Generation of DNA Methylation Signatures and Classification of Variants in Rare Neurodevelopmental Disorders Using EpigenCentral. Issue 11 (11th November 2022)

• Record Type: Journal Article
• Authors: Awamleh, Zain; Goodman, Sarah; Kallurkar, Prajkta; Wu, Wendy; Lu, Kevin; Choufani, Sanaa; Turinsky, Andrei L.; Weksberg, Rosanna
• Is Part Of: Current protocols. Volume 2:Issue 11(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-11-11
• Subjects: DNA methylation signatures -- episignatures -- neurodevelopmental disorders -- Mendelian disorders; Life sciences -- Laboratory manuals -- Periodicals; Biology -- Laboratory manuals -- Periodicals; Life sciences -- Technique -- Periodicals; Biology -- Technique -- Periodicals; 570.028
• DOI: 10.1002/cpz1.597
• Languages: English
• ISSNs: 2691-1299

Abstract

Abstract: There are more than 700 genes that encode proteins that function in epigenetic regulation and chromatin modification. Germline variants in these genes (typically heterozygous) are associated with rare neurodevelopmental disorders (NDDs) characterized by growth abnormalities and intellectual and developmental delay. Advancements in next‐generation sequencing have dramatically increased the detection of pathogenic sequence variants in genes encoding epigenetic machinery associated with NDDs and, concurrently, the number of clinically uninterpretable variants classified as variants of uncertain significance (VUS). Recently, DNA methylation (DNAm) signatures, disorder‐specific patterns of DNAm change, have emerged as a functional tool that provides insights into disorder pathophysiology and can classify pathogenicity of variants in NDDs. To date, our group and others have identified DNAm signatures for more than 60 Mendelian neurodevelopmental disorders caused by variants in genes encoding epigenetic machinery. There is broad interest in both the research and clinical communities to develop and catalog DNAm signatures in rare NDDs, but there are challenges in optimizing study design considerations and availability of platforms that integrate bioinformatics tools with the appropriate statistical framework required to analyze genome‐wide DNAm data. We previously published EpigenCentral, a platform for analysis of DNAm data in rare NDDs. In this article, we utilize the published Weaver syndrome dataset to provide step‐by‐step protocols for using EpigenCentral for exploratory analysis to identify DNAm signatures and for classification of NDD variants. We also provide important considerations for experimental design and interpretation of DNAm results. © 2022 Wiley Periodicals LLC. Basic Protocol 1 : Exploratory analysis to identify disorder‐specific DNAm signatures Basic Protocol 2 : Classification of variants associated with neurodevelopmental disorders