Integrated analysis of immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network in Henoch-Schönlein purpura nephritis of children

Integrated analysis of immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network in Henoch-Schönlein purpura nephritis of children | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Integrated analysis of immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network in Henoch-Schönlein purpura nephritis of children Lingfei Huang, Yanhong Li, Yi Xie, Fei Liu, Jianhua Mao, Jing Miao This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1834065/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Long noncoding RNAs (lncRNAs) play important roles in the regulation of immunological and apoptotic function. Here, we aimed to explore critical immune- and apoptosis-related lncRNAs in the occurrence and development of Henoch-Schönlein purpura nephritis (HSPN) in children. Through differentially expressed analysis, we identified differentially expressed lncRNAs, immune- and apoptosis-related mRNAs in the peripheral blood samples of children with HSPN. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses validated the immunological and apoptotic roles of the differentially expressed immune-related and apoptosis-related mRNAs. Following, we analyzed the correlations of differentially expressed lncRNAs and immune- and apoptosis-related mRNAs by Spearman’s correlation analysis, and determined 100 critical immune- and apoptosis-related lncRNAs in HSPN of children. Based on competing endogenous RNAs (ceRNA) mechanism, we constructed the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network in HSPN of children, and validated the expression levels of lncRNAs in the lncRNA-miRNA-mRNA regulatory network. Collectively, we proposed that the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network might participate in the modulation of pathogenesis of HSPN in children. In addition, the lncRNAs in the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network (upregulated SNHG3, LINC00152, TUG1, GAS5, FGD5-AS1, DLEU2, and SCARNA9; downregulated SNHG1, NEAT1, DISC1-IT1, and PVT1) could become novel biomarkers for the diagnosis of HNSP in children. lncRNA immune apoptosis HSPN children Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Introduction Henoch-Schönlein purpura (HSP) is the most common IgA-mediated systemic small vessel vasculitis of childhood, characterized by palpable purpuric rash, arthritis, abdominal pain, renal involvement, etc. [1, 2]. The prognosis of HSP is mostly dependent upon the severity of renal involvement, and chronic kidney disease is in up to 20% of children with HSP nephritis (HSPN). Immunosuppressants and multiple-agents therapy are benefit to ameliorate proteinuria and histological severity [3-5]. So far, the mechanism of HSPN has not been elucidated. However, it is worth mentioning that the immune system dysfunction is common seen and the serum levels of IgA1-containing immune complexes is drastically elevated in HSPN patients [6, 7]. Particularly, previous studies demonstrated all HSP patients contain IgA1-containing circulating immune complexes of small molecular mass, whereas IgA1-IgG-containing circulating immune complexes of large-molecular mass distinctly exist in HSPN patients [6]. Furthermore, existing studies have confirmed that apoptosis is involved in regulating the occurrence and development of nephritis [8]. Therefore, it is of great significance to explore the underlying immune- and apoptosis-related regulators and molecular mechanisms of HSPN in children. Long non-coding RNAs (lncRNAs) are non-coding RNAs with a length of >200 nucleotides [9-10]. Recently, next generation sequencing (NGS) has found a great deal of lncRNA transcripts and revealed their essential roles in cell differentiation, cell lineage selection, organogenesis, and tissue homeostasis effect [11-13]. The functions of lncRNA are complex and diverse. Mechanistically, lncRNA can act as scaffolds, guides, decoys, or enhancers to regulate gene expression and thereby exert their functions [14, 15]. Increasing studies have confirmed that lncRNAs are involved in regulating the occurrence and development of multiple diseases including various cancers, kidney disease, and cardiovascular disease, providing novel biomarkers and drug targets for diagnosis and therapy of disease [16-18]. Recently, the important roles of lncRNA in kidney diseases, including acute renal rejection, diabetic nephropathy, membranous nephropathy, chronic kidney disease and lupus nephritis, has gradually been paid attention. For examples, circulating LNC-EPHA6 was confirmed as a promising marker for vascular injury under acute rejection after kidney transplantation [19]. Another study reported that lncRNA NEAT1 served as a sponge for miR-146b to regulate TRAF6 expression and NF-κB signaling, thus accelerating renal mesangial cell injury in lupus nephritis [20]. However, lncRNAs involved in the occurrence and development of HSPN and corresponding molecular mechanism are still unclear. Exploring the expression pattern and function of lncRNA in HSPN of children is of great significance to design and develop novel strategies for the diagnosis, prognosis and clinical management of children with HSPN. In this study, the lncRNA and mRNA expression profiles of high-throughput sequencing dataset GSE102114 was downloaded to screen out differentially expressed lncRNA, immune-related genes and apoptosis-related genes in the peripheral blood of children with HSPN. Through gene ontology (GO) and The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, protein-protein network (PPI) construction, critical immune- and apoptosis-related genes in HSPN of children were explored. Then, we identified immune- and apoptosis-related lncRNAs that might be involved in the regulation of critical immune- and apoptosis-related genes in HSPN of children through Spearman correlation analysis. According to competing endogenous RNAs (ceRNAs) theory, lncRNAs can serve as sponges for miRNAs to release the interaction of miRNAs and their targe genes, thereby regulating the expression of target genes [21]. Following, we established a lncRNA-miRNA-mRNA regulatory network in HSPN of children based on the ceRNAs mechanism, which would help to understand the mechanism of the occurrence and development of HSPN in children. Materials And Methods Data collection and processing The gene expression profiles of dataset GSE102114 were downloaded from the NCBI Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/), which include the lncRNA and mRNA expression profiles of peripheral blood of 6 children with HSPN and 4 healthy children [22]. A list of 1811 immune-related genes were downloaded from ImmPort (https://www.immport.org/), of which 962 immune-related genes were found in mRNA expression profile of GSE102114 [23]. Besides, a total of 306 apoptosis-related genes were identified through merging several classical apoptosis-related gene sets downloaded from the molecular signature database (MSigDB, https://www.gsea-msigdb.org/gsea/msigdb/index.jsp ), including KEGG_APOPTOSIS, WP_APOPTOSIS_MODULATION_AND_SIGNALING, WP_APOPTOSIS, REACTOME_SUPPRESSION_OF_APOPTOSIS, REACTOME_ REGULATION_OF_APOPTOSIS, REACTOME_INTRINSIC_PATHWAY_FOR_ APOPTOSIS, REACTOME_APOPTOSIS_INDUCED_DNA_ FRAGMENTATION, and REACTOME_APOPTOSIS [24, 25]. Following the expression profile of 279 apoptosis-related genes were extracted from the mRNA expression profile of GSE102114. The lists of immune-related genes and apoptosis-related genes are provided in Table S1. Differential expression analysis Using “limma” R package, differential expression analysis was conducted to screen out differentially expressed lncRNAs and mRNAs, setting absolute log2fold change (log2FC) > 1 and adjusted P value (adj.P.Val) ＜0.05 as the significant threshold. Amongst, differentially expressed immune-related genes and apoptosis-related genes were identified from differentially expressed genes. R packages of “pheatmap” and “ggplot2” were used to display differentially expressed lncRNAs, mRNAs, immune-related genes and apoptosis-related genes. GO and KEGG enrichment analysis GO annotation consists of Biological Process (BP), Cellular Componet (CC), Molecular Function (MF) of genes in different databases using standard expression terms. KEGG (Kyoto Encyclopedia of Genes and Genomes, http://www.kegg.jp/) is a bioinformatics resource of genomes and genes by assigning functional and pathway meanings to genomes and genes, which uncover cellular and organism-level functions from genome sequences and other molecular datasets [26-28]. Here, GO and KEGG enrichment analysis were performed using “clusterProfiler” R package for differentially expressed immune-related genes and apoptosis-related genes, with the adjusted P value <0.05 as threshold. Following, “ggplot2” and “GOplot” R packages were utilized to show the results of top 10 terms of BP, CC, MF of GO and KEGG. Protein-protein interaction (PPI) network construction Through drawing Venn plot using “ggplot2” R package, we overlapped differentially expressed immune-related genes and apoptosis-related genes to identify critical immune- and apoptosis-related genes in HSPN of children. To explore the interactions among the critical immune- and apoptosis-related genes, we uploaded these genes to STRING ( https://string-db.org) , a database of functional protein association networks, to obtain their interaction information [29, 30]. Following, the PPI network was visualized and analyzed by Cytoscape 3.8.2. In addition, top 2 clusters of the Molecular Complex Detection (MCODE) plugins in Cytoscape were constructed in the complex protein networks. Correlation analysis To identify important immune- and apoptosis-related lncRNAs in HSPN of children, Spearman correlation analysis were conducted to analyze the correlations between differentially expressed lncRNAs and critical immune- and apoptosis-related genes. Absolute value of correlation coefficient |r| >0.9 and P value <0.001 was set as the threshold to filter lncRNAs correlated with immune- and apoptosis-related genes. LncRNA-miRNA and miRNA-mRNA prediction, lncRNA-miRNA-mRNA regulatory network construction MiRcode (http://mircode.org/) is a database predicting microRNA targets based on the comprehensive GENCODE gene annotation consisting of more than 10,000 lncRNAs. The potential lncRNA-miRNA pairs were predicted by miRcode. In addition, we retrieved mRNA-miRNA pairs file from TargetScanHuman 8.0 (https://www.targetscan.org/vert_80/docs/help.html/), released at September 2021 [31]. Based on ceRNA mechanism, lncRNAs and mRNAs that were predicted to bind to the same miRNAs and exhibited positive correlations were considered as ceRNAs. Consequently, the immune- and apoptosis-related lncRNA-miRNA-mRNA for HSPN of children was constructed, which was visualized by Cytoscape 3.8.2. qRT-PCR validation The peripheral blood samples of 11 HSP/HSPN children and 3 age-matched healthy children were enrolled from the Children's Hospital, Zhejiang University School of Medicine (Hangzhou, China) between August 2021 and November 2021. HSP was diagnosed according to the criteria outlined at the Society of Pediatrics, Chinese Medical Association in 2013 [32]. HSPN was diagnosed with the presence of either hematuria and/or proteinuria during the first 6 months of HSP [33]. None of the patients had complications or had taken any immunosuppressants before this study. The clinical characteristics of the children were presented in Table S2. The research was approved by the Ethics Committee of the study hospital. Total RNA of these samples was extracted using RNA Extraction Kit (Omega, Guangzhou, China). Reverse transcription was conducted using PrimeScript RT Master Mix Kit (Takara, Dalian, China). The lncRNA level was assessed using TB Green Premix Ex Taq Kit (Takara, Dalian, China) following manufacturer’ instructions. Primers used in our study are available in Table S3. The relative expression of lncRNAs was calculated by 2 −ΔΔCt method, with GAPDH as the reference. Two-sided unpaired Student’s t-test was applied to compare the difference of lncRNA expression levels between the peripheral blood samples of 11 HSP/HSPN children and 3 age-matched healthy children. The corresponding results were visualized by R package of “ggplot2”. Results Identification of differentially expressed lncRNAs and mRNAs in HSPN of children The differentially expressed lncRNAs and mRNAs were identified in the peripheral blood of 6 children with HSPN and 4 healthy children from GSE102114. We found 396 differentially expressed lncRNAs, among which 184 upregulated and 212 downregulated (|log2FC|>1 and adj.P.Value <0.05, Table S4). Figure 1A and Figure1B displayed the significant expression patterns and distribution of differentially expressed lncRNAs between healthy control and HSPN groups, respectively. Besides, a total of 5417 differentially expressed genes, of which 2737 upregulated and 2680 downregulated (|log2FC|>1 and adj.P.Value <0.05, Table S5). Likewise, Figure 1C and Figure1D displayed the significant expression patterns and distribution of differentially expressed mRNAs between healthy control and HSPN groups, respectively. Abnormally expressed immune-related mRNAs in children HSPN HSPN is characteristic with immune system disorder. Thus, we filtered out differentially expressed immune-related genes from 5417 differentially expressed genes, identifying 314 differentially expressed immune-related genes (185 upregulated and 129 downregulated). Figure 2A and Figure 2B showed the significant expression patterns and distribution of differentially expressed immune-related genes between healthy control and HSPN groups, respectively. The results of GO analysis demonstrated these 314 genes significantly enriched in regulation of innate immune response, T cell activation, positive regulation of cytokine production in BP; external side of plasma membrane, membrane raft, membrane microdomain in CC; receptor ligand activity, cytokine binding, cytokine receptor activity in MF (Figure2C). Meaningfully, these terms were closely associated with immune functions. Similarly, the results of KEGG revealed these 314 genes were significantly enriched in multiple immune-related pathways, including T cell receptor signaling pathway, Natural killer cell mediated cytotoxicity, B cell receptor signaling pathway, etc (Figure2D). Abnormally expressed apoptosis-related mRNAs in children HSPN Following, we aimed to explore important apoptosis-related genes in HSPN of children and observed 124 differentially expressed apoptosis-related genes (71 upregulated and 53 downregulated). Figure 3A and Figure 3B displayed the significant expression patterns and distribution of differentially expressed apoptosis-related genes between healthy control and HSPN groups, respectively.Moreover, the results of GO analysis demonstrated these 124 genes significantly enriched inactivation of innate immune response, response to tumor necrosis factor, and interleukin-1-mediated signaling pathway in BP; proteasome complex, endopeptidase complex, and peptidase complex in CC; endopeptidase activity, ubiquitin protein ligase binding in MF (Figure3C). Interestingly, these terms were also correlated with immune functions. Besides, the results of KEGG revealed these 124 genes were significantly enriched in apoptosis, proteasome, spinocerebellar ataxia, lipid and atherosclerosis, etc (Figure3D). Identification of important immune- and apoptosis-related mRNAs and lncRNAs in children HSPN Through intersecting differentially expressed immune-related and apoptosis-related genes, we identified 43 genes which might simultaneously participate in regulation of immune function and cell apoptosis of children with HSPN (Figure4A). The interactions of these immune- and apoptosis-related genes and constructed the PPI network of these genes are displayed in Figure4B. Especially, the top two highly interconnected subclusters were analyzed by MCODE algorithm of Cytoscape 3.8.2, scoring 9.75 and 9.0 respectively (Figure4B, C). Following, we defined 100 lncRNAs that were significantly correlated with above 43 genes as immune- and apoptosis-related lncRNAs in HSPN of children (|Spearman R| > 0.9 and p < 0.001). The specific correlations of immune- and apoptosis-related lncRNAs and mRNAs in HSPN of children were displayed in Table S6. Construction of the immune- and apoptosis-related lncRNA–miRNA–mRNA ceRNA network for children HSPN According to ceRNA mechanism, immune- and apoptosis-related lncRNAs and mRNAs that exist positive correlations were considered as ceRNAs to construct the ceRNA regulatory network. We identified the miRNAs which might bridge the immune- and apoptosis-related lncRNAs and mRNAs by matching lncRNA-miRNA pairs and miRNA–mRNA pairs (Figure5A, B). Correspondingly, the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network for children with HSPN were established (Figure5C). The specific regulatory relationship in the ceRNA network are displayed in Figure6 and Table S7. Validation of the expression levels of the lncRNAs in HSPN To further confirm the expression levels of lncRNAs in the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network, qRT-PCR assay was conducted in our clinical samples. Consistent with the results of GSE102114, the expression levels of SNHG3, LINC00152, TUG1, GAS5, FGD5-AS1, DLEU2, and SCARNA9 were significantly upregulated, whereas NEAT, PVT1, SNHG1, and DISC1-IT1 were dramatically downregulated in the blood samples of than in normal blood samples (Figure 7A, B). Collectively, the upregulation of SNHG3, LINC00152, TUG1, GAS5, FGD5-AS1, DLEU2, and SCARNA9 might be potential biomarkers for HSPN. Similarly, the downregulation of NEAT, PVT1, SNHG1, and DISC1-IT1 have potential to be indicators for HSPN. Discussion HSPN is accounting for ~ 80% of children with secondary glomerulopathy, and renal involvement is the most important prognostic factor in determining morbidity and mortality of HSP. In terms of etiology, persistent purpura or recurrence, severe abdominal symptoms, arthritis and age > 10 years are the most important risk factors for HSPN in children [ 2 ]. Extensive clinical and experimental data have corroborated the disorders of cellular and humoral immune responses are closely related with the pathogenesis of HSPN in children [ 6 , 34 ]. However, key genes responsible for the dysregulation of humoral and cellular immunity during the progression of HSPN in children remain unknown. In the present study, we identified 314 differentially expressed immune-related mRNAs in the peripheral blood of children with HSPN. GO enrichment analysis revealed these mRNAs were involved in multiple immune-related biological processes, including regulation of innate immune response, T cell activation, positive regulation of cytokine production, and regulation of lymphocyte activation. The results of KEGG enrichment analysis also suggested these immune-related mRNAs might participate in the activation of T cell receptor signaling pathway, Natural killer cell cytotoxicity, B cell receptor signaling pathway, etc. These results indicated that activation of T cells and B cells, as well as elevated cytokine and chemokine production are closely associated with the dysregulation of immune-related mRNAs in HSPN of children. Su QY et. al, have observed a relative increase of T lymphocytes in children with HSPN, which leads to the activation of B cells, increased secretion of inflammatory mediators, and further increases the secretion of immunoglobulins, causing the occurrence of small vasculitis [ 6 ]. Thus, we speculated the dysregulation of these differentially expressed immune-related mRNAs might contribute to the immune dysfunction of children with HSPN. Apoptosis is another critical factor for HSPN of children [ 8 ]. Here, we identified 124 differentially expressed apoptosis-related mRNAs in the peripheral blood of children with HSPN. Interestingly, GO enrichment analysis revealed these apoptosis-related mRNAs also participate in the regulation of immune-related processes, including innate immune response, interleukin-1-mediated signaling pathway, and cellular response to interleukin-1. Besides, the results of KEGG enrichment analysis demonstrated these apoptosis-related mRNAs significantly enriched in apoptosis, proteasome, lipid and atherosclerosis, TNF signaling pathway, and Toll-like receptor signaling pathway, etc. Previous studies have confirmed the deposition of IgA-containing immune complexes are responsible for the renal damage of HSPN patients. During the progression of HSPN, IgA deposition may induce apoptosis of human umbilical vein endothelial cells, thereby causing HSP vascular endothelial damage [ 35 ]. On the other hand, apoptosis may promote the removal of inflammatory cells, contributing to the control of early inflammatory response and repair self-limiting vasculitis [ 36 ]. Hence, there exist complex regulatory links between immune and apoptosis-associated signaling pathways in HSPN of children. Overlapping differentially expressed immune- and apoptosis-related mRNAs in the peripheral blood of children with HSPN, we identified 43 immune- and apoptosis-related mRNAs as critical genes, which might play essential regulatory roles in the pathogenesis of HSPN of children. Recently, accumulating studies have demonstrated that lncRNAs play important roles in regulation immune and apoptosis-related pathways [ 37 – 40 ]. However, the critical lncRNAs responsible for the dysregulations of immune and apoptosis of HSPN in children are largely unknown. In our present study, we identified 396 differentially expressed lncRNAs in the peripheral blood of children with HSPN. Through correlation analysis, a total of 100 lncRNAs correlated with above 43 immune- and apoptosis-related genes were identified as immune- and apoptosis-related lncRNAs in HSPN of children. To further explore the underlying regulatory mechanisms of immune- and apoptosis-related lncRNAs and mRNAs in HSPN of children, we constructed the immune- and apoptosis-related lncRNAs-miRNA-mRNAs regulatory network based on ceRNAs mechanism. In the lncRNAs-miRNA-mRNAs regulatory network, elevated expression of SNHG3, LINC00152, TUG1, GAS5, FGD5-AS1, DLEU2, and SCARNA9 might promote the expression of TLR4, IL1RAP, CDH1, PSMC2, PSMD1, PSMD6, PSMD10, PSMD14, PIK3CA, PIK3CB, CASP3, PPP3R1, TRIM27, HMGB1, MAPK1, and MAPK8; while decreased expression of SNHG1, NEAT1, DISC1-IT1, and PVT1 might induce the downregulation of AKT2, TNFRSF10B, PIK3R5, and PIK3CD. Furthermore, we validated the upregulation of SNHG3, LINC00152, TUG1, GAS5, FGD5-AS1, DLEU2, and SCARNA9, downregulation of SNHG1, NEAT1, DISC1-IT1, and PVT1 in the peripheral blood of children with HSPN collected from the Children's Hospital, Zhejiang University School of Medicine. These results suggested the dysregulation of these lncRNAs might be biomarkers for the diagnosis of HSPN in children. So far, existing studies mainly focused on the roles of these lncRNAs in the regulation of occurrence and development of various cancers [ 41 – 42 ]. For example, ample evidence suggests SNHG3 acts as an oncogenic lncRNA to facilitate cell proliferation, migration and invasion, and suppress cell apoptosis in glioma, renal cell carcinoma, lung cancer, and prostate cancer [ 43 ]. Interestingly, SNHG3, TUG1, GAS5, and SCARNA9 were identified as immune-related lncRNAs in different cancers [ 44 – 47 ]. Besides, the anti-apoptotic effect of SNHG3, LINC00152, TUG1, and FGD5-AS1has been validated in different cancer cell models [ 43 , 48 – 50 ]. Nevertheless, their immunological and apoptotic roles in the progression of HSPN in children have not been explored to date. Based on the results of our present study, we proposed that the dysregulation of these lncRNAs (upregulation of SNHG3, LINC00152, TUG1, GAS5, FGD5-AS1, DLEU2, and SCARNA9; downregulation of SNHG1, NEAT1, DISC1-IT1, and PVT1) might be responsible for the immune imbalance of children with HSPN through modulation of immune- and apoptosis-related genes, which lead to the deposition of IgA-containing immune complexes, and thereby inducing the occurrence and development of HSPN in children. Of course, further experimental studies are necessary to validate these speculations. There were several limitations in this study. Firstly, the sample size for our analysis and validation were relatively small. The present results should be further validated in larger cohorts. Secondly, miRNAs in the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network were determined by miRNA-target prediction. Further experimental validations are necessary in future. In conclusion, the present study constructed an immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network of HSPN in children, which provided a basis and direction for future molecular mechanisms of the pathogenesis of HSPN in children. These lncRNAs and mRNAs in the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network have potential to be novel diagnostic and therapeutic biomarkers for HSPN of children. Declarations Data Availability Statement The dataset used in this study can be found in GSE102114 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE102114). Ethics Statement Ethical review and approval was not required for the study. Written informed consent for participation was not required for this study. Author Contributions Lingfei Huang and Yanhong Li performed data collection, conducted data analysis and Writed original draft. Yi Xie and Fei Liu performed data collection. Jianhua Mao and Jing Miao supervised the project and conceptualized the research. All authors contributed to the article and approved the submitted version. Conflict of Interest The authors declare that there are no potential conflicts of interest. Acknowledgments Project support was provided by Natural Science Foundation of Zhejiang Province (grant No. LQY20H300002), Hospital Pharmacy Research Funding Project of Zhejiang Pharmaceutical Association (grant No. 2014ZYY05). References McCarthy HJ, Tizard EJ. Clinical practice: Diagnosis and management of Henoch-Schönlein purpura. Eur J Pediatr. 2010 Jun;169(6):643–50. doi: 10.1007/s00431-009-1101-2 . Yang YH, Yu HH, Chiang BL. The diagnosis and classification of Henoch-Schönlein purpura: an updated review. Autoimmun Rev. 2014 Apr-May;13(4–5):355–8. doi: 10.1016/j.autrev.2014.01.031 . Leung AKC, Barankin B, Leong KF. Henoch-Schönlein Purpura in Children: An Updated Review. Curr Pediatr Rev. 2020;16(4):265–276. doi: 10.2174/ 157339631666620050810 4708. Lau KK, Suzuki H, Novak J, Wyatt RJ. Pathogenesis of Henoch-Schönlein purpura nephritis. Pediatr Nephrol. 2010 Jan;25(1):19–26. doi: 10.1007/s00467-009-1230-x . Chen JY, Mao JH. Henoch-Schönlein purpura nephritis in children: incidence, pathogenesis and management. World J Pediatr. 2015 Feb;11(1):29–34. doi: 10.1007/s12519-014-0534-5 . Su Q, Jiang L, Chai J, Dou Z, Rong Z, Zhao X, Yu B, Wang Y, Wang X. Changes of Peripheral Blood Lymphocyte Subsets and Immune Function in Children with Henoch-Schonlein Purpura Nephritis. Iran J Immunol. 2021 Sep;18(3):259–267. doi: 10.22034/iji.2021.89742.1964 . Duan X, Yu D, Yu C, Wang B, Guo Y. Henoch-Schönlein purpura following high-voltage electric burn injury: A case report and review of the literature. Exp Ther Med. 2016 Feb;11(2):540–542. doi: 10.3892/etm.2015.2905 . Yuan P, Bo Y, Ming G, Wen-Jun F, Qin Z, Bo H. Apoptosis of human umbilical vein endothelial cells (HUVEC) induced by IgA1 isolated from Henoch-Schonlein purpura children. Asian Pac J Allergy Immunol. 2014 Mar;32(1):34–8. doi: 10.12932/AP0357.32.1.2014 . Jarroux J, Morillon A, Pinskaya M. History, Discovery, and Classification of lncRNAs. Adv Exp Med Biol. 2017;1008:1–46. doi: 10.1007/978-981-10-5203-3_1 . St Laurent G, Wahlestedt C, Kapranov P. The Landscape of long noncoding RNA classification. Trends Genet. 2015 May;31(5):239–51. doi: 10.1016/j.tig.2015.03.007 . Kazimierczyk M, Kasprowicz MK, Kasprzyk ME, Wrzesinski J. Human Long Noncoding RNA Interactome: Detection, Characterization and Function. Int J Mol Sci. 2020 Feb 4;21(3):1027. doi: 10.3390/ijms21031027 . Melissari MT, Grote P. Roles for long non-coding RNAs in physiology and disease. Pflugers Arch. 2016 Jun;468(6):945–58. doi: 10.1007/s00424-016-1804-y . Yip CW, Sivaraman DM, Prabhu AV, Shin JW. Functional annotation of lncRNA in high-throughput screening. Essays Biochem. 2021 Oct 27;65(4):761–773. doi: 10.1042/EBC20200061 . Chen LL. Linking Long Noncoding RNA Localization and Function. Trends Biochem Sci. 2016 Sep;41(9):761–772. doi: 10.1016/j.tibs.2016.07.003 . Qian X, Zhao J, Yeung PY, Zhang QC, Kwok CK. Revealing lncRNA Structures and Interactions by Sequencing-Based Approaches. Trends Biochem Sci. 2019 Jan;44(1):33–52. doi: 10.1016/j.tibs.2018.09.012 . Bhan A, Soleimani M, Mandal SS. Long Noncoding RNA and Cancer: A New Paradigm. Cancer Res. 2017 Aug 1;77(15):3965–3981. doi: 10.1158/0008-5472.CAN-16-2634 . Epub 2017 Jul 12. Ignarski M, Islam R, Müller RU. Long Non-Coding RNAs in Kidney Disease. Int J Mol Sci. 2019 Jul 3;20(13):3276. doi: 10.3390/ijms20133276 . Sallam T, Sandhu J, Tontonoz P. Long Noncoding RNA Discovery in Cardiovascular Disease: Decoding Form to Function. Circ Res. 2018 Jan 5;122(1):155–166. doi: 10.1161/CIRCRESAHA.117.311802 . Groeneweg KE, Duijs JMGJ, Florijn BW, van Kooten C, de Fijter JW, van Zonneveld AJ, Reinders MEJ, Bijkerk R. Circulating Long Noncoding RNA LNC-EPHA6 Associates with Acute Rejection after Kidney Transplantation. Int J Mol Sci. 2020 Aug 5;21(16):5616. doi: 10.3390/ijms21165616 . Zhang LH, Xiao B, Zhong M, Li Q, Chen JY, Huang JR, Rao H. LncRNA NEAT1 accelerates renal mesangial cell injury via modulating the miR-146b/TRAF6/NF-κB axis in lupus nephritis. Cell Tissue Res. 2020 Dec;382(3):627–638. doi: 10.1007/s00441-020-03248-z . Wang Y, Hou J, He D, Sun M, Zhang P, Yu Y, Chen Y. The Emerging Function and Mechanism of ceRNAs in Cancer. Trends Genet. 2016 Apr;32(4):211–224. doi: 10.1016/j.tig.2016.02.001 . Pang S, Lv J, Wang S, Yang G, Ding X, Zhang J. Differential expression of long non-coding RNA and mRNA in children with Henoch-Schönlein purpura nephritis. Exp Ther Med. 2019 Jan;17(1):621–632. doi: 10.3892/etm.2018.7038 . Bhattacharya S, Dunn P, Thomas CG, Smith B, Schaefer H, Chen J, Hu Z, Zalocusky KA, Shankar RD, Shen-Orr SS, Thomson E, Wiser J, Butte AJ. ImmPort, toward repurposing of open access immunological assay data for translational and clinical research. Sci Data. 2018 Feb 27;5:180015. doi: 10.1038/sdata.2018.15 . Liberzon A, Birger C, Thorvaldsdóttir H, Ghandi M, Mesirov JP, Tamayo P. The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst. 2015 Dec 23;1(6):417–425. doi: 10.1016/j.cels.2015.12.004 . Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005 Oct 25;102(43):15545–50. doi: 10.1073/pnas.0506580102 . Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000 Jan 1;28(1):27–30. doi: 10.1093/nar/28.1.27 . Kanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019 Nov;28(11):1947–1951. doi: 10.1002/pro.3715 . Kanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021 Jan 8;49(D1):D545-D551. doi: 10.1093/nar/gkaa970 . Szklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, Simonovic M, Doncheva NT, Morris JH, Bork P, Jensen LJ, Mering CV. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019 Jan 8;47(D1):D607-D613. doi: 10.1093/nar/gky1131 . Szklarczyk D, Gable AL, Nastou KC, Lyon D, Kirsch R, Pyysalo S, Doncheva NT, Legeay M, Fang T, Bork P, Jensen LJ, von Mering C. The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 2021 Jan 8;49(D1):D605-D612. doi: 10.1093/nar/gkaa1074 . McGeary SE, Lin KS, Shi CY, Pham TM, Bisaria N, Kelley GM, Bartel DP. The biochemical basis of microRNA targeting efficacy. Science. 2019 Dec 20;366(6472):eaav1741. doi: 10.1126/science.aav1741 . Subspecialty Group of Renal Diseases, the Society of Pediatrics, Chinese Medical Association. [Evidence-based guideline for diagnosis and treatment of Henoch-Schonlein purpura nephritis (2016)]. Zhonghua Er Ke Za Zhi. 2017 Sep 2;55(9):647–651. Chinese. doi: 10.3760/cma.j.issn.0578-1310.2017.09.003 . Davin JC, Coppo R. Henoch-Schönlein purpura nephritis in children. Nat Rev Nephrol. 2014 Oct;10(10):563–73. doi: 10.1038/nrneph.2014.126 . Wang Q, Shi YY, Cao M, Dong W, Zhang JB. Role of Imbalance between Th17 Cells and Treg Cells in the Pathogenesis of Children with Henoch-Schonlein Purpura. Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2015 Oct;23(5):1391-6. Chinese. doi: 10.7534/j.issn.1009-2137.2015.05.032 . Del Vecchio GC, Penza R, Altomare M, Piacente L, Aceto G, Lassandro G, De Mattia D, Giordano P. Cytokine pattern and endothelium damage markers in Henoch-Schönlein purpura. Immunopharmacol Immunotoxicol. 2008;30(3):623–9. doi: 10.1080/08923970801973646 . Wang J, Zheng Y, Chen G, Lv Y, Lian F, Jiang D, Ke W, Liu L, Fan C, Gong S. The changes in pyroptosis-related inflammatory factors in the peripheral blood of patients with Henoch-Schonlein purpura. Ann Palliat Med. 2021 Jun;10(6):6687–6693. doi: 10.21037/apm-21-1227 . Chen YG, Satpathy AT, Chang HY. Gene regulation in the immune system by long noncoding RNAs. Nat Immunol. 2017 Aug 22;18(9):962–972. doi: 10.1038/ni.3771 . Denaro N, Merlano MC, Lo Nigro C. Long noncoding RNAs as regulators of cancer immunity. Mol Oncol. 2019 Jan;13(1):61–73. doi: 10.1002/1878-0261.12413 . Zhang Y, Mao Q, Xia Q, Cheng J, Huang Z, Li Y, Chen P, Yang J, Fan X, Liang Y, Lin H. Noncoding RNAs link metabolic reprogramming to immune microenvironment in cancers. J Hematol Oncol. 2021 Oct 15;14(1):169. doi: 10.1186/s13045-021-01179-y . Gutschner T, Diederichs S. The hallmarks of cancer: a long non-coding RNA point of view. RNA Biol. 2012 Jun;9(6):703–19. doi: 10.4161/rna.20481 . Epub 2012 Jun 1. Zheng S, Jiang F, Ge D, Tang J, Chen H, Yang J, Yao Y, Yan J, Qiu J, Yin Z, Ni Y, Zhao L, Chen X, Li H, Yang L. LncRNA SNHG3/miRNA-151a-3p/RAB22A axis regulates invasion and migration of osteosarcoma. Biomed Pharmacother. 2019 Apr;112:108695. doi: 10.1016/j.biopha.2019.108695 . Yuan ZJ, Yu C, Hu XF, He Y, Chen P, Ouyang SX. LINC00152 promotes pancreatic cancer cell proliferation, migration and invasion via targeting miR-150. Am J Transl Res. 2020 May 15;12(5):2241–2256. Xu B, Mei J, Ji W, Bian Z, Jiao J, Sun J, Shao J. LncRNA SNHG3, a potential oncogene in human cancers. Cancer Cell Int. 2020 Nov 4;20(1):536. doi: 10.1186/s12935-020-01608-x . Zhan T, Gao X, Wang G, Li F, Shen J, Lu C, Xu L, Li Y, Zhang J. Construction of Novel lncRNA-miRNA-mRNA Network Associated With Recurrence and Identification of Immune-Related Potential Regulatory Axis in Hepatocellular Carcinoma. Front Oncol. 2021 Jul 15;11:626663. doi: 10.3389/fonc.2021.626663 . Wang W, Zhao Z, Yang F, Wang H, Wu F, Liang T, Yan X, Li J, Lan Q, Wang J, Zhao J. An immune-related lncRNA signature for patients with anaplastic gliomas. J Neurooncol. 2018 Jan;136(2):263–271. doi: 10.1007/s11060-017-2667-6 . Chen Q, Hu L, Huang D, Chen K, Qiu X, Qiu B. Six-lncRNA Immune Prognostic Signature for Cervical Cancer. Front Genet. 2020 Oct 14;11:533628. doi: 10.3389/fgene.2020.533628 . Wang Z, Liu Y, Zhang J, Zhao R, Zhou X, Wang H. An Immune-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer. J Oncol. 2021 Dec 10;2021:9972454. doi: 10.1155/2021/9972454 . Zhang L, Wang Y, Su H. Long non-coding RNA LINC00152/miR-613/CD164 axis regulates cell proliferation, apoptosis, migration and invasion in glioma via PI3K/AKT pathway. Neoplasma. 2020 Jul;67(4):762–772. doi: 10.4149/neo_2020_190706N598 . Li T, Chen Y, Zhang J, Liu S. LncRNA TUG1 promotes cells proliferation and inhibits cells apoptosis through regulating AURKA in epithelial ovarian cancer cells. Medicine (Baltimore). 2018 Sep;97(36):e12131. doi: 10.1097/MD.0000000000012131 . Hao L, Wang J, Bi SJ, Cheng C. Upregulation of Long Noncoding RNA FGD5-AS1 Ameliorates Myocardial Ischemia/Reperfusion Injury via MicroRNA-106a-5p and MicroRNA-106b-5p. J Cardiovasc Pharmacol. 2021 Jul 1;78(1):e45-e54. doi: 10.1097/FJC.0000000000001036 . Additional Declarations No competing interests reported. Supplementary Files TableS1.xlsx TableS2.xlsx TableS3.docx TableS4.xlsx TableS5.xlsx TableS6.xlsx TableS7.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-1834065","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":120899688,"identity":"0b44598f-526d-47b2-9d97-b5504c9ed669","order_by":0,"name":"Lingfei Huang","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lingfei","middleName":"","lastName":"Huang","suffix":""},{"id":120899689,"identity":"43d4e137-74c0-4498-9dbc-b1e38d4a224b","order_by":1,"name":"Yanhong Li","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yanhong","middleName":"","lastName":"Li","suffix":""},{"id":120899690,"identity":"76cfad9d-a1e1-4f23-adb2-dcc872d1996f","order_by":2,"name":"Yi Xie","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Yi","middleName":"","lastName":"Xie","suffix":""},{"id":120899691,"identity":"2e40aed4-f338-4d0d-b881-07b3eb4e7464","order_by":3,"name":"Fei Liu","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Fei","middleName":"","lastName":"Liu","suffix":""},{"id":120899692,"identity":"a652d19d-b4df-4b34-8a44-f6f83331e631","order_by":4,"name":"Jianhua Mao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAo0lEQVRIiWNgGAWjYJCCAwkGNjz87A3E62A88KAiTUay5wDxWpgPPjhz2MbghgOR6g1u5D44kNh2nofhBgPjh485RGlJNwBquc3DOLuBWXLmNiK0mN1OYwBrYZY5wMbMS4KWczxsEgmkaEk4c4CHh2gt9vefAbVUJPNI8BxsJs4vkj3HmD/+MLCztz/efPDDR2K0IAHGBtLUj4JRMApGwSjADQBYzTpJCt6wQwAAAABJRU5ErkJggg==","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Jianhua","middleName":"","lastName":"Mao","suffix":""},{"id":120899693,"identity":"3b497e5d-6cfa-429e-884d-7c4c210f944c","order_by":5,"name":"Jing Miao","email":"","orcid":"","institution":"Zhejiang University School of Medicine","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jing","middleName":"","lastName":"Miao","suffix":""}],"badges":[],"createdAt":"2022-07-07 07:44:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1834065/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1834065/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":24164593,"identity":"870d9c3b-c55b-42c5-9bad-97302a7c8222","added_by":"auto","created_at":"2022-07-21 19:52:16","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":644698,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of differentially expressed lncRNAs and mRNAs in HSPN of children.\u003c/strong\u003e A, C. Heatmaps for the expression patterns of differentially expressed lncRNAs (A) and mRNAs (C) in the peripheral blood of children with HSPN and healthy control. Red indicates relative high expression; blue represents relative low expression. B, D. Volcano plots for the distribution of differentially expressed lncRNAs (B) and mRNAs (D) in the peripheral blood of children with HSPN and healthy control. Red dots indicate upregulated lncRNAs or mRNAs; blue dots represent downregulated lncRNAs or mRNAs.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/9b4ca03fae31b19cd7be5e6f.png"},{"id":24164595,"identity":"cb828762-47d8-47b3-8a67-2b966ad2a528","added_by":"auto","created_at":"2022-07-21 19:52:16","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1248962,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAbnormally expressed immune-related mRNAs in children HSPN. \u003c/strong\u003eA. Heatmap for the expression patterns of differentially expressed immune-related mRNAs in the peripheral blood of children with HSPN and healthy control. Red indicates relative high expression; blue represents relative low expression. B. Volcano plot for the distribution of differentially expressed immune-related mRNAs in the peripheral blood of children with HSPN and healthy control. Red dots indicate upregulated lncRNAs or mRNAs; blue dots represent downregulated lncRNAs or mRNAs. C. The top 10 terms of BP, CC, and MF of GO analysis enriched by differentially expressed immune-related mRNAs. D. The top 10 pathways of KEGG enriched by differentially expressed immune-related mRNAs. BP, biological processes; CC, cellular components; MF, molecular functions; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/2c75a2bb30c2d55fc2105c20.png"},{"id":24164596,"identity":"784e8678-d4ce-4b4d-957e-be65d7b14df2","added_by":"auto","created_at":"2022-07-21 19:52:16","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1269615,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAbnormally expressed apoptosis-related mRNAs in children HSPN. \u003c/strong\u003eA. Heatmap for the expression patterns of differentially expressed apoptosis-related mRNAs in the peripheral blood of children with HSPN and healthy control. Red indicates relative high expression; blue represents relative low expression. B. Volcano plot for the distribution of differentially expressed apoptosis-related mRNAs in the peripheral blood of children with HSPN and healthy control. Red dots indicate upregulated lncRNAs or mRNAs; blue dots represent downregulated lncRNAs or mRNAs. C. The top 10 terms of BP, CC, and MF of GO analysis enriched by differentially expressed apoptosis-related mRNAs. D. The top 10 pathways of KEGG enriched by differentially expressed apoptosis-related mRNAs. BP, biological processes; CC, cellular components; MF, molecular functions; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genomes.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/eabfe213a918becbc6481869.png"},{"id":24164891,"identity":"a84085db-bf05-423d-b324-26160eba21c7","added_by":"auto","created_at":"2022-07-21 20:02:16","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":1259318,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eIdentification of important immune- and apoptosis-related mRNAs and lncRNAs in children HSPN. \u003c/strong\u003eA. Venn plot of differentially expressed immune-related mRNAs and apoptosis-related mRNAs. B. PPI network of 43 immune- and apoptosis-related genes. C, D. The interconnected subclusters of PPI network, scoring 9.75 (C) and 9.0 (D), respectively. PPI, protein-protein interaction.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/7941d6a206d542b7bc23df73.png"},{"id":24164296,"identity":"90d027f8-e50d-460f-abac-fbef60ebc882","added_by":"auto","created_at":"2022-07-21 19:47:16","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":3262777,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eConstruction of the immune- and apoptosis-related lncRNA–miRNA–mRNA ceRNA network for HSPN of children. \u003c/strong\u003eA, Venn plot of miRNAs targeting immune- and apoptosis-related lncRNAs and miRNAs targeting immune- and apoptosis-related mRNAs. B. The Sankey diagram showing the associations of immune- and apoptosis-related lncRNA and miRNAs, and immune- and apoptosis-related mRNAs. C. The immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network for HSPN of children. Hexagon shows lncRNA (orange, upregulated; dark blue, downregulated). Diamond indicates miRNA. Rectangle represents mRNAs (red, upregulated; green, downregulated). Gray lines indicate interactions between the RNAs.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/2f981b1468c3b136214e0c5e.png"},{"id":24164288,"identity":"d32101a6-199c-4898-a331-29f947591e7b","added_by":"auto","created_at":"2022-07-21 19:47:16","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":2184680,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSubnetwork of immune- and apoptosis-related lncRNAs and their potential targeted miRNAs-mRNAs.\u003c/strong\u003e A. SNHG3; B. LINC00152; C. TUG1; D. GAS5; E. FGD5-AS1; F. DLEU2; G. SCARNA9; H. NEAT1; I. PVT1; J. SNHG1; K. DISC1-IT1. Hexagon shows lncRNA (orange, upregulated; dark blue, downregulated). Diamond indicates miRNA. Rectangle represents mRNAs (red, upregulated; green, downregulated). Gray lines indicate interactions between the RNAs.\u003c/p\u003e","description":"","filename":"Figure6.png","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/078700dc9deef028e8d2026d.png"},{"id":24164696,"identity":"2d806ad4-5cf0-462a-96a9-9eee351282e7","added_by":"auto","created_at":"2022-07-21 19:57:16","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":59659,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003e\u003cspan class=\"ql-cursor\"\u003e\u003c/span\u003eValidation of the expression levels of the lncRNAs in the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network of HSPN in children. \u003c/strong\u003eA. The relative expression levels of 7 upregulated lncRNAs between the peripheral blood of children with HSPN and healthy controls. B. The relative expression levels of 4 downregulated lncRNAs between the peripheral blood of children with HSPN and healthy controls. ***, \u003cem\u003eP\u003c/em\u003e \u0026lt;0.001; **, 0.001\u0026lt;\u003cem\u003eP\u003c/em\u003e\u0026lt;0.01.\u003c/p\u003e","description":"","filename":"Figure7.png","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/288c6ad7e1817ce0d95b9300.png"},{"id":24339456,"identity":"aa066213-99d9-4130-a623-5cb5615aeb4f","added_by":"auto","created_at":"2022-07-26 11:59:51","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":3696989,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/76a27519-e675-4b19-b663-40a906092430.pdf"},{"id":24164695,"identity":"818bad4f-06eb-4226-9ab1-b2664f607ba2","added_by":"auto","created_at":"2022-07-21 19:57:16","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":40538,"visible":true,"origin":"","legend":"","description":"","filename":"TableS1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/ea2b3a2c3cf839b72b29a5a4.xlsx"},{"id":24164283,"identity":"05aa4acc-e191-4545-ab64-fa60e791ad43","added_by":"auto","created_at":"2022-07-21 19:47:16","extension":"xlsx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":10230,"visible":true,"origin":"","legend":"","description":"","filename":"TableS2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/7b8115201a20eba2c4e642ba.xlsx"},{"id":24164293,"identity":"771c822b-4519-4373-83cf-a39f64523a58","added_by":"auto","created_at":"2022-07-21 19:47:16","extension":"docx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":12462,"visible":true,"origin":"","legend":"","description":"","filename":"TableS3.docx","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/e904c8cc1656ca7734e0cb08.docx"},{"id":24164598,"identity":"3448ad82-f00f-4140-91d9-0153f0b71f88","added_by":"auto","created_at":"2022-07-21 19:52:16","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":50942,"visible":true,"origin":"","legend":"","description":"","filename":"TableS4.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/6932ee0e4927973faba3bdb3.xlsx"},{"id":24164289,"identity":"9a6a7966-b644-4ff1-94cb-68c6286e80c6","added_by":"auto","created_at":"2022-07-21 19:47:16","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":489251,"visible":true,"origin":"","legend":"","description":"","filename":"TableS5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/fbcf8a53a4ad57fadca62e8e.xlsx"},{"id":24164601,"identity":"e649cdd0-5d2e-427a-af70-57870158c9ab","added_by":"auto","created_at":"2022-07-21 19:52:16","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":47012,"visible":true,"origin":"","legend":"","description":"","filename":"TableS6.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/9b193c879cf2707dba0cf983.xlsx"},{"id":24164600,"identity":"90d34544-e188-458b-9e75-60b062ec1345","added_by":"auto","created_at":"2022-07-21 19:52:16","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":13091,"visible":true,"origin":"","legend":"","description":"","filename":"TableS7.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-1834065/v1/15741d98d62bde4a657ee899.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrated analysis of immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network in Henoch-Schönlein purpura nephritis of children","fulltext":[{"header":"Introduction","content":"\u003cp\u003eHenoch-Sch\u0026ouml;nlein purpura (HSP) is the most common IgA-mediated systemic small vessel vasculitis\u0026nbsp;of childhood, characterized by palpable purpuric rash, arthritis, abdominal pain, renal involvement, etc. [1, 2]. The prognosis of HSP is mostly dependent upon the severity of renal involvement, and chronic kidney disease is in up to 20% of children with HSP nephritis (HSPN). Immunosuppressants and multiple-agents therapy are benefit to\u0026nbsp;ameliorate\u0026nbsp;proteinuria and histological severity [3-5].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSo far, the mechanism of HSPN has not been elucidated. However, it is worth mentioning that the immune system dysfunction is common seen and the serum levels of IgA1-containing immune complexes is drastically elevated in HSPN patients [6, 7]. Particularly, previous studies demonstrated all HSP patients contain IgA1-containing circulating immune complexes of small molecular mass, whereas IgA1-IgG-containing circulating immune complexes of large-molecular mass distinctly exist in HSPN patients [6]. Furthermore, existing studies have confirmed that apoptosis is involved in regulating the occurrence and development of nephritis [8]. Therefore, it is of great significance to explore the underlying immune- and apoptosis-related regulators and molecular mechanisms of HSPN in children.\u003c/p\u003e\n\u003cp\u003eLong non-coding RNAs (lncRNAs) are non-coding RNAs with a length of \u0026gt;200 nucleotides [9-10]. Recently, next generation sequencing (NGS) has found a great deal of lncRNA transcripts and revealed their essential roles in cell differentiation, cell lineage selection, organogenesis, and tissue homeostasis effect [11-13]. The functions of lncRNA are complex and diverse. Mechanistically, lncRNA can act as scaffolds, guides, decoys, or enhancers to regulate gene expression and thereby exert their functions [14, 15]. Increasing studies have confirmed that lncRNAs are involved in regulating the occurrence and development of multiple diseases including various cancers, kidney disease, and cardiovascular disease, providing novel biomarkers and drug targets for diagnosis and therapy of disease [16-18]. Recently, the important roles of lncRNA in kidney diseases, including acute renal rejection, diabetic nephropathy, membranous nephropathy, chronic kidney disease and lupus nephritis, has gradually been paid attention. For examples, circulating LNC-EPHA6 was confirmed as a promising marker for vascular injury under acute rejection after kidney transplantation [19]. Another study reported that lncRNA NEAT1 served as a sponge for miR-146b to regulate TRAF6 expression and NF-\u0026kappa;B signaling, thus accelerating renal mesangial cell injury in lupus nephritis [20].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHowever, lncRNAs involved in the occurrence and development of HSPN and corresponding molecular mechanism are still unclear. Exploring the expression pattern and function of lncRNA in HSPN of children is of great significance to design and develop novel strategies for the diagnosis, prognosis and clinical management of children with HSPN. In this study, the lncRNA and mRNA expression profiles of high-throughput sequencing dataset GSE102114 was downloaded to screen out differentially expressed lncRNA, immune-related genes and apoptosis-related genes in the peripheral blood of children with HSPN. Through gene ontology (GO) and The Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, protein-protein network (PPI) construction, critical immune- and apoptosis-related genes in HSPN of children were explored. Then, we identified immune- and apoptosis-related lncRNAs that might be involved in the regulation of critical immune- and apoptosis-related genes in HSPN of children through Spearman correlation analysis. According to competing endogenous RNAs (ceRNAs) theory, lncRNAs can serve as sponges for miRNAs to release the interaction of miRNAs and their targe genes, thereby regulating the expression of target genes [21]. Following, we established a lncRNA-miRNA-mRNA regulatory network in HSPN of children based on the ceRNAs mechanism, which would help to understand the mechanism of the occurrence and development of HSPN in children.\u003c/p\u003e"},{"header":"Materials And Methods","content":"\u003cp\u003e\u003cstrong\u003eData collection and processing\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe gene expression profiles of dataset GSE102114 were downloaded from the NCBI Gene Expression Omnibus (GEO, https://www.ncbi.nlm.nih.gov/geo/), which include the lncRNA and mRNA expression profiles of peripheral blood of 6 children with HSPN and 4 healthy children [22]. A list of 1811 immune-related genes were downloaded from ImmPort (https://www.immport.org/), of which 962 immune-related genes were found in mRNA expression profile of GSE102114 [23]. Besides, a total of 306 apoptosis-related genes were identified through merging several classical apoptosis-related gene sets downloaded from the molecular signature database (MSigDB, https://www.gsea-msigdb.org/gsea/msigdb/index.jsp ), including KEGG_APOPTOSIS, WP_APOPTOSIS_MODULATION_AND_SIGNALING, WP_APOPTOSIS, REACTOME_SUPPRESSION_OF_APOPTOSIS, REACTOME_ REGULATION_OF_APOPTOSIS, REACTOME_INTRINSIC_PATHWAY_FOR_ APOPTOSIS, REACTOME_APOPTOSIS_INDUCED_DNA_ FRAGMENTATION, and REACTOME_APOPTOSIS [24, 25]. Following the expression profile of 279 apoptosis-related genes were extracted from the mRNA expression profile of GSE102114. The lists of immune-related genes and apoptosis-related genes are provided in Table S1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDifferential expression analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing \u0026ldquo;limma\u0026rdquo; R package, differential expression analysis was conducted to screen out differentially expressed lncRNAs and mRNAs, setting absolute log2fold change (log2FC) \u0026gt; 1 and adjusted \u003cem\u003eP\u003c/em\u003e value (adj.P.Val)\u0026nbsp;＜0.05 as the significant threshold. Amongst, differentially expressed immune-related genes and apoptosis-related genes were identified from differentially expressed genes. R packages of \u0026ldquo;pheatmap\u0026rdquo; and \u0026ldquo;ggplot2\u0026rdquo; were used to display differentially expressed lncRNAs, mRNAs, immune-related genes and apoptosis-related genes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGO and KEGG enrichment analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eGO annotation consists of Biological Process (BP), Cellular Componet (CC), Molecular Function (MF) of genes in different databases using standard expression terms. KEGG (Kyoto Encyclopedia of Genes and Genomes, http://www.kegg.jp/) is a bioinformatics resource of genomes and genes by assigning functional and pathway meanings to genomes and genes, which uncover cellular and organism-level functions from genome sequences and other molecular datasets [26-28]. Here, GO and KEGG enrichment analysis were performed using \u0026ldquo;clusterProfiler\u0026rdquo; R package for differentially expressed immune-related genes and apoptosis-related genes, with the adjusted P value \u0026lt;0.05 as threshold. Following, \u0026ldquo;ggplot2\u0026rdquo; and \u0026ldquo;GOplot\u0026rdquo; R packages were utilized to show the results of top 10 terms of BP, CC, MF of GO and KEGG.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProtein-protein interaction (PPI) network construction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThrough drawing Venn plot using \u0026ldquo;ggplot2\u0026rdquo; R package, we overlapped differentially expressed immune-related genes and apoptosis-related genes to identify critical immune- and apoptosis-related genes in HSPN of children. To explore the interactions among the critical immune- and apoptosis-related genes, we uploaded these genes to STRING (\u003ccite\u003ehttps://string-db.org)\u003c/cite\u003e, a database of functional protein association networks, to obtain their interaction information [29, 30]. Following, the PPI network was visualized and analyzed by Cytoscape 3.8.2. In addition, top 2 clusters of the Molecular Complex Detection (MCODE) plugins in Cytoscape were constructed in the complex protein networks.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorrelation analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo identify important immune- and apoptosis-related lncRNAs in HSPN of children, Spearman correlation analysis were conducted to analyze the correlations between differentially expressed lncRNAs and critical immune- and apoptosis-related genes. Absolute value of correlation coefficient |r| \u0026gt;0.9 and P value \u0026lt;0.001 was set as the\u0026nbsp;threshold to filter lncRNAs correlated with immune- and apoptosis-related genes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLncRNA-miRNA and miRNA-mRNA prediction, lncRNA-miRNA-mRNA regulatory network construction\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMiRcode (http://mircode.org/) is a database predicting microRNA targets based on the comprehensive GENCODE gene annotation consisting of more than 10,000 lncRNAs. The potential lncRNA-miRNA pairs were predicted by miRcode. In addition, we retrieved mRNA-miRNA pairs file from TargetScanHuman 8.0 (https://www.targetscan.org/vert_80/docs/help.html/), released at September 2021 [31]. Based on ceRNA mechanism, lncRNAs and mRNAs that were predicted to bind to the same miRNAs and exhibited positive correlations were considered as ceRNAs. Consequently, the immune- and apoptosis-related lncRNA-miRNA-mRNA for HSPN of children was constructed, which was visualized by Cytoscape 3.8.2.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eqRT-PCR\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;validation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe peripheral blood samples of\u0026nbsp;11 HSP/HSPN children and 3 age-matched healthy children were enrolled from the Children\u0026apos;s Hospital, Zhejiang University School of Medicine (Hangzhou, China) between August 2021 and November 2021. HSP was diagnosed according to the criteria outlined at the Society of Pediatrics, Chinese Medical Association in 2013 [32]. HSPN was diagnosed with the presence of either hematuria and/or proteinuria during the first 6 months of HSP [33]. None of the patients had complications or had taken any immunosuppressants before this study.\u0026nbsp;The clinical characteristics of the children were presented in Table S2.\u0026nbsp;The research was approved by the Ethics Committee of the study hospital.\u0026nbsp;Total RNA of these samples was extracted using RNA Extraction Kit (Omega, Guangzhou, China). Reverse transcription was conducted using PrimeScript RT Master Mix Kit (Takara, Dalian, China). The lncRNA level was assessed using TB Green Premix Ex Taq Kit (Takara, Dalian, China) following manufacturer\u0026rsquo; instructions. Primers used in our study are available in Table S3.\u0026nbsp;The relative expression of lncRNAs was calculated by 2\u003csup\u003e\u0026minus;\u0026Delta;\u0026Delta;Ct\u003c/sup\u003e method, with GAPDH as the reference. Two-sided unpaired Student\u0026rsquo;s t-test was applied to compare the difference of lncRNA expression levels between the peripheral blood samples of 11 HSP/HSPN children and 3 age-matched healthy children. The corresponding results were visualized by R package of \u0026ldquo;ggplot2\u0026rdquo;.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eIdentification of differentially expressed lncRNAs and mRNAs in HSPN of children\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe differentially expressed lncRNAs and mRNAs were identified in the peripheral blood of 6 children with HSPN and 4 healthy children from GSE102114. We found 396 differentially expressed lncRNAs, among which 184 upregulated and 212 downregulated (|log2FC|\u0026gt;1 and adj.P.Value \u0026lt;0.05, Table S4). Figure 1A and Figure1B displayed the significant expression patterns and distribution of differentially expressed lncRNAs between healthy control and HSPN groups,\u0026nbsp;respectively. Besides, a total of 5417 differentially expressed genes, of which 2737 upregulated and 2680 downregulated (|log2FC|\u0026gt;1 and adj.P.Value \u0026lt;0.05, Table S5). Likewise, Figure 1C and Figure1D displayed the significant expression patterns and distribution of differentially expressed mRNAs between healthy control and HSPN groups,\u0026nbsp;respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbnormally expressed immune-related mRNAs in children HSPN\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHSPN is characteristic with immune system disorder. Thus, we filtered out differentially expressed immune-related genes from\u0026nbsp;5417 differentially expressed genes, identifying 314 differentially expressed immune-related genes (185 upregulated and 129 downregulated). Figure 2A and Figure 2B showed the significant expression patterns and distribution of differentially expressed immune-related genes between healthy control and HSPN groups,\u0026nbsp;respectively.\u0026nbsp;The results of GO analysis demonstrated these 314 genes significantly enriched in regulation of innate immune response, T cell activation, positive regulation of cytokine production in BP; external side of plasma membrane, membrane raft, membrane microdomain in CC; receptor ligand activity, cytokine binding, cytokine receptor activity in MF (Figure2C). Meaningfully, these terms were closely associated with immune functions. Similarly, the results of KEGG revealed these 314 genes were significantly enriched in multiple immune-related pathways, including T cell receptor signaling pathway, Natural killer cell mediated cytotoxicity, B cell receptor signaling pathway, etc (Figure2D).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbnormally expressed apoptosis-related mRNAs in children HSPN\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFollowing, we aimed to explore important apoptosis-related genes in HSPN of children and observed 124\u0026nbsp;differentially expressed apoptosis-related genes (71 upregulated and 53 downregulated). Figure 3A and Figure 3B displayed the significant expression patterns and distribution of differentially expressed apoptosis-related genes between healthy control and HSPN groups,\u0026nbsp;respectively.Moreover, the results of GO analysis demonstrated these 124 genes significantly enriched inactivation of innate immune response, response to tumor necrosis factor, and interleukin-1-mediated signaling pathway in BP; proteasome complex, endopeptidase complex, and peptidase complex in CC; endopeptidase activity, ubiquitin protein ligase binding in MF (Figure3C). Interestingly, these terms were also correlated with immune functions. Besides, the results of KEGG revealed these 124 genes were significantly enriched in apoptosis, proteasome, spinocerebellar ataxia, lipid and atherosclerosis, etc (Figure3D).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIdentification of important immune- and apoptosis-related mRNAs and lncRNAs in children HSPN\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThrough intersecting differentially expressed immune-related and apoptosis-related genes, we identified 43 genes which might simultaneously participate in regulation of immune function and cell apoptosis of children with HSPN (Figure4A). The interactions of these immune- and apoptosis-related genes and constructed the PPI network of these genes are displayed in Figure4B. Especially, the top two highly interconnected subclusters were analyzed by MCODE algorithm of Cytoscape 3.8.2, scoring 9.75 and 9.0 respectively (Figure4B, C). Following, we defined 100 lncRNAs that were significantly correlated with above 43 genes as immune- and apoptosis-related lncRNAs in HSPN of children (|Spearman R| \u0026gt; 0.9 and p \u0026lt; 0.001). The specific correlations of immune- and apoptosis-related lncRNAs and mRNAs in HSPN of children were displayed in Table S6.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConstruction of the\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eimmune- and apoptosis-related lncRNA\u0026ndash;miRNA\u0026ndash;mRNA ceRNA network for\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003echildren HSPN\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to ceRNA mechanism, immune- and apoptosis-related lncRNAs and mRNAs that exist positive correlations were considered as ceRNAs to construct the ceRNA regulatory network. We identified the miRNAs which might bridge the immune- and apoptosis-related lncRNAs and mRNAs by\u0026nbsp;matching lncRNA-miRNA pairs and miRNA\u0026ndash;mRNA pairs (Figure5A, B). Correspondingly, the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network for children with HSPN were established (Figure5C). The specific regulatory relationship in the ceRNA network are\u0026nbsp;displayed\u0026nbsp;in Figure6 and Table S7.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eValidation of the expression levels of the lncRNAs in HSPN\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further confirm the expression levels of lncRNAs in the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network, qRT-PCR assay was conducted in our clinical samples. Consistent with the results of GSE102114, the expression levels of SNHG3, LINC00152, TUG1, GAS5, FGD5-AS1, DLEU2, and SCARNA9 were significantly upregulated, whereas NEAT, PVT1, SNHG1, and DISC1-IT1 were dramatically downregulated in the blood samples of than in normal blood samples (Figure 7A, B). Collectively, the upregulation of SNHG3, LINC00152, TUG1, GAS5, FGD5-AS1, DLEU2, and SCARNA9 might be potential biomarkers for HSPN. Similarly, the downregulation of NEAT, PVT1, SNHG1, and DISC1-IT1 have potential to be indicators for HSPN.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eHSPN is accounting for ~\u0026thinsp;80% of children with secondary glomerulopathy, and renal involvement is the most important prognostic factor in determining morbidity and mortality of HSP. In terms of etiology, persistent purpura or recurrence, severe abdominal symptoms, arthritis and age\u0026thinsp;\u0026gt;\u0026thinsp;10 years are the most important risk factors for HSPN in children [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Extensive clinical and experimental data have corroborated the disorders of cellular and humoral immune responses are closely related with the pathogenesis of HSPN in children [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e]. However, key genes responsible for the dysregulation of humoral and cellular immunity during the progression of HSPN in children remain unknown.\u003c/p\u003e \u003cp\u003eIn the present study, we identified 314 differentially expressed immune-related mRNAs in the peripheral blood of children with HSPN. GO enrichment analysis revealed these mRNAs were involved in multiple immune-related biological processes, including regulation of innate immune response, T cell activation, positive regulation of cytokine production, and regulation of lymphocyte activation. The results of KEGG enrichment analysis also suggested these immune-related mRNAs might participate in the activation of T cell receptor signaling pathway, Natural killer cell cytotoxicity, B cell receptor signaling pathway, etc. These results indicated that activation of T cells and B cells, as well as elevated cytokine and chemokine production are closely associated with the dysregulation of immune-related mRNAs in HSPN of children. Su QY et. al, have observed a relative increase of T lymphocytes in children with HSPN, which leads to the activation of B cells, increased secretion of inflammatory mediators, and further increases the secretion of immunoglobulins, causing the occurrence of small vasculitis [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Thus, we speculated the dysregulation of these differentially expressed immune-related mRNAs might contribute to the immune dysfunction of children with HSPN.\u003c/p\u003e \u003cp\u003eApoptosis is another critical factor for HSPN of children [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Here, we identified 124 differentially expressed apoptosis-related mRNAs in the peripheral blood of children with HSPN. Interestingly, GO enrichment analysis revealed these apoptosis-related mRNAs also participate in the regulation of immune-related processes, including innate immune response, interleukin-1-mediated signaling pathway, and cellular response to interleukin-1. Besides, the results of KEGG enrichment analysis demonstrated these apoptosis-related mRNAs significantly enriched in apoptosis, proteasome, lipid and atherosclerosis, TNF signaling pathway, and Toll-like receptor signaling pathway, etc. Previous studies have confirmed the deposition of IgA-containing immune complexes are responsible for the renal damage of HSPN patients. During the progression of HSPN, IgA deposition may induce apoptosis of human umbilical vein endothelial cells, thereby causing HSP vascular endothelial damage [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. On the other hand, apoptosis may promote the removal of inflammatory cells, contributing to the control of early inflammatory response and repair self-limiting vasculitis [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Hence, there exist complex regulatory links between immune and apoptosis-associated signaling pathways in HSPN of children. Overlapping differentially expressed immune- and apoptosis-related mRNAs in the peripheral blood of children with HSPN, we identified 43 immune- and apoptosis-related mRNAs as critical genes, which might play essential regulatory roles in the pathogenesis of HSPN of children.\u003c/p\u003e \u003cp\u003eRecently, accumulating studies have demonstrated that lncRNAs play important roles in regulation immune and apoptosis-related pathways [\u003cspan additionalcitationids=\"CR38 CR39\" citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. However, the critical lncRNAs responsible for the dysregulations of immune and apoptosis of HSPN in children are largely unknown. In our present study, we identified 396 differentially expressed lncRNAs in the peripheral blood of children with HSPN. Through correlation analysis, a total of 100 lncRNAs correlated with above 43 immune- and apoptosis-related genes were identified as immune- and apoptosis-related lncRNAs in HSPN of children. To further explore the underlying regulatory mechanisms of immune- and apoptosis-related lncRNAs and mRNAs in HSPN of children, we constructed the immune- and apoptosis-related lncRNAs-miRNA-mRNAs regulatory network based on ceRNAs mechanism. In the lncRNAs-miRNA-mRNAs regulatory network, elevated expression of SNHG3, LINC00152, TUG1, GAS5, FGD5-AS1, DLEU2, and SCARNA9 might promote the expression of TLR4, IL1RAP, CDH1, PSMC2, PSMD1, PSMD6, PSMD10, PSMD14, PIK3CA, PIK3CB, CASP3, PPP3R1, TRIM27, HMGB1, MAPK1, and MAPK8; while decreased expression of SNHG1, NEAT1, DISC1-IT1, and PVT1 might induce the downregulation of AKT2, TNFRSF10B, PIK3R5, and PIK3CD.\u003c/p\u003e \u003cp\u003eFurthermore, we validated the upregulation of SNHG3, LINC00152, TUG1, GAS5, FGD5-AS1, DLEU2, and SCARNA9, downregulation of SNHG1, NEAT1, DISC1-IT1, and PVT1 in the peripheral blood of children with HSPN collected from the Children's Hospital, Zhejiang University School of Medicine. These results suggested the dysregulation of these lncRNAs might be biomarkers for the diagnosis of HSPN in children. So far, existing studies mainly focused on the roles of these lncRNAs in the regulation of occurrence and development of various cancers [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. For example, ample evidence suggests SNHG3 acts as an oncogenic lncRNA to facilitate cell proliferation, migration and invasion, and suppress cell apoptosis in glioma, renal cell carcinoma, lung cancer, and prostate cancer [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Interestingly, SNHG3, TUG1, GAS5, and SCARNA9 were identified as immune-related lncRNAs in different cancers [\u003cspan additionalcitationids=\"CR45 CR46\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Besides, the anti-apoptotic effect of SNHG3, LINC00152, TUG1, and FGD5-AS1has been validated in different cancer cell models [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e, \u003cspan additionalcitationids=\"CR49\" citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Nevertheless, their immunological and apoptotic roles in the progression of HSPN in children have not been explored to date. Based on the results of our present study, we proposed that the dysregulation of these lncRNAs (upregulation of SNHG3, LINC00152, TUG1, GAS5, FGD5-AS1, DLEU2, and SCARNA9; downregulation of SNHG1, NEAT1, DISC1-IT1, and PVT1) might be responsible for the immune imbalance of children with HSPN through modulation of immune- and apoptosis-related genes, which lead to the deposition of IgA-containing immune complexes, and thereby inducing the occurrence and development of HSPN in children. Of course, further experimental studies are necessary to validate these speculations.\u003c/p\u003e \u003cp\u003eThere were several limitations in this study. Firstly, the sample size for our analysis and validation were relatively small. The present results should be further validated in larger cohorts. Secondly, miRNAs in the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network were determined by miRNA-target prediction. Further experimental validations are necessary in future.\u003c/p\u003e \u003cp\u003eIn conclusion, the present study constructed an immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network of HSPN in children, which provided a basis and direction for future molecular mechanisms of the pathogenesis of HSPN in children. These lncRNAs and mRNAs in the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network have potential to be novel diagnostic and therapeutic biomarkers for HSPN of children.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eData Availability Statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset used in this study can be found in GSE102114 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE102114).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical review and approval was not required for the study. Written informed consent for participation was not required for this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLingfei Huang and Yanhong Li performed data collection, conducted data analysis and Writed original draft. Yi Xie and Fei Liu performed data collection. Jianhua Mao and Jing Miao supervised the project and conceptualized the research. All authors contributed to the article and approved the submitted version.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that there are no potential conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eProject support was provided by Natural Science Foundation of Zhejiang Province (grant No. LQY20H300002), Hospital Pharmacy Research Funding Project of Zhejiang Pharmaceutical Association (grant No. 2014ZYY05).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMcCarthy HJ, Tizard EJ. Clinical practice: Diagnosis and management of Henoch-Sch\u0026ouml;nlein purpura. Eur J Pediatr. 2010 Jun;169(6):643\u0026ndash;50. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00431-009-1101-2\u003c/span\u003e\u003cspan address=\"10.1007/s00431-009-1101-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYang YH, Yu HH, Chiang BL. The diagnosis and classification of Henoch-Sch\u0026ouml;nlein purpura: an updated review. Autoimmun Rev. 2014 Apr-May;13(4\u0026ndash;5):355\u0026ndash;8. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.autrev.2014.01.031\u003c/span\u003e\u003cspan address=\"10.1016/j.autrev.2014.01.031\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLeung AKC, Barankin B, Leong KF. Henoch-Sch\u0026ouml;nlein Purpura in Children: An Updated Review. Curr Pediatr Rev. 2020;16(4):265\u0026ndash;276. doi: 10.2174/ 157339631666620050810 4708.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLau KK, Suzuki H, Novak J, Wyatt RJ. Pathogenesis of Henoch-Sch\u0026ouml;nlein purpura nephritis. Pediatr Nephrol. 2010 Jan;25(1):19\u0026ndash;26. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00467-009-1230-x\u003c/span\u003e\u003cspan address=\"10.1007/s00467-009-1230-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen JY, Mao JH. Henoch-Sch\u0026ouml;nlein purpura nephritis in children: incidence, pathogenesis and management. World J Pediatr. 2015 Feb;11(1):29\u0026ndash;34. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12519-014-0534-5\u003c/span\u003e\u003cspan address=\"10.1007/s12519-014-0534-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSu Q, Jiang L, Chai J, Dou Z, Rong Z, Zhao X, Yu B, Wang Y, Wang X. Changes of Peripheral Blood Lymphocyte Subsets and Immune Function in Children with Henoch-Schonlein Purpura Nephritis. Iran J Immunol. 2021 Sep;18(3):259\u0026ndash;267. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.22034/iji.2021.89742.1964\u003c/span\u003e\u003cspan address=\"10.22034/iji.2021.89742.1964\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDuan X, Yu D, Yu C, Wang B, Guo Y. Henoch-Sch\u0026ouml;nlein purpura following high-voltage electric burn injury: A case report and review of the literature. Exp Ther Med. 2016 Feb;11(2):540\u0026ndash;542. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3892/etm.2015.2905\u003c/span\u003e\u003cspan address=\"10.3892/etm.2015.2905\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYuan P, Bo Y, Ming G, Wen-Jun F, Qin Z, Bo H. Apoptosis of human umbilical vein endothelial cells (HUVEC) induced by IgA1 isolated from Henoch-Schonlein purpura children. Asian Pac J Allergy Immunol. 2014 Mar;32(1):34\u0026ndash;8. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.12932/AP0357.32.1.2014\u003c/span\u003e\u003cspan address=\"10.12932/AP0357.32.1.2014\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJarroux J, Morillon A, Pinskaya M. History, Discovery, and Classification of lncRNAs. Adv Exp Med Biol. 2017;1008:1\u0026ndash;46. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/978-981-10-5203-3_1\u003c/span\u003e\u003cspan address=\"10.1007/978-981-10-5203-3_1\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSt Laurent G, Wahlestedt C, Kapranov P. The Landscape of long noncoding RNA classification. Trends Genet. 2015 May;31(5):239\u0026ndash;51. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tig.2015.03.007\u003c/span\u003e\u003cspan address=\"10.1016/j.tig.2015.03.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKazimierczyk M, Kasprowicz MK, Kasprzyk ME, Wrzesinski J. Human Long Noncoding RNA Interactome: Detection, Characterization and Function. Int J Mol Sci. 2020 Feb 4;21(3):1027. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms21031027\u003c/span\u003e\u003cspan address=\"10.3390/ijms21031027\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMelissari MT, Grote P. Roles for long non-coding RNAs in physiology and disease. Pflugers Arch. 2016 Jun;468(6):945\u0026ndash;58. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00424-016-1804-y\u003c/span\u003e\u003cspan address=\"10.1007/s00424-016-1804-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYip CW, Sivaraman DM, Prabhu AV, Shin JW. Functional annotation of lncRNA in high-throughput screening. Essays Biochem. 2021 Oct 27;65(4):761\u0026ndash;773. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1042/EBC20200061\u003c/span\u003e\u003cspan address=\"10.1042/EBC20200061\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen LL. Linking Long Noncoding RNA Localization and Function. Trends Biochem Sci. 2016 Sep;41(9):761\u0026ndash;772. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tibs.2016.07.003\u003c/span\u003e\u003cspan address=\"10.1016/j.tibs.2016.07.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eQian X, Zhao J, Yeung PY, Zhang QC, Kwok CK. Revealing lncRNA Structures and Interactions by Sequencing-Based Approaches. Trends Biochem Sci. 2019 Jan;44(1):33\u0026ndash;52. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tibs.2018.09.012\u003c/span\u003e\u003cspan address=\"10.1016/j.tibs.2018.09.012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhan A, Soleimani M, Mandal SS. Long Noncoding RNA and Cancer: A New Paradigm. Cancer Res. 2017 Aug 1;77(15):3965\u0026ndash;3981. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1158/0008-5472.CAN-16-2634\u003c/span\u003e\u003cspan address=\"10.1158/0008-5472.CAN-16-2634\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2017 Jul 12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIgnarski M, Islam R, M\u0026uuml;ller RU. Long Non-Coding RNAs in Kidney Disease. Int J Mol Sci. 2019 Jul 3;20(13):3276. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms20133276\u003c/span\u003e\u003cspan address=\"10.3390/ijms20133276\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSallam T, Sandhu J, Tontonoz P. Long Noncoding RNA Discovery in Cardiovascular Disease: Decoding Form to Function. Circ Res. 2018 Jan 5;122(1):155\u0026ndash;166. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1161/CIRCRESAHA.117.311802\u003c/span\u003e\u003cspan address=\"10.1161/CIRCRESAHA.117.311802\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGroeneweg KE, Duijs JMGJ, Florijn BW, van Kooten C, de Fijter JW, van Zonneveld AJ, Reinders MEJ, Bijkerk R. Circulating Long Noncoding RNA LNC-EPHA6 Associates with Acute Rejection after Kidney Transplantation. Int J Mol Sci. 2020 Aug 5;21(16):5616. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms21165616\u003c/span\u003e\u003cspan address=\"10.3390/ijms21165616\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang LH, Xiao B, Zhong M, Li Q, Chen JY, Huang JR, Rao H. LncRNA NEAT1 accelerates renal mesangial cell injury via modulating the miR-146b/TRAF6/NF-κB axis in lupus nephritis. Cell Tissue Res. 2020 Dec;382(3):627\u0026ndash;638. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s00441-020-03248-z\u003c/span\u003e\u003cspan address=\"10.1007/s00441-020-03248-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Y, Hou J, He D, Sun M, Zhang P, Yu Y, Chen Y. The Emerging Function and Mechanism of ceRNAs in Cancer. Trends Genet. 2016 Apr;32(4):211\u0026ndash;224. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.tig.2016.02.001\u003c/span\u003e\u003cspan address=\"10.1016/j.tig.2016.02.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePang S, Lv J, Wang S, Yang G, Ding X, Zhang J. Differential expression of long non-coding RNA and mRNA in children with Henoch-Sch\u0026ouml;nlein purpura nephritis. Exp Ther Med. 2019 Jan;17(1):621\u0026ndash;632. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3892/etm.2018.7038\u003c/span\u003e\u003cspan address=\"10.3892/etm.2018.7038\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBhattacharya S, Dunn P, Thomas CG, Smith B, Schaefer H, Chen J, Hu Z, Zalocusky KA, Shankar RD, Shen-Orr SS, Thomson E, Wiser J, Butte AJ. ImmPort, toward repurposing of open access immunological assay data for translational and clinical research. Sci Data. 2018 Feb 27;5:180015. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/sdata.2018.15\u003c/span\u003e\u003cspan address=\"10.1038/sdata.2018.15\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiberzon A, Birger C, Thorvaldsd\u0026oacute;ttir H, Ghandi M, Mesirov JP, Tamayo P. The Molecular Signatures Database (MSigDB) hallmark gene set collection. Cell Syst. 2015 Dec 23;1(6):417\u0026ndash;425. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.cels.2015.12.004\u003c/span\u003e\u003cspan address=\"10.1016/j.cels.2015.12.004\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSubramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES, Mesirov JP. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci U S A. 2005 Oct 25;102(43):15545\u0026ndash;50. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1073/pnas.0506580102\u003c/span\u003e\u003cspan address=\"10.1073/pnas.0506580102\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res. 2000 Jan 1;28(1):27\u0026ndash;30. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/nar/28.1.27\u003c/span\u003e\u003cspan address=\"10.1093/nar/28.1.27\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanehisa M. Toward understanding the origin and evolution of cellular organisms. Protein Sci. 2019 Nov;28(11):1947\u0026ndash;1951. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/pro.3715\u003c/span\u003e\u003cspan address=\"10.1002/pro.3715\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKanehisa M, Furumichi M, Sato Y, Ishiguro-Watanabe M, Tanabe M. KEGG: integrating viruses and cellular organisms. Nucleic Acids Res. 2021 Jan 8;49(D1):D545-D551. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/nar/gkaa970\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkaa970\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzklarczyk D, Gable AL, Lyon D, Junge A, Wyder S, Huerta-Cepas J, Simonovic M, Doncheva NT, Morris JH, Bork P, Jensen LJ, Mering CV. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets. Nucleic Acids Res. 2019 Jan 8;47(D1):D607-D613. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/nar/gky1131\u003c/span\u003e\u003cspan address=\"10.1093/nar/gky1131\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSzklarczyk D, Gable AL, Nastou KC, Lyon D, Kirsch R, Pyysalo S, Doncheva NT, Legeay M, Fang T, Bork P, Jensen LJ, von Mering C. The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 2021 Jan 8;49(D1):D605-D612. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/nar/gkaa1074\u003c/span\u003e\u003cspan address=\"10.1093/nar/gkaa1074\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcGeary SE, Lin KS, Shi CY, Pham TM, Bisaria N, Kelley GM, Bartel DP. The biochemical basis of microRNA targeting efficacy. Science. 2019 Dec 20;366(6472):eaav1741. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1126/science.aav1741\u003c/span\u003e\u003cspan address=\"10.1126/science.aav1741\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSubspecialty Group of Renal Diseases, the Society of Pediatrics, Chinese Medical Association. [Evidence-based guideline for diagnosis and treatment of Henoch-Schonlein purpura nephritis (2016)]. Zhonghua Er Ke Za Zhi. 2017 Sep 2;55(9):647\u0026ndash;651. Chinese. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3760/cma.j.issn.0578-1310.2017.09.003\u003c/span\u003e\u003cspan address=\"10.3760/cma.j.issn.0578-1310.2017.09.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDavin JC, Coppo R. Henoch-Sch\u0026ouml;nlein purpura nephritis in children. Nat Rev Nephrol. 2014 Oct;10(10):563\u0026ndash;73. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/nrneph.2014.126\u003c/span\u003e\u003cspan address=\"10.1038/nrneph.2014.126\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Q, Shi YY, Cao M, Dong W, Zhang JB. Role of Imbalance between Th17 Cells and Treg Cells in the Pathogenesis of Children with Henoch-Schonlein Purpura. Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2015 Oct;23(5):1391-6. Chinese. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.7534/j.issn.1009-2137.2015.05.032\u003c/span\u003e\u003cspan address=\"10.7534/j.issn.1009-2137.2015.05.032\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDel Vecchio GC, Penza R, Altomare M, Piacente L, Aceto G, Lassandro G, De Mattia D, Giordano P. Cytokine pattern and endothelium damage markers in Henoch-Sch\u0026ouml;nlein purpura. Immunopharmacol Immunotoxicol. 2008;30(3):623\u0026ndash;9. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1080/08923970801973646\u003c/span\u003e\u003cspan address=\"10.1080/08923970801973646\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang J, Zheng Y, Chen G, Lv Y, Lian F, Jiang D, Ke W, Liu L, Fan C, Gong S. The changes in pyroptosis-related inflammatory factors in the peripheral blood of patients with Henoch-Schonlein purpura. Ann Palliat Med. 2021 Jun;10(6):6687\u0026ndash;6693. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.21037/apm-21-1227\u003c/span\u003e\u003cspan address=\"10.21037/apm-21-1227\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen YG, Satpathy AT, Chang HY. Gene regulation in the immune system by long noncoding RNAs. Nat Immunol. 2017 Aug 22;18(9):962\u0026ndash;972. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/ni.3771\u003c/span\u003e\u003cspan address=\"10.1038/ni.3771\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDenaro N, Merlano MC, Lo Nigro C. Long noncoding RNAs as regulators of cancer immunity. Mol Oncol. 2019 Jan;13(1):61\u0026ndash;73. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/1878-0261.12413\u003c/span\u003e\u003cspan address=\"10.1002/1878-0261.12413\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang Y, Mao Q, Xia Q, Cheng J, Huang Z, Li Y, Chen P, Yang J, Fan X, Liang Y, Lin H. Noncoding RNAs link metabolic reprogramming to immune microenvironment in cancers. J Hematol Oncol. 2021 Oct 15;14(1):169. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s13045-021-01179-y\u003c/span\u003e\u003cspan address=\"10.1186/s13045-021-01179-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGutschner T, Diederichs S. The hallmarks of cancer: a long non-coding RNA point of view. RNA Biol. 2012 Jun;9(6):703\u0026ndash;19. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4161/rna.20481\u003c/span\u003e\u003cspan address=\"10.4161/rna.20481\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2012 Jun 1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZheng S, Jiang F, Ge D, Tang J, Chen H, Yang J, Yao Y, Yan J, Qiu J, Yin Z, Ni Y, Zhao L, Chen X, Li H, Yang L. LncRNA SNHG3/miRNA-151a-3p/RAB22A axis regulates invasion and migration of osteosarcoma. Biomed Pharmacother. 2019 Apr;112:108695. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.biopha.2019.108695\u003c/span\u003e\u003cspan address=\"10.1016/j.biopha.2019.108695\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYuan ZJ, Yu C, Hu XF, He Y, Chen P, Ouyang SX. LINC00152 promotes pancreatic cancer cell proliferation, migration and invasion via targeting miR-150. Am J Transl Res. 2020 May 15;12(5):2241\u0026ndash;2256.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXu B, Mei J, Ji W, Bian Z, Jiao J, Sun J, Shao J. LncRNA SNHG3, a potential oncogene in human cancers. Cancer Cell Int. 2020 Nov 4;20(1):536. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12935-020-01608-x\u003c/span\u003e\u003cspan address=\"10.1186/s12935-020-01608-x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhan T, Gao X, Wang G, Li F, Shen J, Lu C, Xu L, Li Y, Zhang J. Construction of Novel lncRNA-miRNA-mRNA Network Associated With Recurrence and Identification of Immune-Related Potential Regulatory Axis in Hepatocellular Carcinoma. Front Oncol. 2021 Jul 15;11:626663. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fonc.2021.626663\u003c/span\u003e\u003cspan address=\"10.3389/fonc.2021.626663\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang W, Zhao Z, Yang F, Wang H, Wu F, Liang T, Yan X, Li J, Lan Q, Wang J, Zhao J. An immune-related lncRNA signature for patients with anaplastic gliomas. J Neurooncol. 2018 Jan;136(2):263\u0026ndash;271. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s11060-017-2667-6\u003c/span\u003e\u003cspan address=\"10.1007/s11060-017-2667-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen Q, Hu L, Huang D, Chen K, Qiu X, Qiu B. Six-lncRNA Immune Prognostic Signature for Cervical Cancer. Front Genet. 2020 Oct 14;11:533628. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fgene.2020.533628\u003c/span\u003e\u003cspan address=\"10.3389/fgene.2020.533628\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang Z, Liu Y, Zhang J, Zhao R, Zhou X, Wang H. An Immune-Related Long Noncoding RNA Signature as a Prognostic Biomarker for Human Endometrial Cancer. J Oncol. 2021 Dec 10;2021:9972454. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1155/2021/9972454\u003c/span\u003e\u003cspan address=\"10.1155/2021/9972454\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang L, Wang Y, Su H. Long non-coding RNA LINC00152/miR-613/CD164 axis regulates cell proliferation, apoptosis, migration and invasion in glioma via PI3K/AKT pathway. Neoplasma. 2020 Jul;67(4):762\u0026ndash;772. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4149/neo_2020_190706N598\u003c/span\u003e\u003cspan address=\"10.4149/neo_2020_190706N598\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLi T, Chen Y, Zhang J, Liu S. LncRNA TUG1 promotes cells proliferation and inhibits cells apoptosis through regulating AURKA in epithelial ovarian cancer cells. Medicine (Baltimore). 2018 Sep;97(36):e12131. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/MD.0000000000012131\u003c/span\u003e\u003cspan address=\"10.1097/MD.0000000000012131\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHao L, Wang J, Bi SJ, Cheng C. Upregulation of Long Noncoding RNA FGD5-AS1 Ameliorates Myocardial Ischemia/Reperfusion Injury via MicroRNA-106a-5p and MicroRNA-106b-5p. J Cardiovasc Pharmacol. 2021 Jul 1;78(1):e45-e54. doi: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/FJC.0000000000001036\u003c/span\u003e\u003cspan address=\"10.1097/FJC.0000000000001036\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"lncRNA, immune, apoptosis, HSPN, children","lastPublishedDoi":"10.21203/rs.3.rs-1834065/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1834065/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eLong noncoding RNAs (lncRNAs) play important roles in the regulation of immunological and apoptotic function. Here, we aimed to explore critical immune- and apoptosis-related lncRNAs in the occurrence and development of Henoch-Sch\u0026ouml;nlein purpura nephritis (HSPN) in children. Through differentially expressed analysis, we identified differentially expressed lncRNAs, immune- and apoptosis-related mRNAs in the peripheral blood samples of children with HSPN. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses validated the immunological and apoptotic roles of the differentially expressed immune-related and apoptosis-related mRNAs. Following, we analyzed the correlations of differentially expressed lncRNAs and immune- and apoptosis-related mRNAs by Spearman\u0026rsquo;s correlation analysis, and determined 100 critical immune- and apoptosis-related lncRNAs in HSPN of children. Based on competing endogenous RNAs (ceRNA) mechanism, we constructed the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network in HSPN of children, and validated the expression levels of lncRNAs in the lncRNA-miRNA-mRNA regulatory network. Collectively, we proposed that the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network might participate in the modulation of pathogenesis of HSPN in children. In addition, the lncRNAs in the immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network (upregulated SNHG3, LINC00152, TUG1, GAS5, FGD5-AS1, DLEU2, and SCARNA9; downregulated SNHG1, NEAT1, DISC1-IT1, and PVT1) could become novel biomarkers for the diagnosis of HNSP in children.\u003c/p\u003e","manuscriptTitle":"Integrated analysis of immune- and apoptosis-related lncRNA-miRNA-mRNA regulatory network in Henoch-Schönlein purpura nephritis of children","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-07-21 19:47:13","doi":"10.21203/rs.3.rs-1834065/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dda32d2f-cfe0-4e66-8dc0-df9ab4f91aa9","owner":[],"postedDate":"July 21st, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-07-26T11:59:30+00:00","versionOfRecord":[],"versionCreatedAt":"2022-07-21 19:47:13","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1834065","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1834065","identity":"rs-1834065","version":["v1"]},"buildId":"rHA-KDH7Qsr4HCuvH75dn","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}