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Classifying molecular phenotypes of variants for pathogenic properties and to guide therapeutic development. | LitMetric

AI Article Synopsis

Article Abstract

Due to advances in sequencing technologies, identification of genetic variants is rapid. However, the functional consequences of most genomic variants remain unknown. Consequently, variants of uncertain significance (VUS) that appear in clinical DNA diagnostic reports lack sufficient data for interpretation. Algorithms exist to aid prediction of a variant's likelihood of pathogenicity, but these predictions usually lack empiric evidence. To examine the feasibility of generating functional evidence in vitro for a given variant's role in disease, a panel of 29 coding sequence variants in the gene was assessed. encodes glucose-6 phosphatase enzyme, and reduction in its function causes the rare metabolic disease glycogen storage disease type 1a (GSD1a). Variants were heterologously expressed as fusion proteins in a hepatocyte-derived cell line and examined for effects on steady-state protein levels, biosynthetic processing, and intracellular distribution. The screen revealed variant effects on protein levels, N-linked glycosylation status, and cellular distribution. Of the eight VUS tested, seven behaved similar to wild-type protein while one VUS, p.Cys109Tyr, exhibited features consistent with pathogenicity for all molecular phenotypes assayed, including significantly reduced protein levels, alteration in protein glycosylation status, and abnormally diffuse protein localization pattern, and has recently been reported in a patient with GSD1a. Our results show that such a screen can add empiric evidence to existing databases to aid in diagnostics, and also provides further classification for molecular phenotypes that could be used in future therapeutic screening approaches for small molecule or gene editing strategies directed at specific variants.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8260485PMC
http://dx.doi.org/10.1002/jmd2.12215DOI Listing

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