A genetic risk score based on direct associations with coronary heart disease improves coronary heart disease risk prediction in the Atherosclerosis Risk in Communities (ARIC), but not in the Rotterdam and Framingham Offspring, Studies.
OBJECTIVE
Multiple studies have identified single-nucleotide polymorphisms (SNPs) that are associated with coronary heart disease (CHD). We examined whether SNPs selected based on predefined criteria will improve CHD risk prediction when added to traditional risk factors (TRFs).


METHODS
SNPs were selected from the literature based on association with CHD, lack of association with a known CHD risk factor, and successful replication. A genetic risk score (GRS) was constructed based on these SNPs. Cox proportional hazards model was used to calculate CHD risk based on the Atherosclerosis Risk in Communities (ARIC) and Framingham CHD risk scores with and without the GRS.


RESULTS
The GRS was associated with risk for CHD (hazard ratio [HR] = 1.10; 95% confidence interval [CI]: 1.07-1.13). Addition of the GRS to the ARIC risk score significantly improved discrimination, reclassification, and calibration beyond that afforded by TRFs alone in non-Hispanic whites in the ARIC study. The area under the receiver operating characteristic curve (AUC) increased from 0.742 to 0.749 (Δ = 0.007; 95% CI, 0.004-0.013), and the net reclassification index (NRI) was 6.3%. Although the risk estimates for CHD in the Framingham Offspring (HR = 1.12; 95% CI: 1.10-1.14) and Rotterdam (HR = 1.08; 95% CI: 1.02-1.14) Studies were significantly improved by adding the GRS to TRFs, improvements in AUC and NRI were modest.


CONCLUSIONS
Addition of a GRS based on direct associations with CHD to TRFs significantly improved discrimination and reclassification in white participants of the ARIC Study, with no significant improvement in the Rotterdam and Framingham Offspring Studies.
Department of Medical Genetics, Marshfield Clinic, Marshfield, WI, USA.
Ariel
A
Brautbar
Lisa A
LA
Pompeii
Abbas
A
Dehghan
Julius S
JS
Ngwa
Vijay
V
Nambi
Salim S
SS
Virani
Fernando
F
Rivadeneira
André G
AG
Uitterlinden
Albert
A
Hofman
Jacqueline C M
JC
Witteman
Michael J
MJ
Pencina
Aaron R
AR
Folsom
L Adrienne
LA
Cupples
Christie M
CM
Ballantyne
Eric
E
Boerwinkle
D019540:Area Under Curve; D003327:Coronary Disease / Q000208:ethnology / Q000235:genetics* / Q000401:mortality; D016002:Discriminant Analysis; D005260:Female; D020022:Genetic Predisposition to Disease; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D008957:Models, Genetic; D015999:Multivariate Analysis; D009426:Netherlands / Q000453:epidemiology; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D011379:Prognosis; D016016:Proportional Hazards Models; D011446:Prospective Studies; D012372:ROC Curve; D018570:Risk Assessment; D012307:Risk Factors; D014481:United States / Q000453:epidemiology; D044465:White People / Q000235:genetics