Evidence map›Paper›PMID 31665258›Full record

ReviewEuropean heart journal. Cardiovascular pharmacotherapy2020

Differential epigenetic factors in the prediction of cardiovascular risk in diabetic patients.

Claudio Napoli, Giuditta Benincasa, Concetta Schiano, Marco Salvatore

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

Review in European heart journal. Cardiovascular pharmacotherapy, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 40 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
40citing papers in PubMed, 1 pooled it
3.6field-weighted citation impact, top 6% 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

40 citing papers in PubMed, 1 synthesis or guideline pooled it, 75 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Claudio NapoliDepartment of Advanced Clinical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Pz. Miraglia 2, Naples 80138, Italy.
Giuditta BenincasaDepartment of Advanced Clinical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Pz. Miraglia 2, Naples 80138, Italy.
Concetta SchianoDepartment of Advanced Clinical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Pz. Miraglia 2, Naples 80138, Italy.
Marco SalvatoreIRCCS SDN, via E. Gianturco 113, Naples 80143, Italy.
University of Campania "Luigi Vanvitelli" · ITSDN Istituto di Ricerca Diagnostica e Nucleare · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Hyperglycaemia can strongly alter the epigenetic signatures in many types of human vascular cells providing persistent perturbations of protein-protein interactions both in micro- and macro-domains. The establishment of these epigenetic changes may precede cardiovascular (CV) complications and help us to predict vascular lesions in diabetic patients. Importantly, these epigenetic marks may be transmitted across several generations (transgenerational effect) and increase the individual risk of disease. Aberrant DNA methylation and imbalance of histone modifications, mainly acetylation and methylation of H3, represent key determinants of vascular lesions and, thus, putative useful biomarkers for prevention and diagnosis of CV risk in diabetics. Moreover, a differential expression of some micro-RNAs (miRNAs), mainly miR-126, may be a useful prognostic biomarker for atherosclerosis development in asymptomatic subjects. Recently, also environmental-induced chemical perturbations in mRNA (epitranscriptome), mainly the N6-methyladenosine, have been associated with obesity and diabetes. Importantly, reversal of epigenetic changes by modulation of lifestyle and use of metformin, statins, fenofibrate, and apabetalone may offer useful therapeutic options to prevent or delay CV events in diabetics increasing the opportunity for personalized therapy. Network medicine is a promising molecular-bioinformatic approach to identify the signalling pathways underlying the pathogenesis of CV lesions in diabetic patients. Moreover, machine learning tools combined with tomography are advancing the individualized assessment of CV risk in these patients. We remark the need for combining epigenetics and advanced bioinformatic platforms to improve the prediction of vascular lesions in diabetics increasing the opportunity for CV precision medicine.

Indexed as

Epigenesis, GeneticTranscriptomeBlood GlucoseCardiovascular DiseasesDiabetes MellitusHumansPrecision MedicinePrimary PreventionRisk AssessmentRisk FactorsSecondary PreventionSystems AnalysisBlood GlucoseCardiovascular preventionDiabetic vasculatureEpigeneticsMachine learningNetwork medicinePersonalized therapy

Identifiers

PMID31665258
PMCPMC7363021
OpenAlexW2982545301

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.