Blindness, hearing loss and brown crumbly teeth: determining the molecular basis of Heimler and Heimler plus syndromes and other related conditions.

Enamel is the body’s hardest, most mineralised tissue and protects the underlying tissues of the tooth from the forces exerted during mastication and from bacterial attack. Amelogenesis imperfecta (AI) is a heterogeneous group of genetic conditions that result in defective dental enamel formation. AI can present as either isolated disease or as part of a syndrome. This thesis documents the identification of the genes involved in Heimler syndrome (HS) and in hypomineralised AI. HS is an autosomal recessively inherited combination of sensorineural hearing loss, AI and variable nail abnormalities, with or without visual defects. Biallelic mutations in the peroxisomal biogenesis factor genes, PEX1 and PEX6 were identified through whole exome sequencing (WES) of ten HS patients from seven families. Both proteins were found to be present throughout the retina. Mutations in PEX1 and PEX6 were already known to cause the Zellweger syndrome spectrum disorders (ZSSD), a group of conditions of varying severity. HS represents a mild ZSSD and results from combinations of mutations that include at least one hypomorphic variant, leaving patients with some residual peroxisomal function. For two additional families, mutations in the Usher syndrome (USH) gene, USH2A, were identified, highlighting the phenotypic overlap of HS with the more common USH. One family with autosomal dominantly inherited hypomineralised AI was recruited and DNA from three affected individuals was subjected to WES. DNA copy number variant analysis identified a heterozygous in-frame deletion of exons 3-6 of amelotin. Exfoliated primary teeth from an affected family member had enamel that was of a lower mineral density compared to control enamel and exhibited structural defects. Some of this appeared to be associated with organic material as evidenced by elemental analysis. Both cases in this study highlight the heterogeneity of AI and the importance of a genetic diagnosis for the clinical management of patients.