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The challenge of understanding and predicting phenotypic diversity in urea cycle disorders.

Authors :
Posset, Roland
Zielonka, Matthias
Gleich, Florian
Garbade, Sven F.
Hoffmann, Georg F.
Kölker, Stefan
Source :
Journal of Inherited Metabolic Disease; Nov2023, Vol. 46 Issue 6, p1007-1016, 10p
Publication Year :
2023

Abstract

The Urea Cycle Disorders Consortium (UCDC) and the European registry and network for Intoxication type Metabolic Diseases (E‐IMD) are the worldwide largest databases for individuals with urea cycle disorders (UCDs) comprising longitudinal data from more than 1100 individuals with an overall long‐term follow‐up of approximately 25 years. However, heterogeneity of the clinical phenotype as well as different diagnostic and therapeutic strategies hamper our understanding on the predictors of phenotypic diversity and the impact of disease‐immanent and interventional variables (e.g., diagnostic and therapeutic interventions) on the long‐term outcome. A new strategy using combined and comparative data analyses helped overcome this challenge. This review presents the mechanisms and relevant principles that are necessary for the identification of meaningful clinical associations by combining data from different data sources, and serves as a blueprint for future analyses of rare disease registries. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01418955
Volume :
46
Issue :
6
Database :
Complementary Index
Journal :
Journal of Inherited Metabolic Disease
Publication Type :
Academic Journal
Accession number :
173587051
Full Text :
https://doi.org/10.1002/jimd.12678