Analysis Of Weighted Gene Co-Expression Network In Diabetic Kidney Disease

Background:Diabetic kidney disease(DKD)is one of the most common microvascular complication of diabetes mellitus and has become the leading cause of chronic kidney disease in China.However,due to the complex pathogenesis and rapid progress of DKD,the current research on DKD is still lack of breakthrough progress.The pathogenesis of DKD,novel biomarkers that can reflect disease progression and new therapeutic targets have always been the hotspots and difficulties in the field of kidney disease.With the continuous development of gene sequencing technology,research methods are also more flexible and varied.Genomics,gene microarray chip data and single-cell sequencing technology make it possible to obtain massive gene sequencing data in a short time.The information contained in these data can help us better explore the development of existing research fields.Weighted gene co-expression network analysis(WGCNA)is an efficient and accurate bioinformatics analysis method,which can be used for comprehensive and effective data mining.In this study,the WGCNA analysis was used to analyze the DKD expression profile data,to find the key modules related to the clinical characteristics of DKD,and to further discuss its functions.Moreover,the expression of the hub gene in DKD and its correlation with clinical indicators were verified to provide experimental evidence for in-depth exploration of the mechanism of DKD,with a view to providing new ideas and clues for the treatment of DKD.Method:1.In this study,the GSE96804 dataset was obtained from the GEO public database.A total of 41 samples from DKD patients and 20 samples from the control group were selected as the research objects.Weighted gene co-expression network analysis(WGCNA)was used to construct the network to find DKD-related modules.The differentially expressed genes between the DKD group and the control group were analyzed using the Limma package of R language.The differentially expressed genes were intersected with the DKD-related modules obtained by the WGCNA method to obtain the hub genes,and the GO and KEGG enrichment analysis was performed.2.A total of 34 human peripheral blood samples were collected from December 2019 to December 2020 to the First Affiliated Hospital of Zhengzhou University,including 12 cases in the DKD group,11 cases in the diabetes group,and 11 cases in the healthy control group.Real-time qPCR analysis was used to verify the expression of NPIPA2 and ANKRD36 in each group,and the relative expression abundance was expressed by calculating the 2-△△CT value.GAPDH was used as internal control.3.The first examination results of selected patients were collected.Clinical indicators include:urine albumin/creatinine ratio(ACR),hemoglobin(Hb),serum creatinine(Scr),albumin(ALB),triglycerides(TG),total cholesterol(TC),low-density lipoprotein cholesterol(LDL-C),high-density lipoprotein cholesterol(HDL-C),glomerular filtration rate(eGFR),glycosylated hemoglobin(HbAlc).Correlation analysis between the clinical data and the relative expression of the corresponding sample is performed to identify clinical indicators that are significantly related to the hub gene,and further explore the mechanism.Result:1.Differential expression analysis results:According to the screening threshold,a total of 418 significantly differentially expressed genes were obtained,of which 123 genes were up-regulated and 295 genes were down-regulated in DKD group compared with the control group.2.WGCNA analysis results:A total of 15 gene modules were identified by WGCNA analysis,of which the green module was most significantly associated with diabetic kidney disease.The genes in this module are mainly enriched in sugar and lipid metabolism,regulation of small GTPase mediated signal transduction,adenylate cyclase-activating G-protein coupled receptor signaling pathway,regulation of Rho protein signal transduction,PPAR signaling pathway,oxidoreductase activity.3.Hub genes selection:The intersection of the two methods produced 14 hub genes,which were(ANKRD36、ANKRD36B、ANKRD36C),(NPIPA2、NPIPB3、NPIPB4、NPIPB5、NPIPB11、NPIPB13),(SPDYE1、SPDYE3),TAS2R31,GOLGA8A,LINC00342.4.qRT-PCR analysis results:The relative expression of NPIPA2 was significantly increased in diabetic kidney disease and diabetic patients,and was positively correlated with urinary albumin/creatinine ratio(ACR)and serum creatinine(SCR)(P<0.05),and negatively correlated with albumin(ALB)and hemoglobin(HB)(P<0.05).5.qRT-PCR analysis results:The relative expression of ANKRD36 was significantly increased in patients with diabetic kidney disease,and the correlation with urinary albumin/creatinine ratio(ACR),serum creatinine(SCR),albumin(ALB)and hemoglobin(HB)was consistent with NPIPA2,but not statistically significant.It was positively correlated with triglyceride(TG)and blood white blood cell(WBC).Conclusion:1.The genes in the module significantly related to DKD are mainly enriched in sugar and lipid metabolism,regulation of small GTPase mediated signal transduction,regulation of Rho protein signal transduction,adenylate cyclase-activating G-protein coupled receptor signaling pathway,PPAR signaling pathway,oxidoreductase activity.2.NPIPA2 and ANKRD36 are highly expressed in DKD,and NPIPA2 is closely related to the condition of DKD,which provides an experimental basis for further exploring the mechanism of DKD.