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In a previous pathway-based, extreme phenotype study, we identified 1064 variants associated with supravalvar aortic stenosis (SVAS) severity in people with Williams syndrome (WS) and either no SVAS or surgical SVAS. Here, we use those variants to develop and test polygenic risk scores (PRS). We used the clumping and thresholding (CT) approach on the full 1064 variants and a 427-variant subset that was part of 13 biologically relevant pathways identified in the previous study. We also used a lasso approach on the full set. We were able to achieve an area under the curve (AUC) of >0.99 for the two CT PRS methods, using only 622 and 320 variants respectively when 2/3 of the initial 217 participants data were used for training and 1/3 for testing. The lasso performed less well. We then evaluated the performance of those PRS variant sets on an additional group of 138 patients with WS with intermediate severity SVAS and found a misclassification rate of <10% between the surgical and intermediate groups, suggesting potential for clinical utility of the score., Competing Interests: Disclosures: The authors report no conflicts.

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.

Williams-Beuren syndrome (WBS) and 7q11.23 duplication syndrome (Dup7) are rare neurodevelopmental disorders caused by deletion and duplication of a 1.5 Mb region that includes at least five genes with a known role in epigenetic regulation. We have shown that CNV of this chromosome segment causes dose-dependent, genome-wide changes in DNA methylation, but the specific genes driving these changes are unknown. We measured genome-wide whole blood DNA methylation in six participants with atypical CNV of 7q11.23 (three with deletions and three with duplications) using the Illumina HumanMethylation450k array and compared their profiles with those from groups of individuals with classic WBS or classic Dup7 and with typically developing (TD) controls. Across the top 1000 most variable positions we found that only the atypical rearrangements that changed the copy number of GTF2IRD1 and/or GTF2I (coding for the TFII-IRD1 and TFII-I proteins) clustered with their respective syndromic cohorts. This finding was supported by results from hierarchical clustering across a selection of differentially methylated CpGs, in addition to pyrosequencing validation. These findings suggest that CNV of the GTF2I genes at the telomeric end of the 7q11.23 interval is a key contributor to the large changes in DNA methylation that are seen in blood DNA from our WBS and Dup7 cohorts, compared to TD controls. Our findings suggest that members of the TFII-I protein family are involved in epigenetic processes that alter DNA methylation on a genome-wide level., (© 2023. Springer Nature Limited and Centre of Excellence in Genomic Medicine Research, King Abdulaziz University.)