Journal
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
Volume 24, Issue 9, Pages -Publisher
MDPI
DOI: 10.3390/ijms24098021
Keywords
SGMS2 gene; bone fractures; low bone mineral density
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Calvarial doughnut lesions (CDL) with bone fragility is a rare autosomal dominant skeletal disorder characterized by low bone mineral density, fractures, and specific sclerotic lesions of the cranial bones. The disease is caused by pathogenic variants in the SGMS2 gene, with a recurrent variant c.148C>T (p.Arg50Ter) identified in multiple families. The phenotypic variability in patients with this variant highlights the importance of considering it in the diagnosis of the disease.
Calvarial doughnut lesions (CDL) with bone fragility with or without spondylometaphyseal dysplasia (MIM: #126550) is a rare autosomal dominant skeletal disorder characterized by low bone mineral density, spinal and peripheral fractures, and specific sclerotic lesions of the cranial bones. In the current classification of skeletal disorders, the disease is included in the group of bone fragility disorders along with osteogenesis imperfecta. The disease is caused by pathogenic variants in the SGMS2 gene, the protein product of which is sphingomyelin synthase 2, which primarily contributes to sphingomyelin (SM) synthesis-the main lipid component of the plasma membrane essential for bone mineralization. To date, 15 patients from eight families with CDL with bone fragility have been described in the literature, and a recurrent variant c.148C>T (p.Arg50Ter) in the SGMS2 gene has been identified, which was found in patients from six families. We diagnosed the disease in 11 more patients from three unrelated families, caused by the same heterozygous nonsense variant c.148C>T (p.Arg50Ter) in the SGMS2 gene. Our results show wide interfamilial and intrafamilial phenotypic variability in patients with a detected recurrent variant in the SGMS2 gene, the presence of which must be taken into consideration in the diagnosis of the disease. The primary analysis of this variant will contribute to optimal molecular genetic diagnostics, which can reduce diagnostic costs and time.
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