Population Heterogeneity and Selection of Coronary Artery Disease Polygenic Scores.

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

Journal

Journal of personalized medicine
ISSN: 2075-4426
Titre abrégé: J Pers Med
Pays: Switzerland
ID NLM: 101602269

Informations de publication

Date de publication:
26 Sep 2024
Historique:
received: 30 08 2024
revised: 16 09 2024
accepted: 24 09 2024
medline: 25 10 2024
pubmed: 25 10 2024
entrez: 25 10 2024
Statut: epublish

Résumé

The 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. We 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. Distributions between patients and controls were significantly different for 49 scores ( European 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.

Sections du résumé

BACKGROUND/OBJECTIVES OBJECTIVE
The 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.
METHODS METHODS
We 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.
RESULTS RESULTS
Distributions between patients and controls were significantly different for 49 scores (
CONCLUSIONS CONCLUSIONS
European 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.

Identifiants

pubmed: 39452533
pii: jpm14101025
doi: 10.3390/jpm14101025
pii:
doi:

Types de publication

Journal Article

Langues

eng

Subventions

Organisme : Ministero dell'Istruzione, dell'Università e della Ricerca
ID : D15D18000410001
Organisme : European Union's Horizon 2020 research and innovation programme
ID : 101016775

Auteurs

Carla Debernardi (C)

Genomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.

Angelo Savoca (A)

Genomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.

Alessandro De Gregorio (A)

Genomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.

Elisabetta Casalone (E)

Genomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.

Miriam Rosselli (M)

Genomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.

Elton Jalis Herman (EJ)

Genomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.

Cecilia Di Primio (C)

Genomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.

Rosario Tumino (R)

Cancer Registry and Histopathology Unit, Azienda Ospedaliera "Civile-M.P. Arezzo", 97100 Ragusa, Italy.

Sabina Sieri (S)

Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, 20100 Milan, Italy.

Paolo Vineis (P)

MRC-PHE Centre for Environment and Health, Imperial College London, London W12 0BZ, UK.

Salvatore Panico (S)

Department of Clinical and Experimental Medicine, University Federico II, 80100 Naples, Italy.

Carlotta Sacerdote (C)

Piedmont Reference Centre for Epidemiology and Cancer Prevention (CPO Piemonte), 10126 Turin, Italy.

Diego Ardissino (D)

Cardiology Department, Azienda Ospedaliero-Universitaria of Parma, 43100 Parma, Italy.
Department of Medicine and Surgery, University of Parma, 43100 Parma, Italy.

Rosanna Asselta (R)

Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, 20072 Milan, Italy.
IRCCS Humanitas Research Hospital, Rozzano, 20089 Milan, Italy.

Giuseppe Matullo (G)

Genomic Variation, Complex Diseases and Population Medicine Unit, Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
Medical Genetic Service, Città della Salute e della Scienza, 10126 Turin, Italy.

Classifications MeSH