Single-nucleotide Polymorphism rs17860041 A/C in the Promoter of the <i>PPIA</i> Gene is Associated with Susceptibility to Kawasaki Disease in Chinese Children

Shi, Ruting; Luo, Yeping; Li, Shentang; Kong, Min; Liu, Xin; Yu, Meng; Wu, Ji-Ping; Huang, Lihua; Yang, Zhangping

doi:10.1080/08820139.2020.1727919

Cited by 4 publications

(3 citation statements)

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“…Moreover, this enzyme has been shown to be a key molecule in multiple biological functions, including molecular chaperoning,protein folding,protein tra cking,immune modulation,and cell signaling [6]. Studies have also reported that PPIA is involved in several diseases, including kawasaki disease [7],amyotrophic lateral sclerosis [8],atherosclerosis,myocardial infarction [9],severe sepsis [10],vascular smooth muscle cell disease [11],rheumatoid arthritis and HIV infection [12].Moreover,several studies have shown that PPIA is expressed in some cancers,including lung cancer,nasopharyngeal carcinoma [13],gastric adenocarcinoma [14],thyroid carcinoma [15],neuroblastoma [16],ovarian cancer [17],pancreatic cancer [18],breast cancer,colorectal cancer [19][20],melanoma [21],liver hepatocellular carcinoma [22].Many researchers have assessed PPIA function in cancer.It has been suggested that PPIA plays an important role in the whole pathological process of cancer development.High expression levels of PPIA were associated with decreased overall survival in liver hepatocellular carcinoma,colorectal cancer,low-grade glioma, acute myeloid leukemia.However,in gastric adenocarcinoma, high expression levels of CypA are positively correlated with invasiveness and distant metastasis.Therefore,both low and high expression of PPIA are associated with tumor prognosis.…”

Section: Introductionmentioning

confidence: 99%

Identification Of PPIA As A Prognostic Biomarker Of Lung Adenocarcinoma From Bioinformatics Analysis

Chen

et al. 2022

Preprint

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Background: We aim to investigate the expression of the peptidylprolyl isomerase A (PPIA) gene in lung adenocarcinoma(LUAD),and to investigate the diagnostic, prognostic value and correlation with immune infiltrates of PPIA in LUAD.Methods: Transcriptional expression profiles of PPIA between LUAD tissues and normal tissues were downloaded from the Cancer Genome Atlas (TCGA).The PPIA protein expression was assessed by the Clinical Proteomic Tumor Analysis Consortium (CPTAC) .Receiver operating characteristic(ROC) curve was used to differentiate LUAD from adjacent normal tissues.Kaplan-Meier method was conducted to assess the effect of PPIA on survival.Protein-protein interaction (PPI) networks were constructed by the STRING.Functional enrichment analyses were performed using the“ClusterProfiler”package.The relationship between PPIA mRNA expression and immune infiltrates was determined by tumor immune estimation resource (TIMER) and tumor-immune system interaction database (TISIDB).Results: The expression of PPIA in LUAD tissues was significantly upregulated than those in adjacent normal tissues. High PPIA mRNA expression was associated with lymph node metastases and high TNM stage. The ROC curve analysis showed that PPIA had an AUC value of 0.804(95% CI: 0.764-0.843).Kaplan-Meier survival analysis showed LUAD patients with high-PPIA had a worse prognosis than those with low-PPIA(mOS: 42.2months VS 87.2months,P＜0.001). Correlation analysis indicated PPIA mRNA expression was correlated with immune infiltrates.PPIA expression had correlations with CD4+ T cell (r = -0.29, P = 5.51e-11),macrophage M1 (r = 0.106, P = 1.84e-02), and B cell (r = -0.181, P =5.40e-5).Conclusion: Our research showed that PPIA could be used as a prognostic biomarker.Up-regulation of PPIA expression is significantly related to poor prognosis and immune infiltration of LUAD and may be a potential therapeutic molecular target for LUAD patients.

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Section: Introductionmentioning

confidence: 99%

Identification Of PPIA As A Prognostic Biomarker Of Lung Adenocarcinoma From Bioinformatics Analysis

Chen

et al. 2022

Preprint

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“…Surveys of possible KD-associated genetic loci or expression profiles are ongoing. Previous studies have revealed the associations of KD susceptibility with polymorphism loci in genes of the oxidative stress signaling pathway ( 1 ), inflammatory processes ( 2 , 3 ), cell adhesion molecules ( 4 ), and microRNAs ( 5 ).…”

Section: Introductionmentioning

confidence: 99%

Association of miR-181c/d gene locus rs8108402 C/T polymorphism with susceptibility to Kawasaki disease in Chinese children

Yao

Yang

et al. 2022

Front. Pediatr.

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BackgroundKawasaki disease (KD) is an acute systemic vasculitis of unknown etiology. The rs8108402 C/T single nucleotide polymorphism (SNP) is located in the promoter region of miR-181-c/d gene and the intron of Nanos3 gene. The miR-181 family contributes to the pathogenesis of cardiovascular and inflammatory disorders, while Nanos3 is involved in DNA transcription regulation and cell proliferation. However, no studies have examined the association between miR-181c/d and Nanos3 polymorphisms and the susceptibility and progression of KD.ObjectiveThe purpose of our study is to examine the association of miR-181c/miR-181d/Nanos3 gene locus rs8108402 C/T polymorphism with KD susceptibility, intravenous immunoglobulin (IVIG) responsiveness, and the development of coronary artery lesions (CAL).MethodsPeripheral blood specimens from 100 children with KD and 100 healthy children were collected. The polymorphism of rs8108402 C/T was detected using polymerase chain reaction-sequencing-based typing technique.ResultsThere were statistically significant differences in C and T allele frequency distributions between the KD group and healthy controls for the polymorphic site rs8108402 C/T (P = 0.002). The distribution of the genotypes CC, CT, and TT also presented statistical significant difference between the KD and control groups (P = 0.003). Compared to the rs8108402 C allele, the T allele was associated with increased KD susceptibility (OR = 2.080, 95% CI = 1.317∼3.283). However, there were no significant associations discovered between the rs8108402 C/T polymorphism and CAL formation or IVIG unresponsiveness in the study.ConclusionSNP rs8108402 C/T located in the miR-181c/d promoter and Nanos3 intronic region is associated with susceptibility to Kawasaki disease but not with the development of coronary artery lesions or IVIG unresponsiveness in Chinese children.

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“…Recent studies have shown that both pro-inflammatory and regulatory T cells in the blood play critical roles in regulating the severity and susceptibility to KD [14,15]. Although many single nucleotide polymorphisms associated with KD are homologous in other inflammatory diseases such as rheumatoid arthritis, ulcerative colitis, and systemic habitual lupus erythematosus, the exact molecular mechanism underlying KD has not been elucidated [16][17][18].…”

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confidence: 99%

Diagnostic model based on bioinformatics and machine learning to distinguish Kawasaki disease using multiple datasets

Zhang

Zhuo

2022

BMC Pediatr

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Background Kawasaki disease (KD), characterized by systemic vasculitis, is the leading cause of acquired heart disease in children. Herein, we developed a diagnostic model, with some prognosis ability, to help distinguish children with KD. Methods Gene expression datasets were downloaded from Gene Expression Omnibus (GEO), and gene sets with a potential pathogenic mechanism in KD were identified using differential expressed gene (DEG) screening, pathway enrichment analysis, random forest (RF) screening, and artificial neural network (ANN) construction. Results We extracted 2,017 DEGs (1,130 with upregulated and 887 with downregulated expression) from GEO. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that the DEGs were significantly enriched in innate/adaptive immune response-related processes. Subsequently, the results of weighted gene co-expression network analysis and DEG screening were combined and, using RF and ANN, a model with eight genes (VPS9D1, CACNA1E, SH3GLB1, RAB32, ADM, GYG1, PGS1, and HIST2H2AC) was constructed. Classification results of the new model for KD diagnosis showed excellent performance for different datasets, including those of patients with KD, convalescents, and healthy individuals, with area under the curve values of 1, 0.945, and 0.95, respectively. Conclusions We used machine learning methods to construct and validate a diagnostic model using multiple bioinformatic datasets, and identified molecules expected to serve as new biomarkers for or therapeutic targets in KD.

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Single-nucleotide Polymorphism rs17860041 A/C in the Promoter of the PPIA Gene is Associated with Susceptibility to Kawasaki Disease in Chinese Children

Cited by 4 publications

References 36 publications

Identification Of PPIA As A Prognostic Biomarker Of Lung Adenocarcinoma From Bioinformatics Analysis

Identification Of PPIA As A Prognostic Biomarker Of Lung Adenocarcinoma From Bioinformatics Analysis

Association of miR-181c/d gene locus rs8108402 C/T polymorphism with susceptibility to Kawasaki disease in Chinese children

Diagnostic model based on bioinformatics and machine learning to distinguish Kawasaki disease using multiple datasets

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