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Article Dans Une Revue Human Molecular Genetics Année : 2020

Metabolomics hallmarks OPA1 variants correlating with their in-vitro phenotype and predicting clinical severity

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Interpretation of variants of uncertain significance is an actual major challenge. We addressed this question on a set of OPA1 missense variants responsible for variable severity of neurological impairments. We used targeted metabolomics to explore the different signatures of OPA1 variants expressed in Opa1 deleted mouse embryonic fibroblasts (Opa1 −/− MEFs), grown under selective conditions. Multivariate analyses of data discriminated Opa1 +/+ from Opa1 −/− MEFs metabolic signatures and classified OPA1 variants according to their in vitro severity. Indeed, the mild p.I382M hypomorphic variant was segregating close to the wild-type allele, while the most severe p.R445H variant was close to Opa1 −/− MEFs, and the p.D603H and p.G439V alleles, responsible for isolated and syndromic presentations, respectively, were intermediary between the p.I382M and the p.R445H variants. The most discriminant metabolic features were hydroxyproline, the spermine/spermidine ratio, amino acid pool and several phospholipids, emphasizing proteostasis, endoplasmic reticulum (ER) stress and phospholipid remodeling as the main mechanisms ranking OPA1 allele impacts on metabolism. These results demonstrate the high resolving power of metabolomics in hierarchizing OPA1 missense mutations by their in vitro severity, fitting clinical expressivity. This suggests that our methodological approach can be used to discriminate the pathological significance of variants in genes responsible for other rare metabolic diseases and may be instrumental to select possible compounds eligible for supplementation treatment.
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hal-02543163 , version 1 (16-06-2020)

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Juan Manuel Chao Barca, Mario Fogazza, Michela Rugolo, Stéphanie Chupin, Valentina del Dotto, et al.. Metabolomics hallmarks OPA1 variants correlating with their in-vitro phenotype and predicting clinical severity. Human Molecular Genetics, 2020, 29, pp.1319-1329. ⟨10.1093/hmg/ddaa047⟩. ⟨hal-02543163⟩
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