Predicting the disease severity in male individuals with ornithine transcarbamylase deficiency

for the Urea Cycle Disorders Consortium (UCDC) and the European registry and network for Intoxication type Metabolic Diseases (E-IMD) Consortia Study Group

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: Ornithine transcarbamylase deficiency (OTC-D) is an X-linked metabolic disease and the most common urea cycle disorder. Due to high phenotypic heterogeneity, ranging from lethal neonatal hyperammonemic events to moderate symptoms and even asymptomatic individuals, the prediction of the disease course at an early disease stage is very important to individually adjust therapies such as medical treatment or liver transplantation. In this translational study, we developed a severity-adjusted classification system based on in vitro residual enzymatic OTC activity. Methods: Applying a cell-based expression system, residual enzymatic OTC activities of 71 pathogenic OTC variants were spectrophotometrically determined and subsequently correlated with clinical and biochemical outcome parameters of 119 male individuals with OTC-D (mOTC-D) as reported in the UCDC and E-IMD registries. Results: Integration of multiple data sources enabled the establishment of a robust disease prediction model for mOTC-D. Residual enzymatic OTC activity not only correlates with age at first symptoms, initial peak plasma ammonium concentration and frequency of metabolic decompensations but also predicts mortality. The critical threshold of 4.3% residual enzymatic activity distinguishes a severe from an attenuated phenotype. Interpretation: Residual enzymatic OTC activity reliably predicts the disease severity in mOTC-D and could thus serve as a tool for severity-adjusted evaluation of therapeutic strategies and counselling patients and parents.

Original languageEnglish
Pages (from-to)1715-1726
Number of pages12
JournalAnnals of Clinical and Translational Neurology
Volume9
Issue number11
DOIs
StatePublished - Nov 2022

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