Table 1: Associated genes, miRNAs and Transcription Factors of Psoriasis
Further the genes, miRNAs and proteins in indirect approach were subjected to network analysis and the further details about the statistical methods were given below.
Network construction & analysis (Cytohubba)
Genes and their regulators were subjected to the analysis by various statistical methods (Degree, Edge Percolated Component, Maximum Neighborhood Component, Density of Maximum Neighborhood Component, and Maximal Clique Centrality with six centralities Bottleneck, EcCentricity, Closeness, Radiality, Betweenness and Stress) to identify their connectivity.
In case of MCC analysis in direct approach; VDR, MTHFR, GSTP1, ABCC1, TYMS and SLC19A1 were ranked from 1 to 6 respectively. Then; CYP1A2 and HLA-B were ranked 7. Finally; MAX and MYC were ranked 9. VDR polymorphism is associated with Psoriasis (Figure 1).
In case of DMNC analysis in direct approach; MTHFR, AHR, ARNT, CUX1, E2F1, EP300, hsa-miR-103, hsa-miR-107, hsa-miR-125a-3p and hsa-miR-138 were ranked 1. MTHFR polymorphism is a possible factor for reducing the clinical severity of psoriasis (Figure 2).
In case of MNC analysis in direct approach; MTHFR, AHR, ARNT, CUX1, E2F1, EP300, hsa-miR-103, hsa-miR-107, hsa-miR-125a-3p and hsa-miR-138 were ranked 1. MTHFR polymorphism is a possible factor for reducing the clinical severity of psoriasis (Figure 3).
In case of degree analysis in direct approach; VDR, MTHFR, GSTP1, ABCC1, TYMS and SLC19A1 were ranked from 1 to 6 respectively. Then; CYP1A2 and HLA-B were ranked 7. Finally; MAX and MYC were ranked 9. VDR polymorphism is associated with Psoriasis (Figure 4).
In case of EPC analysis in direct approach; MTHFR, VDR, SLC19A1, GSTP1, MAX, MYC, ABCC1, hsa-miR-24, TYMS and USF1 were ranked from 1 to 10 respectively. MTHFR polymorphism is a possible factor for reducing the clinical severity of psoriasis (Figure 5).
In case of Bottleneck Analysis in direct approach; VDR, hsamiR-24 and MTHFR were ranked from 1 to 3. Then, MYC and GSTP1 were ranked 4. Further; ABCC1, TYMS and STAT1 were ranked from 6 to 8. Finally, YY1and HLA-B were ranked 9. VDR polymorphism is associated with Psoriasis (Figure 6).
In case of Eccentricity Analysis in direct approach; JUN, MAX, MYC, CREB1 and hsa-miR-24 were ranked Then; MTHFR, SLC19A1, TYMS, VDR and GSTP1 were ranked 6. JUN is associated with psoriasis because it’s involved in the epidermal signaling (Figure 7).
In case of Closeness Analysis in direct approach; VDR, MTHFR, MAX, hsa-miR-24 and JUN were ranked from 1 to 5 respectively. Then, MYC and GSTP1 were ranked 6. ABCC1, TYMS and SLC19A1 were ranked from 8 to 10 respectively. VDR polymorphism is associated with Psoriasis (Figure 8).
In case of Radiality Analysis in direct approach; MAX, hsa-miR-24, VDR, MTHFR, JUN, MYC, GSTP1, TYMS, SLC19A1 and ABCC1 were ranked from 1 to 10 respectively (Figure 9).
In case of Betweenness Analysis in direct approach; VDR, MTHFR, GSTP1, MAX, hsa-miR-24, ABCC1, TYMS, MYC, HLA-B and JUN were ranked from 1 to 10 respectively. VDR polymorphism is associated with Psoriasis (Figure 10).
In case of Stress Analysis in direct approach; MTHFR, VDR, GSTP1, MAX, CYP1A2, ABCC1, hsa-miR- 24, HLA-B, MYC and SLC19A1 were ranked from 1 to 10. MTHFR polymorphism is a possible factor for reducing the clinical severity of psoriasis (Figure 11).
In case of Clustering coefficient Analysis in direct approach; MTHFR, AHR, ARNT, CUX1, E2F1, EP300 hsa-miR-103, hsa-miR-107, hsa-miR-125a-3p and hsa-miR-138 were ranked from 1 to 10. MTHFR polymorphism is a possible factor for reducing the clinical severity of psoriasis (Figure 12) (Table 2).
Table 2: Network Analysis (Direct Approach)
Conclusion
Overall network analysis of pharmacogenomic based regulatory network in psoriasis resulted in identifying 25 potential regulators of Psoriasis [20 Transcription Factors (VDR, MTHFR, GSTP1, ABCC1, TYMS, SLC19A1, CYP1A2, HLA-B, MAX, MYC, AHR, ARNT, CUX1, E2F1 and EP300) and 5 miRNAs (hsa-miR-103, hsa-miR-107, hsa-miR125a-3p, hsa-miR-138 and hsa-miR-24)]. In a biological context, these potential regulators of psoriasis have a maximum probability to become a potential biomarker for Psoriasis and there was an identical pattern in the comparative-network analysis to illustrate the fact that there is a maximum probability for these potential regulators to be considered to treat psoriasis in future.
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