Multiple‐microarray analysis for identification of hub genes involved in tubulointerstial injury in diabetic nephropathy

Mi, Zeng; Liu, Jialu; Yang, Wenxia; Zhang, Shumin; Liu, Fuyou; Dong, Zheng; Peng, Yong; Sun, Lin; Xiao, Li

doi:10.1002/jcp.28313

Cited by 42 publications

(34 citation statements)

References 86 publications

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“…KNG1 is a regulator of blood coagulation and belongs to the kinin‐kallikrein system. It has been reported that the activation of KNG1 plays a role in bacterial infections . Kerishnan et al.…”

Section: Discussionmentioning

confidence: 99%

Identification of New Peptide Biomarkers for Bacterial Bloodstream Infection

Wen

Kong

et al. 2019

Proteomics Clinical Apps

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Purpose Due to a lack of effective early diagnostic measures, new diagnostic methods for bacterial bloodstream infections (BSIs) are urgently needed. A protein–peptide profiling approach can be used to identify novel diagnostic biomarkers of BSIs. Experimental design In this study, MALDI‐TOF MS and nano‐LC/ESI‐MS/MS are used to analyze serum peptides. In addition, GO and network analyses are conducted as a means of analyzing these potential protein markers. Finally, the potential biomarkers are verified in independent clinical samples via ELISA. Results m/z 1533.8, 2794.3, 3597.3, 5007.3, and 7816.7 reveal an identical trend; the intensity of m/z 1533.8, 2794.3, and 3597.3 are higher in the infection group relative to controls, whereas the intensity of m/z 5007.3 and 7816.7 are lower in the infection group. Four peaks are successfully identified including ITIH4, KNG1, SAA2, and C3. GO and network analyses find these proteins to form an interaction network, which may be correlated with BSI. ELISA results indicate that ITIH4, KNG1, and SAA2 are effective in differentiating infected from normal control group and the febrile group. Conclusions and clinical relevance These biomarkers have the potential to offer new insights into the signaling networks underlying the development and progression of BSI.

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Section: Discussionmentioning

confidence: 99%

Identification of New Peptide Biomarkers for Bacterial Bloodstream Infection

Wen

Kong

et al. 2019

Proteomics Clinical Apps

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“…16 For instance, folate-modified nanoparticle delivery of CCL19 activates the immune system by acting as a tumour suppressor in colon tumour. 17 Zeng et al 18 revealed that CCL19 may be involved in diabetic tubulointerstitial injury. Although the upregulation of CCL19 has been discovered in DN, the role of CCL19 in DN remains elusive.…”

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confidence: 99%

MiR‐325‐3p inhibits renal inflammation and fibrosis by targeting CCL19 in diabetic nephropathy

Sun

Wang

et al. 2020

Clin Exp Pharma Physio

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Diabetic nephropathy (DN) is the primary cause of end-stage renal disease, 1 and causes cardiovascular mortalities for patients with obesity or diabetes. 2 The typical structural characteristics of DN are thickening of tubular basement membranes and glomerular hypertrophy resulting from the aberrant deposition of the extracellular matrix (ECM) in the kidneys. 3 Additionally, renal dysfunction caused by DN is closely related to ECM deposition in glomerular mesangium and tubulointerstitium. 4 Tubulointerstitial fibrosis and glomerulosclerosis are the key factors of DN. 5,6 Unfortunately, effective therapeutic methods for DN have not been discovered, thus, further exploration of the molecular mechanisms in the pathophysiology of DN is in urgent need. MicroRNAs (miRNAs) are a category of non-coding RNA (ncRNA) molecules with 20-24 nucleotides in length. 7 Dysregulation of miR-NAs has been reported to regulate several biological process during the progression of DN. 8,9 In detail, miRNA-23a/27a attenuates renal fibrosis through muscle-kidney crosstalk in streptozotocin-induced diabetic mice. 10 Furthermore, miR-21 promotes renal tubular extracellular matrix (ECM) synthesis and accumulation to aggravate renal fibrosis in DN. 11 Most recently, miR-325-3p was confirmed to get involved in immobilization-induced suppression of luteinizing hormone translation and secretion. 12 Besides, miR-325-3p suppresses

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“…To further explore the function of the DEGs in AR, we used the database for Annotation, Visualization, and Integrated Discovery (DAVID) 4 to perform the GO and KEGG pathway analyses (Ogata et al, 1999;Ashburner et al, 2000). DAVID is an online bioinformatics database that is commonly used to generate systematic functional annotations about genes and proteins (Zeng et al, 2019). GO analysis consists of molecular function (MF), cellular component (CC), and biological processes (BP) analyses.…”

Section: Functional Enrichment Analysismentioning

confidence: 99%

Hub Genes Identification in a Murine Model of Allergic Rhinitis Based on Bioinformatics Analysis

Shi

et al. 2020

Front. Genet.

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This study aimed to identify allergic rhinitis (AR)-related hub genes and functionally enriched pathways in a murine model. Dataset GSE52804 (including three normal controls and three AR mice) was downloaded from Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified. Gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and protein-protein interaction (PPI) analyses of DEGs were performed to identify the hub genes in AR. The DEGs were classified into different modules by using the weighted gene co-expression network analysis (WGCNA). Moreover, to verify the potential hub genes, nasal mucosa tissues were obtained from murine AR models (n = 5) and controls (n = 5), and qRT-PCR and Western blot were performed. In this study, a total of 634 DEGs were identified. They were significantly enriched in 14 GO terms, such as integral component of membrane, plasma membrane, and G-protein-coupled receptor signaling pathway. Meanwhile, there were eight terms of KEGG pathways significantly enriched, such as Olfactory transduction, Cytokine-cytokine receptor interaction, and TNF signaling pathway. The top 10 hub genes (Rtp1,

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Multiple‐microarray analysis for identification of hub genes involved in tubulointerstial injury in diabetic nephropathy

Cited by 42 publications

References 86 publications

Identification of New Peptide Biomarkers for Bacterial Bloodstream Infection

Identification of New Peptide Biomarkers for Bacterial Bloodstream Infection

MiR‐325‐3p inhibits renal inflammation and fibrosis by targeting CCL19 in diabetic nephropathy

Hub Genes Identification in a Murine Model of Allergic Rhinitis Based on Bioinformatics Analysis

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