Format

Send to

Choose Destination
Am J Hum Genet. 2018 Jan 4;102(1):156-174. doi: 10.1016/j.ajhg.2017.12.008.

Genomic DNA Methylation Signatures Enable Concurrent Diagnosis and Clinical Genetic Variant Classification in Neurodevelopmental Syndromes.

Author information

1
Department of Pathology and Laboratory Medicine, Western University, London, ON N6A5C1, Canada; Molecular Genetics Laboratory, Molecular Diagnostics Division, London Health Sciences Centre, London, ON N6A5W9, Canada.
2
Departments of Pediatrics, Biochemistry and Oncology, Western University and Children's Health Research Institute, London, ON N6A5C1, Canada.
3
Department of Pathology and Laboratory Medicine, Western University, London, ON N6A5C1, Canada.
4
Greenwood Genetics Center, Greenwood, SC 29646, USA.
5
Department of Pathology and Molecular Medicine, McMaster University, Hamilton, ON L8S4L8, Canada.
6
Department of Biochemistry, Microbiology and Immunology, University of Ottawa, Ottawa, ON K1H8M5, Canada.
7
Children's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, ON K1H5B2, Canada.
8
Department of Pediatrics, University of Montreal, Montreal, QC H3T1J4, Canada.
9
Department of Pathology and Laboratory Medicine, Western University, London, ON N6A5C1, Canada; Molecular Genetics Laboratory, Molecular Diagnostics Division, London Health Sciences Centre, London, ON N6A5W9, Canada. Electronic address: bekim.sadikovic@lhsc.on.ca.

Abstract

Pediatric developmental syndromes present with systemic, complex, and often overlapping clinical features that are not infrequently a consequence of Mendelian inheritance of mutations in genes involved in DNA methylation, establishment of histone modifications, and chromatin remodeling (the "epigenetic machinery"). The mechanistic cross-talk between histone modification and DNA methylation suggests that these syndromes might be expected to display specific DNA methylation signatures that are a reflection of those primary errors associated with chromatin dysregulation. Given the interrelated functions of these chromatin regulatory proteins, we sought to identify DNA methylation epi-signatures that could provide syndrome-specific biomarkers to complement standard clinical diagnostics. In the present study, we examined peripheral blood samples from a large cohort of individuals encompassing 14 Mendelian disorders displaying mutations in the genes encoding proteins of the epigenetic machinery. We 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, we have demonstrated that a machine learning tool can be built to concurrently screen for multiple syndromes with high sensitivity and specificity, and we 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.

KEYWORDS:

ATRX syndrome; CHARGE syndrome; Claes-Jensen syndrome; Floating Harbor syndrome; Kabuki syndrome; Sotos syndrome; epigenomic machinery; machine learning; molecular diagnosis; pediatric developmental disorders

PMID:
29304373
PMCID:
PMC5777983
DOI:
10.1016/j.ajhg.2017.12.008
[Indexed for MEDLINE]
Free PMC Article

Supplemental Content

Full text links

Icon for Elsevier Science Icon for PubMed Central
Loading ...
Support Center