DNA Methylation Characteristics for Recognizing Mowat-Wilson Syndrome

Background

Mowat-Wilson syndrome (MOWS) is a rare neurodevelopmental disorder caused by heterozygous deletions or loss-of-function mutations in the ZEB2 gene. This gene encodes a transcription factor involved in neural development. Individuals with MOWS often present with moderate to severe global developmental delay, intellectual disability, epilepsy, and characteristic facial phenotypes. Additionally, short stature, Hirschsprung’s disease, and brain and heart abnormalities may be present. However, the rarity of the syndrome and the diversity of phenotypes make its diagnosis more challenging in the neonatal period. To address this issue, researchers conducted a study aimed at simplifying the diagnostic process for MOWS by identifying a new diagnostic biomarker.

Paper Source

This study was jointly completed by researchers including Stefano Giuseppe Caraffi, Liselot van der Laan, Kathleen Rooney, and others from several internationally renowned institutions such as Azienda USL-IRCCS in Reggio Emilia, University of Amsterdam, and London Health Sciences Centre. The paper was published in the European Journal of Human Genetics, with an online publication date of February 13, 2024.

Research Process

Study Subjects and Grouping

The study included 29 individuals (17 females and 12 males) with clinically and molecularly confirmed MOWS. These individuals were randomly divided into two groups: a discovery group (n=24) and a validation group (n=5). All individuals had pathogenic or likely pathogenic variants in the ZEB2 gene, including large gene deletions, nonsense mutations, frameshift mutations, and missense mutations.

DNA Methylation Analysis

Genomic DNA was extracted from circulating leukocytes in peripheral blood and analyzed for DNA methylation using Illumina Infinium MethylationEPIC BeadChip Arrays. The process included quality control, feature selection, normalization, and background correction. After rigorous probe comparison and performance checks, 772,557 probes were retained for subsequent analysis.

Data Analysis

DNA methylation data analysis was performed using previously published methods. First, matched control groups were selected from the Episign Knowledge Database by comparing gender, age, batch, and array type. Then, feature selection and differential methylation analysis were conducted. Finally, MOWS-specific DNA methylation characteristics were validated through multidimensional scaling analysis and hierarchical clustering analysis.

Construction of Prediction Model

To improve the accuracy of the classification model, researchers trained a classifier model for MOWS using the support vector machine algorithm. This model uses selected features to classify samples and generates a Methylation Variant Pathogenicity (MVP) score ranging from 0 to 1, indicating the similarity of a sample to the methylation characteristics of the MOWS cohort.

Research Results

MOWS-Specific DNA Methylation Characteristics

The study identified and validated MOWS-specific DNA methylation characteristics, including 296 differentially methylated probes. These probes mainly showed hypomethylation, consistent with ZEB2’s primary role as a transcriptional repressor. Additionally, the study found that differential methylation of the ZEB2 gene itself supports the hypothesis of its self-regulatory capacity.

Result Validation

Through analysis of 5 case samples in the validation group, the study further confirmed the MOWS-specific DNA methylation characteristics. The support vector machine classifier yielded high MVP scores (>0.75) for all test samples, validating the reliability of the MOWS-specific DNA methylation characteristics.

Comparison with Other Disease Characteristics

To explore the intersection of MOWS DNA methylation characteristics with other neurodevelopmental disorders, the study compared MOWS DNA methylation characteristics with specific methylation characteristics of 56 other diseases. Results showed that MOWS characteristics were highly specific, with very low overlap rates with methylation probes of other diseases, with a maximum of 10-11% overlap with CHARGE syndrome and BAFopathies.

Research Significance and Value

By defining convincing and reproducible DNA methylation characteristics for MOWS, the study provides a highly sensitive diagnostic molecular marker. The findings of this study not only help establish diagnostic tools for MOWS but will also play an important role in the pioneering clinical diagnostic test “episode classifier” for rare Mendelian genetic disorders. Furthermore, the research provides an informative tool for reclassifying missense variants of uncertain functional significance. This study also offers new insights into understanding the molecular mechanisms of ZEB2 deficiency, which is expected to guide further molecular pathophysiological research on this disorder.

Future research will focus on exploring DNA methylation patterns in MOWS individuals with ambiguous genotype detection results and/or atypical clinical phenotypes, with the aim of further confirming and expanding the findings of this study.