TY - JOUR T1 - Bioinformatics approach identified of novel genes of tuberculosis susceptibility JF - European Respiratory Journal JO - Eur Respir J DO - 10.1183/13993003.congress-2016.PA2725 VL - 48 IS - suppl 60 SP - PA2725 AU - Elena Bragina AU - Alexey Rudko AU - Evgeny Tiys AU - Nadezhda Babushkina AU - Vladimir Ivanisenko AU - Maxim Freidin Y1 - 2016/09/01 UR - http://erj.ersjournals.com/content/48/suppl_60/PA2725.abstract N2 - Tuberculosis (TB) is infection disease caused by Mycobacterium tuberculosis; however, genetic background of individuals shows influences on susceptibility to disease.Our goal is to establish the novel genes associated with TB using bioinformatics approach.We carried out the reconstruction of associative network representing links between proteins and genes involved in the development of TB. The associative network of TB was reconstructed using the ANDSystem software. For analysis of genes associated with TB from associative network we used genome databases (Ensembl, NCBI, HuGE Navigator). We used RegulomeDB to predict whether a variant affects transcription factor binding and gene expression.In the associative network, well studied proteins and genes with a decisive importance in the efficiency of the human immune response against a pathogen predominated. This approach identified 12 novel genes (ADA, CP, CD80, CXCR4, HCST, MUC16, CD69, PACRG, AGER, SPP1, CD4, CD79A) encoding for the proteins in the associative network polymorphisms of which has not been studied regarding the development of TB. The 328 promoter variants of novel TB genes have in varying degrees regulatory effect in accordance with the score assigned to the RegulomeDB. In addition 34 of them have maximum score assuming the maximum possible effect on gene expression.In this work, we identified 12 novel candidate for TB genes. In these genes we found 34 SNPs with possible effect on gene expression. Their validation may help to improve of knowledge of pathogenetic mechanisms of TB and solve the global problem of this disease treatment.This work is supported by the Russian Science Foundation under grant (15-15-00074). ER -