Association of Initial and Longitudinal Changes in C-reactive Protein With the Risk of Cardiovascular Disease, Cancer, and Mortality.

OBJECTIVE: To evaluate the value of serial C-reactive protein (CRP) measurements in predicting the risk of cardiovascular disease (CVD), cancer, and mortality. METHODS: The analysis was performed using data from two prospective, population-based observational cohorts: the Prevention of Renal and Vascular End-Stage Disease (PREVEND) study and the Framingham Heart Study (FHS). A total of 9253 participants had CRP measurements available at two examinations (PREVEND: 1997-1998 and 2001-2002; FHS Offspring cohort: 1995-1998 and 1998-2001). All CRP measurements were natural log-transformed before analyses. Cardiovascular disease included fatal and nonfatal cardiovascular, cerebrovascular and peripheral vascular events, and heart failure. Cancer included all malignancies except nonmelanoma skin cancers. RESULTS: The mean age of the study population at baseline was 52.4±12.1 years and 51.2% (n=4733) were women. Advanced age, female sex, smoking, body mass index, and total cholesterol were associated with greater increases in CRP levels over time (Pall<.001 in the multivariable model). Baseline CRP, as well as increase in CRP over time (ΔCRP), were associated with incident CVD (hazard ratio [HR]: 1.29 per 1-SD increase; 95% confidence interval [CI]: 1.29 to 1.47, and HR per 1-SD increase: 1.19; 95% CI: 1.09 to 1.29 respectively). Similar findings were observed for incident cancer (baseline CRP, HR: 1.17; 95% CI: 1.09 to 1.26; ΔCRP, HR: 1.08; 95% CI: 1.01 to 1.15) and mortality (baseline CRP, HR: 1.29; 95% CI: 1.21 to 1.37; ΔCRP, HR: 1.10; 95% CI: 1.05 to 1.16). CONCLUSION: Initial as well as subsequent increases in CRP levels predict future CVD, cancer, and mortality in the general population.

Genetics of the Framingham Heart Study population.

This chapter provides an introduction to the Framingham Heart Study and the genetic research related to cardiovascular diseases conducted in this unique population. It briefly describes the origins of the study, the risk factors that contribute to heart disease, and the approaches taken to discover the genetic basis of some of these risk factors. The genetic architecture of several biological risk factors has been explained using family studies, segregation analysis, heritability, and phenotypic and genetic correlations. Many quantitative trait loci underlying cardiovascular diseases have been discovered using different molecular markers. Additionally, initial results from genome-wide association studies using 116,000 markers and the prospects of using 550,000 markers for association studies are presented. Finally, the use of this unique sample to study genotype and environment interactions is described.