Autosomal Recessive Amelogenesis Imperfecta: clinical and genetic aspects
Amelogenesis imperfecta; Dental Enamel; Genes, Recessive; Molecular Diagnostic Techniques; Whole Exome Sequencing
Amelogenesis imperfecta (AI) is a genetic condition characterized by quantitative and/or qualitative alterations of tooth enamel. AI can manifest in isolation or as a manifestation of some syndrome. In recent years, variants in 26 genes have been identified in cases of IA. The aim of this study was to carry out the clinical characterization and molecular diagnosis of four families with diagnostic hypothesis of autosomal recessive IA (AIAR) being followed-up in the Centro de Atendimento Odontológico de Doenças Raras, of the Hospital Universitário de Brasília. Clinical records were evaluated, blood from patients and families was collected for DNA extraction by the salting out method, and sent for exome sequencing. New variants were validated by Sanger sequencing. Sequences were analyzed on the Varstation® platform from Varsomics and Frankliin, Genoox. After signing the free and informed consent form, six patients from five families, previously diagnosed with hypoplastic AI, underwent molecular examination. Biallelic or homozygous variants in 3 different genes were identified. Variants in the LTBP3 gene (c.85_105delCTGCTGCTGCTGCTGCTGCTG, p. Leu29_Leu35del; c.3214C>T, p. Gln1072Ter) were detected in one patient who also had skeletal changes. Two patients with renal changes had variants in FAM20A, (c.343_362delTCGCTCCTGGCCAGCCAGGA, p. Ser115Glyfs*48 and c.406C>T, p. Arg136*; c.1112G>A, p. Trp371*); two sisters with isolated AI had a variant in RELT (c.3214C>T, p. Gln1072Ter); and in one patient no pathogenic variants were identified. The results of this study extend the knowledge of the orodental phenotype of patients with isolated and syndromic AI in Distrito Federal and the spectrum of variants in LTBP3, FAM20A and RELT genes. Furthermore, they highlight the importance of detailed phenotypic characterization, and of the multiprofessional team in the diagnosis of patients with AI.