Evidence map›Paper›PMID 32708735›Full record

ReviewGenes2020

DNA Methylation Dysfunction in Chronic Kidney Disease.

Diego Ingrosso, Alessandra F Perna

Open access · goldAbstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in Genes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 1 pooled it
1.3field-weighted citation impact, top 20% of its field
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

19 citing papers in PubMed, 1 synthesis or guideline pooled it, 26 citations in OpenAlex.

  1. Pooled it
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  16. Are Alterations in DNA Methylation Related to CKD Development?International journal of molecular sciences · 2022
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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 at 2 institutions in 1 country.

Diego IngrossoDepartment of Precision Medicine, School of Medicine, University of Campania "Luigi Vanvitelli", 80138 Naples, Italy.
Alessandra F PernaDepartment of Medical Translational Sciences, School of Medicine, University of Campania "Luigi Vanvitelli", 80131 Naples, Italy.
University of Campania "Luigi Vanvitelli" · ITUniversity of Campania "Luigi Vanvitelli" · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Renal disease is the common denominator of a number of underlying disease conditions, whose prevalence has been dramatically increasing over the last two decades. Two aspects are particularly relevant to the subject of this review: (I) most cases are gathered under the umbrella of chronic kidney disease since they require-predictably for several lustrums-continuous clinical monitoring and treatment to slow down disease progression and prevent complications; (II) cardiovascular disease is a terrible burden in this population of patients, in that it claims many lives yearly, while only a scant minority reach the renal disease end stage. Why indeed a review on DNA methylation and renal disease? As we hope to convince you, the present evidence supports the role of the existence of various derangements of the epigenetic control of gene expression in renal disease, which hold the potential to improve our ability, in the future, to more effectively act toward disease progression, predict outcomes and offer novel therapeutic approaches.

Indexed as

Cardiovascular DiseasesDisease ProgressionDNA MethylationEpigenesis, GeneticHumansKidney Failure, ChronicPrognosisRenal Insufficiency, ChronicTherapies, InvestigationalCKDdialysisdisease markersDNA methylationepigenetic regulationESRDmethylation reactionsrenal failure

Identifiers

PMID32708735
PMCPMC7397141
OpenAlexW3042521120

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.