Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2020 Dec 6;21(23):9303.
doi: 10.3390/ijms21239303.

Diagnostic Utility of Genome-Wide DNA Methylation Analysis in Mendelian Neurodevelopmental Disorders

Sadegheh Haghshenas  1   2 , Pratibha Bhai  2 , Erfan Aref-Eshghi  3 , Bekim Sadikovic  1   2   4
Affiliations
Review

Diagnostic Utility of Genome-Wide DNA Methylation Analysis in Mendelian Neurodevelopmental Disorders

Sadegheh Haghshenas et al. Int J Mol Sci. .

Abstract

Mendelian neurodevelopmental disorders customarily present with complex and overlapping symptoms, complicating the clinical diagnosis. Individuals with a growing number of the so-called rare disorders exhibit unique, disorder-specific DNA methylation patterns, consequent to the underlying gene defects. Besides providing insights to the pathophysiology and molecular biology of these disorders, we can use these epigenetic patterns as functional biomarkers for the screening and diagnosis of these conditions. This review summarizes our current understanding of DNA methylation episignatures in rare disorders and describes the underlying technology and analytical approaches. We discuss the computational parameters, including statistical and machine learning methods, used for the screening and classification of genetic variants of uncertain clinical significance. Describing the rationale and principles applied to the specific computational models that are used to develop and adapt the DNA methylation episignatures for the diagnosis of rare disorders, we highlight the opportunities and challenges in this emerging branch of diagnostic medicine.

Keywords: DNA methylation; constitutional disorders; epigenetics; episignature; machine learning; neurodevelopmental disorders; overgrowth with intellectual disability syndromes; random forest; support vector machines.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Summary of a DNA methylation analysis and constructing the classification model.
Figure 2
Figure 2
Classification of unresolved cases. (A) Six individuals suspected of having mental retardation, X-linked syndromic, Claes-Jensen-type (MRXSCJ) were supplied to the multi-class support vector machine (SVM) classifier. The methylation variant pathogenicity (MVP) scores generated by the model illustrate that 4 individuals are classified as cases of MRXSCJ, one as not having any of the 15 syndromes, and one (the red one) is classified as a Sotos syndrome 1 (Sotos1) case. (B) The multiple dimensional scaling (MDS) plot with MRXSCJ samples (purple circles), healthy control samples (green circles), and Sotos1 samples (red circles). This plot illustrates the clustering of four of the individuals described in panel A with the MRXSCJ case samples (blue circles) and two individuals separate from the MRXSCJ case samples. The grey circle represents the patient classified as not having any of the 15 syndromes, and the pink circle depicts the individual classified as a Sotos1 case.
See this image and copyright information in PMC

References

    1. Wakap S.N., Lambert D.M., Olry A., Rodwell C., Gueydan C., Lanneau V., Murphy D., Le Cam Y., Rath A. Estimating cumulative point prevalence of rare diseases: Analysis of the Orphanet database. Eur. J. Hum. Genet. 2020;28:165–173. doi: 10.1038/s41431-019-0508-0. - DOI - PMC - PubMed
    1. Tatton-Brown K., Loveday C., Yost S., Clarke M., Ramsay E., Zachariou A., Elliott A., Wylie H., Ardissone A., Rittinger O., et al. Mutations in Epigenetic Regulation Genes Are a Major Cause of Overgrowth with Intellectual Disability. Am. J. Hum. Genet. 2017;100:725–736. doi: 10.1016/j.ajhg.2017.03.010. - DOI - PMC - PubMed
    1. Parenti I., Rabaneda L.G., Schoen H., Novarino G. Neurodevelopmental Disorders: From Genetics to Functional Pathways. Trends Neurosci. 2020;43:608–621. doi: 10.1016/j.tins.2020.05.004. - DOI - PubMed
    1. Aref-Eshghi E., Rodenhiser D.I., Schenkel L.C., Lin H., Skinner C., Ainsworth P., Paré G., Hood R.L., Bulman D.E., Kernohan K.D., et al. Genomic DNA Methylation Signatures Enable Concurrent Diagnosis and Clinical Genetic Variant Classification in Neurodevelopmental Syndromes. Am. J. Hum. Genet. 2018;102:156–174. doi: 10.1016/j.ajhg.2017.12.008. - DOI - PMC - PubMed
    1. Hood R.L., Lines M.A., Nikkel S.M., Schwartzentruber J., Beaulieu C., Nowaczyk M.J.M., Allanson J., Kim C.A., Wieczorek D., Moilanen J.S., et al. Mutations in SRCAP, encoding SNF2-related CREBBP activator protein, cause Floating-Harbor syndrome. Am. J. Hum. Genet. 2012;90:308–313. doi: 10.1016/j.ajhg.2011.12.001. - DOI - PMC - PubMed

MeSH terms