Transcriptome and Differential Methylation Integration Analysis Identified Important Differential Methylation Annotation Genes and Functional Epigenetic Modules Related to Vitiligo

Abstract

Vitiligo is an pigmentation disorder caused by a variety of pathogenic factors; its main pathophysiological conditions include oxidative stress, immune activation, and genetic background. Additionally, DNA methylation is often associated with the pathogenesis of vitiligo; however, the underlying mechanism remains unknown. In the present study, we used the Human Methylation 850K BeadChip platform to detect DNA methylation changes in the vitiligo melanocytes. We then integrated the results with the transcriptome data of vitiligo melanocytes and lesions to analyse the correlation between differentially methylated levels and differentially expressed genes. The results showed that there was a significant negative correlation between methylation levels and differentially expressed genes. Subsequently, we enriched GO and KEGG based on methylated differentially expressed genes (MDEGs) using R package ClusterProfiler, and the results were closely related to the pathogenesis of vitiligo. In addition, we also constructed a PPI network of MDEGs and excavated three important functional epigenetic modules, involving a total of 12 (BCL2L1, CDK1, ECT2, HELLS, HSP90AA1, KIF23, MC1R, MLANA, PBK, PTGS2, SOX10, and TYRP1) genes. These genes affect melanocyte melanogenesis, cellular oxidative stress and other important biological processes. Our comprehensive analysis results support the significant contribution of the status of DNA methylation modification to vitiligo, which will help us to better understand the molecular mechanism of vitiligo and explore new therapeutic strategies.

Development of a Multi-Target Strategy for the Treatment of Vitiligo via Machine Learning and Network Analysis Methods

“…It was a practicality for most biological studies (Fortino et al, 2020;Shen et al, 2020;Unger et al, 2020). Among these important transcriptomic features, several top-ranked variables were closely related to the melanogenesis and immune characteristics, which was the main phenotypes of vitiligo (Picardo et al, 2015;Niu and Aisa, 2017;Pu et al, 2021;Zhang et al, 2021). Moreover, we constructed a more comprehensive VitNet and obtained 160 articulation proteins by the GAPR method.…”

“…Among these articulation proteins, previous study had reported that Imatinib (ABL1 inhibitor) induced repigmentation of vitiligo lesions ( Han et al, 2008 ). A recent study also found that PBK, CDK1 and TXN were considered as potential therapeutic targets by transcriptome and methylation analysis ( Pu et al, 2021 ). However, whether these targets were related to melanogenesis had not been proved.…”

Correlation Between Immune-Related Genes and Tumor-Infiltrating Immune Cells With the Efficacy of Neoadjuvant Chemotherapy for Breast Cancer

“…The Kyoto Encyclopedia of Genes and Genomes (KEGG) ( https://www.kegg.jp/ ) ( Kanehisa et al, 2017 ) is a database that provides gene and genome functional significance at the molecular and pathway levels. The DOSE, ClusterProfiler, Org.Hs.eg.db, and Enrichplot packages in R ( Yu et al, 2012 ; Yu et al, 2015 ; Pu et al, 2021 ) were used for the GO and KEGG pathway enrichment analyses of DEGs.…”

Integrated Multiomics Analyses Revealing Different Molecular Profiles Between Early- and Late-Stage Lung Adenocarcinoma

“…Gene expression quantification was performed using RSEM (17) to obtain the fragment per kilo exon per million reads (FPKM) of each gene. DEGs were analyzed using DEseq2, and the clusterProfiler of the R software package was used to perform gene pathway enrichment analysis with a threshold of p < 0.05 (18)(19)(20). The enrichment analysis mapping was performed using a p-value.…”