摘要目的 构建儿童紫癜性肾炎(HSPN)差异基因的共表达网络,筛选HSPN进展相关的功能模块和关键基因,为HSPN的诊断、治疗和预后探寻安全、无创的肾脏损伤生物标志物。方法 分析临床指标与HSPN进展的相关性;筛选HSP和HSPN患者的差异表达基因;通过权重基因共表达网络分析获得与临床指标相关的网络模块,并进行模块内基因的GO富集分析;根据MM和GS筛选模块的关键基因,分析关键基因在HSP、HSPN type I、HSPN type II和HSPN type III 4个进展组中的表达情况。结果 血尿/蛋白尿水平、血清IgA、CRP和C3水平与HSPN进展有关。2 399个基因在紫癜性肾炎患者中差异表达,利用权重基因共表达网络分析获得10个网络模块,3个模块与临床指标相关程度最高;模块基因主要富集在中性粒细胞介导的免疫反应、细胞因子活性、白细胞迁移、血小板α颗粒和细胞粘附等通路中;模块中筛选出8个HSPN进展的关键基因,分别为GPX1-201, INHBA-201, PHLDA1-201, VEGFA-205, CALM2-201, CDKN2D-202, LDLRAP1-201和MAP1LC3B-201,其中4个与炎症和免疫反应、细胞周期调控等生物学过程有关。结论 本文获得的3个功能模块通过参与炎症、免疫反应和凝血反应等生物学过程影响HSPN进展相关的临床指标;筛选出的8个关键基因具有生物学意义,可能成为HSPN进展和肾脏损伤程度的潜在分子标志物,为深入研究HSPN的进展机制和发掘潜在的生物标志物提供指导和方向。
Abstract:Objective To construct the co-expression network Henoch-Schonlein purpura nephritis (HSPN) of children to screen the functional modules and key genes that related with the progression of HSPN, so as to explore the safe and non-invasive biomarkers of renal injury for the diagnosis, treatment and prognosis of HSPN. Methods We analyzed the correlations between clinical indicators and HSPN progression, and screened the differentially expressed genes between HSP and HSPN patients. Network modules related to the clinical indicators were obtained through weighted gene co-expression network analysis, and GO enrichment analysis was performed for genes in these modules. Key genes were selected according to MM and GS, and their expressions were analyzed in the four progression groups of HSP, HSPN type I, HSPN type II and HSPN type III. Results Hematuria/proteinuria, serum IgA, CRP and C3 were related with the progression of HSPN. Totally 2 399 genes were differentially expressed in HSPN patients, and ten modules were obtained by weighted gene co-expression network analysis, three of which were most relevant to the clinical indicators. Genes in the modules were mainly enriched in the biological processes of immune response mediated by neutrophils, cytokine activity, leukocyte migration, platelet alpha granules and cell adhesion. Eight genes were selected as key genes for the progression of HSPN, namely GPX1-201, INHBA-201, PHLDA1-201, VEGFA-205, CALM2 -201, CDKN2D-202, LDLRAP1-201 and MAP1LC3B-201. Four of them were involved in biological processes such as inflammation and immune response, and cell cycle regulation. Conclusion The three functional modules obtained in this paper affected the clinical indicators related with HSPN progression by participating in biological processes such as inflammation, immune response, and coagulation response; the selected eight key genes were of biological significance and may become the potential biomarkers for progression and kidney injury of HSPN, which might provide guidance and direction for further studying of the HSPN progression mechanism and exploring the potential biomarkers.
张奇,孙琳,刘美娜. 儿童紫癜性肾炎进展的功能模块和关键基因的筛选研究[J]. 中国医院统计, 2021, 28(2): 118-125.
Zhang Qi, Sun Lin, Liu Meina. Screening of functional modules and key genes in the progression of Henoch-Schonlein purpura nephritis in children. journal1, 2021, 28(2): 118-125.
[1]KAWASAKI Y, ONO A, OHARA S, et al. Henoch-Sch-nlein purpura nephritis in childhood: Pathogenesis, prognostic factors and treatment[J]. Fukushima J Med Sci, 2013, 59(1):15-26.
[2]CHEN J Y, MAO J H. Henoch-Sch-nlein purpura nephritis in children: Incidence, pathogenesis and management[J]. World J Pediatr, 2015, 11(1):29-34.
[3]POHL M. HenochSchnlein purpura nephritis[J]. Pediatr Nephrol, 2015, 30(2):245-252.
[4]YANG Y H, YU H H, CHIANG B L. The diagnosis and classification of Henoch-Sch-nlein purpura: An updated review[J]. Autoimmun Rev, 2014, 13(4-5):355-358.
[5]XIE B, ZHANG W, ZHANG Q, et al. An integrated transcriptomic and proteomic analysis identifies significant novel pathways for henoch-sch-nlein purpura nephritis progression[J]. Biomed Res Int, 2020, 2020:2489175.
[6]SUN L, XIE B, ZHANG Q J, et al. Biomarkers identification by a combined clinical and metabonomics analysis in Henoch-Schonlein purpura nephritis children[J]. Oncotarget, 2017, 8(69):114239-114250.
[7]中华医学会儿科学分会肾脏学组.紫癜性肾炎诊治循证指南:2016[J].中华儿科杂志,2017, 55(9):647-651.
[8]LANGFELDER P, HORVATH S. WGCNA: an R package for weighted correlation network analysis [J]. BMC Bioinformatics, 2008, 9(1):559.
[9]DAVIN J C, COPPO R. HenochSchnlein purpura nephritis in children [J]. Nat Rev Nephrol, 2014, 10(10):563-573.
[10]陈祥云,邱彩玲,张志玲,等.过敏性紫癜患儿血清CRP、IL-21及TNF-α的水平变化及临床应用价值分析[J].临床研究,2020,17(7):56-59.
[11]袁婷婷,张锐锋,商巧雨.紫癜性肾炎患儿血清APN、CysC、OPN 和IgA1水平分析[J].临床输血与检验,2019,21(6):623-626.
[12]陈述枚,莫樱.过敏性紫癜肾炎的病因和发病机制[J].中国实用儿科杂志,2001,16(4):193-194.
[13]莫樱,陈述枚.紫癜性肾炎的发病机制与病理诊断[J].中国实用儿科杂志,2006,21(6):407-411.
[14]JEROTIC D, MATIC M, SUVAKOV S, et al. Association of Nrf2, SOD2 and GPX1 polymorphisms with biomarkers of oxidative distress and survival in endstage renal disease patients[J]. Toxins (Basel), 2019, 11(7):E431.
[15]STEVENS M, OLTEAN S. Modulation of VEGF-A alternative splicing as a novel treatment in chronic kidney disease[J]. Genes (Basel), 2018, 9(2):E98.
[16]TANG Z F, LI C W, KANG B X, et al. GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses[J]. Nucleic Acids Res, 2017, 45(W1):W98W102.