Naslov
Protein fucosylation in diagnosis of maturity onset diabetes of the young

Autori
Pavić, Tamara ; Juszczak, Agata ; Pape Medvidović, Edita ; Novokmet, Mislav ; McCarthy, Mark ; Lauc, Gordan ; Owen, Katharine ; Gornik, Olga

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
XIII International Symposium on Glycoconjugates (GLYCO 23) / Glycoconjugate Journal 32 (2015) (5) 173-312 / - , 2015, 284-285

Skup
XXIII International Symposium on Glycoconjugates (GLYCO 23)

Mjesto i datum
Split, Hrvatska, 15.09.2015. - 20.09.2015

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Monogenic diabetes ; HNF1A ; Glycosylation

Sažetak
Maturity onset diabetes of the young (MODY) is a monogenic form of diabetes caused by mutations in one of the 11 different genes, which consequently leads to pancreatic beta- cell dysfunction. HNF1A-MODY is the most common form seen in adults and it is frequently misdiagnosed as type 1 or type 2 diabetes. Identification of this form of diabetes is of great significance, since the hyperglycaemia in HNF1A-MODY is very sensitive to oral treatment with sulfonylurea and may lead to an individual being able to discontinue assumed life-long insulin treatment. Current diagnostic protocols miss cases through low sensitivity and, up to date, the only reliable method for diagnosis confirmation is the sequencing of susceptible gene. Our previous studies have identified HNF1A as a master regulator of plasma protein fucosylation and have also determined that the fucose level is significantly lower in HNF1A- MODY patients than in other types of diabetes and healthy controls. The aim of the current study was to evaluate the diagnostic accuracy of the glycan test in a clinical setting using an unselected population with young-onset diabetes. Patients enrolled had increased risk of diagnostic misclassification and were recruited through the Croatian Registry of Diabetes and Young Diabetes in Oxford Study. Employed computational approach, based on random forest classification of total N-glycan profiles, served to determine the best algorithm to distinguish HNF1A-MODY patients from population without HNF1A-MODY. Described approach has the potential to produce a rational diagnostic protocol and could improve the differential diagnosis of diabetes.

Izvorni jezik
Engleski

Znanstvena područja
Biologija, Kliničke medicinske znanosti

POVEZANOST RADA