Argininemia: Pathophysiology and Novel Methods for Evaluation of the Disease

Author:

Nteli Despoina1,Nteli Maria1,Konstantinidis Konstantinos1,Foka Anastasia1,Charisi Foteini1,Michailidou Iliana1,Stavropoulou De Lorenzo Sotiria1ORCID,Boziki Marina1ORCID,Tzitiridou-Chatzopoulou Maria2,Spandou Evangelia3,Simeonidou Constantina3,Bakirtzis Christos1ORCID,Kesidou Evangelia13ORCID

Affiliation:

1. Laboratory of Experimental Neurology and Neuroimmunology, 2nd Department of Neurology, AHEPA University Hospital, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54636 Thessaloniki, Greece

2. School of Healthcare Sciences, Midwifery Department, University of West Macedonia, Koila, 50150 Kozani, Macedonia, Greece

3. Laboratory of Physiology, Faculty of Health Sciences, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece

Abstract

Argininemia or arginase-1 deficiency constitutes a rare, genetic, metabolic disorder caused by mutations in arginase 1—the last enzyme of the urea cycle—that hydrolyses L-arginine to ornithine and urea. The disease is associated with progressive development of spasticity and other symptoms, including seizures, developmental delay, cognitive impairment, and hepatic pathology. The present review attempts to summarize the current knowledge on the pathophysiology of the disease and highlight novel methods for its evaluation. Different factors, such as the accumulation of arginine, ammonia, and guanidino compounds, act as neurotoxins and may account for the neurological sequelae observed in the disease. New markers, such as arginine/ornithine ratio along with metabolomics, machine learning algorithms, and genetic methods, can be useful in the early diagnosis of argininemia, while mobile phone apps can assist argininemic patients in adhering to the strict diet required. Neurophysiology, multi-modal imaging, and new modelling methods, such as induced pluripotent stem cells, hold promise for providing new insights into the pathophysiology of the disease. There are still many uncertainties regarding the underlying mechanisms of argininemia, but the use of novel modelling methods and new technology can lead to the decipherment of its pathophysiology, improvement of diagnostic accuracy, and better disease management.

Publisher

MDPI AG

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