Evidence map›Paper›PMID 42871784›Full record

ReviewGenes & diseases2027

Genetic kidney diseases: Decoding molecular taxonomies to drive precision nephrology and therapeutic innovation.

Zhi-Ying Liu, Xu-Jie Zhou

Abstract readReview
In one paragraph

Review in Genes & diseases, 2027. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

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.

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

2 authors.

Zhi-Ying LiuRenal Division, Peking University First Hospital, Beijing 100034, China.
Xu-Jie ZhouRenal Division, Peking University First Hospital, Beijing 100034, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Genomic advances have transformed the landscape of genetic kidney diseases, enabling a shift from traditional phenotype-based diagnostics to molecularly precise classification. Large-scale genetic testing has revealed that approximately 10% of chronic kidney diseases are monogenic, greatly improving disease recognition and refining epidemiological prevalence-most notably for autosomal dominant polycystic kidney disease, Alport syndrome, podocytopathies, and autosomal dominant tubulointerstitial kidney disease. Importantly, genetic diagnostics have clarified previously uncertain etiologies in both pediatric and adult populations, enhancing diagnosis, prognosis, and clinical management. Integration of molecular genetics into nephrology has also exposed key limitations of phenotype-driven classification: genotype-phenotype discordance, single-gene variants causing diverse clinical syndromes, and similar phenotypes arising from distinct genetic etiologies. This complexity underscores the risks of relying solely on clinical observation, including inappropriate treatments or missed diagnoses that compromise patient outcomes. For instance, multiple renal cysts can result from various genetic disorders, and misclassification as autosomal dominant polycystic kidney disease may lead to inappropriate tolvaptan use. Molecular diagnostics now enable precision medicine by guiding therapy, optimizing transplantation decisions, and facilitating genetic counseling. Meanwhile, innovative therapies targeting the DNA-RNA-protein-epigenetic axis are advancing toward mechanism-driven treatments that deliver genuine patient benefits. Nonetheless, critical gaps remain in variant interpretation, equitable access to testing, and translation of genetic discoveries to clinical practice. The ongoing evolution of multi-omics integration, robust variant curation, and targeted delivery platforms holds promise for further breakthroughs, transforming outcomes and care standards for patients with genetic kidney diseases and ushering in an era of true precision nephrology.

Indexed as

Emerging therapiesGenetic kidney diseaseGenetic testingMolecular mechanismsPrecision medicine

Identifiers

PMID42871784
PMCPMC13659334

What OpenQuestion holds

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Registered trials

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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.