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Five-gene signature predicts acute kidney injury in early kidney transplant patients.

ABSTRACT: Patients with acute kidney injury (AKI) show high morbidity and mortality, and a lack of effective biomarkers increases difficulty in its early detection. Weighted gene co-expression network analysis (WGCNA) detected a total of 22 gene modules and 6 miRNA modules, of which 4 gene modules and 3 miRNA modules were phenotypically co-related. Functional analysis revealed that these modules were related to different molecular pathways, which mainly involved PI3K-Akt signaling pathway and ECM-receptor interaction. The brown modules related to transplantation mainly involved immune-related pathways. Finally, five genes with the highest AUC were used to establish a diagnosis and prediction model of AKI. The model showed a high area under curve (AUC) in the training set and validation set, and their prediction accuracy for AKI was as high as 100%. Similarly, the prediction accuracy of AKI after 24 h in the 0 h transplant sample was 100%. This study may provide new features for the diagnosis and prediction of AKI after kidney transplantation, and facilitate the diagnosis and drug development of AKI in kidney transplant patients.

SUBMITTER: Zhai X

PROVIDER: S-EPMC9004575 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Five-gene signature predicts acute kidney injury in early kidney transplant patients.

Zhai Xia X Lou Hongqiang H Hu Jing J

Aging 20220323 6

Patients with acute kidney injury (AKI) show high morbidity and mortality, and a lack of effective biomarkers increases difficulty in its early detection. Weighted gene co-expression network analysis (WGCNA) detected a total of 22 gene modules and 6 miRNA modules, of which 4 gene modules and 3 miRNA modules were phenotypically co-related. Functional analysis revealed that these modules were related to different molecular pathways, which mainly involved PI3K-Akt signaling pathway and ECM-receptor ...[more]

PMID: 35320116

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Project description:Hepatocellular carcinoma (HCC) is one of the most common public health challenges, worldwide. Because of molecular complexity and tumor heterogeneity, there are no effective predictive models for prognosis of HCC. This underlines the unmet need for accurate prognostic models for HCC. Analysis of GSE14520 data from gene omnibus (GEO) database identified multiple differentially expressed mRNAs (DEMs) between HCC and normal tissues. After randomly stratifying the patients into the training and testing groups, we performed univariate, lasso, and multivariable Cox regression analyses to delineate the prognostic gene signature in training set. We then used Kaplan-Meier plot, time-dependent receiver operating characteristic (ROC), multivariable Cox regression analysis of clinical information, nomogram, and decision curve analysis (DCA) to evaluate the predictive and overall survival value of a novel five-gene signature (CNIH4, SOX4, SPP1, SORBS2, and CCL19) within and across sets, separately and combined. We also validated the prognostic value of the five-gene signature using The Cancer Genome Atlas-Liver Hepatocellular Carcinoma (TCGA-LIHC), GSE54236 and International Cancer Genome Consortium (ICGC) sets. Multivariable Cox regression analysis revealed that the five-gene signature and tumor node metastasis (TNM) stage were independent prognostic factors for overall survival of HCC patients in GSE14520 and TCGA-LIHC. Combining TNM stage clinical pathological parameters and nomogram greatly improved the prognosis prediction of HCC. Further gene set enrichment analysis (GSEA) revealed enrichment of KEGG pathways related to cell cycle in the high-risk group and histidine metabolism in the low-risk group. Finally, all these five mRNAs are overexpressed between 12 pairs of HCC and adjacent normal tissues by quantitative real-time PCR validation. In brief, a five-gene prognostic signature and a nomogram were identified and constructed, respectively, and further validated for their HCC prognostic value. The five-gene risk score together with TNM stage models could aid in rationalizing customized therapies in HCC patients.

Project description:ObjectivesAcute kidney injury is a frequent complication of cardiac surgery and increases morbidity and mortality. As preoperative biomarkers predicting the development of acute kidney injury are not available, we have tested the hypothesis that preoperative plasma levels of endogenous ouabain may function as this type of biomarker.Rationale and designEndogenous ouabain is an adrenal stress hormone associated with adverse cardiovascular outcomes. Its involvement in acute kidney injury is unknown. With studies in patients and animal settings, including isolated podocytes, we tested the above mentioned hypothesis.PatientsPreoperative endogenous ouabain was measured in 407 patients admitted for elective cardiac surgery and in a validation population of 219 other patients. We also studied the effect of prolonged elevations of circulating exogenous ouabain on renal parameters in rats and the influence of ouabain on podocyte proteins both "in vivo" and "in vitro."Main resultsIn the first group of patients, acute kidney injury (2.8%, 8.3%, 20.3%, p < 0.001) and ICU stay (1.4±0.38, 1.7±0.41, 2.4±0.59 days, p = 0.014) increased with each incremental preoperative endogenous ouabain tertile. In a linear regression analysis, the circulating endogenous ouabain value before surgery was the strongest predictor of acute kidney injury. In the validation cohort, acute kidney injury (0%, 5.9%, 8.2%, p < 0.0001) and ICU stay (1.2±0.09, 1.4±0.23, 2.2±0.77 days, p = 0.003) increased with the preoperative endogenous ouabain tertile. Values for preoperative endogenous ouabain significantly improved (area under curve: 0.85) risk prediction over the clinical score alone as measured by integrate discrimination improvement and net reclassification improvement. Finally, in the rat model, elevated circulating ouabain reduced creatinine clearance (-18%, p < 0.05), increased urinary protein excretion (+ 54%, p < 0.05), and reduced expression of podocyte nephrin (-29%, p < 0.01). This last finding was replicated ex vivo by incubating podocyte primary cell cultures with low-dose ouabain.ConclusionsPreoperative plasma endogenous ouabain levels are powerful biomarkers of acute kidney injury and postoperative complications and may be a direct cause of podocyte damage.

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Five-gene signature predicts acute kidney injury in early kidney transplant patients.

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Five-gene signature predicts acute kidney injury in early kidney transplant patients.

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