Top

European Journal of Medical Research

Published in:

Open Access 01-12-2021 | Polycystic Kidney Disease | Research

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

Authors: Na Du, Dan Dong, Luyao Sun, Lihe Che, Xiaohua Li, Yong Liu, Bin Wang

Published in: European Journal of Medical Research | Issue 1/2021

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.

Available only for authorised users

Bergmann C, Guay-Woodford LM, Harris PC, Horie S, Peters DJM, Torres VE. Polycystic kidney disease. Nat Rev Dis Primers. 2018;4(1):50. https://doi.org/10.1038/s41572-018-0047-y.CrossRefPubMedPubMedCentral

Grieben M, Pike AC, Shintre CA, Venturi E, El-Ajouz S, Tessitore A, Shrestha L, Mukhopadhyay S, Mahajan P, Chalk R, et al. Structure of the polycystic kidney disease TRP channel Polycystin-2 (PC2). Nat Struct Mol Biol. 2017;24(2):114–22. https://doi.org/10.1038/nsmb.3343.CrossRefPubMed

Chumley P, Zhou J, Mrug S, Chacko B, Parant JM, Challa AK, Wilson LS, Berryhill TF, Barnes S, Kesterson RA, et al. Truncating PKHD1 and PKD2 mutations alter energy metabolism. Am J Physiol Renal Physiol. 2019;316(3):F414–25. https://doi.org/10.1152/ajprenal.00167.2018.CrossRefPubMed

Kim DY, Park JH. Genetic mechanisms of ADPKD. Adv Exp Med Biol. 2016;933:13–22. https://doi.org/10.1007/978-981-10-2041-4_2.CrossRefPubMed

Cornec-Le GE, Olson RJ, Besse W, Heyer CM, Gainullin VG, Smith JM, Audrezet MP, Hopp K, Porath B, Shi B, et al. Monoallelic mutations to DNAJB11 cause atypical autosomal-dominant polycystic kidney disease. Am J Hum Genet. 2018;102(5):832–44. https://doi.org/10.1016/j.ajhg.2018.03.013.CrossRef

Padovano V, Podrini C, Boletta A, Caplan MJ. Metabolism and mitochondria in polycystic kidney disease research and therapy. Nat Rev Nephrol. 2018;14(11):678–87. https://doi.org/10.1038/s41581-018-0051-1.CrossRefPubMed

Bergmann C. Recent advances in the molecular diagnosis of polycystic kidney disease. Expert Rev Mol Diagn. 2017;17(12):1037–54. https://doi.org/10.1080/14737159.2017.1386099.CrossRefPubMed

Yang Y, Muzny DM, Xia F, Niu Z, Person R, Ding Y, Ward P, Braxton A, Wang M, Buhay C, et al. Molecular findings among patients referred for clinical whole-exome sequencing. JAMA. 2014;312(18):1870–9. https://doi.org/10.1001/jama.2014.14601.CrossRefPubMedPubMedCentral

Mallawaarachchi AC, Hort Y, Cowley MJ, McCabe MJ, Minoche A, Dinger ME, Shine J, Furlong TJ. Whole-genome sequencing overcomes pseudogene homology to diagnose autosomal dominant polycystic kidney disease. Eur J Hum Genet. 2016;24(11):1584–90. https://doi.org/10.1038/ejhg.2016.48.CrossRefPubMedPubMedCentral

10.

Braun DA, Schueler M, Halbritter J, Gee HY, Porath JD, Lawson JA, Airik R, Shril S, Allen SJ, Stein D, et al. Whole exome sequencing identifies causative mutations in the majority of consanguineous or familial cases with childhood-onset increased renal echogenicity. Kidney Int. 2016;89(2):468–75. https://doi.org/10.1038/ki.2015.317.CrossRefPubMedPubMedCentral

11.

Chen S, Zhou Y, Chen Y, Gu J. fastp: an ultra-fast all-in-one FASTQ preprocessor. Bioinformatics. 2018;34(17):i884–90. https://doi.org/10.1093/bioinformatics/bty560.CrossRefPubMedPubMedCentral

12.

Kumar P, Henikoff S, Ng PC. Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm. Nat Protoc. 2009;4(7):1073–81. https://doi.org/10.1038/nprot.2009.86.CrossRefPubMed

13.

Flanagan SE, Patch AM, Ellard S. Using SIFT and PolyPhen to predict loss-of-function and gain-of-function mutations. Genet Test Mol Biomarkers. 2010;14(4):533–7. https://doi.org/10.1089/gtmb.2010.0036.CrossRefPubMed

14.

Schwarz JM, Rodelsperger C, Schuelke M, Seelow D. MutationTaster evaluates disease-causing potential of sequence alterations. Nat Methods. 2010;7(8):575–6. https://doi.org/10.1038/nmeth0810-575.CrossRefPubMed

15.

Itan Y, Shang L, Boisson B, Ciancanelli MJ, Markle JG, Martinez-Barricarte R, Scott E, Shah I, Stenson PD, Gleeson J, et al. The mutation significance cutoff: gene-level thresholds for variant predictions. Nat Methods. 2016;13(2):109–10. https://doi.org/10.1038/nmeth.3739.CrossRefPubMedPubMedCentral

16.

Liu X, Wu C, Li C, Boerwinkle E. dbNSFP v3.0: a one-stop database of functional predictions and annotations for human nonsynonymous and splice-site SNVs. Hum Mutat. 2016;37(3):235–41. https://doi.org/10.1002/humu.22932.CrossRefPubMedPubMedCentral

17.

Yu G, Wang LG, Han Y, He QY. clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS. 2012;16(5):284–7. https://doi.org/10.1089/omi.2011.0118.CrossRefPubMedPubMedCentral

18.

Song X, Di Giovanni V, He N, Wang K, Ingram A, Rosenblum ND, Pei Y. Systems biology of autosomal dominant polycystic kidney disease (ADPKD): computational identification of gene expression pathways and integrated regulatory networks. Hum Mol Genet. 2009;18(13):2328–43. https://doi.org/10.1093/hmg/ddp165.CrossRefPubMed

19.

Law CW, Alhamdoosh M, Su S, Dong X, Tian L, Smyth GK, Ritchie ME. RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR. F1000Res. 2016. https://doi.org/10.12688/f1000research.9005.3.CrossRefPubMed

20.

Cornec-Le Gall E, Alam A, Perrone RD. Autosomal dominant polycystic kidney disease. Lancet. 2019;393(10174):919–35. https://doi.org/10.1016/S0140-6736(18)32782-X.CrossRefPubMed

21.

Douguet D, Patel A, Honore E. Structure and function of polycystins: insights into polycystic kidney disease. Nat Rev Nephrol. 2019;15(7):412–22. https://doi.org/10.1038/s41581-019-0143-6.CrossRefPubMed

22.

Ghata J, Cowley BD Jr. Polycystic kidney disease. Compr Physiol. 2017;7(3):945–75. https://doi.org/10.1002/cphy.c160018.CrossRefPubMed

23.

Shi W, Xu D, Gu J, Xue C, Yang B, Fu L, Song S, Liu D, Zhou W, Lv J, et al. Saikosaponin-d inhibits proliferation by up-regulating autophagy via the CaMKKbeta-AMPK-mTOR pathway in ADPKD cells. Mol Cell Biochem. 2018;449(1–2):219–26. https://doi.org/10.1007/s11010-018-3358-0.CrossRefPubMed

24.

Sun Y, Liu Z, Cao X, Lu Y, Mi Z, He C, Liu J, Zheng Z, Li MJ, Li T, et al. Activation of P-TEFb by cAMP-PKA signaling in autosomal dominant polycystic kidney disease. Sci Adv. 2019;5(6):eaaw3593. https://doi.org/10.1126/sciadv.aaw3593.CrossRefPubMedPubMedCentral

25.

Kang HW, Ozdemir C, Kawano Y, LeClair KB, Vernochet C, Kahn CR, Hagen SJ, Cohen DE. Thioesterase superfamily member 2/Acyl-CoA thioesterase 13 (Them2/Acot13) regulates adaptive thermogenesis in mice. J Biol Chem. 2013;288(46):33376–86. https://doi.org/10.1074/jbc.M113.481408.CrossRefPubMedPubMedCentral

26.

Lin CC, Kurashige M, Liu Y, Terabayashi T, Ishimoto Y, Wang T, Choudhary V, Hobbs R, Liu LK, Lee PH, et al. A cleavage product of Polycystin-1 is a mitochondrial matrix protein that affects mitochondria morphology and function when heterologously expressed. Sci Rep. 2018;8(1):2743. https://doi.org/10.1038/s41598-018-20856-6.CrossRefPubMedPubMedCentral

27.

Tian L, Suzuki M, Nakajima T, Kubo R, Sekine Y, Shibuya K, Hiroshima K, Nakatani Y, Fujisawa T, Yoshino I, et al. Clinical significance of aberrant methylation of prostaglandin E receptor 2 (PTGER2) in nonsmall cell lung cancer: association with prognosis, PTGER2 expression, and epidermal growth factor receptor mutation. Cancer. 2008;113(6):1396–403. https://doi.org/10.1002/cncr.23694.CrossRefPubMed

28.

Baba Y, Nosho K, Shima K, Goessling W, Chan AT, Ng K, Chan JA, Giovannucci EL, Fuchs CS, Ogino S. PTGER2 overexpression in colorectal cancer is associated with microsatellite instability, independent of CpG island methylator phenotype. Cancer Epidemiol Biomarkers Prev. 2010;19(3):822–31. https://doi.org/10.1158/1055-9965.EPI-09-1154.CrossRefPubMedPubMedCentral

29.

Sugino Y, Misawa A, Inoue J, Kitagawa M, Hosoi H, Sugimoto T, Imoto I, Inazawa J. Epigenetic silencing of prostaglandin E receptor 2 (PTGER2) is associated with progression of neuroblastomas. Oncogene. 2007;26(53):7401–13. https://doi.org/10.1038/sj.onc.1210550.CrossRefPubMed

30.

Liu Y, Rajagopal M, Lee K, Battini L, Flores D, Gusella GL, Pao AC, Rohatgi R. Prostaglandin E(2) mediates proliferation and chloride secretion in ADPKD cystic renal epithelia. Am J Physiol Renal Physiol. 2012;303(10):F1425-1434. https://doi.org/10.1152/ajprenal.00010.2012.CrossRefPubMedPubMedCentral

31.

Elberg G, Elberg D, Lewis TV, Guruswamy S, Chen L, Logan CJ, Chan MD, Turman MA. EP2 receptor mediates PGE2-induced cystogenesis of human renal epithelial cells. Am J Physiol Renal Physiol. 2007;293(5):F1622-1632. https://doi.org/10.1152/ajprenal.00036.2007.CrossRefPubMed

Title: Identification of ACOT13 and PTGER2 as novel candidate genes of autosomal dominant polycystic kidney disease through whole exome sequencing
Authors: Na Du
Dan Dong
Luyao Sun
Lihe Che
Xiaohua Li
Yong Liu
Bin Wang
Publication date: 01-12-2021
Publisher: BioMed Central
Keyword: Polycystic Kidney Disease
Published in: European Journal of Medical Research / Issue 1/2021
Electronic ISSN: 2047-783X
DOI: https://doi.org/10.1186/s40001-021-00613-8

Keynote webinar | Spotlight on medication adherence

Springer Medicine

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

Abstract

Background

Methods

Results

Conclusions

Keynote webinar | Spotlight on medication adherence

Springer Medicine

Abstract

Background

Methods

Results

Conclusions

Please log in to get access to this content

Other articles of this Issue 1/2021

The effects of hyperbaric oxygen therapy (HBOT) on coronavirus disease-2019 (COVID-19): a systematic review

Investigation of antibiotic susceptibilities of Brucella Strains isolated from various clinical samples in eastern Turkey

AdipoR2 inhibits human glioblastoma cell growth through the AMPK/mTOR pathway

A case of Castleman disease with hemophagocytic syndrome derived from HHV8 infection

Using Kano diagrams to display the most cited article types, affiliated countries, authors and MeSH terms on spinal surgery in recent 12 years

Histopathological characteristics of cervical extensor tissue in patients with dropped head syndrome