Dataset Information

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.

ABSTRACT: 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).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.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 (? = 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.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.

SUBMITTER: Brautbar A

PROVIDER: S-EPMC3595115 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

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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.

Brautbar Ariel A Pompeii Lisa A LA Dehghan Abbas A Ngwa Julius S JS Nambi Vijay V Virani Salim S SS Rivadeneira Fernando F Uitterlinden André G AG Hofman Albert A Witteman Jacqueline C M JC Pencina Michael J MJ Folsom Aaron R AR Cupples L Adrienne LA Ballantyne Christie M CM Boerwinkle Eric E

Atherosclerosis 20120612 2

<h4>Objective</h4>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).<h4>Methods</h4>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 ...[more]

PMID: 22789513

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Project description:Recent literature has presented evidence that cardiovascular risk factors (CVRF) play an important role on cognitive performance in elderly individuals, both those who are asymptomatic and those who suffer from symptoms of neurodegenerative disorders. Findings from studies applying neuroimaging methods have increasingly reinforced such notion. Studies addressing the impact of CVRF on brain anatomy changes have gained increasing importance, as recent papers have reported gray matter loss predominantly in regions traditionally affected in Alzheimer's disease (AD) and vascular dementia in the presence of a high degree of cardiovascular risk. In the present paper, we explore the association between CVRF and brain changes using pattern recognition techniques applied to structural MRI and the Framingham score (a composite measure of cardiovascular risk largely used in epidemiological studies) in a sample of healthy elderly individuals. We aim to answer the following questions: is it possible to decode (i.e., to learn information regarding cardiovascular risk from structural brain images) enabling individual predictions? Among clinical measures comprising the Framingham score, are there particular risk factors that stand as more predictable from patterns of brain changes? Our main findings are threefold: (i) we verified that structural changes in spatially distributed patterns in the brain enable statistically significant prediction of Framingham scores. This result is still significant when controlling for the presence of the APOE 4 allele (an important genetic risk factor for both AD and cardiovascular disease). (ii) When considering each risk factor singly, we found different levels of correlation between real and predicted factors; however, single factors were not significantly predictable from brain images when considering APOE4 allele presence as covariate. (iii) We found important gender differences, and the possible causes of that finding are discussed.

Project description:BackgroundRemnant lipoproteins (RLPs), the triglyceride-enriched precursors to low-density lipoprotein, are an emerging risk factor for coronary heart disease (CHD). We sought to determine the association of RLP cholesterol (RLP-C) levels with incident CHD in 2 diverse, prospective, longitudinal observational US cohorts.Methods and resultsWe analyzed cholesterol levels from serum lipoprotein samples separated via density gradient ultracentrifugation in 4114 US black participants (mean age 53.8 years, 64% women) from the Jackson Heart Study and a random sample of 818 predominantly white participants (mean age 57.3 years, 52% women) from the Framingham Offspring Cohort Study. Multivariable-adjusted hazard ratios (HRs) for RLP-C (the sum of very low-density lipoprotein3 cholesterol and intermediate-density lipoprotein cholesterol) were derived to estimate associations with incident CHD events consisting of myocardial infarction, CHD death, and revascularizations for each cohort separately and as a combined population. There were 146 CHD events in the combined population. After adjustments for age, sex, body mass index, smoking, blood pressure, diabetes, and lipid-lowering therapy for the combined population, RLP-C (HR 1.23 per 1-SD increase, 95% CI 1.06-1.42, P<0.01) and intermediate-density lipoprotein cholesterol (HR 1.26 per 1-SD increase, 95% CI 1.08-1.47, P<0.01) predicted CHD during an 8-year follow-up. Associations were attenuated by high-density lipoprotein cholesterol and ultimately lost significance with inclusion of real low-density lipoprotein cholesterol, which excludes Lp(a) and IDL cholesterol fractions. Similar associations were seen in multivariable analyses within each cohort.ConclusionRLP-C levels are predictive of incident CHD in this diverse group of primary prevention subjects. Interventions aimed at reducing RLP-C to prevent CHD warrant further intensive investigation.Clinical trial registrationURL: http://www.ClinicalTrials.gov. Unique identifier: NCT00415415.

Dataset Information

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.

Publications

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.

Similar Datasets

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