Genome-Wide DNA Methylation Profiling Solves Uncertainty in Classifying NSD1 Variants

索托斯综合征 遗传学 置信区间 生物 表型 基因组 生物信息学 计算生物学 基因 医学 内科学
作者
Marco Ferilli,Andrea Ciolfi,Lucia Pedace,Marcello Niceta,Francesca Clementina Radio,Simone Pizzi,Evelina Miele,Camilla Cappelletti,Cecilia Mancini,Tiziana Galluccio,Marco Andreani,Maria Iascone,Luigi Chiriatti,Antonio Novelli,Alessia Micalizzi,Marta Matraxia,Lucia Menale,Flavio Faletra,Paolo Prontera,Alba Pilotta
出处
期刊:Genes [Multidisciplinary Digital Publishing Institute]
卷期号:13 (11): 2163-2163 被引量:8
标识
DOI:10.3390/genes13112163
摘要

Background: Inactivating NSD1 mutations causing Sotos syndrome have been previously associated with a specific genome-wide DNA methylation (DNAm) pattern. Sotos syndrome is characterized by phenotypic overlap with other overgrowth syndromes, and a definite diagnosis might not be easily reached due to the high prevalence of variants of unknown significance (VoUS) that are identified in patients with a suggestive phenotype. Objective: we performed microarray DNAm profiling in a set of 11 individuals with a clinical suspicion of Sotos syndrome and carrying an NSD1 VoUS or previously unreported variants to solve uncertainty in defining pathogenicity of the observed variants. The impact of the training cohort size on sensitivity and prediction confidence of the classifier was assessed. Results: The Sotos syndrome-specific DNAm signature was validated in six individuals with a clinical diagnosis of Sotos syndrome and carrying bona fide pathogenic NSD1 variants. Applying this approach to the remaining 11 individuals with NSD1 variants, we succeeded in confirming pathogenicity in eight subjects and excluding the diagnosis of Sotos syndrome in three. The sensitivity and prediction confidence of the classifier based on the different sizes of the training sets did not show substantial differences, though the overall performance was improved by using a data balancing strategy. Conclusions: The present approach solved uncertainty in cases with NDS1 VoUS, further demonstrating the clinical utility of DNAm profiling.
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