Intra-familial phenotype variant in hypoplastic amelogenesis imperfecta under a complex genetic component: a family report, whole-exome sequencing, and literature review.

Abstract

Background: Amelogenesis imperfecta (AI) encompasses a group of conditions characterized by abnormalities in the development or function of tooth enamel. Clinical manifestations include different forms and degrees of enamel frailty, associated with sensitivity, tooth fractures, stains, abnormal tooth morphology, missing teeth, etc. AI is genetically heterogeneous, with over 70 genes associated with autosomal dominant, autosomal recessive, X-linked, and oligogenic inheritance.

Objective: To identify genetic variants associated with AI in a single family.

Methodology: We describe the clinical findings of a family affected by AI, composed of five individuals: four affected (the father and three daughters) and one unaffected (the mother). The observed segregation pattern suggests a dominant, X-linked inheritance. Genetic variants were screened using whole-exome sequencing. The initial bioinformatic analysis was conducted using Qiagen QCI, and variants were selected based on their presence in all four affected family members and absence in the unaffected mother. Search terms included "amelogenesis imperfecta," "tooth," and "enamel." Several types of software were used to classify variants according to pathogenicity.

Results: Candidate variants were identified in six genes. Three of these variants were detected in autosomal genes: NM_031889.3(ENAM):c.1726T>C (p.F576L), NM_022168.4(IFIH1):c.1764dupA, (p.A589fs*21), and NM_032383.5(HPS3):c.1897A>T (p.M633L). Three variants were detected in X-linked genes: NM_006150.5(PRICKLE3):c.8C>G (p.A3G), NM_004484.4(GPC3):c.584A>G (p.N195S), and NM_152787.5(TAB3):c.1936G>A (p.V646M). None of these variants were classified as pathogenic or likely pathogenic in AI.

Discussion: Among the identified genes, only ENAM has previously been associated with AI; however, IFIH1, PRICKLE3, and GPC3 are associated with dental/enamel development. The relatively high number of candidate genes and variants detected may reflect an oligogenic component already proposed for AI.

Conclusions: This study provides a set of new candidate genes and genetic variants for AI. Despite sharing the same variants, AI-affected family members show considerable phenotypic variant, suggesting the involvement of non-shared genetic or environmental factors.