Fergelot P, Dubourg C, Cormier-Daire V, Rondeau S, Lecoquierre F, Saugier-Veber P, Nicolas G, Lesca G, Chatron N, Sanlaville D, Vitobello A, Faivre L, Thauvin-Robinet C, Laumonnier F, Raynaud M, Alders M, Mannens M, Henneman P, Hennekam RC, Velasco G, Francastel C, Ulveling D, Ciolfi A, Pizzi S, Tartaglia M, Heide S, Héron D, Mignot C, Keren B, Whalen S, Afenjar A, Bienvenu T, Campeau PM, Rousseau J, Levy MA, Brick L, Kozenko M, Balci TB, Siu VM, Stuart A, Kadour M, Masters J, Takano K, Kleefstra T, de Leeuw N, Field M, Shaw M, Gecz J, Ainsworth PJ, Lin H, Rodenhiser DI, Friez MJ, Tedder M, Lee JA, DuPont BR, Stevenson RE, Skinner SA, Schwartz CE, Genevieve D, Sadikovic B

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/32109418

Résumé

Genetic syndromes frequently present with overlapping clinical features and inconclusive or ambiguous genetic findings which can confound accurate diagnosis and clinical management. An expanding number of genetic syndromes have been shown to have unique genomic DNA methylation patterns (called "episignatures"). Peripheral blood episignatures can be used for diagnostic testing as well as for the interpretation of ambiguous genetic test results. We present here an approach to episignature mapping in 42 genetic syndromes, which has allowed the identification of 34 robust disease-specific episignatures. We examine emerging patterns of overlap, as well as similarities and hierarchical relationships across these episignatures, to highlight their key features as they are related to genetic heterogeneity, dosage effect, unaffected carrier status, and incomplete penetrance. We demonstrate the necessity of multiclass modeling for accurate genetic variant classification and show how disease classification using a single episignature at a time can sometimes lead to classification errors in closely related episignatures. We demonstrate the utility of this tool in resolving ambiguous clinical cases and identification of previously undiagnosed cases through mass screening of a large cohort of subjects with developmental delays and congenital anomalies. This study more than doubles the number of published syndromes with DNA methylation episignatures and, most significantly, opens new avenues for accurate diagnosis and clinical assessment in individuals affected by these disorders.