PUBLICATION
Identification of Key Genes and Candidated Pathways in Human Autosomal Dominant Polycystic Kidney Disease by Bioinformatics Analysis
- Authors
- Liu, D., Huo, Y., Chen, S., Xu, D., Yang, B., Xue, C., Fu, L., Bu, L., Song, S., Mei, C.
- ID
- ZDB-PUB-200130-15
- Date
- 2019
- Source
- Kidney & blood pressure research 44: 533-552 (Journal)
- Registered Authors
- Keywords
- Autosomal dominant polycystic kidney disease, Bioinformatics analysis, Key genes, Metabolic pathways
- MeSH Terms
-
- Animals
- Case-Control Studies
- Computational Biology/methods*
- Datasets as Topic
- Decorin/genetics
- Gene Expression Profiling
- Gene Expression Regulation
- Humans
- Metabolic Networks and Pathways
- Mice
- Microarray Analysis
- Polycystic Kidney, Autosomal Dominant/genetics*
- Polycystic Kidney, Autosomal Dominant/metabolism
- Zebrafish
- PubMed
- 31330507 Full text @ Kidney Blood Press. Res.
Citation
Liu, D., Huo, Y., Chen, S., Xu, D., Yang, B., Xue, C., Fu, L., Bu, L., Song, S., Mei, C. (2019) Identification of Key Genes and Candidated Pathways in Human Autosomal Dominant Polycystic Kidney Disease by Bioinformatics Analysis. Kidney & blood pressure research. 44:533-552.
Abstract
Background/aims Autosomal dominant polycystic kidney disease (ADPKD) is the most common genetic form of kidney disease. High-throughput microarray analysis has been applied for elucidating key genes and pathways associated with ADPKD. Most genetic profiling data from ADPKD patients have been uploaded to public databases but not thoroughly analyzed. This study integrated 2 human microarray profile datasets to elucidate the potential pathways and protein-protein interactions (PPIs) involved in ADPKD via bioinformatics analysis in order to identify possible therapeutic targets.
Methods The kidney tissue microarray data of ADPKD patients and normal individuals were searched and obtained from NCBI Gene Expression Omnibus. Differentially expressed genes (DEGs) were identified, and enriched pathways and central node genes were elucidated using related websites and software according to bioinformatics analysis protocols. Seven DEGs were validated between polycystic kidney disease and control kidney samples by quantitative real-time polymerase chain reaction.
Results Two original human microarray datasets, GSE7869 and GSE35831, were integrated and thoroughly analyzed. In total, 6,422 and 1,152 DEGs were extracted from GSE7869 and GSE35831, respectively, and of these, 561 DEGs were consistent between the databases (291 upregulated genes and 270 downregulated genes). From 421 nodes, 34 central node genes were obtained from a PPI network complex of DEGs. Two significant modules were selected from the PPI network complex by using Cytotype MCODE. Most of the identified genes are involved in protein binding, extracellular region or space, platelet degranulation, mitochondrion, and metabolic pathways.
Conclusions The DEGs and related enriched pathways in ADPKD identified through this integrated bioinformatics analysis provide insights into the molecular mechanisms of ADPKD and potential therapeutic strategies. Specifically, abnormal decorin expression in different stages of ADPKD may represent a new therapeutic target in ADPKD, and regulation of metabolism and mitochondrial function in ADPKD may become a focus of future research.
Genes / Markers
Expression
Phenotype
Mutations / Transgenics
Human Disease / Model
Sequence Targeting Reagents
Fish
Orthology
Engineered Foreign Genes
Mapping