Investigation of the Clinical and Genetic Spectrum of PMM2-CDG: Insights from a Family with a Novel Variant and Previous Studies

光谱(功能分析) 遗传学 生物 医学 物理 量子力学
作者
Parnian Alagha,Tara Akhtarkhavari,Ebrahim Shokouhian,Fatemeh Ghodratpour,Sanaz Arzhangi,Hossein Najmabadi,Kimia Kahrizi
出处
期刊:Archives of Iranian Medicine [Academy of Medical Sciences, I.R. Iran]
卷期号:28 (7): 387-397
标识
DOI:10.34172/aim.34187
摘要

Background: PMM2-CDG, also known as congenital disorder of glycosylation type 1a, is the most common N-linked glycosylation disorder, characterized by a wide range of neurological and multisystem manifestations. Understanding the genotype-phenotype correlations is essential for accurate diagnosis and patient management. This study aims to identify the genetic cause of PMM2-CDG in an Iranian family with multiple affected members, and to analyze the genetic and clinical spectrum of the disorder through a comprehensive literature review. Methods: Exome sequencing re-analysis was performed to detect disease-causing variants in three affected siblings. Additionally, a literature review was conducted, analyzing 91 previously reported cases of PMM2-CDG to determine the most prevalent variants and associated clinical features. Results: A novel splice site variant (c.640-9T>A) was identified alongside a previously reported missense mutation (c.647A>T; p.N216I) in the affected individuals. The literature review revealed that the most frequent PMM2 variants were p.R141H (28.8%), p.V231M (12.8%), p.N216I (6.4%), and p.V129M (5.8%), with 77.6% of mutations occurring in exons 5 and 8. The most common clinical findings included developmental delay, ocular abnormalities (hypertelorism, strabismus), muscular system defects (hypotonia, muscle weakness), neurological symptoms (abnormal MRI findings), cardiovascular involvement (pericarditis, pericardial effusion), and clotting disorders. Conclusion: We expect that our detailed clinical study will improve the genotype-phenotype interpretation of causal PMM2-CDG variants and the analysis of next-generation sequencing data, leading to clarification of the cause of complicated cases of rare diseases.
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