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ArticleKidney international reports2025

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

Matthias Christoph Braunisch, Clara M Großewinkelmann, Martin Menke, Nora Hannane, Riccardo Berutti, Jasmina Ćomić, Roman Günthner, Lutz Renders, Christoph Schmaderer, Uwe Heemann and 3 more

Abstract read
In one paragraph

Article in Kidney international reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Matthias Christoph BraunischDepartment of Nephrology, Klinikum rechts der Isar, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Clara M GroßewinkelmannInstitute of Human Genetics, Klinikum rechts der Isar, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Martin MenkeInstitute of Human Genetics, Klinikum rechts der Isar, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Nora HannaneDepartment of Nephrology, Klinikum rechts der Isar, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Riccardo BeruttiInstitute of Human Genetics, Klinikum rechts der Isar, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Jasmina ĆomićDepartment of Nephrology, Klinikum rechts der Isar, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Roman GünthnerDepartment of Nephrology, Klinikum rechts der Isar, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Lutz RendersDepartment of Nephrology, Klinikum rechts der Isar, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Christoph SchmadererDepartment of Nephrology, Klinikum rechts der Isar, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Uwe HeemannDepartment of Nephrology, Klinikum rechts der Isar, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Korbinian M RiedhammerDepartment of Nephrology, Klinikum rechts der Isar, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Matias WagnerInstitute of Human Genetics, Klinikum rechts der Isar, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.
Julia HoefeleInstitute of Human Genetics, Klinikum rechts der Isar, Technical University of Munich, TUM School of Medicine and Health, Munich, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Monogenic kidney diseases, though rare, exhibit a wide spectrum of clinical manifestations. The clinical and genetic diversity and potential biases in patient referrals and identification present challenges in accurately estimating prevalences based solely on phenotype. Our aim was to determine the calculated lifetime risk associated with autosomal recessive kidney diseases (ARKDs) using population-based genotype data. Methods: We conducted a comprehensive literature review to compile a list of 149 genes associated with ARKDs, including 31 glomerulopathies, 16 tubulopathies, 87 ciliopathies, and 15 congenital anomalies of the kidney and urinary tract (CAKUT). Disease-causing variants were collected from ClinVar, HGMD, LOVD, and our in-house database and evaluated for inclusion. Minor allele frequencies of 12,912 variants were then obtained from the Genome Aggregation Database (gnomAD) and the in-house database to estimate the lifetime risk. Results: The combined estimated lifetime risk was 27.49 per 100,000 (19.35-39.65) based on the European gnomAD dataset. The 3 disorders with the highest lifetime risk (>1.5 per 100,000), accounted for 24% of the overall lifetime risk and were caused by Conclusion: 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.

Indexed as

autosomal recessive kidney diseaselifetime riskmonogenic kidney diseasepopulation geneticsprevalence

Identifiers

PMID40677321
PMCPMC12266173

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