RESUMEN
Autosomal dominant Kabuki syndrome (KS) is a rare multiple congenital anomalies/neurodevelopmental disorder caused by heterozygous inactivating variants or structural rearrangements of the lysine-specific methyltransferase 2D (KMT2D) gene. While it is often recognizable due to a distinctive gestalt, the disorder is clinically variable, and a phenotypic scoring system has been introduced to help clinicians to reach a clinical diagnosis. The phenotype, however, can be less pronounced in some patients, including those carrying postzygotic mutations. The full spectrum of pathogenic variation in KMT2D has not fully been characterized, which may hamper the clinical classification of a portion of these variants. DNA methylation (DNAm) profiling has successfully been used as a tool to classify variants in genes associated with several neurodevelopmental disorders, including KS. In this work, we applied a KS-specific DNAm signature in a cohort of 13 individuals with KMT2D VUS and clinical features suggestive or overlapping with KS. We succeeded in correctly classifying all the tested individuals, confirming diagnosis for three subjects and rejecting the pathogenic role of 10 VUS in the context of KS. In the latter group, exome sequencing allowed to identify the genetic cause underlying the disorder in three subjects. By testing five individuals with postzygotic pathogenic KMT2D variants, we also provide evidence that DNAm profiling has power to recognize pathogenic variants at different levels of mosaicism, identifying 15% as the minimum threshold for which DNAm profiling can be applied as an informative diagnostic tool in KS mosaics.
Asunto(s)
Anomalías Múltiples , Metilación de ADN , Proteínas de Unión al ADN , Cara , Enfermedades Hematológicas , Mosaicismo , Proteínas de Neoplasias , Enfermedades Vestibulares , Humanos , Enfermedades Vestibulares/genética , Enfermedades Vestibulares/diagnóstico , Cara/anomalías , Enfermedades Hematológicas/genética , Enfermedades Hematológicas/diagnóstico , Anomalías Múltiples/genética , Anomalías Múltiples/diagnóstico , Proteínas de Unión al ADN/genética , Masculino , Femenino , Proteínas de Neoplasias/genética , Niño , Preescolar , Adolescente , Mutación de Línea Germinal , Lactante , Fenotipo , AdultoRESUMEN
BACKGROUND: Supravalvar aortic stenosis (SVAS) is a characteristic feature of Williams-Beuren syndrome (WBS). Its severity varies: ~20% of people with Williams-Beuren syndrome have SVAS requiring surgical intervention, whereas ~35% have no appreciable SVAS. The remaining individuals have SVAS of intermediate severity. Little is known about genetic modifiers that contribute to this variability. METHODS AND RESULTS: We performed genome sequencing on 473 individuals with Williams-Beuren syndrome and developed strategies for modifier discovery in this rare disease population. Approaches include extreme phenotyping and nonsynonymous variant prioritization, followed by gene set enrichment and pathway-level association tests. We next used GTEx v8 and proteomic data sets to verify expression of candidate modifiers in relevant tissues. Finally, we evaluated overlap between the genes/pathways identified here and those ascertained through larger aortic disease/trait genome-wide association studies. We show that SVAS severity in Williams-Beuren syndrome is associated with increased frequency of common and rarer variants in matrisome and immune pathways. Two implicated matrisome genes (ACAN and LTBP4) were uniquely expressed in the aorta. Many genes in the identified pathways were previously reported in genome-wide association studies for aneurysm, bicuspid aortic valve, or aortic size. CONCLUSIONS: Smaller sample sizes in rare disease studies necessitate new approaches to detect modifiers. Our strategies identified variation in matrisome and immune pathways that are associated with SVAS severity. These findings suggest that, like other aortopathies, SVAS may be influenced by the balance of synthesis and degradation of matrisome proteins. Leveraging multiomic data and results from larger aorta-focused genome-wide association studies may accelerate modifier discovery for rare aortopathies like SVAS.