Novel tuberculosis susceptibility candidate genes revealed by the reconstruction and analysis of associative networks

Elena Yu Bragina; Evgeny S Tiys; Alexey A Rudko; Vladimir A Ivanisenko; Maxim B Freidin

doi:10.1016/j.meegid.2016.10.030

Novel tuberculosis susceptibility candidate genes revealed by the reconstruction and analysis of associative networks

Infect Genet Evol. 2016 Dec:46:118-123. doi: 10.1016/j.meegid.2016.10.030. Epub 2016 Oct 31.

Authors

Elena Yu Bragina¹, Evgeny S Tiys², Alexey A Rudko³, Vladimir A Ivanisenko⁴, Maxim B Freidin³

Affiliations

¹ Laboratory of Population Genetics, Research Institute of Medical Genetics, Tomsk NRMC, Nabereznaya Ushaiki Str. 10, Tomsk 634050, Russia. Electronic address: elena.bragina72@gmail.com.
² Laboratory of Computer-Assisted Proteomics, The Federal Research Centre Institute of Cytology and Genetics of The Siberian Branch of the Russian Academy of Sciences, Lavrentiev Ave. 10, Novosibirsk 630090, Russia; Laboratory of Computer Genomics, Novosibirsk State University, Pirogova Str. 2, Novosibirsk 630090, Russia.
³ Laboratory of Population Genetics, Research Institute of Medical Genetics, Tomsk NRMC, Nabereznaya Ushaiki Str. 10, Tomsk 634050, Russia.
⁴ Laboratory of Computer-Assisted Proteomics, The Federal Research Centre Institute of Cytology and Genetics of The Siberian Branch of the Russian Academy of Sciences, Lavrentiev Ave. 10, Novosibirsk 630090, Russia.

PMID: 27810501
DOI: 10.1016/j.meegid.2016.10.030

Abstract

Tuberculosis (TB) is a common infectious disease caused by M. tuberculosis. The risk of the disease is dependent on complex interactions between host genetics and environmental factors. Accumulated genomic data, along with novel methodological approaches such as associative networks, facilitate studies into the inherited basis of TB. In the current study, we carried out the reconstruction and analysis of an associative network representing molecular interactions between proteins and genes associated with TB. The network predominantly comprises of well-studied key proteins and genes which are able to govern the immune response against M. tuberculosis. However, this approach also allowed us to reveal 12 proteins encoded by genes, the polymorphisms of which have never been studied in relation to M. tuberculosis infection. These proteins include surface antigens (CD4, CD69, CD79, CD80, MUC16) and other important components of the immune response, inflammation, pathogen recognition, cell migration and activation (HCST, ADA, CP, SPP1, CXCR4, AGER, PACRG). Thus, the associative network approach enables the discovery of new candidate genes for TB susceptibility.

Keywords: Associative network; Genes; Susceptibility; Tuberculosis.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Computational Biology
Genetic Predisposition to Disease / genetics*
Humans
Protein Interaction Maps / genetics*
Protein Interaction Maps / immunology*
Software
Tuberculosis / genetics*
Tuberculosis / immunology