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ARV1 mutation is known to present as developmental and epileptic encephalopathy (DEE)-38. However, the phenotypic spectrum has been expanding ever since it was reported in 2016. Along with seizures and developmental delay, other unique clinical features include ophthalmological abnormalities and movement disorders in the form of ataxia and dystonia, especially in those with missense mutation. These manifestations closely mimic ataxia telangiectasia. Elevation of alpha-fetoprotein levels is an important investigative marker in the diagnosis of ataxia telangiectasia and ataxia with oculomotor apraxia syndromes. ARV1 can also be associated with increased alpha-fetoprotein. There are no reports evaluating alpha-fetoprotein levels in cases with ARV1 mutation, which is significant in the context of ocular abnormalities with ataxia. We report a case of ARV1 mutation presenting with ataxia, ocular abnormalities, and elevated alpha-fetoprotein levels, thus mimicking autosomal recessive cerebellar ataxias. This study provides a comprehensive literature review of the cases reported so far, thus expanding the understanding of the spectrum of presentation, and helps in correlating the clinical picture with the underlying causative genetic mutation. ARV1 gene is another example of one gene with phenotypic pleiotropy. Though presentation with DEE is common, a few, especially those with missense mutations, can present with ataxia and ocular abnormalities. All cases presenting with ataxia who have increased alpha-fetoprotein levels and seizures should be tested for the ARV1 gene, when testing for ataxia genes is negative. The underlying genetic mechanism can explain the varying clinical manifestations of the ARV1 gene.

Determination of genetic interaction networks (GINs) surrounding drug targets identifies buffering genes and provides molecular insight into drug response in individuals. Here we used backcross methodology to create Saccharomyces cerevisiae deletion libraries in three genetic backgrounds resistant to statins, which are additional to the statin-sensitive S288C deletion library that has provided much of what is known about GINs in eukaryotes. Whole genome sequencing and linkage group analysis confirmed the genomic authenticity of the new deletion libraries. Statin response was probed by drug-gene interactions with atorvastatin and cerivastatin treatments, as well as gene-gene interactions with the statin target HMG1 and HMG2 genes or the sterol homeostatic ARV1 gene. The 20 GINs generated from these interactions were not conserved by function or topology across the four genetic backgrounds. Centrality measures and hierarchical agglomerative clustering identified master regulators that if removed collapsed the networks. Community structure distinguished a characteristic early secretory pathway pattern of gene usage in each genetic background. ER stress in statin-resistant backgrounds was buffered by protein folding genes, which was confirmed by reduced activation of the unfolded protein response in statin-resistant backgrounds relative to the statin-sensitive S288C background. These network analyses of new gene deletion libraries provide insight into the complexity of GINs underlying individual drug response.