Systems biology of autosomal dominant polycystic kidney disease (ADPKD): computational identification of gene expression pathways and integrated regulatory networks

Background and Objectives: Cyst pressure induces renin-angiotensin-aldosterone system activation and kidney hypoxia in autosomal dominant polycystic kidney disease (ADPKD). Lipopolysaccharide-induced Toll-like receptor activation causes metabolic disturbances that are triggered by increased succinate levels and hypoxia inducible factors, which results in inflammation via IL-1β activation. Since we aimed to investigate the role of both inflammation and hypoxia in the clinical course of ADPKD, via succinate levels from sera samples, HIF-1α gene expression from whole blood and urine samples and IL-1βgene expression from whole blood were measured. Methods: One hundred ADPKD patients and 100 matched healthy controls were enrolled to this cross-sectional study. Twenty-four-hour ambulatory blood pressure monitoring was conducted in all participants. Blood, serum, and urine samples were taken after 12-h fasting for the measurement of biochemical parameters and succinate levels. Whole blood and urine samples were used for HIF-1α and IL-1β geneexpression by using quantitative real-time PCR. Results: There were significant differences in whole blood HIF-1α, IL-1β geneexpression, and serumsuccinate levels between the ADPKD patients and the control subjects. Whole blood HIF-1αgene expression, IL-1β geneexpression, and serumsuccinate levels were also significantly different in ADPKD patients with hypertension in comparison with normotensive ones (p < 0.05). Serum succinate levels and blood IL-1β geneexpression were increased in ADPKD patients with high levels of HIF-1α geneexpression (p = 0.018 and p = 0.029, respectively). Conclusions: Increased age,low eGFR, and HIF-1α and IL-1β geneexpressions were also independently associated with hypertension in ADPKD patients. Inflammation and hypoxia are both relevant factors that might be associated with hypertension in ADPKD.

Download Full-text

Novel splicing and missense mutations in autosomal dominant polycystic kidney disease 1 (PKD1) gene: Expression of mutated genes

Human Mutation ◽

10.1002/1098-1004(200011)16:5<444::aid-humu11>3.0.co;2-c ◽

2000 ◽

Vol 16 (5) ◽

pp. 444-445 ◽

Cited By ~ 8

Author(s):

Gianluca Aguiari ◽

Simone Savelli ◽

Monica Garbo ◽

Angela Bozza ◽

Giuseppina Augello ◽

...

Keyword(s):

Gene Expression ◽

Kidney Disease ◽

Polycystic Kidney Disease ◽

Autosomal Dominant ◽

Missense Mutations ◽

Polycystic Kidney ◽

Pkd1 Gene ◽

Autosomal Dominant Polycystic Kidney

Download Full-text

Identification of ACOT13 and PTGER2 as novel candidate genes of autosomal dominant polycystic kidney disease through whole exome sequencing

European Journal of Medical Research ◽

10.1186/s40001-021-00613-8 ◽

2021 ◽

Vol 26 (1) ◽

Author(s):

Na Du ◽

Dan Dong ◽

Luyao Sun ◽

Lihe Che ◽

Xiaohua Li ◽

...

Keyword(s):

Gene Expression ◽

Kidney Disease ◽

Exome Sequencing ◽

Polycystic Kidney Disease ◽

Whole Exome Sequencing ◽

Autosomal Dominant ◽

R Package ◽

Polycystic Kidney ◽

Whole Exome ◽

Autosomal Dominant Polycystic Kidney

Abstract Background Autosomal dominant polycystic kidney disease (ADPKD) is the most common monogenic kidney disorder. Half of the patients would slowly progress to end-stage renal disease. However, the potential target for ADPKD treatment is still lacking. Methods Four ADPKD patients and two healthy family members were included in this study. The peripheral blood samples were obtained and tested by the whole exome sequencing (WES). The autosomal mutations in ADPKD patients were retained as candidate sites. The Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment, and protein–protein interaction network (PPI) analyses were performed by clusterProfiler R package. A dataset containing 18 ADPKD patients and three normal samples were downloaded from the Gene Expression Omnibus (GEO) database and analyzed using the limma R package. Results A total of six mutant genes were identified based on the dominant genetic pattern and most of them had not been reported to be associated with ADPKD. Furthermore, 19 harmful genes were selected according to the harmfulness of mutation. GO and KEGG enrichment analyses showed that the processes of single-organism cellular process, response to stimulus, plasma membrane, cell periphery, and anion binding as well as cyclic adenosine monophosphate (cAMP) signaling pathway and pathways in cancer were significantly enriched. Through integrating PPI and gene expression analyses, acyl-CoA thioesterase 13 (ACOT13), which has not been reported to be related to ADPKD, and prostaglandin E receptor 2 (PTGER2) were identified as potential genes associated with ADPKD. Conclusions Through combination of WES, gene expression, and PPI network analyses, we identified ACOT13 and PTGER2 as potential ADPKD-related genes.

Download Full-text