Evidence map›Paper›PMID 39802625›Full record

ReviewJournal of molecular and cellular cardiology plus2023

Transcriptomic research in atherosclerosis: Unravelling plaque phenotype and overcoming methodological challenges.

Miron Sopić, Kanita Karaduzovic-Hadziabdic, Dimitris Kardassis, Lars Maegdefessel, Fabio Martelli, Ari Meerson, Jelena Munjas, Loredan S Niculescu, Monika Stoll, Paolo Magni and 2 more

Abstract readReview
In one paragraph

Review in Journal of molecular and cellular cardiology plus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
  5. Review
  6. 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

12 authors.

Miron SopićDepartment of Medical Biochemistry, Faculty of Pharmacy, University of Belgrade, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg.
Kanita Karaduzovic-HadziabdicFaculty of Engineering and Natural Science, Computer Science, International University of Sarajevo, Bosnia and Herzegovina.
Dimitris KardassisLaboratory of Biochemistry, University of Crete Medical School and Gene Regulation and Epigenetics Group, Institute of Molecular Biology and Biotechnology, Foundation for Research and Technology of Hellas, Heraklion 71003, Greece.
Lars MaegdefesselInstitute of Molecular Vascular Medicine, Klinikum rechts der Isar, Technical University Munich, Germany.
Fabio MartelliMolecular Cardiology Laboratory, IRCCS-Policlinico San Donato, via Morandi 30, 20097, San Donato Milanese, Milan, Italy.
Ari MeersonMolecular Biology of Chronic Diseases Laboratory, Genomic Center, Galilee Research Institute (MIGAL), Kiryat Shmona, Israel.
Jelena MunjasDepartment of Medical Biochemistry, Faculty of Pharmacy, University of Belgrade, Serbia.
Loredan S NiculescuLipidomics Department, Institute of Cellular Biology and Pathology "Nicolae Simionescu" of the Romanian Academy, 8, B.P. Hasdeu Street, Bucharest 050568, Romania.
Monika StollUniversity of Münster, Institute of Hunan Genetics, Division of Genetic Epidemiology, Münster, Germany.
Paolo MagniDepartment of Pharmacological and Biomolecular Sciences "Rodolfo Paoletti", Università degli Studi di Milano, via Balzaretti 9, 20133, Milan, Italy.
Yvan DevauxCardiovascular Research Unit, Department of Population Health, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg.
CardioRNA COST Action CA17129 and AtheroNET COST Action CA21153

Funding

Computational and functional strategies to decipher lncRNAs in human atherosclerosisR01HL150359 · NHLBI · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI LI, MINGYAO, REILLY, MUREDACH P · 2020 to 2023
$2.7M
NHLBI NIH HHS R01 HL150359
6 · The paper itself

Abstract

Atherosclerotic disease is a major cause of acute cardiovascular events. A deeper understanding of its underlying mechanisms will allow advancing personalized and patient-centered healthcare. Transcriptomic research has proven to be a powerful tool for unravelling the complex molecular pathways that drive atherosclerosis. However, low reproducibility of research findings and lack of standardization of procedures pose significant challenges in this field. In this review, we discuss how transcriptomic research can help in understanding the different phenotypes of the atherosclerotic plaque that contribute to the development and progression of atherosclerosis. We highlight the methodological challenges that need to be addressed to improve research outputs, and emphasize the importance of research protocols harmonization. We also discuss recent advances in transcriptomic research, including bulk or single-cell sequencing, and their added value in plaque phenotyping. Finally, we explore how integrated multiomics data and machine learning improve understanding of atherosclerosis and provide directions for future research.

Indexed as

Atherosclerotic plaqueData integration, machine learningTranscriptomics

Identifiers

PMID39802625
PMCPMC11708385

What OpenQuestion holds

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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.