Evidence map›Paper›PMID 39452533›Full record

ArticleJournal of personalized medicine2024

Population Heterogeneity and Selection of Coronary Artery Disease Polygenic Scores.

Carla Debernardi, Angelo Savoca, Alessandro De Gregorio, Elisabetta Casalone, Miriam Rosselli, Elton Jalis Herman, Cecilia Di Primio, Rosario Tumino, Sabina Sieri, Paolo Vineis and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of personalized medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

15 authors.

Carla DebernardiGenomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.ORCID 0000-0002-7573-3693
Angelo SavocaGenomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
Alessandro De GregorioGenomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
Elisabetta CasaloneGenomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
Miriam RosselliGenomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
Elton Jalis HermanGenomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.ORCID 0009-0004-6349-1764
Cecilia Di PrimioGenomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
Rosario TuminoCancer Registry and Histopathology Unit, Azienda Ospedaliera "Civile-M.P. Arezzo", 97100 Ragusa, Italy.
Sabina SieriEpidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, 20100 Milan, Italy.ORCID 0000-0001-5201-172X
Paolo VineisMRC-PHE Centre for Environment and Health, Imperial College London, London W12 0BZ, UK.
Salvatore PanicoDepartment of Clinical and Experimental Medicine, University Federico II, 80100 Naples, Italy.
Carlotta SacerdotePiedmont Reference Centre for Epidemiology and Cancer Prevention (CPO Piemonte), 10126 Turin, Italy.ORCID 0000-0002-8008-5096
Diego ArdissinoCardiology Department, Azienda Ospedaliero-Universitaria of Parma, 43100 Parma, Italy.
Rosanna AsseltaDepartment of Biomedical Sciences, Humanitas University, Pieve Emanuele, 20072 Milan, Italy.ORCID 0000-0001-5351-0619
Giuseppe MatulloGenomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.ORCID 0000-0003-0674-7757

Funding

European Union's Horizon 2020 research and innovation programme 101016775Ministero dell'Istruzione, dell'Università e della Ricerca D15D18000410001
6 · The paper itself

Abstract

BACKGROUND/

objectivesThe identification of coronary artery disease (CAD) high-risk individuals is a major clinical need for timely diagnosis and intervention. Many different polygenic scores (PGSs) for CAD risk are available today to estimate the genetic risk. It is necessary to carefully choose the score to use, in particular for studies on populations, which are not adequately represented in the large datasets of European biobanks, such as the Italian one. This work aimed to analyze which PGS had the best performance within the Italian population.

methodsWe used two Italian independent cohorts: the EPICOR case-control study (576 individuals) and the Atherosclerosis, Thrombosis, and Vascular Biology (ATVB) Italian study (3359 individuals). We evaluated 266 PGS for cardiovascular disease risk from the PGS Catalog, selecting 51 for CAD.

resultsDistributions between patients and controls were significantly different for 49 scores (

conclusionsEuropean CAD PGS could have different risk estimates in peculiar populations, such as the Italian one, as well as in various geographical macro areas. Therefore, further evaluation is recommended for clinical applicability.

Indexed as

coronary artery disease (CAD)disease genetic riskpolygenic risk score (PRS)population heterogeneity

Identifiers

PMID39452533
PMCPMC11508882

What Socratic 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 Socratic graph.