Meta-GWAS on PCSK9 concentrations reveals associations of novel loci outside the PCSK9 locus in White populations.

Cardiovascular disease FADS2 Meta-GWAS PCSK9

Journal

Atherosclerosis
ISSN: 1879-1484
Titre abrégé: Atherosclerosis
Pays: Ireland
ID NLM: 0242543

Informations de publication

Date de publication:
Dec 2023
Historique:
received: 10 08 2023
revised: 23 10 2023
accepted: 07 11 2023
pubmed: 22 11 2023
medline: 22 11 2023
entrez: 21 11 2023
Statut: ppublish

Résumé

Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key regulator of lipid homeostasis. A few earlier genome-wide association studies (GWAS) investigated genetic variants associated with circulating PCSK9 concentrations. However, uncertainty remains about some of the genetic loci discovered beyond the PCSK9 locus. By conducting the largest PCSK9 meta-analysis of GWAS (meta-GWAS) so far, we aimed to identify novel loci and validate the previously reported loci that regulate PCSK9 concentrations. We performed GWAS for PCSK9 concentrations in two large cohorts (GCKD (n = 4,963) and KORA F3 (n = 2,895)). These were meta-analyzed with previously published data encompassing together 20,579 individuals. We further conducted a second meta-analysis in statin-naïve individuals (n = 15,390). A genetic risk score (GRS) was constructed on PCSK9-increasing SNPs and assessed its impact on the risk for coronary artery disease (CAD) in 394,943 statin-naïve participants (17,077 with events) of the UK Biobank by performing CAD-free survival analysis. Nine loci were genome-wide significantly associated with PCSK9 concentrations. These included the previously described PCSK9, APOB, KCNA1/KCNA5, and TM6SF2/SUGP1 loci. All imputed SNPs in the PCSK9 locus account for ∼15% of variance of PCSK9 concentrations. We further identified FADS2 as a novel locus that was also found in statin-naïve participants. All imputed SNPs within the FADS2 locus explain ∼1.2% of variance of PCSK9 concentrations. Additionally, four further loci (a region on chromosome 5, SDK1, SPATA16 and HPR) were genome-wide significant in either the main model or the statin-naïve subset. The linear increase in a PCSK9 genetic risk score was associated with 1.41-fold (95%CI 1.16-1.72, p < 0.001) higher risk for incident CAD. We identified five novel loci (FADS2, SPATA16, SDK1, HPR and a region on chromosome 5) for PCSK9 concentrations that would require further research. Additionally, we confirm the genome-wide significant loci that were previously detected.

Sections du résumé

BACKGROUND AND AIMS OBJECTIVE
Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key regulator of lipid homeostasis. A few earlier genome-wide association studies (GWAS) investigated genetic variants associated with circulating PCSK9 concentrations. However, uncertainty remains about some of the genetic loci discovered beyond the PCSK9 locus. By conducting the largest PCSK9 meta-analysis of GWAS (meta-GWAS) so far, we aimed to identify novel loci and validate the previously reported loci that regulate PCSK9 concentrations.
METHODS METHODS
We performed GWAS for PCSK9 concentrations in two large cohorts (GCKD (n = 4,963) and KORA F3 (n = 2,895)). These were meta-analyzed with previously published data encompassing together 20,579 individuals. We further conducted a second meta-analysis in statin-naïve individuals (n = 15,390). A genetic risk score (GRS) was constructed on PCSK9-increasing SNPs and assessed its impact on the risk for coronary artery disease (CAD) in 394,943 statin-naïve participants (17,077 with events) of the UK Biobank by performing CAD-free survival analysis.
RESULTS RESULTS
Nine loci were genome-wide significantly associated with PCSK9 concentrations. These included the previously described PCSK9, APOB, KCNA1/KCNA5, and TM6SF2/SUGP1 loci. All imputed SNPs in the PCSK9 locus account for ∼15% of variance of PCSK9 concentrations. We further identified FADS2 as a novel locus that was also found in statin-naïve participants. All imputed SNPs within the FADS2 locus explain ∼1.2% of variance of PCSK9 concentrations. Additionally, four further loci (a region on chromosome 5, SDK1, SPATA16 and HPR) were genome-wide significant in either the main model or the statin-naïve subset. The linear increase in a PCSK9 genetic risk score was associated with 1.41-fold (95%CI 1.16-1.72, p < 0.001) higher risk for incident CAD.
CONCLUSIONS CONCLUSIONS
We identified five novel loci (FADS2, SPATA16, SDK1, HPR and a region on chromosome 5) for PCSK9 concentrations that would require further research. Additionally, we confirm the genome-wide significant loci that were previously detected.

Identifiants

pubmed: 37989062
pii: S0021-9150(23)05305-4
doi: 10.1016/j.atherosclerosis.2023.117384
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

117384

Informations de copyright

Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Azin Kheirkhah (A)

Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.

Johanna Franziska Schachtl-Riess (JF)

Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.

Claudia Lamina (C)

Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.

Silvia Di Maio (S)

Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.

Adriana Koller (A)

Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.

Sebastian Schönherr (S)

Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.

Stefan Coassin (S)

Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.

Lukas Forer (L)

Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria.

Peggy Sekula (P)

Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.

Christian Gieger (C)

Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Germany.

Annette Peters (A)

Institute of Epidemiology II, Helmholtz Zentrum München - German Research Center for Environmental Health, Germany.

Anna Köttgen (A)

Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center - University of Freiburg, Freiburg, Germany.

Kai-Uwe Eckardt (KU)

Department of Nephrology and Hypertension, University Hospital Erlangen, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany; German Chronic Kidney Disease Study, Germany; Department of Nephrology and Medical Intensive Care, Charité - Universitätsmedizin Berlin, Berlin, Germany.

Florian Kronenberg (F)

Institute of Genetic Epidemiology, Medical University of Innsbruck, Innsbruck, Austria. Electronic address: florian.kronenberg@i-med.ac.at.

Classifications MeSH