KidneyNetwork: using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease
European Journal of Human Genetics, vol. 31, pp. 1300–1308
Abstract
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.
Authors 21
-
University Medical Center Groningen · University of Groningen · Oncode Institute
Affiliation as printed
Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
Oncode Institute, Utrecht, The Netherlands
-
University Medical Center Utrecht
Affiliation as printed
Department of Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
-
University Medical Center Groningen · University of Groningen
Affiliation as printed
Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
-
University Medical Center Groningen · University of Groningen · Oncode Institute
Affiliation as printed
Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
Oncode Institute, Utrecht, The Netherlands
-
University Medical Center Groningen · University of Groningen
Affiliation as printed
Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
-
University Medical Center Groningen · University of Groningen
Affiliation as printed
Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
-
University Medical Center Groningen · University of Groningen
Affiliation as printed
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
-
University Medical Center Groningen · University of Groningen · Oncode Institute
Affiliation as printed
Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
Oncode Institute, Utrecht, The Netherlands
-
University Medical Center Utrecht
Affiliation as printed
Department of Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
-
University Medical Center Utrecht
Affiliation as printed
Department of Nephrology, University Medical Center Utrecht, Utrecht, The Netherlands
-
University Hospital Leipzig · Leipzig University
Affiliation as printed
Medical Department III - Endocrinology, Nephrology, Rheumatology Department of Internal Medicine, Division of Nephrology, University of Leipzig Medical Center, Leipzig, Germany
-
Humboldt-Universität zu Berlin · University Hospital Leipzig · Freie Universität Berlin · Charité - Universitätsmedizin Berlin · Leipzig University
Affiliation as printed
Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
Medical Department III - Endocrinology, Nephrology, Rheumatology Department of Internal Medicine, Division of Nephrology, University of Leipzig Medical Center, Leipzig, Germany
-
Affiliation as printed
Department of Internal Medicine (Nephrology), Yale School of Medicine, New Haven, CT, USA
-
Leiden University Medical Center
Affiliation as printed
Department of Clinical Genetics, Leiden University Medical Center, Leiden, The Netherlands
-
Leiden University Medical Center · St. Antonius Ziekenhuis
Affiliation as printed
Department of Internal Medicine, Leiden University Medical Center, Leiden, The Netherlands
Department of Internal Medicine, St Antonius Hospital, Nieuwegein, The Netherlands
-
Humboldt-Universität zu Berlin · University Hospital Leipzig · Freie Universität Berlin · Charité - Universitätsmedizin Berlin · Leipzig University
Affiliation as printed
Department of Nephrology and Medical Intensive Care, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Berlin, Germany
Medical Department III - Endocrinology, Nephrology, Rheumatology Department of Internal Medicine, Division of Nephrology, University of Leipzig Medical Center, Leipzig, Germany
-
University Medical Center Groningen · University of Groningen
Affiliation as printed
Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
-
Affiliation as printed
Department of Internal Medicine (Nephrology), Yale School of Medicine, New Haven, CT, USA
-
University Medical Center Groningen · University of Groningen · University Medical Center Utrecht · Oncode Institute
Affiliation as printed
Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
Department of Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
Oncode Institute, Utrecht, The Netherlands
-
University Medical Center Groningen · University of Groningen · Oncode Institute
Affiliation as printed
Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
Oncode Institute, Utrecht, The Netherlands
-
Albertien M. van Eerde corresponding
University Medical Center Utrecht
Affiliation as printed
Department of Genetics, University Medical Center Utrecht, Utrecht, The Netherlands. A.vanEerde@umcutrecht.nl
Department of Genetics, University Medical Center Utrecht, Utrecht, The Netherlands
Cited by 17 stored of 15
17 results
No patents citing this paper on Lens.org (checked 2026-10-11).