Molecular mechanisms behind IgA Nephropathy

Examensarbete för masterexamen

Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.12380/166755
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Type: Examensarbete för masterexamen
Master Thesis
Title: Molecular mechanisms behind IgA Nephropathy
Authors: Liu, Peidi
Abstract: The master thesis work is emphasized on global gene expression analysis in order to find out molecular mechanisms behind IgA Nephropathy (IgAN). Microarray experiments have been conducted on microdissected human renal biopsies that are collected at the Sahlgrenska University Hospital in Gothenburg. The work is composed of biological computational analysis and molecular biology. IgAN is considered to be the most common glomerulonephritis around the world. The disease may lead to renal failure and there is presently no cure for the disease. In the end stage of the disease, dialysis or kidney transplantation is necessary for the patients to survive. Unfortunately, after decades of research, the molecular mechanisms behind IgAN are still unknown. In case of IgAN, IgA deposits can be found in human glomeruli and it leads to cell proliferation and inflammation. The diagnosis of the disease is depending on observing morphological changes and findings of IgA depositions in the glomeruli. However, it has been found out that even when a new kidney has been transplanted, the disease can reappear after some time. Furthermore, it is also been known that according to different races and regions, the situation is not the same. This phenomenon gives a clue that IgAN is a disease associated with gene regulations. Large-scale genomic analysis tools have enabled the era of carrying out genome-wide gene expression experiments. These tools give us possibilities to investigate the whole genome regulation in IgAN. By using statistical analysis to compare the difference between IgAN patients and healthy controls, significant up and down regulated genes can be found out based on p-values and fold changes, as well as corresponding KEGG pathways. From the result, interesting genes can be selected and experimented with real-time PCR in order to validate if the genes are truly up or down regulated. Thus potential genes that are possibly related to trigger IgAN can be concluded. By investigating gene correlation and also protein expression, diagnostic molecular markers will hopefully be possible to discover.
Keywords: Matematisk statistik;Grundläggande vetenskaper;Mathematical statistics;Basic Sciences
Issue Date: 2012
Publisher: Chalmers tekniska högskola / Institutionen för matematiska vetenskaper
Chalmers University of Technology / Department of Mathematical Sciences
URI: https://hdl.handle.net/20.500.12380/166755
Collection:Examensarbeten för masterexamen // Master Theses



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