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. Aulchenko^7
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.