Use of whole genome sequencing to determine the genetic basis of visceral myopathies including Prune Belly syndrome

Abstract

Abstract Objectives/aims The visceral myopathies (VM) are a group of disorders characterised by poorly contractile or acontractile smooth muscle. They manifest in both the GI and GU tracts, ranging from megacystis to Prune Belly syndrome. We aimed to apply a bespoke virtual genetic panel and describe novel variants associated with this condition using whole genome sequencing data within the Genomics England 100,000 Genomes Project. Methods We screened the Genomics England 100,000 Genomes Project rare diseases database for patients with VM-related phenotypes. These patients were screened for sequence variants and copy number variants (CNV) in ACTG2, ACTA2, MYH11, MYLK, LMOD1, CHRM3, MYL9, FLNA and KNCMA1 by analysing whole genome sequencing data. The identified variants were analysed using variant effect predictor online tool, and any possible segregation in other family members and novel missense mutations was modelled using in silico tools. The VM cohort was also used to perform a genome-wide variant burden test in order to identify confirm gene associations in this cohort. Results We identified 76 patients with phenotypes consistent with a diagnosis of VM. The range of presentations included megacystis/microcolon hypoperistalsis syndrome, Prune Belly syndrome and chronic intestinal pseudo-obstruction. Of the patients in whom we identified heterozygous ACTG2 variants, 7 had likely pathogenic variants including 1 novel likely pathogenic allele. There were 4 patients in whom we identified a heterozygous MYH11 variant of uncertain significance which leads to a frameshift and a predicted protein elongation. We identified one family in whom we found a heterozygous variant of uncertain significance in KCNMA1 which in silico models predicted to be disease causing and may explain the VM phenotype seen. We did not find any CNV changes in known genes leading to VM-related disease phenotypes. In this phenotype selected cohort, ACTG2 is the largest monogenic cause of VM-related disease accounting for 9% of the cohort, supported by a variant burden test approach, which identified ACTG2 variants as the largest contributor to VM-related phenotypes. Conclusions VM are a group of disorders that are not easily classified and may be given different diagnostic labels depending on their phenotype. Molecular genetic analysis of these patients is valuable as it allows precise diagnosis and aids understanding of the underlying disease manifestations. We identified ACTG2 as the most frequent genetic cause of VM. We recommend a nomenclature change to ‘autosomal dominant ACTG2 visceral myopathy’ for patients with pathogenic variants in ACTG2 and associated VM phenotypes.