Otoinflamatuvar Hastalıklarda Rolü Olan mRNA ve miRNA Moleküllerinin Meta-analizi
View/ Open
Date
2023-04Author
Ustabaş, Gizem
xmlui.dri2xhtml.METS-1.0.item-emb
6 ayxmlui.mirage2.itemSummaryView.MetaData
Show full item recordAbstract
Autoinflammatory diseases are the group of diseases in which inflammatory responses are increased as a result of the innate immune system being affected. These diseases can be grouped as monogenic and polygenic in terms of their genetic characteristics. Among the autoinflammatory diseases
examined within the scope of the thesis; PFAPA is polygenic and AAA, CAPS, TRAPS,
MKD diseases are caused by mutations in different genes, but the similar phenotype
seen in these diseases suggests that similar pathways and molecules are affected. In
the literature, there are omic-based studies in which autoinflammatory diseases are
included Within the scope of this thesis, it was aimed to evaluate these data together,
and microarray data sets of mRNA and miRNA-based omic studies were analyzed
using programs such as R (4.0.5), BRB-ArrayTools and MeV. Differentially expressed
genes were analyzed using DAVID program and InnateDB database and those related
to inflammation were determined. Then, the binding possibilities of differentially
expressed common mRNAs in these diseases and miRNAs obtained from data sets
were shown using the TargetScan database. Finally, the proteins targeted by
differentially expressed mRNAs and miRNAs significantly were identified and the
protein-protein relationships between these proteins were determined by STRING
analysis. As a result of the analyzes, STAT1, NAIP, FAS, MAPK14 proteins, which are
important proteins in terms of inflammation, were mainly demonstrated and it was
shown that they were interacted with the proteins encoded by the genes that cause
the selected diseases. This preliminary data supported the hypothesis that common
molecules affect the pathogenesis in selected diseases, and it became important to
examine these findings in the laboratory. This thesis will make important
contributions to the better classification of diseases by elucidating the pathways that
cause inflammation in autoinflammatory diseases and to the identification of
molecules that may be the target of treatment in the long term.