ReviewNature reviews. Nephrology2025
A guide to gene-disease relationships in nephrology.
Review in Nature reviews. Nephrology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Gene-disease relationships for glomerular phenotypes: expert recommendations from ClinGen.Nature reviews. Nephrology · 2026Review
- Diagnostic Yield and Clinical Utility of Genetic Testing in Turkish Adults with Suspected Inherited Kidney Disease: Insights from a Population with High Parental Consanguinity.Journal of clinical practice and research · 2026Article
- Fifty Shades of Risk: Population Studies and the Genetic Architecture of Kidney Diseases.Journal of the American Society of Nephrology : JASN · 2026Review
- Chronic Kidney Disease of unexplained cause (CKDx): a consensus statement by the Genes & Kidney Working Group of the ERA.Nephrology, dialysis, transplantation : official publication of the European Dialysis and Transplant Association - European Renal Association · 2025Article
- Nephrogenomics, precision medicine and the role of genetic testing in adult kidney disease management.Nature reviews. Nephrology · 2025Review
- Gene-Disease Relationships in Kidney Genetics.Seminars in nephrology · 2025Review
- Genetic Kidney Disease Across the Lifespan - Emerging Insights From Clinical Genomics in Older People.Kidney international reports · 2025Article
- Navigating Genetic Testing in Nephrology: Options and Decision-Making Strategies.Kidney international reports · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
The use of next-generation sequencing technologies such as exome and genome sequencing in research and clinical care has transformed our understanding of the molecular architecture of genetic kidney diseases. Although the capability to identify and rigorously assess genetic variants and their relationship to disease has advanced considerably in the past decade, the curation of clinically relevant relationships between genes and specific phenotypes has received less attention, despite it underpinning accurate interpretation of genomic tests. Here, we discuss the need to accurately define gene-disease relationships in nephrology and provide a framework for appraising genetic and experimental evidence critically. We describe existing international programmes that provide expert curation of gene-disease relationships and discuss sources of discrepancy as well as efforts at harmonization. Further, we highlight the need for alignment of disease and phenotype terminology to ensure robust and reproducible curation of knowledge. These collective efforts to support evidence-based translation of genomic sequencing into practice across clinical, diagnostic and research settings are crucial for delivering the promise of precision medicine in nephrology, providing more patients with timely diagnoses, accurate prognostic information and access to targeted treatments.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.