Evidence map›Paper›PMID 40825915›Full record

ReviewJournal of cardiovascular translational research2025

Roles of Long Non-Coding RNAs in the Pathogenesis of Cardiovascular Disorders: Challenges and Opportunities.

Nan Deng

Abstract readReview
PubMed Publisher
In one paragraph

Review in Journal of cardiovascular translational research, 2025. 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

1 author.

Nan DengDepartment of Cardiovascular Medicine, People's Hospital of Chongqing Hechuan, Hechuan, Chongqing, 401520, China. 13110288856@163.com.ORCID 0009-0008-5752-168X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular disease (CVD) is a prominent contributor to global mortality rates, and its prevalence is consistently on the rise. The utilization of deep sequencing-based transcriptome profiling methodologies has yielded empirical support for the notion that the transcriptional activity of the human genome is more expansive than previously postulated. Long Non-Coding RNAs (lncRNAs) are a heterogeneous collection of noncoding transcripts with a length exceeding 200 nucleotides. Transposable elements represent a significant proportion of the human genome, and their potential contribution could be as high as 90%. LncRNAs can exert control over several biological processes through their ability to modulate the transcriptional activity of coding genes, engage in direct protein interactions, and potentially encode proteins. lncRNAs have been acknowledged as significant factors in the causation and progression of myocardial infarction, heart failure, cardiac hypertrophy, arrhythmias, and other pathological processes that have a considerable influence on the prognosis and survival of individuals afflicted with CVD. Moreover, the observable patterns of expression demonstrated by lncRNAs in different CVD scenarios greatly augment their potential as biomarkers and targets for intervention. To lay a strong foundation for future research on the mitigation and management of CVDs, we comprehensively examine current scholarly literature on lncRNAs in the context of cardiovascular disorders. The discourse also involves the potential usefulness of lncRNAs as biomarkers and targets for therapeutic interventions.

Indexed as

Cardiovascular DiseasesRNA, Long NoncodingAnimalsGene Expression ProfilingGene Expression RegulationGenetic Predisposition to DiseaseHumansPrognosisRNA, Long NoncodingBiomarkerCardiovascular disordersNon-coding RNATherapy

Identifiers

What Socratic holds

Textmetadata
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 Socratic graph.