A Practical Strategy for Exploring the Pharmacological Mechanism of Luteolin Against COVID-19/Asthma Comorbidity: Findings of System Pharmacology and Bioinformatics Analysis

Asthma patients may increase their susceptibility to SARS-CoV-2 infection and the poor prognosis of coronavirus disease 2019 (COVID-19). However, anti-COVID-19/asthma comorbidity approaches are restricted on condition. Existing evidence indicates that luteolin has antiviral, anti-inflammatory, and immune regulation capabilities. We aimed to evaluate the possibility of luteolin evolving into an ideal drug and explore the underlying molecular mechanisms of luteolin against COVID-19/asthma comorbidity. We used system pharmacology and bioinformatics analysis to assess the physicochemical properties and biological activities of luteolin and further analyze the binding activities, targets, biological functions, and mechanisms of luteolin against COVID-19/asthma comorbidity. We found that luteolin may exert ideal physicochemical properties and bioactivity, and molecular docking analysis confirmed that luteolin performed effective binding activities in COVID-19/asthma comorbidity. Furthermore, a protein–protein interaction network of 538 common targets between drug and disease was constructed and 264 hub targets were obtained. Then, the top 6 hub targets of luteolin against COVID-19/asthma comorbidity were identified, namely, TP53, AKT1, ALB, IL-6, TNF, and VEGFA. Furthermore, the enrichment analysis suggested that luteolin may exert effects on virus defense, regulation of inflammation, cell growth and cell replication, and immune responses, reducing oxidative stress and regulating blood circulation through the Toll-like receptor; MAPK, TNF, AGE/RAGE, EGFR, ErbB, HIF-1, and PI3K–AKT signaling pathways; PD-L1 expression; and PD-1 checkpoint pathway in cancer. The possible “dangerous liaison” between COVID-19 and asthma is still a potential threat to world health. This research is the first to explore whether luteolin could evolve into a drug candidate for COVID-19/asthma comorbidity. This study indicated that luteolin with superior drug likeness and bioactivity has great potential to be used for treating COVID-19/asthma comorbidity, but the predicted results still need to be rigorously verified by experiments.

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Biodata Mining-based Elucidation of Mechanisms of Hesperetin as a Candidate for Atherosclerosis

10.21203/rs.3.rs-83163/v1 ◽

2020 ◽

Author(s):

Lianzhou Huang ◽

Zexiu Huang ◽

Yuanqiu Chen ◽

Xin Jin ◽

Ji Xiao ◽

...

Keyword(s):

Active Ingredient ◽

Molecular Mechanisms ◽

Fluid Shear Stress ◽

Biological Activities ◽

Interaction Network ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Citrus Aurantium ◽

Wide Range ◽

Anti Inflammatory

Abstract BackgroundHesperetin, an active ingredient derived from Citrus × aurantium L., possesses a wide range of biological activities, including anti-inflammatory, anti-oxidation, and anti-cancer activity. Notably, hesperetin has been proposed as a candidate for atherosclerosis owing to the lipid-regulating and anti-inflammatory effect, while the underlying mechanisms remains obscure.ResultsIn our present study, the pharmacological and molecular properties of hesperetin were first evaluated to determine the druggability of hesperetin. Subsequently, 53 hesperetin-atherosclerosis crossover targets were collected to establish the protein-protein interaction network. The result of Gene Ontology enrichment analysis indicated that the crossover targets were involved in the regulation of lipid metabolism and inflammatory response. Moreover, the Kyoto Encyclopedia of Genes and Genomes pathway analyses demonstrated that the crossover targets were highly correlated with the pathogenesis of atherosclerosis, such as fluid shear stress and atherosclerosis pathway and the TNF signaling pathway. Finally, an entire hesperetin-target-pathway network was constructed to provide a systematic overview of the pharmacological mechanisms of action of hesperetin against atherosclerosis.ConclusionsThe pharmacological mechanisms of actions of hesperetin against atherosclerosis was unveiled based on biodata mining from the public database and the bioinformatics data analysis-based strategy in this study, contributing to a deeper understanding of the molecular mechanisms of hesperetin in the treatment of atherosclerosis. Based on the results of network pharmacology analysis, we can conclude that hesperetin is surely an excellent candidate for atherosclerosis. We believe our work would be beneficial for further research and development of hesperetin as a natural active ingredient derived from Citrus × aurantium L. for the treatment of atherosclerosis.

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Gene Expression Profile of Active HE4 Stimulation in Epithelial Ovarian Cancer Cells: Microarray Study and Comprehensive Bioinformatics Analysis

10.21203/rs.3.rs-46014/v1 ◽

2020 ◽

Author(s):

Liancheng Zhu ◽

Mingzi Tan ◽

Haoya Xu ◽

Bei Lin

Keyword(s):

Ovarian Cancer ◽

Epithelial Ovarian Cancer ◽

Clinical Significance ◽

Molecular Mechanisms ◽

Bioinformatics Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Coexpression Analysis ◽

Pathway Enrichment

Abstract Background.Human Epididymis Protein 4 (HE4) is a novel serum biomarker for diagnosis of epithelial ovarian cancer (EOC) with high specificity and sensitivity compared with CA125, and the increasing researches have been carried out on its roles in promoting carcinogenesis and chemoresistance in EOC in recent years, however, its underlying molecular mechanisms remain poorly understood. The aim of this study was to elucidate the molecular mechanisms of HE4 stimulation and to identify the key genes and pathways mediating carcinogenesis in EOC using microarray and bioinformatics analysis.Methods. We established a stable HE4-silence ES-2 ovarian cancer cell line labeled as “S”, and its active HE4 protein stimulated cells labeled as “S4”. Human whole genome microarray analysis was used to identify deferentially expressed genes (DEGs) from triplicate samples of S4 and S cells. “clusterProfiler” package in R, DAVID, Metascape, and Gene Set Enrichment Analysis (GSEA) were used to perform gene ontology (GO) and pathway enrichment analysis, and cBioPortal for WFDC2 coexpression analysis. GEO dataset (GSE51088) and quantitative real-time polymerase chain reaction (qRT-PCR) was applied for validation. The protein–protein interaction (PPI) network and modular analyses were performed using Metascape and Cytoscape. Results.In total, 713 DEGs were found (164 up regulated and 549 down regulated) and further analyzed by GO, pathway enrichment and PPI analyses. We found that MAPK pathway accounted for a significant portion of the enriched terms. WFDC2 coexpression analysis revealed ten WFDC2 coexpressed genes (TMEM220A, SEC23A, FRMD6, PMP22, APBB2, DNAJB4, ERLIN1, ZEB1, RAB6B, and PLEKHF1) that were also dramatically changed in S4 cells and validated by dataset GSE51088. Kaplan–Meier survival statistics revealed clinical significance for all of the 10 target genes. Finally, PPI was constructed, sixteen hub genes and eight molecular complex detections (MCODEs) were identified, the seeds of five most significant MCODEs were subjected to GO and KEGG enrichment analysis and their clinical significance was evaluated.Conclusions.By applying microarray and bioinformatics analyses, we identified DEGs and determined a comprehensive gene network of active HE4 stimulation in EOC cells. We offered several possible mechanisms and identified therapeutic and prognostic targets of HE4 in EOC.

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Gene expression profiles following active HE4 stimulation in epithelial ovarian cancer cells: microarray study and comprehensive bioinformatics analysis

10.21203/rs.3.rs-100248/v1 ◽

2020 ◽

Author(s):

Liancheng Zhu ◽

Mingzi Tan ◽

Haoya Xu ◽

Bei Lin

Keyword(s):

Ovarian Cancer ◽

Epithelial Ovarian Cancer ◽

Molecular Mechanisms ◽

Bioinformatics Analysis ◽

Enrichment Analysis ◽

Gene Set Enrichment Analysis ◽

Pathway Enrichment Analysis ◽

Ppi Network ◽

Coexpression Analysis ◽

Pathway Enrichment

Abstract Background: Human epididymis protein 4 (HE4) is a novel serum biomarker for diagnosing epithelial ovarian cancer (EOC) with high specificity and sensitivity, compared with CA125. Recent studies have focused on the roles of HE4 in promoting carcinogenesis and chemoresistance in EOC; however, the molecular mechanisms underlying its action remain poorly understood. This study was conducted to determine the molecular mechanisms underlying HE4 stimulation and identifying key genes and pathways mediating carcinogenesis in EOC by microarray and bioinformatics analysis.Methods: We established a stable HE4-silenced ES-2 ovarian cancer cell line labeled as “S”; the S cells were stimulated with the active HE4 protein, yielding cells labeled as “S4”. Human whole-genome microarray analysis was used to identify differentially expressed genes (DEGs) in S4 and S cells. The “clusterProfiler” package in R, DAVID, Metascape, and Gene Set Enrichment Analysis were used to perform gene ontology (GO) and pathway enrichment analysis, and cBioPortal was used for WFDC2 coexpression analysis. The GEO dataset (GSE51088) and quantitative real-time polymerase chain reaction were used to validate the results. Protein–protein interaction (PPI) network and modular analyses were performed using Metascape and Cytoscape, respectively. Results: In total, 713 DEGs were identified (164 upregulated and 549 downregulated) and further analyzed by GO, pathway enrichment, and PPI analyses. We found that the MAPK pathway accounted for a significant large number of the enriched terms. WFDC2 coexpression analysis revealed ten WFDC2-coexpressed genes (TMEM220A, SEC23A, FRMD6, PMP22, APBB2, DNAJB4, ERLIN1, ZEB1, RAB6B, and PLEKHF1) whose expression levels were dramatically altered in S4 cells; this was validated using the GSE51088 dataset. Kaplan–Meier survival statistics revealed that all 10 target genes were clinically significant. Finally, in the PPI network, 16 hub genes and 8 molecular complex detections (MCODEs) were identified; the seeds of the five most significant MCODEs were subjected to GO and KEGG enrichment analyses and their clinical relevance was evaluated.Conclusions: Through microarray and bioinformatics analyses, we identified DEGs and determined a comprehensive gene network following active HE4 stimulation in EOC cells. We proposed several possible mechanisms underlying the action of HE4 and identified the therapeutic and prognostic targets of HE4 in EOC.

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Analysis of Expression Profiles of mRNA and lncRNA in Oviduct During Estrus Phase of Sheep (Ovis Aries) with Two Fecundity (FecB Gene) Genotypes

10.21203/rs.3.rs-119198/v1 ◽

2021 ◽

Author(s):

Weihao Chen ◽

Zhifeng Li ◽

Wei Sun ◽

Mingxing Chu

Keyword(s):

Embryo Development ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Interaction Network ◽

Enrichment Analysis ◽

Ovis Aries ◽

Functional Enrichment ◽

Saga Complex ◽

Rna Seq ◽

Estrus Phase

Abstract Background:In sheep, FecB is the essential biomarker of the fertility, previous researches have provided a detailed insight on the regulation involved estrus phase and FecB in the reproductive-related tissues including hypothalamus, pituitary, and ovary. However, as the host of embryo development and connection between the ovary and the uterus, little is known about the interaction between mRNAs and lncRNAs in sheep oviduct. In the present study, RNA-Seq was performed to identify the transcriptomic profiles of mRNAs and lncRNAs in oviduct during estrus phase of sheep with FecBBB/++ genotypes.Results:In total, 21,863 lncRNAs and 43,674 mRNAs were identified, 57 DE lncRNAs and 637 DE mRNAs were revealed in the comparisons between follicular phase and luteal phase, 26 DE lncRNAs and 421 DE lncRNAs were revealed in the comparisons between FecB BB genotype and FecB ++ genotype. Functional enrichment analysis suggested that GO and KEGG terms related to reproduction such as SAGA complex, ATP-binding cassette (ABC), Nestin, and Hippo signalling pathway. DE-interaction network suggested that LNC_018420 maybe the key regulators related to embryo development in sheep oviduct.Conclusion:This was the first study to reveal the transcriptomic profiles of mRNAs and lncRNAs in the oviduct of FecB BB/++ sheep at estrus phase using RNA-Seq. Our findings can provide new understanding on the molecular mechanisms of mRNAs and lncRNAs underlying sheep embryo development and also opening new lines of investigation in sheep reproduction.

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Gene Prioritization through Consensus Strategy, Enrichment Methodologies Analysis, and Networking for Osteosarcoma Pathogenesis

International Journal of Molecular Sciences ◽

10.3390/ijms21031053 ◽

2020 ◽

Vol 21 (3) ◽

pp. 1053 ◽

Cited By ~ 4

Author(s):

Alejandro Cabrera-Andrade ◽

Andrés López-Cortés ◽

Gabriela Jaramillo-Koupermann ◽

César Paz-y-Miño ◽

Yunierkis Pérez-Castillo ◽

...

Keyword(s):

Molecular Mechanisms ◽

Bone Cancer ◽

Interaction Network ◽

Enrichment Analysis ◽

Protein Protein Interaction ◽

Pathogenic Genes ◽

Total List ◽

Consensus Strategy ◽

Primary Bone ◽

Molecular Etiology

Osteosarcoma is the most common subtype of primary bone cancer, affecting mostly adolescents. In recent years, several studies have focused on elucidating the molecular mechanisms of this sarcoma; however, its molecular etiology has still not been determined with precision. Therefore, we applied a consensus strategy with the use of several bioinformatics tools to prioritize genes involved in its pathogenesis. Subsequently, we assessed the physical interactions of the previously selected genes and applied a communality analysis to this protein–protein interaction network. The consensus strategy prioritized a total list of 553 genes. Our enrichment analysis validates several studies that describe the signaling pathways PI3K/AKT and MAPK/ERK as pathogenic. The gene ontology described TP53 as a principal signal transducer that chiefly mediates processes associated with cell cycle and DNA damage response It is interesting to note that the communality analysis clusters several members involved in metastasis events, such as MMP2 and MMP9, and genes associated with DNA repair complexes, like ATM, ATR, CHEK1, and RAD51. In this study, we have identified well-known pathogenic genes for osteosarcoma and prioritized genes that need to be further explored.

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A Systems Pharmacology Approach for Identifying the Multiple Mechanisms of Action for the Rougui-Fuzi Herb Pair in the Treatment of Cardiocerebral Vascular Diseases

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2020/5196302 ◽

2020 ◽

Vol 2020 ◽

pp. 1-17

Author(s):

Chun Li ◽

Xia Du ◽

Yang Liu ◽

Qi-Qi Liu ◽

Wen Bing Zhi ◽

...

Keyword(s):

Molecular Mechanisms ◽

Chinese Herb ◽

Vascular Diseases ◽

Enrichment Analysis ◽

Chinese Herbs ◽

Pathway Enrichment Analysis ◽

High Morbidity ◽

Active Ingredients ◽

Active Compounds ◽

System Pharmacology

Cardiocerebral vascular diseases (CCVDs) are the main reasons for high morbidity and mortality all over the world, including atherosclerosis, hypertension, myocardial infarction, stroke, and so on. Chinese herbs pair of the Cinnamomum cassia Presl (Chinese name, rougui) and the Aconitum carmichaelii Debx (Chinese name, fuzi) can be effective in CCVDs, which is recorded in the ancient classic book Shennong Bencao Jing, Mingyibielu and Thousand Golden Prescriptions. However, the active ingredients and the molecular mechanisms of rougui-fuzi in treatment of CCVDs are still unclear. This study was designed to apply a system pharmacology approach to reveal the molecular mechanisms of the rougui-fuzi anti-CCVDs. The 163 candidate compounds were retrieved from Traditional Chinese Medicine System Pharmacology Database and Analysis Platform (TCMSP). And 84 potential active compounds and the corresponding 42 targets were obtained from systematic model. The underlying mechanisms of the therapeutic effect for rougui-fuzi were investigated with gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis. Then, component-target-disease (C-T-D) and target-pathway (T-P) networks were constructed to further dissect the core pathways, potential targets, and active compounds in treatment of CCVDs for rougui-fuzi. We also constituted protein-protein in interaction (PPI) network by the reflect target protein of the crucial pathways against CCVDs. As a result, 21 key compounds, 8 key targets, and 3 key pathways were obtained for rougui-fuzi. Afterwards, molecular docking was performed to validate the reliability of the interactions between some compounds and their corresponding targets. Finally, UPLC-Q-Exactive-MSE and GC-MS/MS were analyzed to detect the active ingredients of rougui-fuzi. Our results may provide a new approach to clarify the molecular mechanisms of Chinese herb pair in treatment with CCVDs at a systematic level.

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A Network Pharmacology Approach to Uncover the Mechanisms of Shen-Qi-Di-Huang Decoction against Diabetic Nephropathy

Evidence-based Complementary and Alternative Medicine ◽

10.1155/2018/7043402 ◽

2018 ◽

Vol 2018 ◽

pp. 1-14 ◽

Cited By ~ 9

Author(s):

Sha Di ◽

Lin Han ◽

Qing Wang ◽

Xinkui Liu ◽

Yingying Yang ◽

...

Keyword(s):

Diabetic Nephropathy ◽

Signaling Pathway ◽

Molecular Mechanisms ◽

Interaction Network ◽

Enrichment Analysis ◽

Network Pharmacology ◽

Pathway Enrichment Analysis ◽

Protein Protein Interaction ◽

Regulation Of Blood Pressure ◽

Protein Protein Interaction Network

Shen-Qi-Di-Huang decoction (SQDHD), a well-known herbal formula from China, has been widely used in the treatment of diabetic nephropathy (DN). However, the pharmacological mechanisms of SQDHD have not been entirely elucidated. At first, we conducted a comprehensive literature search to identify the active constituents of SQDHD, determined their corresponding targets, and obtained known DN targets from several databases. A protein-protein interaction network was then built to explore the complex relations between SQDHD targets and those known to treat DN. Following the topological feature screening of each node in the network, 400 major targets of SQDHD were obtained. The pathway enrichment analysis results acquired from DAVID showed that the significant bioprocesses and pathways include oxidative stress, response to glucose, regulation of blood pressure, regulation of cell proliferation, cytokine-mediated signaling pathway, and the apoptotic signaling pathway. More interestingly, five key targets of SQDHD, named AKT1, AR, CTNNB1, EGFR, and ESR1, were significant in the regulation of the above bioprocesses and pathways. This study partially verified and predicted the pharmacological and molecular mechanisms of SQDHD on DN from a holistic perspective. This has laid the foundation for further experimental research and has expanded the rational application of SQDHD in clinical practice.

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Identification of Potential Key Genes and Molecular Mechanisms of Medulloblastoma Based on Integrated Bioinformatics Approach

BioMed Research International ◽

10.1155/2022/1776082 ◽

2022 ◽

Vol 2022 ◽

pp. 1-17

Author(s):

Md. Rakibul Islam ◽

Lway Faisal Abdulrazak ◽

Mohammad Khursheed Alam ◽

Bikash Kumar Paul ◽

Kawsar Ahmed ◽

...

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Expression Profiles ◽

Gene Expression Profiles ◽

Interaction Network ◽

Enrichment Analysis ◽

Clinical Information ◽

Gene Expression Omnibus ◽

Hub Genes ◽

New Treatments

Background. Medulloblastoma (MB) is the most occurring brain cancer that mostly happens in childhood age. This cancer starts in the cerebellum part of the brain. This study is designed to screen novel and significant biomarkers, which may perform as potential prognostic biomarkers and therapeutic targets in MB. Methods. A total of 103 MB-related samples from three gene expression profiles of GSE22139, GSE37418, and GSE86574 were downloaded from the Gene Expression Omnibus (GEO). Applying the limma package, all three datasets were analyzed, and 1065 mutual DEGs were identified including 408 overexpressed and 657 underexpressed with the minimum cut-off criteria of ∣ log fold change ∣ > 1 and P < 0.05 . The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and WikiPathways enrichment analyses were executed to discover the internal functions of the mutual DEGs. The outcomes of enrichment analysis showed that the common DEGs were significantly connected with MB progression and development. The Search Tool for Retrieval of Interacting Genes (STRING) database was used to construct the interaction network, and the network was displayed using the Cytoscape tool and applying connectivity and stress value methods of cytoHubba plugin 35 hub genes were identified from the whole network. Results. Four key clusters were identified using the PEWCC 1.0 method. Additionally, the survival analysis of hub genes was brought out based on clinical information of 612 MB patients. This bioinformatics analysis may help to define the pathogenesis and originate new treatments for MB.

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Bioinformatics Analysis Reveals the Potential Diagnostic Biomarkers for Abdominal Aortic Aneurysm

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.656263 ◽

2021 ◽

Vol 8 ◽

Author(s):

Xinsheng Xie ◽

En ci Wang ◽

Dandan Xu ◽

Xiaolong Shu ◽

Yu fei Zhao ◽

...

Keyword(s):

Gene Expression ◽

Molecular Mechanisms ◽

Bioinformatics Analysis ◽

Inflammatory Responses ◽

Expression Profiles ◽

Enrichment Analysis ◽

Aortic Aneurysms ◽

Differentially Expressed ◽

Pathway Enrichment Analysis ◽

Abdominal Aortic

Objectives: Abdominal aortic aneurysms (AAAs) are associated with high mortality rates. The genes and pathways linked with AAA remain poorly understood. This study aimed to identify key differentially expressed genes (DEGs) linked to the progression of AAA using bioinformatics analysis.Methods: Gene expression profiles of the GSE47472 and GSE57691 datasets were acquired from the Gene Expression Omnibus (GEO) database. These datasets were merged and normalized using the “sva” R package, and DEGs were identified using the limma package in R. The functions of these DEGs were assessed using Cytoscape software. We analyzed the DEGs using Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Protein–protein interaction networks were assembled using Cytoscape, and crucial genes were identified using the Cytoscape plugin, molecular complex detection. Data from GSE15729 and GSE24342 were also extracted to verify our findings.Results: We found that 120 genes were differentially expressed in AAA. Genes associated with inflammatory responses and nuclear-transcribed mRNA catabolic process were clustered in two gene modules in AAA. The hub genes of the two modules were IL6, RPL21, and RPL7A. The expression levels of IL6 correlated positively with RPL7A and negatively with RPL21. The expression of RPL21 and RPL7A was downregulated, whereas that of IL6 was upregulated in AAA.Conclusions: The expression of RPL21 or RPL7A combined with IL6 has a diagnostic value for AAA. The novel DEGs and pathways identified herein might provide new insights into the underlying molecular mechanisms of AAA.

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Gene Co-expression Network Analysis for Identifying Modules and Functionally Enriched Pathways in Vitiligo Disease: A Systems Biology Study

Iranian Journal of Allergy Asthma and Immunology ◽

10.18502/ijaai.v19i5.4467 ◽

2020 ◽

Author(s):

Afshin Derakhshani ◽

Homa Mollaei ◽

Negin Parsamanesh ◽

Mohammad Fereidouni ◽

Ebrahim Miri-Moghaddam ◽

...

Keyword(s):

Systems Biology ◽

Network Analysis ◽

Messenger Rna ◽

Molecular Mechanisms ◽

Biological Activities ◽

Neutrophil Migration ◽

Enrichment Analysis ◽

Autoimmune Disorder ◽

Hub Genes ◽

Novel Biomarkers

Vitiligo is the most common cause of skin, hair, and oral depigmentation which is known as an autoimmune disorder. Genetic and environmental factors have important roles in the progression of the disease. Dysregulation of gene expression, like microRNAs (miRNA), may serve as major relevant factors. Several biological processes are involved in vitiligo disease and developing a comprehensive approach helps us to better understand the molecular mechanisms of disease. In this research, we describe how a weighted gene co-expression network analysis as a systems biology approach assists to define the primary gene modules, hub genes, and messenger RNA (mRNA)-miRNA regulatory network in vitiligo disease as the novel biomarkers. The results demonstrated a module with a high correlation with vitiligo state. Moreover, gene enrichment analysis showed that this module's genes were mostly involved in some biological activities including G protein-coupled receptors signaling pathway, lymphocyte chemotaxis, chemokine activity, neutrophil migration, granulocyte chemotaxis, etc. The co-expression network was constructed using top hub genes of the correlated module which are named as CXCL10, ARL9, AKR1B10, COX7B, RPL26, SPA17, NDUFAF2, RPF2, DAPL1, RPL34, CWC15, NDUFB3, RPL26L1, ACOT13, HSPB11, and NSA2. MicroRNAs prediction tool (miRWalk) revealed top miRNAs correlated with the interested module. Finally, a drug-target network was constructed which indicated interactions of some food and drug administration (FDA) approved drugs with hub genes. Our findings specified one important module and main hub genes which can be considered as novel biomarkers for vitiligo therapeutic purposes.

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