دورية أكاديمية
KidneyNetwork: using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease.
| العنوان: | KidneyNetwork: using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease. |
|---|---|
| المؤلفون: | Boulogne F; Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.; Oncode Institute, Utrecht, The Netherlands., Claus LR; Department of Genetics, University Medical Center Utrecht, Utrecht, The Netherlands., Wiersma H; Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands., Oelen R; Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.; Oncode Institute, Utrecht, The Netherlands., Schukking F; Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands., de Klein N; Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands., Li S; Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.; Genomics Coordination Center, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands., Westra HJ; Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.; Oncode Institute, Utrecht, The Netherlands., van der Zwaag B; Department of Genetics, University Medical Center Utrecht, Utrecht, The Netherlands., van Reekum F; Department of Nephrology, University Medical Center Utrecht, Utrecht, The Netherlands., Sierks D; Medical Department III - Endocrinology, Nephrology, Rheumatology Department of Internal Medicine, Division of Nephrology, University of Leipzig Medical Center, Leipzig, Germany., Schönauer R; Medical Department III - Endocrinology, Nephrology, Rheumatology Department of Internal Medicine, Division of Nephrology, University of Leipzig Medical Center, Leipzig, Germany.; Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany., Li Z; Department of Internal Medicine (Nephrology), Yale School of Medicine, New Haven, CT, USA., Bijlsma EK; Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands., Bos WJW; Department of Internal Medicine, St Antonius Hospital, Nieuwegein, The Netherlands.; Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands., Halbritter J; Medical Department III - Endocrinology, Nephrology, Rheumatology Department of Internal Medicine, Division of Nephrology, University of Leipzig Medical Center, Leipzig, Germany.; Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany., Knoers NVAM; Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands., Besse W; Department of Internal Medicine (Nephrology), Yale School of Medicine, New Haven, CT, USA., Deelen P; Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.; Oncode Institute, Utrecht, The Netherlands.; Department of Genetics, University Medical Center Utrecht, Utrecht, The Netherlands., Franke L; Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands.; Oncode Institute, Utrecht, The Netherlands., van Eerde AM; Department of Genetics, University Medical Center Utrecht, Utrecht, The Netherlands. A.vanEerde@umcutrecht.nl. |
| مؤلفون مشاركون: | Genomics England Research Consortium |
| المصدر: | European journal of human genetics : EJHG [Eur J Hum Genet] 2023 Nov; Vol. 31 (11), pp. 1300-1308. Date of Electronic Publication: 2023 Feb 20. |
| نوع المنشور: | Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't |
| اللغة: | English |
| بيانات الدورية: | Publisher: Nature Publishing Group Country of Publication: England NLM ID: 9302235 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1476-5438 (Electronic) Linking ISSN: 10184813 NLM ISO Abbreviation: Eur J Hum Genet Subsets: MEDLINE |
| أسماء مطبوعة: | Publication: <2003->: London : Nature Publishing Group Original Publication: Basel ; New York : Karger, [1992- |
| مواضيع طبية MeSH: | Kidney Diseases* , Kidney Diseases, Cystic* , Liver Diseases*, Humans ; Kidney ; Phenotype ; Gene Expression |
| مستخلص: | Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the disorder as potentially pathogenic variants can reside in genes that are not yet known to be involved in kidney disease. We have developed KidneyNetwork, that utilizes tissue-specific expression to inform candidate gene prioritization specifically for kidney diseases. KidneyNetwork is a novel method constructed by integrating a kidney RNA-sequencing co-expression network of 878 samples with a multi-tissue network of 31,499 samples. It uses expression patterns and established gene-phenotype associations to predict which genes could be related to what (disease) phenotypes in an unbiased manner. We applied KidneyNetwork to rare variants in exome sequencing data from 13 kidney disease patients without a genetic diagnosis to prioritize candidate genes. KidneyNetwork can accurately predict kidney-specific gene functions and (kidney disease) phenotypes for disease-associated genes. The intersection of prioritized genes with genes carrying rare variants in a patient with kidney and liver cysts identified ALG6 as plausible candidate gene. We strengthen this plausibility by identifying ALG6 variants in several cystic kidney and liver disease cases without alternative genetic explanation. We present KidneyNetwork, a publicly available kidney-specific co-expression network with optimized gene-phenotype predictions for kidney disease phenotypes. We designed an easy-to-use online interface that allows clinicians and researchers to use gene expression and co-regulation data and gene-phenotype connections to accelerate advances in hereditary kidney disease diagnosis and research. TRANSLATIONAL STATEMENT: Genetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the patient's disorder. Potentially pathogenic variants can reside in genes not yet known to be involved in kidney disease, making it difficult to interpret the relevance of these variants. This reveals a clear need for methods to predict the phenotypic consequences of genetic variation in an unbiased manner. Here we describe KidneyNetwork, a tool that utilizes tissue-specific expression to predict kidney-specific gene functions. Applying KidneyNetwork to a group of undiagnosed cases identified ALG6 as a candidate gene in cystic kidney and liver disease. In summary, KidneyNetwork can aid the interpretation of genetic variants and can therefore be of value in translational nephrogenetics and help improve the diagnostic yield in kidney disease patients. (© 2023. The Author(s).) |
| References: | J Am Soc Nephrol. 2019 Nov;30(11):2091-2102. (PMID: 31395617) Mol Genet Metab. 2003 Jul;79(3):221-8. (PMID: 12855228) Am J Med Genet A. 2005 Aug 15;137(1):22-6. (PMID: 16007612) Nature. 2020 Mar;579(7799):443-447. (PMID: 32103179) N Engl J Med. 2019 Jan 10;380(2):142-151. (PMID: 30586318) Nature. 2020 May;581(7809):434-443. (PMID: 32461654) Nephrol Dial Transplant. 2022 Jan 25;37(2):349-357. (PMID: 33306124) J Am Soc Nephrol. 2020 Oct;31(10):2326-2340. (PMID: 32764137) Hum Genet. 2000 May;106(5):538-45. (PMID: 10914684) Hum Mutat. 2015 Oct;36(10):928-30. (PMID: 26220891) Genet Med. 2020 Aug;22(8):1374-1383. (PMID: 32398770) Biometrics. 1988 Sep;44(3):837-45. (PMID: 3203132) Nat Rev Genet. 2011 Aug 18;12(9):628-40. (PMID: 21850043) Genet Med. 2017 Oct;19(10):1151-1158. (PMID: 28518168) Mol Biol Evol. 2002 Sep;19(9):1451-63. (PMID: 12200473) Kidney Int. 2019 Apr;95(4):914-928. (PMID: 30773290) J Clin Invest. 2017 May 1;127(5):1772-1785. (PMID: 28375157) Clin Genet. 2010 May;77(5):507-9. (PMID: 20447155) Brief Bioinform. 2018 Jul 20;19(4):575-592. (PMID: 28077403) Mol Genet Metab. 2000 Jul;70(3):219-23. (PMID: 10924277) J Inherit Metab Dis. 2016 Sep;39(5):713-723. (PMID: 27287710) Genome Med. 2020 Aug 24;12(1):75. (PMID: 32831124) PLoS Comput Biol. 2015 May 13;11(5):e1004220. (PMID: 25970446) BMC Bioinformatics. 2011 Mar 17;12:77. (PMID: 21414208) Nat Commun. 2019 Jun 28;10(1):2837. (PMID: 31253775) Nucleic Acids Res. 2019 Jan 8;47(D1):D1018-D1027. (PMID: 30476213) |
| معلومات مُعتمدة: | K08 DK119642 United States DK NIDDK NIH HHS; S10 OD018521 United States OD NIH HHS; U54 HG006504 United States HG NHGRI NIH HHS; HHSN268201000029C United States HL NHLBI NIH HHS; HHSN261200800001E United States CA NCI NIH HHS |
| تواريخ الأحداث: | Date Created: 20230222 Date Completed: 20231103 Latest Revision: 20231108 |
| رمز التحديث: | 20240628 |
| مُعرف محوري في PubMed: | PMC10620423 |
| DOI: | 10.1038/s41431-023-01296-x |
| PMID: | 36807342 |
| قاعدة البيانات: | MEDLINE |
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