MicroRNAs (miRNAs) are small non-coding RNAs that regulate gene expression. Emerging evidence has suggested a role for miRNAs in the development of diabetic kidney disease (DKD), indicating that miRNAs may represent potential biomarkers of this disease. However, results are still inconclusive. Therefore, we performed a systematic review of the literature on the subject, followed by bioinformatic analysis. PubMed and EMBASE were searched to identify all studies that compared miRNA expressions between patients with DKD and diabetic patients without this complication or healthy subjects. MiRNA expressions were analyzed in kidney biopsies, urine/urinary exosomes or total blood/plasma/serum. MiRNAs consistently dysregulated in DKD patients were submitted to bioinformatic analysis to retrieve their putative target genes and identify potentially affected pathways under their regulation. As result, twenty-seven studies were included in the systematic review. Among 151 dysregulated miRNAs reported in these studies, 6 miRNAs were consistently dysregulated in DKD patients compared to controls: miR-21-5p, miR-29a-3p, miR-126-3p, miR-192-5p, miR-214-3p, and miR-342-3p. Bioinformatic analysis indicated that these 6 miRNAs are involved in pathways related to DKD pathogenesis, such as apoptosis, fibrosis, and extracellular matrix accumulation. In conclusion, six miRNAs seem to be dysregulated in patients with different stages of DKD, constituting potential biomarkers of this disease.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.mce.2018.06.005 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Enhanced O-glycosylation Site Prediction Using Explainable Machine Learning Technique with Spatial Local Environment.
Bioinformatics
January 2025
Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, United States.
Motivation: The accurate prediction of O-GlcNAcylation sites is crucial for understanding disease mechanisms and developing effective treatments. Previous machine learning models primarily relied on primary or secondary protein structural and related properties, which have limitations in capturing the spatial interactions of neighboring amino acids. This study introduces local environmental features as a novel approach that incorporates three-dimensional spatial information, significantly improving model performance by considering the spatial context around the target site.
View Article and Find Full Text PDFscHNTL: single-cell RNA-seq data clustering augmented by high-order neighbors and triplet loss.
Bioinformatics
January 2025
School of Computing and Artificial Intelligence, Southwest Jiaotong University, Sichuan 611756, China.
Motivation: The rapid development of single-cell RNA sequencing (scRNA-seq) has significantly advanced biomedical research. Clustering analysis, crucial for scRNA-seq data, faces challenges including data sparsity, high dimensionality, and variable gene expressions. Better low-dimensional embeddings for these complex data should maintain intrinsic information while making similar data close and dissimilar data distant.
View Article and Find Full Text PDFThe key role of the NUDT3 gene in lung adenocarcinoma progression and its association with the manganese ion metabolism family.
Discov Oncol
January 2025
School of Medicine, Anhui University of Science & Technology, Huainan, China.
Background: Lung adenocarcinoma is one of the most common malignant tumors worldwide. Its complex molecular mechanisms and high tumor heterogeneity pose significant challenges for clinical treatment. The manganese ion metabolism family plays a crucial role in various biological processes, and the abnormal expression of the NUDT3 gene in multiple cancers has drawn considerable attention.
View Article and Find Full Text PDFSHP2 promotes the epithelial-mesenchymal transition in triple negative breast cancer cells by regulating β-catenin.
J Cancer Res Clin Oncol
January 2025
Key Laboratory of Laboratory Medicine, Ministry of Education of China, School of Laboratory Medicine and Life Sciences, Wenzhou Medical University, Wenzhou, 325035, Zhejiang, China.
Purpose: Growing evidence suggests that the tyrosine phosphatase SHP2 is pivotal for tumor progression. Triple-negative breast cancer (TNBC) is the most lethal subtype of breast cancer, characterized by its high recurrence rate, aggressive metastasis, and resistance to chemotherapy. Understanding the mechanisms of tumorigenesis and the underlying molecular pathways in TNBC could aid in identifying new therapeutic targets.
View Article and Find Full Text PDFCharacterization of the host specificity of the SH3 cell wall binding domain of the staphylococcal phage 88 endolysin.
Arch Microbiol
January 2025
Department of Microbiology, Faculty of Biotechnology and Biomolecular Sciences, Universiti Putra Malaysia, Serdang, Selangor, 43400, Malaysia.
Bacteriophages produce endolysins at the end of the lytic cycle, which are crucial for lysing the host cells and releasing virion progeny. This lytic feature allows endolysins to act as effective antimicrobial alternatives when applied exogenously. Staphylococcal endolysins typically possess a modular structure with one or two enzymatically active N-terminal domains (EADs) and a C-terminal cell wall binding domain (CBD).
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!