Information and analytical platform “Digital Phenotype” to identify the relationship between phenotypic and genetic data of patients with hereditary diseases

Abstract

This paper presents the possibilities of using the Information and Analytical Platform “Digital Phenotype” for a formalized quantitative description of the clinical manifestations of hereditary diseases in children based on deep phenotyping in order to analyze and identify geno-phenotypic correlations, form registers of hereditary diseases and improve the reliability of predicting the course of these diseases. The platform was developed on the basis of the combined use of expert deep phenotyping of a number of rare hereditary disabling diseases manifesting in childhood and modern information technologies for building web applications that allow entering and assessing the severity of phenotypic features, checking the correctness of the input data, forming search queries, exporting chosen digital data. The software design technology is based on the architecture of a relational data model using a cross-platform solution based on the Laravel-AngularJS-mySQL stack. The results of the application of statistical methods for the analysis of geno-phenotypic correlations are presented on the example of identifying the connection of lens dislocation with the presence of a missense mutation in Marfan syndrome. It was shown that in children with mutations at the C-terminus of the MECP2 protein, the level of blood phosphates is lower than in patients with mutations at the N-terminus of the protein.