The first report of a gross deletion in the SCNN1G gene in a case presenting with hyponatremic convulsion at fifth year of treatment
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Leyla Gizem Bolaç Özyılmaz
,
Ayberk Türkyılmaz
,
Özge Pelin Akbay
,
Aydilek Dağdeviren Çakır
and
Ahmet Uçar
Abstract
Objectives
Systemic pseudohypoaldosteronism type 1(PHA1) is a rare, autosomal recessive disorder resulting from loss-of-function mutations in epithelial sodium channel subunit genes. These mutations lead to aldosterone resistance in multiple tissues and typically manifest as hyponatremia, hyperkalemia, and metabolic acidosis.
Case presentation
We report the case of a male infant with a history of severe neonatal hyponatremia and hyperkalemia. The case presented to our center with persistent electrolyte imbalances and treatment-resistant eczematous skin lesions. Initial sequencing of PHA1-associated genes (SCNN1A, SCNN1B, and SCNN1G) did not reveal any pathogenic variants. At the age of five, the case experienced a febrile seizure, during which laboratory related biochemical tests showed isolated hyponatremia with normokalemia. Further genetic work-up with high-resolution chromosomal microarray analysis was performed, revealing a novel homozygous gross deletion involving exons 2–3 of the SCNN1G gene.
Conclusions
This is the first reported case of a homozygous gross deletion in the SCNN1G gene. This case expands the phenotypic and genotypic spectrum of systemic PHA1 and emphasizes the importance of considering copy number variants in genetically unresolved cases of PHA1, especially those presenting with atypical electrolyte profiles and extrarenal manifestations such as persistent eczema.
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Research ethics: The study was conducted in accordance with the Declaration of Helsinki. The local Institutional Review Board deemed the study exempt from review.
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Informed consent: Informed consent was obtained from the patient’s legal guardians.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors declare no conflicts of interest.
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Research funding: None declared.
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Data availability: Not applicable.
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