Analiza N-glikoma imunoglobulina G u blizanaca s križoboljom

master's thesis

• Title (english): Glycomic phenotyping of twin patients with low back pain
• Author: Dunja Vučenović
• Mentor: Frances Mary Kingsley Williams (mentor)
• Mentor: Vlatka Zoldoš (mentor)
• Committee member: Vlatka Zoldoš (predsjednik povjerenstva)
• Committee member: Vesna Benković (član povjerenstva)
• Committee member: Silvija Černi (član povjerenstva)
• Committee member: Kristian Vlahoviček (član povjerenstva)
• Granter: University of Zagreb; Faculty of Science; (Department of Biology); Zagreb
• Defense date and country: 2015-09-30, Croatia
• Scientific / art field, discipline and subdiscipline: NATURAL SCIENCES; Biology

Abstract

Križobolja je sveprisutan mišićno-skeletni sindrom koji se javlja u svim dobnim skupinama. Detaljne informacije o dijagnozi ovog sindroma potrebne su zbog njegove kliničke i socijalne važnosti. Trenutno postoje ograničeni biomarkeri (uglavnom su to snimke dobivene magnetskom rezonancijom) zbog čega je potrebno razviti nove, jednostavnije metode rane detekcije križobolje. Jedan od glavnih uzroka kronične križobolje jest lokalizirana upala u epiduralnom prostoru. Kako je svaki upalni proces povezan s brojnim promjenama na mjestu upale, tako su uočene i promjene u glikanima vezanim za Fc regiju imunoglobulina G (IgG).
U ovom radu nastojala sam odrediti postoje li različiti profili količine glikana kod blizanca iz TwinsUK baze podataka s križoboljom i zdravih pojedinaca. Da bih to ostvarila, analizirala sam N-glikom IgG-a 4416 blizanaca koji su odgovorili na upitnike o povijesti boli, čiji je glikanski profil određen i koji su podvrgnuti snimanju kralježnice magnetskom rezonancijom. S dobivenim podatcima sam, koristeći statističke metode za analizu blizanaca, tražila asocijaciju N-glikana s fenotipovima boli. Dodatno sam koristila i metode koje se koriste u genomici za određivanje razlike u ekspresiji gena kod pacijenata i kontrola te tako dobila module različitih količina N-glikana. Dobivenim modulima kreirala sam prediktivne algoritme koji govore o vjerojatnosti razvoja križobolje kod novih ispitanika.

Abstract (english)

Lumbago is a common musculoskeletal condition in all ages. Owing to its clinical and social impact, a clear diagnosis of this syndrome is needed in order to define besides pain intensity also the interference of pain with daily and work activity. Currently, there are limited biomarkers (mostly imaging), but there is a need for novel and simpler detection methods. One of the major determinants of pain in persistent lumbago is localised inflammation in epidural space. As every inflammatory process is linked with changes on the inflamed region, so are altered N-glycan IgG compositions. In this study, using classical twin design conducted between twins from TwinsUK registry, I assessed whether twins reporting episodes of lumbago had detectable levels of altered IgG glycosylation. I analysed IgG N-glycome of 4416 twins having completed pain history questionnaires, whose glycan profile was determined and who underwent magnetic-resonance spine scan. With this data, using statistical methods for twin studies, I looked for association between glycan quantities and pain phenotypes. Additionally, I used methods applied in genomics and obtained modules of glycans that show different patterns of glycan quantities. With these modules I built prediction algorithms that are giving likelihood of person reporting episodes of lumbago.

• Keywords: križobolja; glikani; regresija; mješoviti modeli; WGCNA; LASSO
• Keywords (english): lumbago; glycans; regression; mixed models; WGCNA; LASSO
• Language: croatian
• URN:NBN: urn:nbn:hr:217:329753
• Study programme: Title: Molecular Biology; Study programme type: university; Study level: graduate; Academic / professional title: magistar/magistra molekularne biologije (magistar/magistra molekularne biologije)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Open access
• Created on: 2017-04-24 09:25:53