Estimating Lifetime Risk of Autosomal Recessive Kidney Diseases Using Population-Based Genotypic Data

This study offers a comprehensive population-genetic assessment of the lifetime risk associated with ARKDs focusing on European populations, shedding light on previously underestimated prevalences and diagnostic probabilities. Consequently, these findings provide crucial insights for optimizing resource allocation towards therapy development, enhancing public health strategies, and guiding future biomedical research endeavors.

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Publication Details

Journal
Kidney International Reports
Published
2025-04-21
DOI
https://doi.org/10.1016/j.ekir.2025.04.036
Citations
1
Primary Topic
Renal Diseases and Glomerulopathies
Type
article
Field-Weighted Citation Impact
1.43

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article

Estimating Lifetime Risk of Autosomal Recessive Kidney Diseases Using Population-Based Genotypic Data

Riccardo Berutti, Matthias C. Braunisch, Lutz Renders, Uwe Heemann et al.
1 citations
Kidney International Reports
Renal Diseases and Glomerulopathies
1.43
article

Estimating Lifetime Risk of Autosomal Recessive Kidney Diseases Using Population-Based Genotypic Data

Riccardo Berutti, Matthias C. Braunisch, Lutz Renders, Uwe Heemann, Clara Großewinkelmann, Christoph Schmaderer, Julia Hoefele, Roman Günthner, Jasmina Ćomić, Matias Wagner, Nora Hannane, Martin Menke, Korbinian M. Riedhammer
article en
1 citations

Abstract

This study offers a comprehensive population-genetic assessment of the lifetime risk associated with ARKDs focusing on European populations, shedding light on previously underestimated prevalences and diagnostic probabilities. Consequently, these findings provide crucial insights for optimizing resource allocation towards therapy development, enhancing public health strategies, and guiding future biomedical research endeavors.

Kidney International ReportsVol. 10(7)
Boston Children's Hospital (US), Harvard University (US), TUM Klinikum (DE), Helmholtz Zentrum München (DE), Technical University of Munich (DE), Ludwig-Maximilians-Universität München (DE)
Deutsche Forschungsgemeinschaft, Technische Universität München
Openalex Percentile: Top 21%
Renal Diseases and Glomerulopathies
1.43
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