Statistical relations between N-glycome of circulating immunoglobuline G and total plasma N-Glycome
Sofya Feoktistova1, Sodbo Sharapov2, Yakov A. Tsepilov3, Tim Spector4, Gordan Lauc5, Frano Vuckovic6, Yurii S. Aulchenko7
1Laboratory of Glycogenomics Institute of Cytology and Genetics Novosibirsk, Russia, sayfutdinovas@gmail.com
2Laboratory of Glycogenomics Institute of Cytology and Genetics Novosibirsk, Russia, sharapovsodbo@gmail.com
3Laboratory of Theoretical and Applied Functional Genomics Novosibirsk State University Novosibirsk, Russia, drosophila.simulans@gmail.com
4Department of Twin Research and Genetic Epidemiology, School of Life Course Sciences King’s College London London, United Kingdom, tim.spector@kcl.ac.uk
5Genos Glycoscience Research Laboratory Zagreb, Croatia, glauc@genos.hr
6Genos Glycoscience Research Laboratory Zagreb, Croatia, fvuckovic@genos.hr
7Laboratory of Glycogenomics Institute of Cytology and Genetics Novosibirsk, Russia, y.s.aulchenko@polyomica.com
Glycosylation is the most common co-translational and post-translational modification of proteins. Glycans influence the physical properties of proteins as well as their biological functions. Alteration in glycosylation is observed in many human diseases.Defining genetic factors, altering glycosylation, can provide a basis for novel approaches to diagnostic and pharmaceutical applications. Predictionof IgG N-glycome from total plasma N-Glycome (TPNG) will allow to increase the power of genetic analysisof tissue specific glycosylation processes.