Pregled bibliografske jedinice broj: 813849
Modeling IgG glycosylation changes in aging
Modeling IgG glycosylation changes in aging // 23rd International Symposium on Glycoconjugates / Lauc, Gordan (ur.).
Zagreb, 2015. str. 24-24 (predavanje, međunarodna recenzija, sažetak, znanstveni)
CROSBI ID: 813849 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Modeling IgG glycosylation changes in aging
Autori
Vojta, Aleksandar ; Benedetti, Elisa ; Lauc, Gordan ; Krumsiek, Jan
Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni
Izvornik
23rd International Symposium on Glycoconjugates
/ Lauc, Gordan - Zagreb, 2015, 24-24
Skup
23rd International Symposium on Glycoconjugates
Mjesto i datum
Split, Hrvatska, 15.09.2015. - 20.09.2015
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
glycosylation; IgG; aging; MCMC; network
Sažetak
Most membrane and extracellular proteins are glycosylated, which makes the attached oligosaccharide an integral part of the glycoprotein, thus altering its structure and function. Glycosylation of IgG antibodies is of particular interest. The glycan part critically affects the effector function of the antibody. The glycosylation pattern is a result of a complex interplay of many enzymes connected into an intricate network. In order to understand how this network changes with age, we used the IgG glycome data from several hundreds of individuals. We built a correlation network of glycan structures based on our extensive dataset. Our model uses covariance regression with Markov chain Monte Carlo simulations, with independent fitting of the mean and the covariance for each glycan structure. This strategy required careful model selection, evidence of Markov chain convergence and visualization of the covariance matrix in a network form, which represents the basis for biological interpretation. We found good clustering into different IgG classes when the model was applied to the integral dataset, with strong positive correlations within individual IgG classes and mostly negative correlations between different classes. To gain a deeper insight into the aging process, we shifted our focus to the correlations within individual IgG classes. Our preliminary results have identified several key glycosylation enzymes that might serve as control points for the whole network and point to their role in changes in the glycome observed during aging, affecting the IgG effector function and thus having a possibly important role in both the autoimmune diseases and cancer.
Izvorni jezik
Engleski
Znanstvena područja
Biologija