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

Na Du; Dan Dong; Luyao Sun; Lihe Che; Xiaohua Li; Yong Liu; Bin Wang

doi:10.1186/s40001-021-00613-8

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

Eur J Med Res. 2021 Dec 9;26(1):142. doi: 10.1186/s40001-021-00613-8.

Authors

Na Du¹, Dan Dong², Luyao Sun¹, Lihe Che¹, Xiaohua Li¹, Yong Liu^#³, Bin Wang^#⁴

Affiliations

¹ Infectious Diseases Department, The First Hospital of Jilin University, No.1 Xinmin Street, Changchun, 130021, Jilin, China.
² Department of Obstetrics and Gynecology, The First Hospital of Jilin University, No.1 Xinmin Street, Changchun, 130021, Jilin, China.
³ Genetic Diagnosis Center, The First Hospital of Jilin University, No.1 Xinmin Street, Changchun, 130021, Jilin, China. liuyong0228@jlu.edu.cn.
⁴ Infectious Diseases Department, The First Hospital of Jilin University, No.1 Xinmin Street, Changchun, 130021, Jilin, China. wangbinlucky2018@jlu.edu.cn.

^# Contributed equally.

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.

Keywords: ACOT13; Gene mutations; PTGER2; Polycystic kidney disease; Whole exome sequencing.

MeSH terms

Exome Sequencing / methods*
Female
Gene Expression Regulation*
Humans
Male
Pedigree
Polycystic Kidney, Autosomal Dominant / diagnosis
Polycystic Kidney, Autosomal Dominant / genetics*
Polycystic Kidney, Autosomal Dominant / metabolism
RNA / genetics*
Receptors, Prostaglandin E, EP2 Subtype / biosynthesis
Receptors, Prostaglandin E, EP2 Subtype / genetics*
Thiolester Hydrolases / biosynthesis
Thiolester Hydrolases / genetics*
Tomography, X-Ray Computed

Substances

PTGER2 protein, human
Receptors, Prostaglandin E, EP2 Subtype
RNA
ACOT13 protein, human
Thiolester Hydrolases