(magistrsko delo)
Anja Grušovnik (Author), Uroš Potočnik (Mentor), Mario Gorenjak (Co-mentor)

Abstract

Revmatoidni artritis in osteoartritis sta najpogosteje prisotni vrsti artritisa. Osteoartritis je primarno degenerativna bolezen sklepov, revmatoidni artritis pa je kronična avtoimunska bolezen. Obe bolezni sta z genetskega vidika kompleksni. Z revmatoidnim artritisom je do danes povezanih približno 100 lokusov, z osteoartritisom pa 64. Glavni namen naloge je bil s pomočjo uporabe asociacijskih študij, genske ontologije in bioinformatskih orodij odkriti molekularne biološke poti in procese, ki so odgovorni za nastanek in razvoj obeh bolezni ter jih med seboj primerjati. Dve izmed glavnih metod raziskovanja patofizologije sta genska ontologija in asociacijske študije celotnega genoma. Izvedena je bila meta-statistična analiza več polimorfizmov za obe bolezni. Uporabili smo različna bioinformatska orodja. Izdelana je bila tudi vizualizacija omrežij molekularnih interakcij in bioloških poti. Pri meta-statistični analizi izbranih polimorfizmov za osteoartritis je bil DVWA edini signifikanten gen, pri revmatoidnem artritisu pa PTPN22, CTLA4, STAT4, AFF3, CD40 in KIF5A. Rezultati programa DAVID so podali 2 signifikantna klastra za osteoartritis ter 13 signifikantnih klastrov za revmatoidni artritis. Bolezni si delita 260 skupnih ključev genske ontologije in 31 genov. Pri vizualiziranih mrežah bioloških poti smo lahko našli nekatere podobnosti, zlasti pri pozitivnih in negativnih regulacijah bioloških procesov; zanimive so bile tudi podobnosti znotraj imunskega sistema in ubikvitinacije. Naše domneve so tako bile utemeljene: z GWA študijami in pristopom genske ontologije smo lahko zbrali podatke in izpostavili pomembne biološke procese obeh bolezni ter jih med seboj primerjali. Izkazalo se je tudi, da so nekatere molekularne interakcije in biološke poti primerljive.

Keywords

GWAS;meta-statistična analiza;DAVID;Cytoscape;vizualizacija;

Data

Language: Slovenian
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UM MF - Faculty of Medicine
Publisher: [A. Grušovnik]
UDC: 575.112(043.2)
COBISS: 2543524 Link will open in a new window
Views: 970
Downloads: 101
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Other data

Secondary language: English
Secondary title: Molecular pathogenesis of rheumatoid arthritis and osteoarthritis by using gene ontology approach
Secondary abstract: Rheumatoid arhtirits and osteoarthritis are the most common types of arthritis. Osteoarthritis is primarily a degenerative joint disease and rheumatoid arthritis, however, is a chronic inflammatory autoimmune disease. Both diseases are complex in genetic terms. To date, about 100 loci from GWAS are associated with rheumatoid arthritis and 64 with osteoarthritis. The main purpose of the study was to identify molecular biological pathways and processes responsible for the emergence and developments of both diseases by using association studies, gene ontologies and bioinformatics tools, and then compare each other. Gene ontology and genome wide studies are two main methods of pathophysiology research. A meta-statistical analysis of several polymorphisms for both diseases was performed. In the meta-statistical analysis of selected osteoarthritis polymorphisms, DVWA was the only significant gene, and in rheumatoid arthritis PTPN22, CTLA4, STAT4, AFF3, CD40 and KIF5A. The results of the DAVID provided 2 significant clusters for osteoarthritis and 13 significant clusters for rheumatoid arthritis. Network analysis provided us with 260 common ontology gene keys and 31 genes. We have found some similarities in visualized biological pathway networks, especially in the positive and negative regulation of biological processes; the similarities within the immune system and ubiquitination were also interesting. Our assumptions were thus substantiated. Through GWA studies and the gene ontology approach we were able to gather data and highlight important biological processes of the two diseases and compare them with each other. Some molecular interactions and biological pathways have also been shown to be comparable.
Secondary keywords: GWAS;meta-analysis;DAVID;Cytoscape;visualisation;Genomics;Polymorphism, genetic;Meta-analysis as topic;Genomika;Genetski poliformizem;Mera analiza;
Type (COBISS): Master's thesis/paper
Thesis comment: Univ. v Mariboru, Fak. za zdravstvene vede
Pages: X, 116 str.
ID: 11214671