Dataset Information

Target gene analyses of 39 amelogenesis imperfecta kindreds.

ABSTRACT: Previously, mutational analyses identified six disease-causing mutations in 24 amelogenesis imperfecta (AI) kindreds. We have since expanded the number of AI kindreds to 39, and performed mutation analyses covering the coding exons and adjoining intron sequences for the six proven AI candidate genes [amelogenin (AMELX), enamelin (ENAM), family with sequence similarity 83, member H (FAM83H), WD repeat containing domain 72 (WDR72), enamelysin (MMP20), and kallikrein-related peptidase 4 (KLK4)] and for ameloblastin (AMBN) (a suspected candidate gene). All four of the X-linked AI families (100%) had disease-causing mutations in AMELX, suggesting that AMELX is the only gene involved in the aetiology of X-linked AI. Eighteen families showed an autosomal-dominant pattern of inheritance. Disease-causing mutations were identified in 12 (67%): eight in FAM83H, and four in ENAM. No FAM83H coding-region or splice-junction mutations were identified in three probands with autosomal-dominant hypocalcification AI (ADHCAI), suggesting that a second gene may contribute to the aetiology of ADHCAI. Six families showed an autosomal-recessive pattern of inheritance, and disease-causing mutations were identified in three (50%): two in MMP20, and one in WDR72. No disease-causing mutations were found in 11 families with only one affected member. We conclude that mutation analyses of the current candidate genes for AI have about a 50% chance of identifying the disease-causing mutation in a given kindred.

SUBMITTER: Chan HC

PROVIDER: S-EPMC3292789 | biostudies-literature | 2011 Dec

REPOSITORIES: biostudies-literature

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Target gene analyses of 39 amelogenesis imperfecta kindreds.

Chan Hui-Chen HC Estrella Ninna M R P NM Milkovich Rachel N RN Kim Jung-Wook JW Simmer James P JP Hu Jan C-C JC

European journal of oral sciences 20111201

Previously, mutational analyses identified six disease-causing mutations in 24 amelogenesis imperfecta (AI) kindreds. We have since expanded the number of AI kindreds to 39, and performed mutation analyses covering the coding exons and adjoining intron sequences for the six proven AI candidate genes [amelogenin (AMELX), enamelin (ENAM), family with sequence similarity 83, member H (FAM83H), WD repeat containing domain 72 (WDR72), enamelysin (MMP20), and kallikrein-related peptidase 4 (KLK4)] and ...[more]

PMID: 22243262

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Project description:Amelogenesis imperfecta (AI) is the name given to a heterogeneous group of conditions characterized by inherited developmental enamel defects. AI enamel is abnormally thin, soft, fragile, pitted and/or badly discolored, with poor function and aesthetics, causing patients problems such as early tooth loss, severe embarrassment, eating difficulties, and pain. It was first described separately from diseases of dentine nearly 80 years ago, but the underlying genetic and mechanistic basis of the condition is only now coming to light. Mutations in the gene AMELX, encoding an extracellular matrix protein secreted by ameloblasts during enamel formation, were first identified as a cause of AI in 1991. Since then, mutations in at least eighteen genes have been shown to cause AI presenting in isolation of other health problems, with many more implicated in syndromic AI. Some of the encoded proteins have well documented roles in amelogenesis, acting as enamel matrix proteins or the proteases that degrade them, cell adhesion molecules or regulators of calcium homeostasis. However, for others, function is less clear and further research is needed to understand the pathways and processes essential for the development of healthy enamel. Here, we review the genes and mutations underlying AI presenting in isolation of other health problems, the proteins they encode and knowledge of their roles in amelogenesis, combining evidence from human phenotypes, inheritance patterns, mouse models, and in vitro studies. An LOVD resource (http://dna2.leeds.ac.uk/LOVD/) containing all published gene mutations for AI presenting in isolation of other health problems is described. We use this resource to identify trends in the genes and mutations reported to cause AI in the 270 families for which molecular diagnoses have been reported by 23rd May 2017. Finally we discuss the potential value of the translation of AI genetics to clinical care with improved patient pathways and speculate on the possibility of novel treatments and prevention strategies for AI.

Dataset Information

Target gene analyses of 39 amelogenesis imperfecta kindreds.

Publications

Target gene analyses of 39 amelogenesis imperfecta kindreds.

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