Hindawi BioMed Research International Volume 2019, Article ID 8794013, 7 pages https://doi.org/10.1155/2019/8794013

Research Article Screening and Bioinformatics Analysis of IgA Nephropathy Based on GEO Databases

Wang Qian ,1 Wang Xiaoyi ,2 and Ye Zi 1

 Department of Nephrology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China Department of Gastroenterology, Shanghai Traditional Chinese Medicine-Integrated Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China

Correspondence should be addressed to Wang Qian; [email protected]

Received 21 November 2018; Revised 14 April 2019; Accepted 30 May 2019; Published 16 July 2019

Academic Editor: Graziano Pesole

Copyright © 2019 Wang Qian et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Purpose. To identify novel biomarkers of IgA nephropathy (IgAN) through bioinformatics analysis and elucidate the possible molecular mechanism. Methods. Te GSE93798 and GSE73953 datasets containing microarray data from IgAN patients and healthy controls were downloaded from the GEO database and analyzed by the GEO2R web tool to obtain diferent expressed (DEGs). (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, protein-protein interaction (PPI), and Biological Networks Gene Oncology tool (BiNGO) were then performed to elucidate the molecular mechanism of IgAN. Results. A total of 223 DEGs were identifed, of which 21 were hub genes, and involved in infammatory response, cellular response to lipopolysaccharide, transcription factor activity, extracellular exosome, TNF signaling pathway, and MAPK signaling pathway. Conclusions. TNF and MAPK pathways likely form the basis of IgAN progression, and JUN/JUNB, FOS, NR4A1/2, EGR1, and FOSL1/2 are novel prognostic biomarkers of IgAN.

1. Introduction bioinformatics analysis have enabled genomic and transcrip- tomic screening of IgAN samples and helped identify the Immunoglobulin A nephropathy (IgAN) is the most com- diferentially expressed genes (DEGs) involved in its devel- monly occurring primary glomerulonephritis worldwide and opment and progression. However, due to high false positive is characterized by increased IgA circulation and deposi- rates, it is difcult to obtain reliable results from independent tion in the mesangium [1, 2]. Studies have also shown a microarrays. Terefore, we analyzed two genetic predisposition to IgAN [3], with several genes like microarray datasets from the Gene Expression Omnibus those encoding transforming growth factor-�(TGF-�)[4], (GEO) database to identify the DEGs between IgAN and Megsin [5], Tank binding kinase 1(TBK1) [6], etc. mutated normal human tissues. Subsequently, Gene Ontology (GO) and/or abnormally expressed during IgAN development, and Kyoto Encyclopedia of Genes and Genomes (KEGG) and correlated with its prognosis. IgAN is one of the main enrichment analysis and protein-protein interaction (PPI) causes of end-stage renal disease and has diverse clinical were performed to elucidate the molecular mechanisms of the manifestations that difer widely in terms of pathological DEGs. We selected 8 out of 41 hub genes that are potential types and prognosis. However, due to the lack of efective targets for the diagnosis and treatment of IgAN. diagnostic methods, most IgAN patients are usually diag- nosed at the middle and late stages of the disease, leading 2. Materials and Methods to poor prognosis. Terefore, it is important to understand the precise molecular mechanisms underlying IgAN in order .. Identification of DEGs. Two microarray datasets of to develop efective diagnostic and therapeutic strategies. IgAN—GSE93798 and GSE73953—were downloaded from Over the past few decades, microarray technology and the GEO database (http://www.ncbi.nlm.nih.gov/geo/) using 2 BioMed Research International

“IgAN” as the search term. GSE93798 was submitted by Liu Table 1: Functional roles of 21 hub genes. P, L a s s enEetal.,andGSE73953byOkuzakiD,Nojima´ H et al. GSE93798 was based on Afymetrix’s HGU133 No. Gene symbol MCODE Score Plus 2 chip and includes 42 samples (20 IgAN patients 1CD44 8.00 and 22 healthy controls). GSE73953 is based on Agilent’s 2FOSB 8.67 014850 chip and includes 25 samples (15 IgAN patients 3ZFP36 7.82 and 2 healthy controls). Te DEGs between IgAN patients 4IER2 7.82 and normal subjects were analyzed using the GEO2R web 5FOSL2 7.82 tool (http://www.ncbi.nlm.nih.gov/geo/geo2r). Te screen- 6 MMP2 8.00 ing conditions for the DEGs were absolute value of logFC >1 < 7FOSL1 8.00 and adj. P value 0.01. 8EGR3 8.00 9EGR1 8.67 .. KEGG and GO Enrichment Analyses of DEGs. Te DEGs 10 BTG2 8.67 were uploaded to the DAVID (the database for annota- 11 NR4A1 7.27 tion, visualization, and integrated discovery) version 6.8 12 FOS 8.67 (http://david.ncifcrf.gov) [7] online data analysis tool for 13 HBEGF 7.00 KEGG and GO analyses. P < 0.05 was considered statistically 14 JUNB 8.67 signifcant. 15 IL1B 8.00 16 JUN 8.67 .. PPI Network Construction and Module Analysis. Te 17 DUSP1 8.67 STRING (version 10.0) (http://string-db.org) tool was used to 18 NR4A2 7.82 construct a PPI network of the DEGs with a combined score 19 KLF6 7.00 > 0.4 as the threshold for statistically signifcant interaction. 20 PLG 8.00 Te Cytoscape (version 3.4.0) sofware was used to further analyze the interactive network, with the Molecular Complex 21 SERPINE1 8.00 Detection (MCODE) plugin to identify important molecules in the PPI network. Te recognition criteria were MCODE scores > 5, degree cut-of = 2, node score cut-of = 0.2, Max diferentiation, TNF signaling, glycine, serine and threonine depth = 100, and k-score = 2. , and the MAPK signaling pathway (Figure 2(d)).

.. Hub Genes Selection and Analysis. Te biological pro- cessesofthehubgeneswerevisualizedusingtheBiological .. PPI Network Construction and Module Analysis. Te Networks Gene Oncology tool (BiNGO) (version 3.0.3) PPI network of the DEGs was constructed (Figure 1(b)) and plugin of Cytoscape [8], with signifcance threshold 0.01 and the most signifcant module was obtained using Cytoscape Homo sapiens as the selected organism. Subsequently, the (Figure 1(c)). GO analysis of the module showed signifcant KEGG and GO analyses for the genes in this module were enrichment in the BP terms of infammatory response, cellu- performed using DAVID. lar response to calcium ion, skeletal muscle cell diferentia- tion, cellular response to extracellular stimulus, negative reg- ulation of transcription from RNA polymerase II promoter, 3. Results and cellular response to corticotropin-releasing hormone stimulus (Figure 4(a)), MF terms of transcription factor .. Identification of DEGs in IgAN. Afer standardizing the activity, RNA polymerase II core promoter proximal region microarray results, we identifed a total 14353 DEGs in sequence-specifc binding, transcriptional activator activity, GSE73953 and 348 in GSE93798. A Venn diagram of both and RNA polymerase II core promoter proximal region datasets showed 223 overlapping genes (Figure 1(a)). GO sequence-specifc DNA binding MF terms (Figure 4(b)), analysis showed that the biological processes (BP) terms and CC terms of transcription factor complex, nucleoplasm, of the DEGs were signifcantly enriched in infammatory and nucleus (Figure 4(c)). KEGG pathway analysis revealed response, response to cAMP, response to drug, cellular that the downregulated DEGs were mainly enriched in response to lipopolysaccharide, and xenobiotic metabolic osteoclast diferentiation, estrogen signaling, TNF signaling, process (Figure 2(a)). Te molecular function (MF) terms and MAPK signaling pathways (Figure 4(d)). were mainly enriched in transcription factor activity, RNA polymerase II core promoter proximal region sequence- specifc binding, transcriptional activator activity, and E-box .. Hub Gene Selection and Analysis. Atotalof21genes binding (Figure 2(b)). Finally, cell component (CC) terms were identifed as hub genes, and their names and MCODE were mainly enriched in extracellular exosome, extracel- scores are shown in Table 1. A network of the hub genes lular space, extracellular region, and blood microparticles and their coexpression genes was analyzed using BiNGO tool (Figure 2(c)). KEGG pathway analysis revealed that the of Cytoscape (Figure 3(a)), and the signifcant coexpression downregulated DEGs were mainly enriched in the osteoclast genesareshowninFigures3(b)and3(c). BioMed Research International 3

GLYAT MIOX CSRNP1

ERRFI1 S100A2 GJA4 CMBL CYP4F2 HRG MARCKS IMPA2 TIPARP ECM1 LPAR6 S100A12 PLA2G7 ARRDC2 SERPINA1 HCLS1 APOH DDIT4 PLA2G4AFGB TNFAIP3 GPR65 PTGS1 IFI30 IGSF6 S100A8 MS4A7 AREG LYZ NFKBIZ BAG3 PDE4B APOM PLEK PLG C3AR1RGS1 CLEC5A BHLHE40 SERPINE1 CSF1R CEBPB AGT IL10RA CXCL2CXCR2 CD14CX3CR1 HSPA6 NFIL3 MGAM TWIST1CYBB FPR3 GATM HBEGF ATF3IL1B AK4 GADD45BSOCS3FCGR3B C1QA MYC CCL4 NR4A1 ARG2 ARG1 JUN FOS CCL8PPP1R10 DNAJB1 MAFF BTG2KLF6 CXCL11 PIPOX CDKN1A CXCL10 NR4A2 CD44FOSL1 ZFP36 CTH RRM2SHMT1 CEBPD PPP1R15A CD36 ERAP2 C10orf10 DUSP1CD69 TSC22D3 MMP2 EGR1 CRYM DUSP6 ASS1 KLF4 SDC1IER2 XPNPEP2 PSAT1 PER1 GATA3 DUSP2 TOP2A JUNB FOSB EGR3 FOSL2 SPRY2 COL6A3 MECOM DPEP1 PLD6 NDC80 PMAIP1 COL3A1 SLCO4C1AGPAT9 PDK4 CRISPLD2 IDO1 HBB GADD45G SLC47A1 UCP2 TOX3 ERP27 AGMAT COL1A1 93798 HHEX FNDC1 GSE SLC7A9 RDH10 AKR1B10 SLC16A9 SLC2A2 SLC22A11SLC5A12 SOX17

ALDH8A1 SLC17A1 ABP1 TGFBI MAOA 125 223 14131 SLC13A3 ADH1B

HRSP12 ALDH6A1 AKR1C1 SLC4A4 MGST1 GSE73953 GSTA3 (a) (b)

SERPINE1 IL1B PLG BTG2

HBEGF FOS KLF6 NR4A1 CD44 NR4A2 ZFP36 FOSL1 JUN MMP2 DUSP1 EGR1 EGR3 IER2 JUNB FOSL2 FOSB (c)

Figure 1: Venn diagram, PPI network, and the most signifcant module of DEGs. (a) DEGs were selected with absolute value of logFC >1 and adj. P value <0.01 from the GSE93798 and GSE73953 datasets, which showed an overlap of 223 genes. (b) Te PPI network of DEGs was constructed using Cytoscape. (c) Te most signifcant module was obtained from PPI network.

4. Discussion infammatory reaction [10, 11] and glomerular and tubular fbrosis[12,13].Tumornecrosisfactor(TNF)isacritical IgAN accounts for ∼20% to 47% of primary glomerular dis- cytokine involved in apoptosis, cell survival, infammation, eases and is mainly characterized by hematuria, proteinuria, and immunity. Te MAPK pathway is also associated with hypertension, and renal dysfunction [9]. Te incidence of tubule-interstitial fbrosis in IgAN [14]. Signaling through the the disease has been increasing annually, and 30% to 40% TNF receptor (TNFR1) activates a number of genes via two of the patients progress to end-stage renal disease (ESRD), distinct pathways: NF-kB and the MAPK cascade. Tus, both which is the main cause of primary glomerulonephritis for pathways obtained by enrichment analysis are correlated and renal replacement therapy in China, within 10 years [3]. involved in the pathogenesis of IgAN. Although the most common clinical manifestation of IgAN Using STRING and MCODE, we selected 21 DEGs as is hematuria, there is considerable heterogeneity among the hub genes and found the maximal correlation between diferent cases, which makes early diagnosis challenging. JUN/JUNB,FOS,NR4A1/2,EGR1,andFOSL1/2.Teexpres- We analyzed two IgAN microarray datasets from the GEO sion levels of JUN, an early responding transcription factor, database to screen for DEGs in IgAN and identify potential are very low in under normal conditions. Upon receiving biomarkers. We obtained a total of 223 DEGs, and the an external stimulus, it is rapidly activated and dimerizes upregulated genes were mainly enriched in infammatory with either another JUN protein or with AP-1 to form the response, cell fbrosis, TNF signaling pathway, and MAPK FOS protein. Te JUNB gene is structurally and function- signaling pathway. Previous studies have shown a signifcant ally very similar to JUN and along with JUN and FOS association of IgAN development and prognosis with the forms the upstream element of the TNF/TNFR1 pathway. 4 BioMed Research International

platelet alpha granule lumen xenobiotic metabolic process

mitochondrial outer membrane response to lipopolysaccharide

integral component of plasma membrane response to hydrogen peroxide

extracellular space response to drug

extracellular region response to cAMP

GO Terms -log10(Pvalue)

GO Terms -log10(Pvalue) 8 Platelet degranulation extracellular matrix 8 6 7 extracellular exosome 4 inflammatory response 6 5 2 cellular response to lipopolysaccharide external side of plasma membrane

cellular response to fibroblast growth factor endoplasmic reticulum lumen

cellular response to extracellular stimulus blood microparticle

5101520 2 4 6 Rich Factor Rich Factor Gene_Counts Gene_Counts 5 10 20 15 40 20 60 (a) (b)

Toll-like receptor signaling pathway

TNF signaling pathway transcriptional activator activity Staphylococcus aureus infection transcription factor binding p53 signaling pathway transcription factor activity, sequence-specific DNA binding

Osteoclast diferentiation transcription factor activity

-log10(Pvalue)

GO Terms sequence-specific DNA binding MAPK signaling pathway Pathway Terms Pathway -log10(Pvalue) 3.5 RNA polymerase II core promoter proximal region 5.0 Glycine, serine and threonine metabolism 3.0 4.5 2.5 4.0 protein homodimerization activity 3.5 2.0 3.0 Complement and coagulation cascades 2.5 heparin binding Biosynthesis of amino acids E-box binding Arginine and proline metabolism chemokine activity 34567 8 5 10 15 20 Rich Factor Rich Factor Gene_Counts Gene_Counts 6 5 8 10 10 15 12 20 14 (c) (d)

Figure 2: GO and KEGG pathway enrichment analysis of DEGs. Te color depth of nodes refers to the P-value. Te size of nodes refers to the numbers of genes. (a) GO BP terms. (b) GO CC terms. (c) GO MF terms. (d) KEGG Pathway of DEGs.

Te interaction between the JNK/MAPK and TNF/TNFR1 FOSL1/2 in IgAN patients, and Park et al. found that the FOS pathways forms the molecular basis of glomerular and renal proteins are also involved in the disappearance of podocyte interstitial atrophy and apoptosis, which leads to progressive footprocesses[20].Podocytesmaintainthestructureand renal damage and renal fbrosis [15]. Tese pathways are function of the glomerular fltration membrane and prevent also involved in RAAS activation, complement activation, proteinuria. coagulation cascades [16], and infammation [17]. Early growth response factor 1 (Egr1) is a zinc-fnger FOSL1 and FOSL2 are also members of the FOS gene transcription factor expressed across diferent eukaryotic family [18] and overexpressed in various renal diseases like cells [21]. In humans, it is expressed in various renal cells, IgAN, lupus nephropathy, and focal glomerular sclerosis, including glomerular MCs, endothelial cells, renal tubular with pivotal roles in glomerular sclerosis and mesangial pro- fbroblasts, and epithelial cells [22]. Upregulation of Egr1 is liferation. Rastaldi et al. [19] reported abnormal expression of associated with renal fbrosis and infammation, especially in BioMed Research International 5

positive regulation of apoptosis

positive regulation of positive regulation of nuclear-transcribedmRNA 3'-end mRNA poly(A) tail regulation of apoptosis processing shortening positive regulation of ERK1 and ERK2 cascade negative regulation of apoptosispositive regulation of programmed cell death regulation of nuclear-transcribedpositive regulation mRNARNA of mRNA catabolic poly(A) tail shortening regulation of mRNA 3'-end processing process positive regulation of MAPKKK cascade positivei regulation of mRNA processing regulation of programmed cell death regulation of ERK1 and ERK2 cascade positive regulation of cellularnegative catabolic regulation of elastin process biosynthetic process regulation of mRNA catabolic process negative regulation of programmedmmed cell positive regulation of intracellular protein positive regulation of RNA metabolic deathpositive regulation of cell death kinase cascade regulation of MAPKKK cascade regulation of mRNA processingprocessng positive regulation of catabolic process positive regulation of transcription, regulation of elastin biosynthetic process positive regulation of gene expression positive regulation of signal transduction mitotic regulation of cellular catabolic process positive regulation of transcription, positive regulation of transcription from positive regulation of macromolecule positivepos regulation of cell adhesion RNA polymerase II promoter, mitotic DNA-dependent positivep regulationmmetabolic of nucleobase, processpositive regulation of cellular metabolic regulation of cell death molecule production positive regulation of signaling pathwpathway positive regulation of transcription from nucleonunnucleoside, nucleotide and nucleic acid process regulation of intracellular RNA polymerase II promoter regulationulation ofo RNA metabolic process cascade metabolic process negative regulation of glycoprotein regulation of gene expression regulationgula of catabolic process positive regulation of cell communication positive regulationregulation of cellularof glycoproteinar biosyntheticbiosyntheticeteticc process biosynthetic process process positive regulation of transcription positive regulationnegative of cellular regulationar processpro of cell death regulation of transcription, mitotic regulation ofpositive signal transduction regulationction nof signaling process positive regulation of macromolecule regulation of transcription from RNA regulation of transcription, ppositive regulation of biosynthetic biosynthetic processs positive regulation of metabolic process polymerase II promoter, mitotic DNA-dependent regulation of macromolecule metabolic positivesit ve regulation of nitrogen regulation of cell adhesion molecule regulation of transcription from RNA process regulation of cellular metabolic processregulation of cell adhesion compound metabolic process production polymerase II promoter regulation of nucleobase,se nucleoside, nucnu nucleotide and nucleic acid metabolic positive regulation of regulationanti-apoptosis ofsis signaling pathway regulation of transcription regulationregulatioegulatigul of cellular biosynthetic process negative regulation of cellular processnegativenegativ regulation of macromolecule biosynthetic processnegative regulation of cellular metabolic regulation of cell communication positive regulation of angiogenesis regulation of macromolecule biosynthetic process process biosynthetic process regulation ofpositive signaling regulation processcess of developmental process negative regulation of vascular wound regulation of metabolic process regulation of anatomical structure regulation of cellular process negative regulation of angiogenesis healing regulationregulation ofegulationeg nitrogennegative of compound biosynthetic regulation process of macromolecule morphogenesis metabolic process metabolic process positivesitive regulationre of biologicalgical process negative regulation of cellularregulation process of anti-apoptosis negative regulation of biosynthetic negative regulation of developmental regulation of primary metabolic process process negative regulation of metabolic process process regulation of regulationimmune system of developmentalm processpro process regulation of angiogenesisregulation of vascular wound healing regulation of cell proliferation negative regulation of response to negative regulation of wound healing negative regulation of cell proliferation stimulus negativenegat regulation of biological process negative regulation of response to regulation of cellular localization regulation of biological process regulation of hormone secretion negative regulation of multicellular external stimulus positive regulation of responseorganismal to process stimulus negative regulation of coagulation negative regulation of hormone secretionregulation of fbrinolysis regulation of wound healing regulationgulatioulaatio of response to stimulus regulation of localization regulation of multicellular organismal positive regulation of multicellularprocess organismal process regulation of response to stress negative regulation of transport regulation of coagulation signal transduction regulation of secretion negative regulation of blood coagulation negative regulation of fbrinolysis regulation of response to external positive regulation of response to negative regulation of secretion stimulus external stimulusus regulation of blood coagulation positive regulation of defense response regulation of adiponectin secretion negativene regulation of adiponectin positive regulation of coagulation secretion regulation of transport regulation of system process positive regulation of blood coagulation regulation of leukotriene production regulation of defense response SMAD protein signal transduction positive regulation involvedof leukotriene in infammatory response production involved in infammatory response regulation of endocrine process positive regulation ofregulation infammatory of infammatory response response

signal transmissiontransmembranetra receptor protein serine/threonineser kinase signaling pathway

biological regulation linked receptor protein signaling pathway

signaling process cell surface receptor linked signaling regulation of molecular function chordate embryonic development neurological system process pathway negative regulation of molecular function in utero embryonic development signaling pathway embryonic development ending in birth negative regulation of catalytic activity or egg hatching system process signaling regulation of catalytic activity cognition learning negative regulation of hydrolase activity

embryonic placenta development reproductive process regulation of hydrolase activity negative regulation of peptidase activity embryonic development multicellular organismal process labyrinthine layer blood vesselembryonic organ development multicellular organismal development development reproduction biological_process learning or memory regulation of peptidase activity labyrinthine layer development system development female pregnancy placenta development immune system process regeneration multi-organism process placenta blood vessel development anatomical structure maturationdevelopmental maturation growth immunei system developmentdevelopmentalment process blood vessel development anatomical structure development organ development developmental growth response to other organism anatomical structure morphogenesis behavior response to bacterium vasculature development hemopoietic or lymphoid organ tissue regeneration blood vessel maturation development response to lipopolysaccharide tissue development aging anatomical structure formation involved cellular process in morphogenesiss response to biotic stimulus cellular developmental processwound healing response to molecule of bacterial origin response to stimulus hemopoiesis response to organic nitrogen response to woundingcellular response to stimulus epithelium development syncytium formation response to gravity response to cytokine stimulus cell communication responseresre to mechanical stimulus cell diferentiation response to endogenous stimulus

leukocyte diferentiation response to stress cellular response to chemical stimulus cellular response to extracellularresponserespo to external stimulus response to cAMPresponse to organic substanceresponse to protein stimulus stimulus response to abiotic stimulus epithelial cell diferentiation syncytium formation by plasma cellular response to endogenousresponse to hormone stimulus membrane fusion stimulus response to stimulus response to chemicalcellularcellul response stimulus to organic substancebstan defense response response to steroid hormone stimulus response to corticosteroid stimulus cellular response to external stimulus response to organic cyclic substance response to corticosterone stimulus responsespon to extracellularresponserre stimulus to oxidative stress leading edge cell diferentiation cellular response to hormone stimulus response to mineralocorticoid stimulus macrophage fusion response to drug response to progesterone stimulus response toresponse radiation ton nutrient levels response to inorganic substance response to nutrient

response to reactive oxygen species

response to light stimulus response to vitamin

response to hydrogen peroxide

(a)

response to organic substance

response to organic cyclic substance

positive regulation of apoptosis response to glucocorticoid stimulus

positive regulation of cellular metabolic regulation of apoptosis process response to corticosteroid stimulus positive regulation of RNA metabolic process positive regulation of cellular process positive regulation of gene expression regulation of programmed cell death regulation of transcription from RNA polymerase II promoter -log10(Pvalue) regulation of gene expression positive regulation of programmed cell death BiNGO Terms positive regulation of transcription positive regulation of macromolecule 10.5 metabolic process positive regulation of transcription, 10.0 DNA-dependent positive regulation of cell death positive regulation of RNA metabolic process 9.5 9.0 positive regulation of transcription 8.5 positive regulation of nucleobases positive regulation of transcription from positive regulation of nucleobase, regulation of cellular metabolic process regulation of cell death RNA polymerase II promoter nucleoside, nucleotide and nucleic acid metabolic process positive regulation of cellular process regulation of RNA metabolic process positive regulation of metabolic process positive regulation of biological process regulation of transcription from RNA regulation of cellular process polymerase II promoter positive regulation of macromolecule biosynthetic process positive regulation of biosynthetic 10 20 30 40 process positive regulation of cellular Rich Factor biosynthetic process positive regulation of biological process Gene_Counts positive regulation of nitrogen 6 regulation of macromolecule metabolic compound metabolic process 9 process regulation of metabolic process 12 15 (b) (c)

Figure 3: Interaction network and biological process analysis of the hub genes. Te color depth of nodes refers to the P-value. Te size of nodes refers to the numbers of genes. (a) Hub genes and their coexpression genes were analyzed using BiNGO. (b), (c) Te most signifcant coexpression was obtained from BiNGO network. 6 BioMed Research International

skeletal muscle cell diferentiation transcription factor complex

response to drug

regulation of cell death nucleus positive regulation of transcription

positive regulation of DNA-templated transcription

GO Terms -log10(Pvalue) -log10(Pvalue) nucleoplasm

GO Terms negative regulation of transcription 5 2.5 4 2.0 monocyte aggregation 3 1.5 extracellular space cellular response to extracellular stimulus

cellular response to corticotropin-releasing hormone stimulus 51015

cellular response to calcium ion Rich Factor Gene_Counts 0 200 400 600 4 Rich Factor 5 Gene_Counts 6 2 7 3 8 4 5 9 (a) (b)

TNF signaling pathway transcriptional activator activity Salmonella infection transcription factor binding Pertussis

transcription factor activity Osteoclast diferentiation

MAPK signaling pathway

GO Terms steroid hormone receptor activity -log10(Pvalue) Leishmaniasis -log10(Pvalue) 6 RNA polymerase II transcription factor activity Terms Pathway 5 6 HTLV-I infection 4 4 3 RNA polymerase II core promoter sequence-specific DNA binding 2 Estrogen signaling pathway 2

RNA polymerase II core promoter proximal region binding Chagas disease

chromatin binding Amphetamine addiction 10 15 20 0 40 80 120 160 Rich Factor Rich Factor Gene_Counts Gene_Counts 3 2 4 3 5 4 6 5 6 7 (c) (d)

Figure 4: GO and KEGG pathway enrichment analysis of hub genes. Te color depth of nodes refers to the P-value. Te size of nodes refers to the numbers of genes. (a) GO BP terms. (b) GO CC terms. (c) GO MF terms. (d) KEGG Pathway of hub genes.

the development of diabetic nephropathy [23–25]. Its role in but the involvement of JUN, JUNB, NR4A1/2, and EGR1 in the development of IgAN is not completely clear. this disease has not been widely reported. Tey are directly NR4A1 and NR4A2 are also two early responding genes related to each other and likely mediate the pathological associated with cancer [26] and chronic infammatory dis- changes in the kidneys of IgAN patients. eases [27], including that afecting the kidneys. Westbrook et al. showed increased kidney injury and reduced renal function in the NR4A1 knockout mouse model. NR4A1 plays 5. Conclusion a signifcant role in kidney injury via immune activation, and Twenty-one hub genes were identifed that are potential enhancing NR4A1 expression or function is a potential ther- prognostic/diagnostic biomarkers of IgAN. Teir biological apeutic strategy against kidney disease [28]. Xin et al. showed functions and mechanisms of action in IgAN need to be thepossibleinvolvementofNR4A2inthedevelopmentof studied further. congenital obstructive nephropathy [29]. However, neither protein has been associated with IgAN. Tosummarize, we identifed several hub genes involved in Data Availability the pathological changes of IgAN. Te FOS family genes are associated with renal infammation, fbrosis, and podocyte Te data used to support the fndings of this study are function during the development and progression of IgAN, available from the corresponding author upon request. BioMed Research International 7

Conflicts of Interest in IgA nephropathy,” Biochemical and Biophysical Research Communications,vol.444,no.4,pp.455–460,2014. Te authors declare that they have no conficts of interest. [14] M. Zhang and X.-M. Li, “Relationship of mitogen-activated protein kinases activation with transdiferentiation of renal Authors’ Contributions tubular epithelial cells in patients with IgA nephropathy,” Zhonghua Yi Xue Za Zhi,vol.84,no.11,pp.898–903,2004. Wang Qian and Wang Xiaoyi contributed equally. [15] R. Eferl and E. F. Wagner, “AP-1: a double-edged sword in tumorigenesis,” Nature Reviews Cancer,vol.3,no.11,pp.859– Acknowledgments 868, 2003. [16] H. Jiang, L. Liang, J. Qin et al., “Functional networks of aging Te present study was supported by the Shanghai Municipal markers in the glomeruli of IgA nephropathy: a new therapeutic Commission of Health and Family Planning Clinical Com- opportunity,” Oncotarget,vol.7,no.23,pp.33616–33626,2016. � mission Project (grant nos. 20184Y0207). [17] S. A. Mezzano, M. Barria, M. A. Droguett et al., “Tubular NF- B and AP-1 activation in human proteinuric renal disease,” Kidney International,vol.60,no.4,pp.1366–1377,2001. References [18] T. Takemura, M. Okada, N. Akano et al., “Proto-oncogene expression in human glomerular diseases,” e Journal of [1] H. Jiang, L. Liang, J. Qin et al., “Functional networks of aging Pathology,vol.178,no.3,pp.343–351,1996. markers in the glomeruli of IgA nephropathy: a new therapeutic opportunity,” Oncotarget ,vol.7,no.23,2016. [19] M. Rastaldi, “Transforming growth factor-beta, endothelin-1, and c-fos expression in necrotizing/crescentic IgA glomeru- [2]X.Su,J.Lv,Y.Liuetal.,“Pregnancyandkidneyoutcomes lonephritis,” Nephrology Dialysis Transplantation,vol.13,no.7, in patients with iga nephropathy: a cohort study,” American pp. 1668–1674, 1998. Journal of Kidney Diseases, vol. 70, no. 2, pp. 262–269, 2017. [3]L.-S.LiandZ.-H.Liu,“Epidemiologicdataofrenaldiseases [20]H.J.Park,J.W.Kim,B.Choetal.,“AssociationofFOS-like from a single unit in China: analysis based on 13,519 renal antigen 1 promoter polymorphism with podocyte foot process biopsies,” Kidney International,vol.66,no.3,pp.920–923,2004. efacement in immunoglobulin a nephropathy patients,” Journal of Clinical Laboratory Analysis,vol.28,no.5,pp.391–397,2014. [4]C.Lim,Y.Kim,D.Chaeetal.,“AssociationofC-509Tand T869C polymorphisms of transforming growth factor-b1 gene [21]V.P.Sukhatme,X.M.Cao,L.C.Changetal.,“Azinc with susceptibility to and progression of IgA nephropathy,” fnger-encoding gene coregulated with c-fos during growth and Clinical Nephrology,vol.63,no.02,pp.61–67,2005. diferentiation, and afer cellular depolarization,” Cell,vol.53, no. 1, pp. 37–43, 1988. [5] G. Yating, S. Meiling, S. Jiazhi et al., “Meta-analysis of the relevance between Megsin rs1055901, rs1055902 and rs2689399 [22] V. P. Sukhatme, “Te Egr transcription factor family: From polymorphism and susceptibility of IgA nephrology in Asian signal transduction to kidney diferentiation,” Kidney Interna- population,” Chongqing Medical Journal,vol.46,no.5,pp.648– tional,vol.41,no.3,pp.550–553,1992. 653, 2017. [23]C.Wu,X.Ma,Y.Zhou,Y.Liu,Y.Shao,andQ.Wang,“Klotho [6] Y. Xia, W.Ping, L. Fujun et al., “Association of single nucleotide restraining Egr1/TLR4/mTOR axis to reducing the expression TANK binding kinase-1 gene polymorphism with clinical of fbrosis and infammatory cytokines in high cultured features and histological phenotypes in IgA nephropathy,” rat mesangial cells,” Experimental and Clinical Endocrinology & Shanghai Medical Journal,vol.37,no.5,pp.394–397,2014. Diabetes,2018. [7]D.W.Huang,B.T.Sherman,Q.Tanetal.,“TeDAVIDgene [24]F.Hu,M.Xue,Y.Lietal.,“Earlygrowthresponse1(Egr1)isa functional classifcation tool: a novel biological module-centric transcriptional activator of nox4 in oxidative stress of diabetic algorithm to functionally analyze large gene lists,” Genome kidney disease,” Journal of Diabetes Research,vol.2018,Article Biology,vol.8,no.9,articleR183,2007. ID 3405695, 10 pages, 2018. [8]S.Maere,K.Heymans,andM.Kuiper,“BiNGO:aCytoscape [25] L. Ho, J. Sung, Y. Shen et al., “Egr-1 defciency protects from plugin to assess over-representation of gene ontology categories renal infammation and fbrosis,” Journal of Molecular Medicine, in biological networks,” Bioinformatics,vol.21,no.16,pp.3448- vol.94,no.8,pp.933–942,2016. 3449, 2005. [26] E. Hedrick, S. Lee, G. Kim et al., “Nuclear receptor 4A1 (NR4A1) [9]R.J.Wyatt,“JulianBA.IgAnephropathy,”e New England as a drug target for renal cell adenocarcinoma,” Plos One,vol.10, Journal of Medicine,vol.368,no.25,pp.2402–2414,2013. no. 6, Article ID e0128308, 2015. [10] X. Sheng, X. Zuo, X. Liu, Y. Zhou, and X. Sun, “Crosstalk [27] J. McMorrow and E. Murphy, “Infammation: a role for NR4A between TLR4 and Notch1 signaling in the IgA nephropa- orphan nuclear receptors?” Biochemical Society Transactions, thy during infammatory response,” International Urology and vol. 39, no. 2, pp. 688–693, 2011. Nephrology,vol.50,no.4,pp.779–785,2018. [28] L. Westbrook, A. C. Johnson, K. R. Regner et al., “Genetic [11] Y. Guo and Y. Liao, “miR-200bc/429 cluster alleviates infam- susceptibility and loss of Nr4a1 enhances macrophage-mediated mation in IgA nephropathy by targeting TWEAK/Fn14,” Inter- renal injury in CKD,” Journal of the American Society of national Immunopharmacology,vol.52,pp.150–155,2017. Nephrology, vol. 25, no. 11, pp. 2499–2510, 2014. [12] L. Zhang, C. Han, F. Ye et al., “Plasma gelsolin induced [29] G. Xin, R. Chen, and X. Zhang, “Identifcation of key microR- glomerular fbrosis via the TGF-�1/smads signal transduction NAs, transcription factors and genes associated with congenital pathway in IgA nephropathy,” International Journal of Molecular obstructive nephropathy in a mouse model of megabladder,” Sciences,vol.18,no.2,p.390,2017. Gene,vol.650,pp.77–85,2018. [13] H. Bao, S. Hu, C. Zhang et al., “Inhibition of miRNA-21 prevents fbrogenic activation in podocytes and tubular cells International Journal of Journal of Peptides Nucleic Acids

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