Högskolan i Skövde

This thesis, titled "Analyzing Differentially Expressed miRNAs: Unveiling Enriched Pathways and Their Role in Disease Progression", adresses the critical question of whether common enriched pathways exist among a set of differentially expressed miRNAs (DEMs) and if these pathways significantly contribute to disease progression. The research aims to integrate various bioinformatics tools to identify gene targets of DEMs and conduct pathway enrichment analyses, shedding light on the molecular mechanisms underlying disease emergence.

The study´s objectives involve collecting DEMs associated with a specific disease, predicting gene targets, performing pathway enrichement analyses, identifying common enriched pathways, and assessing their biological relevance.

To achieve these objectives, the research utilizes a combination of TargetScan and miRWalk for miRNA-target interactions, ensuring a robust and accurate prediction of regulatory connections. Additionally, FunRich and ShinyGO are integrated for pathway analysis, providing a user-friendly and efficient approach to interpreting complex biological data. The standarized application of filtering criteria to these tools ensures consistency and reliability in the results, thereby maintaining the integrity of the study.

In the context of sickle cell anemia (SCA), the study´s application demonstrates the effectiveness of the methodology. the findings reveal a network of miRNAs and their predicted gene targets, playing pivotal roles in the regulation of pathways related to cellular adhesion, inflammation, metabolism, cell cycle, oxidative stress, iron metabolism, comlement systems, coagulation, neurotrophic signaling and cell differentiation. Understanding the intricate interactions within these pathways provides valuable insights into the complexity of SCA´s pathogenesis. This study contributes in providing a foundation for potential therapeutic targets and improving the quality of life for individuals affected by SCA.