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Network Analysis of Potential Risk Genes for Psoriasis Huilin Wang, Wenjun Chen, Jin He, Wenjuan Xu and Jiangwei Liu*

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Network Analysis of Potential Risk Genes for Psoriasis Huilin Wang, Wenjun Chen, Jin He, Wenjuan Xu and Jiangwei Liu* Wang et al. Hereditas (2021) 158:21 https://doi.org/10.1186/s41065-021-00186-w RESEARCH Open Access Network analysis of potential risk genes for psoriasis Huilin Wang, Wenjun Chen, Jin He, Wenjuan Xu and Jiangwei Liu* Abstract Background: Psoriasis is a complex chronic infammatory skin disease. The aim of this study was to analyze potential risk genes and molecular mechanisms associated with psoriasis. Methods: GSE54456, GSE114286, and GSE121212 were collected from gene expression omnibus (GEO) database. Diferentially expressed genes (DEGs) between psoriasis and controls were screened respectively in three datasets and common DEGs were obtained. The biological role of common DEGs were identifed by enrichment analysis. Hub genes were identifed using protein–protein interaction (PPI) networks and their risk for psoriasis was evalu- ated through logistic regression analysis. Moreover, diferentially methylated positions (DMPs) between psoriasis and controls were obtained in the GSE115797 dataset. Methylation markers were identifed after comparison with the common genes. Results: A total of 118 common DEGs were identifed, which were mainly involved in keratinocyte diferentiation and IL-17 signaling pathway. Through PPI network, we identifed top 10 degrees as hub genes. Among them, high expres- sion of CXCL9 and SPRR1B may be risk factors for psoriasis. In addition, we selected 10 methylation-modifed genes with the higher area under receiver operating characteristic curve (AUC) value as methylation markers. Nomogram showed that TGM6 and S100A9 may be associated with an increased risk of psoriasis. Conclusion: This suggests that immune and infammatory responses are active in keratinocytes of psoriatic skin. CXCL9, SPRR1B, TGM6 and S100A9 may be potential targets for the diagnosis and treatment of psoriasis. Keywords: Psoriasis, Diferentially expressed genes, Diferentially methylated positions, Pathogenesis Introduction of silver-white multilayered scales are characteristic of Psoriasis is an immune-mediated infammatory skin psoriasis, and the patient’s epidermis is thickened, clearly disease with important physiological and psychosocial demarcating from adjacent non-banded skin [5]. Te dis- consequences [1]. Psoriasis has complex characteris- ease afects more than 10% of the body surface area and tics, afecting about 2% of the general population, and usually requires systemic drug therapy. the prevalence of psoriasis varies from country to coun- Infammatory infltration consisting of dermal den- try [2, 3]. Tere are several clinical variants of this dis- dritic cells, macrophages, T cells, and neutrophils is ease, namely plaque psoriasis, erythrodermic psoriasis present in psoriatic plaques [6]. Help T cells have long and pustular psoriasis, among which plaque psoriasis been recognized as an important pathogenic factor accounts for more than 90% [4]. Clinically, red patches in psoriasis. Further evidence suggests that there is a strong T cell component to maintain psoriasis through T1, T17, and T22 cells and their derived cytokines *Correspondence: [email protected] Department of Dermatology, General Hospital of Xinjiang Military [7]. Te complex interaction of pro-infammatory Command, No. 359 Youhao North Road, Saybak District, Urumqi 830001, cytokines, chemokines, growth factors and chemical Xinjiang, China mediators initiated by T17 cells may be the key factors © The Author(s) 2021. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http:// creat iveco mmons. org/ licen ses/ by/4. 0/. The Creative Commons Public Domain Dedication waiver (http:// creat iveco mmons. org/ publi cdoma in/ zero/1. 0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Wang et al. Hereditas (2021) 158:21 Page 2 of 8 to induce keratinocyte proliferation, angiogenesis and Identifcation of diferentially expressed genes neutrophil infux, ultimately leading to keratinocyte Te diferentially expressed genes (DEGs) between over-proliferation and the characteristics of psoriatic psoriasis and normal were obtained through limma R plaques [8]. Recently, mast cells have been shown to be software package. Te log2 fold change (FC) ≥ 2 and the major producers of interleukin-22 in psoriasis and P-values < 0.05 were considered as a statistically signif- atomic dermatitis [9]. Among various molecules asso- cant diference. ciated with psoriasis, tumor necrosis factor (TNF)-α, IL-23, IL-17 and IL-22 are important regulators of pso- Enrichment analysis riasis [10]. Emerging evidence suggests that diferent phenotypes have diferent immunogenetic characteris- Te enrichment analysis was performed using clus- tics, which may afect treatment options [11]. terProfler R software package for the DEGs, includ- Epidermal gene modifcation is considered as an ing gene ontology (GO) functional analysis and Kyoto essential factor in the pathogenesis of psoriasis [12]. Encyclopedia of Genes and Genomes (KEGG) pathway Epigenetic changes also play an important role in the analysis. Te cellular component (CC), biological pro- cess (BP) and molecular function (MF) terms belonged diferentiation of CD4( +) T lymphocyte subsets and in the pathogenesis of psoriasis [13]. Among all epigenetic to GO function. P-value of < 0.05 was considered statis- mechanisms, DNA methylation is one of the important tically signifcant. factors in keratinocyte diferentiation [14, 15]. Com- mon drugs used to treat psoriasis, such as methotrex- Construction of protein–protein interaction (PPI) network ate, have been reported to interfere with the methyl transfer function of folic acid, thereby restoring nor- Te DEGs were put into the online tool STRING (https:// mal methylation status [16]. However, researchers still string- db. org) to construct the PPI network. A combined need to make greater eforts to elucidate how abnormal score of ≥ 0.5 was considered signifcant. Te hub genes epigenetic modifcations afect the pathogenesis of pso- were chosen based on a higher number of associations riasis. In addition, some environmental factors, includ- with other genes (degree) in the PPI network. ing modifable variables such as physical trauma, drug reversal, psychological stress, obesity, are associated DNA methylation analysis with the development and deterioration of psoriasis GSE115797 included DNA methylation profle of 24 [17]. psoriatic disease skin tissue and adjacent normal skin In this study, psoriasis-related sequencing data in samples. Te signal intensities along with the detec- public databases were used to explore the molecular tion P-values were calculated for each CpG probes after mechanisms and potential risk factors of the disease. BMIQ normalization. Normal skinized average beta val- ues were calculated using ChAMP R software. Diferen- Materials and methods tially methylated positions (DMPs) between psoriasis Data collection and normal were achieved by limma R software pack- age. Set screening threshold with false discovery rate We collected psoriasis-related datasets from the (FDR) < 0.05. gene expression omnibus (GEO) database. GSE54456 included gene expression profle from skin samples of 92 psoriatic and 82 normal punch biopsies. Te genes Statistical analyses annotated in RefSeq was used to quantify gene expres- Statistical analyses were carried out with SPSS Statistics sion levels. Te gene expression was normalized to 21.0. Te diferences between two groups were compared the number of reads per kilobase per million mapped by Student t test. LRM function in RMS R software pack- reads (RPKM). GSE114286 included gene expression age was used for logistic regression analysis. profle from 9 normal skins from healthy volunteers and 18 lesional skins from patients with psoriasis. Te gene expression was normalized through RPKM. Results GSE121212 included gene expression profle of skin Diferentially expressed genes in psoriasis tissues obtained from a carefully matched and tightly By comparing the diferences between psoriasis and defned cohort of 28 psoriasis patients, and 38 healthy healthy controls, we obtained diferentially expressed controls. Paired reads were mapped to the human ref- genes (DEGs). A total of 401, 1857, and 466 DEGs were erence genome (b37), number of reads for each gene obtained in GSE54456, GSE114286 and GSE121212, was counted using HTSeq. respectively (Fig. 1A). Among these DEGs, we found 118 Wang et al. Hereditas (2021) 158:21 Page 3 of 8 Fig. 1 The diferentially expressed genes between psoriasis and control. A Volcano maps of diferentially expressed genes in three datasets. B The common genes in three groups of diferentially expressed genes genes simultaneously present in three datasets and then logistic regression analysis and presented the risk pre- defned them as common DEGs (Fig. 1B).
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