Evidence map›Paper›PMID 40755967›Full record

ReviewClinical kidney journal2025

RNA therapeutics in kidney diseases: prospects and current status.

Francesco Paolo Schena, Emanuela Pasculli

Abstract readReview
In one paragraph

Review in Clinical kidney journal, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Preventing pediatric acute kidney injury: is it even possible?Pediatric nephrology (Berlin, Germany) · 2026
    Review
  3. Review
  4. Review
  5. Article
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.

Francesco Paolo SchenaDepartment of Emergency and Organ Transplantation, University of Bari "Aldo Moro", Bari, Italy.
Emanuela PasculliSchena Foundation, Bari, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this narrative review, we summarize the current knowledge on RNA-based therapies used in rare and ultrarare disorders and congenital diseases in which the kidneys may be involved. In these therapies, RNA molecules are packaged into delivery vehicles to reach the desired target. We describe only drugs that have been approved or are under review for approval by the US Food and Drug Administration and/or the European Medicines Agency. We describe the potential therapeutic role of microRNA (miRNA) in Alport syndrome, polycystic kidney disease and renal cell carcinoma. Notably, large randomized clinical studies are required before these drugs can be introduced into clinical practice. The therapeutic effects of short interfering RNA molecules have been tested and evaluated in patients with various congenital or acquired diseases, such as primary hyperoxaluria, hereditary transthyretin amyloidosis, acute kidney injury after cardiovascular intervention or kidney transplantation (i.e. delayed graft function), and in individuals affected by hypercholesterolemia. In addition, synthetic antisense oligonucleotides have proven effective in patients with moderate or severe hypercholesterolemia who developed statin side effects, such as myalgia or rhabdomyolysis, and in individuals with amyloidosis. These new therapeutic approaches need to be validated through global clinical trials in which large patient samples can be enrolled. Nonetheless, some of these promising new approaches are currently undergoing evaluation for the treatment of common diseases, such as hypertension and diabetes, which are the main causes of chronic kidney disease.

Indexed as

ASOmicroRNARNA interferenceshort interfering RNAtherapy

Identifiers

PMID40755967
PMCPMC12314272

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.