A Multilocus Genetic Risk Score for Coronary Heart Disease: Case-control and Prospective Cohort Analyses

Overview

Journal Lancet

Publisher Elsevier

Specialty General Medicine

Date 2010 Oct 26

PMID 20971364

Citations 256

Authors

Samuli Ripatti

Emmi Tikkanen

Marju Orho-Melander

Aki S Havulinna

Kaisa Silander

Amitabh Sharma

Candace Guiducci

Markus Perola

Antti Jula

Juha Sinisalo

Marja-Liisa Lokki

Markku S Nieminen

Olle Melander

Veikko Salomaa

Leena Peltonen

Sekar Kathiresan

Affiliations

Soon will be listed here.

Abstract

Background: Comparison of patients with coronary heart disease and controls in genome-wide association studies has revealed several single nucleotide polymorphisms (SNPs) associated with coronary heart disease. We aimed to establish the external validity of these findings and to obtain more precise risk estimates using a prospective cohort design.

Methods: We tested 13 recently discovered SNPs for association with coronary heart disease in a case-control design including participants differing from those in the discovery samples (3829 participants with prevalent coronary heart disease and 48,897 controls free of the disease) and a prospective cohort design including 30,725 participants free of cardiovascular disease from Finland and Sweden. We modelled the 13 SNPs as a multilocus genetic risk score and used Cox proportional hazards models to estimate the association of genetic risk score with incident coronary heart disease. For case-control analyses we analysed associations between individual SNPs and quintiles of genetic risk score using logistic regression.

Findings: In prospective cohort analyses, 1264 participants had a first coronary heart disease event during a median 10·7 years' follow-up (IQR 6·7-13·6). Genetic risk score was associated with a first coronary heart disease event. When compared with the bottom quintile of genetic risk score, participants in the top quintile were at 1·66-times increased risk of coronary heart disease in a model adjusting for traditional risk factors (95% CI 1·35-2·04, p value for linear trend=7·3×10(-10)). Adjustment for family history did not change these estimates. Genetic risk score did not improve C index over traditional risk factors and family history (p=0·19), nor did it have a significant effect on net reclassification improvement (2·2%, p=0·18); however, it did have a small effect on integrated discrimination index (0·004, p=0·0006). Results of the case-control analyses were similar to those of the prospective cohort analyses.

Interpretation: Using a genetic risk score based on 13 SNPs associated with coronary heart disease, we can identify the 20% of individuals of European ancestry who are at roughly 70% increased risk of a first coronary heart disease event. The potential clinical use of this panel of SNPs remains to be defined.

Funding: The Wellcome Trust; Academy of Finland Center of Excellence for Complex Disease Genetics; US National Institutes of Health; the Donovan Family Foundation.

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