Quantitative DNA Methylation Analysis and Epigenotype-Phenotype Correlations in Taiwanese Patients with...

Background: Silver-Russell syndrome (SRS; OMIM #180860) is a clinically and genetically heterogeneous imprinting disorder characterized by prenatal and postnatal growth failure. The aim of this study was to identify the epigenotype-phenotype correlations in these patients using quantitative DNA methylation analysis. Methods: One hundred and eighty-three subjects clinically suspected of having SRS were referred for diagnostic testing by the methylation profiling of H19-associated imprinting center (IC) 1 and imprinted PEG1/MEST regions using methylation-specific high-resolution melting analysis and methylation quantification with the MassARRAY assay. Correlations between quantitative DNA methylation status and clinical manifestations of the subjects according to the Netchine-Harbison (N-H) clinical scoring system for SRS were analyzed. Results: Among the 183 subjects, 90 had a clinical diagnosis of SRS [N-H score ≥ 4 (maximum = 6)] and 93 had an SRS score < 4. Molecular lesions were detected in 41% (37/90) of the subjects with a clinical diagnosis of SRS, compared with 3% (3/93) of those with an N-H score < 4. The IC1 methylation level was negatively correlated with the N-H score. The molecular diagnosis rate was positively correlated with the N-H score. Thirty-one subjects had IC1 hypomethylation (IC1 methylation level <35% by the MassARRAY assay), seven had maternal uniparental disomy 7, and two had pathogenic copy number variants. Among the 90 subjects with an N-H score ≥ 4, the IC1 methylation level was significantly different between those with or without some clinical SRS features, including birth length ≤ 10th centile, relative macrocephaly at birth, normal cognitive development, body asymmetry, clinodactyly of the fifth finger, and genital abnormalities. Conclusions: This study confirmed the suitability of the N-H clinical scoring system as clinical diagnostic criteria for SRS. Quantitative DNA methylation analysis using the MassARRAY assay can improve the detection of epigenotype-phenotype correlations, further promoting better genetic counseling and multidisciplinary management for these patients.