Novel Ameloblastin Variants, Contrasting Amelogenesis Imperfecta Phenotypes.

Amelogenesis imperfecta (AI) comprises a group of rare, inherited disorders with abnormal enamel formation. Ameloblastin (AMBN), the second most abundant enamel matrix protein (EMP), plays a critical role in amelogenesis. Pathogenic biallelic loss-of-function AMBN variants are known to cause recessive hypoplastic AI. A report of a family with dominant hypoplastic AI attributed to AMBN missense change p.Pro357Ser, together with data from animal models, suggests that the consequences of AMBN variants in human AI remain incompletely characterized. Here we describe 5 new pathogenic AMBN variants in 11 individuals with AI. These fall within 3 groups by phenotype. Group 1, consisting of 6 families biallelic for combinations of 4 different variants, have yellow hypoplastic AI with poor-quality enamel, consistent with previous reports. Group 2, with 2 families, appears monoallelic for a variant shared with group 1 and has hypomaturation AI of near-normal enamel volume with pitting. Group 3 includes 3 families, all monoallelic for a fifth variant, which are affected by white hypoplastic AI with a thin intact enamel layer. Three variants, c.209C>G; p.(Ser70*) (groups 1 and 2), c.295T>C; p.(Tyr99His) (group 1), and c.76G>A; p.(Ala26Thr) (group 3) were identified in multiple families. Long-read AMBN locus sequencing revealed these variants are on the same conserved haplotype, implying they originate from a common ancestor. Data presented therefore provide further support for possible dominant as well as recessive inheritance for AMBN-related AI and for multiple contrasting phenotypes. In conclusion, our findings suggest pathogenic AMBN variants have a more complex impact on human AI than previously reported.

Fluoride distribution and the effect of some ions along Alexandria coastal Mediterranean seawater of Egypt.

The coastal seawater of Mediterranean of Alexandria receives large amount of discharged waters containing industrial wastes, sewage, and agricultural and domestic drainage. Fluoride and some parameters were (chemical and physical) determined. The data gave indication that the content and the amount of the discharged water largely affect the chemical composition of the coastal water. Stepwise regression analysis was highly significant and the model was very fruitful, where the observed and calculated values were mostly concordant. This may indicated that there was a relation between fluoride content in coastal seawater and its content in the discharged water.