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      Plasma Mucin-1 (CA15-3) Levels in Autosomal Dominant Tubulointerstitial Kidney Disease due to MUC1 Mutations

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          Abstract

          Introduction: Patients with ADTKD- MUC1 have one allele producing normal mucin-1 (MUC1) and one allele producing mutant MUC1, which remains intracellular. We hypothesized that ADTKD- MUC1 patients, who have only 1 secretory-competent wild-type MUC1 allele, should exhibit decreased plasma mucin-1 (MUC1) levels. To test this hypothesis, we repurposed the serum CA15-3 assay used to measure MUC1 in breast cancer to measure plasma MUC1 levels in ADTKD- MUC1. Methods: This cross-sectional study analyzed CA15-3 levels in a reference population of 6,850 individuals, in 85 individuals with ADTKD- MUC1, and in a control population including 135 individuals with ADTKD- UMOD and 114 healthy individuals. Results: Plasma CA15-3 levels (mean ± standard deviation) were 8.6 ± 4.3 U/mL in individuals with ADTKD- MUC1 and 14.6 ± 5.6 U/mL in controls ( p < 0.001). While there was a significant difference in mean CA15-3 levels, there was substantial overlap between the 2 groups. Plasma CA15-3 levels were <5 U/mL in 22% of ADTKD- MUC1 patients, in 0/249 controls, and in 1% of the reference population. Plasma CA15-3 levels were >20 U/mL in 1/85 ADTKD- MUC1 patients, in 18% of control individuals, and in 25% of the reference population. Segregation of plasma CA15-3 levels by the rs4072037 genotype did not significantly improve differentiation between affected and unaffected individuals. CA15-3 levels were minimally affected by gender and estimated glomerular filtration rate. Discussion/Conclusions: Plasma CA15-3 levels in ADTKD- MUC1 patients are approximately 40% lower than levels in healthy individuals, though there is significant overlap between groups. Further investigations need to be performed to see if plasma CA15-3 levels would be useful in diagnosis, prognosis, or assessing response to new therapies in this disorder.

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          The mutational constraint spectrum quantified from variation in 141,456 humans

          Genetic variants that inactivate protein-coding genes are a powerful source of information about the phenotypic consequences of gene disruption: genes that are crucial for the function of an organism will be depleted of such variants in natural populations, whereas non-essential genes will tolerate their accumulation. However, predicted loss-of-function variants are enriched for annotation errors, and tend to be found at extremely low frequencies, so their analysis requires careful variant annotation and very large sample sizes 1 . Here we describe the aggregation of 125,748 exomes and 15,708 genomes from human sequencing studies into the Genome Aggregation Database (gnomAD). We identify 443,769 high-confidence predicted loss-of-function variants in this cohort after filtering for artefacts caused by sequencing and annotation errors. Using an improved model of human mutation rates, we classify human protein-coding genes along a spectrum that represents tolerance to inactivation, validate this classification using data from model organisms and engineered human cells, and show that it can be used to improve the power of gene discovery for both common and rare diseases.
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            Models for Longitudinal Data: A Generalized Estimating Equation Approach

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              Comparative performance of the CKD Epidemiology Collaboration (CKD-EPI) and the Modification of Diet in Renal Disease (MDRD) Study equations for estimating GFR levels above 60 mL/min/1.73 m2.

              The Modification of Diet in Renal Disease (MDRD) Study equation underestimates measured glomerular filtration rate (GFR) at levels>60 mL/min/1.73 m2, with variable accuracy among subgroups; consequently, estimated GFR (eGFR)>or=60 mL/min/1.73 m2 is not reported by clinical laboratories. Here, performance of a more accurate GFR-estimating equation, the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation, is reported by level of GFR and clinical characteristics. Test of diagnostic accuracy. Pooled data set of 3,896 people from 16 studies with measured GFR (not used for the development of either equation). Subgroups were defined by eGFR, age, sex, race, diabetes, prior solid-organ transplant, and body mass index. eGFR from the CKD-EPI and MDRD Study equations and standardized serum creatinine. Measured GFR using urinary or plasma clearance of exogenous filtration markers. Mean measured GFR was 68+/-36 (SD) mL/min/1.73 m2. For eGFR or=90 mL/min/1.73 m2. Limited number of elderly people and racial and ethnic minorities with measured GFR. The CKD-EPI equation is more accurate than the MDRD Study equation overall and across most subgroups. In contrast to the MDRD Study equation, eGFR>or=60 mL/min/1.73 m2 can be reported using the CKD-EPI equation. Copyright (c) 2010 National Kidney Foundation, Inc. All rights reserved.
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                Author and article information

                Journal
                AJN
                Am J Nephrol
                10.1159/issn.0250-8095
                American Journal of Nephrology
                S. Karger AG
                0250-8095
                1421-9670
                2021
                July 2021
                07 June 2021
                : 52
                : 5
                : 378-387
                Affiliations
                [_a] aDepartment of Paediatrics and Inherited Metabolic Disorders, Research Unit of Rare Diseases, First Faculty of Medicine, Charles University, Prague, Czechia
                [_b] bSection on Nephrology, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
                [_c] cDivision of Public Health Sciences, Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
                [_d] dInstitute of Medical Biochemistry and Laboratory Diagnostics, General University Hospital and the First Faculty of Medicine of Charles University, Prague, Czechia
                [_e] eRenal-Electrolyte Division, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA
                [_f] fThe Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
                [_g] gBeth Israel Deaconess Medical Center and Harvard Medical School, Boston, Massachusetts, USA
                [_h] hBiomedical Center and Institute of Microbiology, Faculty of Medicine in Pilsen of Charles University, Pilsen, Czechia
                Article
                515810 Am J Nephrol 2021;52:378–387
                10.1159/000515810
                34098564
                28bc435f-517d-41dc-b17f-162f50b4ac7d
                © 2021 The Author(s) Published by S. Karger AG, Basel

                This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC). Usage and distribution for commercial purposes requires written permission. Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug. Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

                History
                : 21 December 2020
                : 03 March 2021
                Page count
                Figures: 2, Tables: 2, Pages: 10
                Categories
                Patient-Oriented, Translational Research: Research Article

                Cardiovascular Medicine,Nephrology
                ADTKD-MUC1 ,CA15-3,Mucin-1,Autosomal dominant tubulointerstitial kidney disease,rs4072037

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