George D Vavougios1, Sotirios G Zarogiannis2, Karen Angeliki Krogfelt3, Konstantinos Gourgoulianis4, Dimos Dimitrios Mitsikostas5, Georgios Hadjigeorgiou6. 1. Department of Respiratory Medicine, Faculty of Medicine, University of Thessaly, BIOPOLIS, Larissa 41110, Greece. Electronic address: dantevavougios@hotmail.com. 2. Department of Respiratory Medicine, Faculty of Medicine, University of Thessaly, BIOPOLIS, Larissa 41110, Greece; Department of Physiology, Faculty of Medicine, University of Thessaly, BIOPOLIS, Larissa 41110, Greece. 3. Head of unit, Bacteria, Parasites & Fungi Statens Serum Institut, 5 Artillerivej, 45/112, DK-2300 Copenhagen, Denmark. 4. Department of Respiratory Medicine, Faculty of Medicine, University of Thessaly, BIOPOLIS, Larissa 41110, Greece. 5. National and Kapodistrian University of Athens, 1st Division of Neurology, Eginition Hospital, Vasilissis Sofias 72-74, Athens 11528, Greece. 6. Department of Neurology, Faculty of Medicine, University of Thessaly, BIOPOLIS, Larissa 41110, Greece.
Abstract
BACKGROUND: currently only 4 studies have explored the potential role of PARK7's dysregulation in MS pathophysiology Currently, no study has evaluated the potential role of the PARK7 interactome in MS. OBJECTIVE: The aim of our study was to assess the differential expression of PARK7 mRNA in peripheral blood mononuclears (PBMCs) donated from MS versus healthy patients using data mining techniques. METHODS: The PARK7 interactome data from the GDS3920 profile were scrutinized for differentially expressed genes (DEGs); Gene Enrichment Analysis (GEA) was used to detect significantly enriched biological functions. RESULTS: 27 differentially expressed genes in the MS dataset were detected; 12 of these (NDUFA4, UBA2, TDP2, NPM1, NDUFS3, SUMO1, PIAS2, KIAA0101, RBBP4, NONO, RBBP7 AND HSPA4) are reported for the first time in MS. Stepwise Linear Discriminant Function Analysis constructed a predictive model (Wilk's λ = 0.176, χ2 = 45.204, p = 1.5275e-10) with 2 variables (TIDP2, RBBP4) that achieved 96.6% accuracy when discriminating between patients and controls. Gene Enrichment Analysis revealed that induction and regulation of programmed / intrinsic cell death represented the most salient Gene Ontology annotations. Cross-validation on systemic lupus erythematosus and ischemic stroke datasets revealed that these functions are unique to the MS dataset. CONCLUSIONS: Based on our results, novel potential target genes are revealed; these differentially expressed genes regulate epigenetic and apoptotic pathways that may further elucidate underlying mechanisms of autorreactivity in MS.
BACKGROUND: currently only 4 studies have explored the potential role of PARK7's dysregulation in MS pathophysiology Currently, no study has evaluated the potential role of the PARK7 interactome in MS. OBJECTIVE: The aim of our study was to assess the differential expression of PARK7 mRNA in peripheral blood mononuclears (PBMCs) donated from MS versus healthy patients using data mining techniques. METHODS: The PARK7 interactome data from the GDS3920 profile were scrutinized for differentially expressed genes (DEGs); Gene Enrichment Analysis (GEA) was used to detect significantly enriched biological functions. RESULTS: 27 differentially expressed genes in the MS dataset were detected; 12 of these (NDUFA4, UBA2, TDP2, NPM1, NDUFS3, SUMO1, PIAS2, KIAA0101, RBBP4, NONO, RBBP7 AND HSPA4) are reported for the first time in MS. Stepwise Linear Discriminant Function Analysis constructed a predictive model (Wilk's λ = 0.176, χ2 = 45.204, p = 1.5275e-10) with 2 variables (TIDP2, RBBP4) that achieved 96.6% accuracy when discriminating between patients and controls. Gene Enrichment Analysis revealed that induction and regulation of programmed / intrinsic cell death represented the most salient Gene Ontology annotations. Cross-validation on systemic lupus erythematosus and ischemic stroke datasets revealed that these functions are unique to the MS dataset. CONCLUSIONS: Based on our results, novel potential target genes are revealed; these differentially expressed genes regulate epigenetic and apoptotic pathways that may further elucidate underlying mechanisms of autorreactivity in MS.