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      Genetic Analyses in Dent Disease and Characterization of CLCN5 Mutations in Kidney Biopsies

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          Abstract

          Dent disease (DD), an X-linked renal tubulopathy, is mainly caused by loss-of-function mutations in CLCN5 (DD1) and OCRL genes. CLCN5 encodes the ClC-5 antiporter that in proximal tubules (PT) participates in the receptor-mediated endocytosis of low molecular weight proteins. Few studies have analyzed the PT expression of ClC-5 and of megalin and cubilin receptors in DD1 kidney biopsies. About 25% of DD cases lack mutations in either CLCN5 or OCRL genes (DD3), and no other disease genes have been discovered so far. Sanger sequencing was used for CLCN5 gene analysis in 158 unrelated males clinically suspected of having DD. The tubular expression of ClC-5, megalin, and cubilin was assessed by immunolabeling in 10 DD1 kidney biopsies. Whole exome sequencing (WES) was performed in eight DD3 patients. Twenty-three novel CLCN5 mutations were identified. ClC-5, megalin, and cubilin were significantly lower in DD1 than in control biopsies. The tubular expression of ClC-5 when detected was irrespective of the type of mutation. In four DD3 patients, WES revealed 12 potentially pathogenic variants in three novel genes ( SLC17A1, SLC9A3, and PDZK1), and in three genes known to be associated with monogenic forms of renal proximal tubulopathies ( SLC3A, LRP2, and CUBN). The supposed third Dent disease-causing gene was not discovered.

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          DANN: a deep learning approach for annotating the pathogenicity of genetic variants.

          Annotating genetic variants, especially non-coding variants, for the purpose of identifying pathogenic variants remains a challenge. Combined annotation-dependent depletion (CADD) is an algorithm designed to annotate both coding and non-coding variants, and has been shown to outperform other annotation algorithms. CADD trains a linear kernel support vector machine (SVM) to differentiate evolutionarily derived, likely benign, alleles from simulated, likely deleterious, variants. However, SVMs cannot capture non-linear relationships among the features, which can limit performance. To address this issue, we have developed DANN. DANN uses the same feature set and training data as CADD to train a deep neural network (DNN). DNNs can capture non-linear relationships among features and are better suited than SVMs for problems with a large number of samples and features. We exploit Compute Unified Device Architecture-compatible graphics processing units and deep learning techniques such as dropout and momentum training to accelerate the DNN training. DANN achieves about a 19% relative reduction in the error rate and about a 14% relative increase in the area under the curve (AUC) metric over CADD's SVM methodology. All data and source code are available at https://cbcl.ics.uci.edu/public_data/DANN/. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
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            CUBN is a gene locus for albuminuria.

            Identification of genetic risk factors for albuminuria may alter strategies for early prevention of CKD progression, particularly among patients with diabetes. Little is known about the influence of common genetic variants on albuminuria in both general and diabetic populations. We performed a meta-analysis of data from 63,153 individuals of European ancestry with genotype information from genome-wide association studies (CKDGen Consortium) and from a large candidate gene study (CARe Consortium) to identify susceptibility loci for the quantitative trait urinary albumin-to-creatinine ratio (UACR) and the clinical diagnosis microalbuminuria. We identified an association between a missense variant (I2984V) in the CUBN gene, which encodes cubilin, and both UACR (P = 1.1 × 10(-11)) and microalbuminuria (P = 0.001). We observed similar associations among 6981 African Americans in the CARe Consortium. The associations between this variant and both UACR and microalbuminuria were significant in individuals of European ancestry regardless of diabetes status. Finally, this variant associated with a 41% increased risk for the development of persistent microalbuminuria during 20 years of follow-up among 1304 participants with type 1 diabetes in the prospective DCCT/EDIC Study. In summary, we identified a missense CUBN variant that associates with levels of albuminuria in both the general population and in individuals with diabetes.
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              The continuum of causality in human genetic disorders

              Studies of human genetic disorders have traditionally followed a reductionist paradigm. Traits are defined as Mendelian or complex based on family pedigree and population data, whereas alleles are deemed rare, common, benign, or deleterious based on their population frequencies. The availability of exome and genome data, as well as gene and allele discovery for various conditions, is beginning to challenge classic definitions of genetic causality. Here, I discuss recent advances in our understanding of the overlap between rare and complex diseases and the context-dependent effect of both rare and common alleles that underscores the need for revising the traditional categorizations of genetic traits.
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                Author and article information

                Journal
                Int J Mol Sci
                Int J Mol Sci
                ijms
                International Journal of Molecular Sciences
                MDPI
                1422-0067
                14 January 2020
                January 2020
                : 21
                : 2
                : 516
                Affiliations
                [1 ]Laboratory of Histomorphology and Molecular Biology of the Kidney, Clinical Nephrology, Department of Medicine—DIMED, University of Padua, 35128 Padua, Italy; lisa.gianesello@ 123456unipd.it (L.G.); monica.ceol@ 123456unipd.it (M.C.); liliana.terrin@ 123456gmail.com (L.T.); giovanna.priante@ 123456unipd.it (G.P.); dorella.delprete@ 123456unipd.it (D.D.P.)
                [2 ]CRIBI Biotechnology Centre, University of Padua, 35131 Padua, Italy; loris.bertoldi@ 123456phd.unipd.it (L.B.); giorgio.valle@ 123456unipd.it (G.V.)
                [3 ]Pediatric Nephrology, Dialysis and Transplant Unit, Department of Women’s and Children’s Health, Padua University Hospital, 35128 Padua, Italy; luisa.murer@ 123456aopd.veneto.it
                [4 ]Pediatric Nephrology Unit, Regina Margherita Children’s Hospital, 10126 CDSS Turin, Italy; licia.peruzzi@ 123456unito.it
                [5 ]Pediatric Nephrology Unit, University Hospital, P.O. Giovanni XXIII, 70126 Bari, Italy; mario.giordano@ 123456policlinico.ba.it
                [6 ]Pediatric Nephrology, Dialysis and Transplant Unit, Fondazione IRCCS, Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy; fabio.paglialonga@ 123456policlinico.mi.it
                [7 ]Nephrology and Kidney Transplantation Unit, Department of Translational Medicine, University of Piemonte Orientale (UPO), 28100 Novara, Italy; vincenzo.cantaluppi@ 123456med.uniupo.it (V.C.); claudio.musetti@ 123456med.uniupo.it (C.M.)
                Author notes
                [* ]Correspondence: franca.anglani@ 123456unipd.it ; Tel.: +39-049-8212-155
                [†]

                These authors contributed equally to this work.

                [‡]

                Membership of the Dent Disease Italian Network is provided in the Acknowledgments.

                Author information
                https://orcid.org/0000-0001-9327-397X
                https://orcid.org/0000-0002-8516-7680
                https://orcid.org/0000-0002-1870-4466
                https://orcid.org/0000-0002-5704-3867
                https://orcid.org/0000-0003-4224-636X
                https://orcid.org/0000-0003-1534-4458
                Article
                ijms-21-00516
                10.3390/ijms21020516
                7014080
                31947599
                9d810fb0-6baa-42ac-bc57-ad947a7d8770
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 04 December 2019
                : 10 January 2020
                Categories
                Article

                Molecular biology
                dent disease,clcn5 gene mutations,proximal tubular clc-5 expression,megalin,cubilin,kidney biopsies,immunohistochemistry,whole exome sequencing

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