Epigenetic Signatures Show Promise for Diagnosing Neurodevelopmental Disorders

In addition to constitutional disorders, they might find applications in cancer diagnostics.

Scientists at the Western University (London, ON, Canada) and their collaborators analyzed peripheral blood DNA samples from nearly 300 patients with one of 14 Mendelian conditions, all neurodevelopmental syndromes that have been associated with defects in epigenetic regulation as well as from approximately 650 healthy controls. To generate the DNA methylation profiles, they used Illumina's HumanMethylation450 bead chip or their Infinium methylation EPIC arrays.

The team demonstrated that specific but partially overlapping DNA methylation signatures are associated with many of these conditions. The degree of overlap among these epi-signatures is minimal, further suggesting that, consistent with the initial event, the downstream changes are unique to every syndrome. In addition, by combining these epi-signatures, they demonstrated that a machine learning tool can be built to concurrently screen for multiple syndromes with high sensitivity and specificity, and they highlight the utility of this tool in solving ambiguous case subjects presenting with variants of unknown significance, along with its ability to generate accurate predictions for subjects presenting with the overlapping clinical and molecular features associated with the disruption of the epigenetic machinery.

Bekim Sadikovic, PhD, DABMGG, FACMG, an associate professor of pathology and laboratory medicine and the lead investigator of the study said, “Once we introduce this in a clinical setting and start generating larger and larger databases, with clinical information linked to them, much like what happened with microarray testing and now exome sequencing, we will uncover what other genes or conditions may have these epi-signatures. I think the best way forward, from a discovery standpoint, is to put methylation testing into routine clinical use in these patient populations that normally get genomic profiles and allow the data itself to give us additional utility.” The study was published on January 4, 2018, in the American Journal of Human Genetics.

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