126 resultados para Cardiovascular-disease Risk
Resumo:
Alors que la consommation modérée d'alcool est liée à un risque plus faible de développer une maladie coronarienne, l'impact d'une consommation plus importante d'alcool sur les facteurs de risque cardiovasculaire (FRCV) et la maladie coronarienne est moins clair. Nous avons étudié l'association entre la consommation d'alcool, les FRCV et l'estimation du risque à dix ans de faire un événement cardiovasculaire dans l'étude populationnelle lausannoise CoLaus. Dans cette étude, 73% des participants consomment de l'alcool, 16% consomment de 14 à 34 unités d'alcool par semaine et 2% consomment 35 unités ou plus par semaine. Cet article montre notamment l'impact d'une consommation importante d'alcool sur les FRCVet passe en revue les liens entre la consommation d'alcool, le type de boissons et les FRCV. [Abstract] Moderate alcohol consumption has been associated with lower coronary heart disease (CHD) risk. However, the impact of higher alcohol consumption on cardiovascular risk factors (CVRFs) is conflicting. We examined the association between alcohol consumption, CVRFs and the estimated 10-year CHD risk in the population-based CoLaus study in Lausanne, Switzerland. Among 5'769 participants without cardiovascular disease, 73% of the participants were alcohol drinkers; 16% consumed 14-34 drinks/week and 2% consumed >= 35 drinks/week. This article shows the impact of high alcohol consumption on CVRFs and reviews the literature on the associations between alcohol consumption and CVRFs.
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Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.
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Objective: To assess the effectiveness of obesity markers to detect high (>5%) 10- year risk of fatal cardiovascular disease (CVD) as estimated using the SCORE function. Methods: Cross-sectional study including 3,047 women and 2,689 men aged 35-75 years (CoLaus study). Body fat percentage was assessed by tetrapolar bioimpedance. CVD risk was assessed using the SCORE risk function and gender and age-specific cut points for body fat were derived. The diagnostic accuracy of each obesity marker was evaluated through receiver operating characteristics (ROC) analysis. Results: Body fat presented a higher correlation with 10-year CVD risk than waist/hip ratio (WHR), waist or BMI: in men, r=0.31, 0.22, 0.19 and 0.12 and for body fat, WHR, waist and BMI, respectively; the corresponding values in women were 0.18, 0.15, 0.11 and 0.05, respectively (all p<0.05). In both genders, body fat showed the highest area under the ROC curve (AUC): in men, the AUC (and 95% confidence interval) were 76.0 (73.8 - 78.2), 67.3 (64.6 - 69.9), 65.8 (63.1 - 68.5) and 60.6 (57.9 - 63.5) for body fat, WHR, waist and BMI, respectively. In women, the corresponding values were 72.3 (69.2 - 75.3), 66.6 (63.1 - 70.2), 64.1 (60.6 - 67.6) and 58.8 (55.2 - 62.4). The use of body fat percentage criterion enabled to capture three times more subjects with high CVD risk than BMI criterion, and almost twice as much as WHR criterion.. Conclusions: Obesity defined by body fat percentage is more accurate to detect high 10-year risk of fatal CVD than obesity markers based on WHR, waist or BMI.
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BACKGROUND: Only few countries have cohorts enabling specific and up-to-date cardiovascular disease (CVD) risk estimation. Individual risk assessment based on study samples that differ too much from the target population could jeopardize the benefit of risk charts in general practice. Our aim was to provide up-to-date and valid CVD risk estimation for a Swiss population using a novel record linkage approach. METHODS: Anonymous record linkage was used to follow-up (for mortality, until 2008) 9,853 men and women aged 25-74 years who participated in the Swiss MONICA (MONItoring of trends and determinants in CVD) study of 1983-92. The linkage success was 97.8%, loss to follow-up 1990-2000 was 4.7%. Based on the ESC SCORE methodology (Weibull regression), we used age, sex, blood pressure, smoking, and cholesterol to generate three models. We compared the 1) original SCORE model with a 2) recalibrated and a 3) new model using the Brier score (BS) and cross-validation. RESULTS: Based on the cross-validated BS, the new model (BS = 14107×10(-6)) was somewhat more appropriate for risk estimation than the original (BS = 14190×10(-6)) and the recalibrated (BS = 14172×10(-6)) model. Particularly at younger age, derived absolute risks were consistently lower than those from the original and the recalibrated model which was mainly due to a smaller impact of total cholesterol. CONCLUSION: Using record linkage of observational and routine data is an efficient procedure to obtain valid and up-to-date CVD risk estimates for a specific population.
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BACKGROUND: Current guidelines recommend treating patients according to their absolute cardiovascular disease (CVD) risk. We examined perception of CVD risk among adults and how it can be compared with actual CVD risk. METHODS: The perception of CVD risk was assessed by two questions asking about participants' 'risk to get a heart attack or a stroke over the next 10 years' using semiquantitative and quantitative answers in a population-based survey of 816 individuals aged 40-64 years in the Seychelles (African region). Actual CVD risk was calculated using a standard risk prediction score and 24% of adults aged 40-64 years had elevated risk. RESULTS: Only 59% of individuals could give an estimate of perceived CVD risk based on the semiquantitative question and 31% based on the quantitative question. Reporting a perceived CVD risk was strongly associated with high socio-economic status (SES; odds ratio = 9). Among individuals who reported a perceived CVD risk, 48% overestimated their perceived risk versus their actual risk. Reporting a high perceived CVD risk was associated with treatment for CVD risk factors, older age, low SES, and overweight. Reporting a low perceived CVD risk was associated with male sex, younger age, education, normal BMI, and leisure time exercise. CONCLUSION: Only half of the individuals could provide an estimate of their perceived CVD risk, and this perception was strongly associated with SES. Individuals under treatment perceived higher CVD risk than nontreated individuals. Further studies should determine how risk-related information can be better conveyed to individuals as a means to improve adherence to healthy lifestyles and/or treatment.
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OBJECTIVE: The aims of the present study were to assess the associations between mood, anxiety and substance use disorders, including their subtypes, and the prevalence of cardiovascular risk factors (CVRFs). METHOD: Thorough physical investigations, biological measures and standardized interview techniques were used to assess 3716 subjects of an urban area, aged 35-66 years. RESULTS: Atypical depression was associated with increased prevalence of overweight, diabetes and the metabolic syndrome (OR = 1.5, 95% C.I. 1.1-2.0; OR = 2.0, 95% C.I. 1.1-3.5, OR = 1.6, 95% C.I. 1.0-2.4 respectively), whereas decreased prevalence of overweight was found in melancholic (OR = 0.7, 95% C.I. 0.6-0.9) and unspecified depression (OR = 0.8, 95% C.I. 0.7-1.0). Alcohol abuse was associated with diabetes (OR = 1.8, 95% C.I. 1.1-2.9) and dyslipidemia (OR = 1.3, 95% C.I. 1.0-1.8), alcohol dependence with dyslipidemia only (OR = 1.4, 95% C.I. 1.0-2.0). Almost all mental disorders were associated with a lifetime history of regular cigarette smoking, and atypical depression, alcohol misuse and drug dependence were associated with inactivity. CONCLUSION: To conclude results emphasize the need to subtype depression and to pay particular attention to the atypical subtype. Comorbid alcohol misuse may further increase the cardiovascular risk. Efforts to diminish smoking in subjects with mental disorders could be crucial measures to reduce their high incidence of cardiovascular disease.
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Background. Although acquired immune deficiency syndrome-associated morbidity has diminished due to excellent viral control, multimorbidity may be increasing among human immunodeficiency virus (HIV)-infected persons compared with the general population. Methods. We assessed the prevalence of comorbidities and multimorbidity in participants of the Swiss HIV Cohort Study (SHCS) compared with the population-based CoLaus study and the primary care-based FIRE (Family Medicine ICPC-Research using Electronic Medical Records) records. The incidence of the respective endpoints were assessed among SHCS and CoLaus participants. Poisson regression models were adjusted for age, sex, body mass index, and smoking. Results. Overall, 74 291 participants contributed data to prevalence analyses (3230 HIV-infected; 71 061 controls). In CoLaus, FIRE, and SHCS, multimorbidity was present among 26%, 13%, and 27% of participants. Compared with nonsmoking individuals from CoLaus, the incidence of cardiovascular disease was elevated among smoking individuals but independent of HIV status (HIV-negative smoking: incidence rate ratio [IRR] = 1.7, 95% confidence interval [CI] = 1.2-2.5; HIV-positive smoking: IRR = 1.7, 95% CI = 1.1-2.6; HIV-positive nonsmoking: IRR = 0.79, 95% CI = 0.44-1.4). Compared with nonsmoking HIV-negative persons, multivariable Poisson regression identified associations of HIV infection with hypertension (nonsmoking: IRR = 1.9, 95% CI = 1.5-2.4; smoking: IRR = 2.0, 95% CI = 1.6-2.4), kidney (nonsmoking: IRR = 2.7, 95% CI = 1.9-3.8; smoking: IRR = 2.6, 95% CI = 1.9-3.6), and liver disease (nonsmoking: IRR = 1.8, 95% CI = 1.4-2.4; smoking: IRR = 1.7, 95% CI = 1.4-2.2). No evidence was found for an association of HIV-infection or smoking with diabetes mellitus. Conclusions. Multimorbidity is more prevalent and incident in HIV-positive compared with HIV-negative individuals. Smoking, but not HIV status, has a strong impact on cardiovascular risk and multimorbidity.
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BACKGROUND: Atrial arrhythmias increase disease burden in the general adult population. Adults with congenital heart lesions constitute a rapidly growing group of patients with cardiovascular disease. We hypothesized that atrial arrhythmias increase with age and impair health outcomes in this population. METHODS AND RESULTS: We conducted a population-based analysis of prevalence, lifetime risk, mortality, and morbidity associated with atrial arrhythmias in adults with congenital heart disease from l983 to 2005. In 38 428 adults with congenital heart disease in 2005, 5812 had atrial arrhythmias. Overall, the 20-year risk of developing atrial arrhythmia was 7% in a 20-year-old subject and 38% in a 50-year-old subject. More than 50% of patients with severe congenital heart disease reaching age 18 years developed atrial arrhythmias by age 65 years. In patients with congenital heart disease, the hazard ratio of any adverse event in those with atrial arrhythmias compared with those without was 2.50 (95% confidence interval, 2.38 to 2.62; P<0.0001), with a near 50% increase in mortality (hazard ratio, 1.47; 95% confidence interval, 1.37 to 1.58; P<0.001), more than double the risk of morbidity (stroke or heart failure) (hazard ratio, 2.21; 95% confidence interval, 2.07 to 2.36; P<0.001), and 3 times the risk of cardiac interventions (hazard ratio, 3.00; 95% confidence interval, 2.81 to 3.20; P<0.001). CONCLUSIONS: Atrial arrhythmias occurred in 15% of adults with congenital heart disease. The lifetime incidence increased steadily with age and was associated with a doubling of the risk of adverse events. An increase in resource allocation should be anticipated to deal with this increasing burden.
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ABSTRACT: BACKGROUND: Chest pain raises concern for the possibility of coronary heart disease. Scoring methods have been developed to identify coronary heart disease in emergency settings, but not in primary care. METHODS: Data were collected from a multicenter Swiss clinical cohort study including 672 consecutive patients with chest pain, who had visited one of 59 family practitioners' offices. Using delayed diagnosis we derived a prediction rule to rule out coronary heart disease by means of a logistic regression model. Known cardiovascular risk factors, pain characteristics, and physical signs associated with coronary heart disease were explored to develop a clinical score. Patients diagnosed with angina or acute myocardial infarction within the year following their initial visit comprised the coronary heart disease group. RESULTS: The coronary heart disease score was derived from eight variables: age, gender, duration of chest pain from 1 to 60 minutes, substernal chest pain location, pain increases with exertion, absence of tenderness point at palpation, cardiovascular risks factors, and personal history of cardiovascular disease. Area under the receiver operating characteristics curve was of 0.95 with a 95% confidence interval of 0.92; 0.97. From this score, 413 patients were considered as low risk for values of percentile 5 of the coronary heart disease patients. Internal validity was confirmed by bootstrapping. External validation using data from a German cohort (Marburg, n = 774) revealed a receiver operating characteristics curve of 0.75 (95% confidence interval, 0.72; 0.81) with a sensitivity of 85.6% and a specificity of 47.2%. CONCLUSIONS: This score, based only on history and physical examination, is a complementary tool for ruling out coronary heart disease in primary care patients complaining of chest pain.
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Background: Several markers of atherosclerosis and of inflammation have been shown to predict coronary heart disease (CHD) individually. However, the utility of markers of atherosclerosis and of inflammation on prediction of CHD over traditional risk factors has not been well established, especially in the elderly. Methods: We studied 2202 men and women, aged 70-79, without baseline cardiovascular disease over 6-year follow-up to assess the risk of incident CHD associated with baseline noninvasive measures of atherosclerosis (ankle-arm index [AAI], aortic pulse wave velocity [aPWV]) and inflammatory markers (interleukin-6 [IL-6], C-reactive protein [CRP], tumor necrosis factor-a [TNF-a]). CHD events were studied as either nonfatal myocardial infarction or coronary death ("hard" events), and "hard" events plus hospitalization for angina, or the need for coronary-revascularization procedures (total CHD events). Results: During the 6-year follow-up, 283 participants had CHD events (including 136 "hard" events). IL-6, TNF-a and AAI independently predicted CHD events above Framingham Risk Score (FRS) with hazard ratios [HR] for the highest as compared with the lowest quartile for IL-6 of 1.95 (95%CI: 1.38-2.75, p for trend <0.001), TNF-a of 1.45 (95%CI: 1.04-2.02, p for trend 0.03), of 1.66 (95%CI: 1.19-2.31) for AAI 0.9, as compared to AAI 1.01-1.30. CRP and aPWV were not independently associated with CHD events. Results were similar for "hard" CHD events. Addition of IL-6 and AAI to traditional cardiovascular risk factors yielded the greatest improvement in the prediction of CHD; C-index for "hard"/total CHD events increased from 0.62/0.62 for traditional risk factors to 0.64/0.64 for IL-6 addition, 0.65/0.63 for AAI, and 0.66/0.64 for IL-6 combined with AAI. Being in the highest quartile of IL-6 combined with an AAI 0.90 or >1.40 yielded an HR of 2.51 (1.50-4.19) and 4.55 (1.65-12.50) above FRS, respectively. With use of CHD risk categories, risk prediction at 5 years was more accurate in models that included IL-6, AAI or both, with 8.0, 8.3 and 12.1% correctly reclassified, respectively. Conclusions: Among older adults, markers of atherosclerosis and of inflammation, particularly IL-6 and AAI, are independently associated with CHD. However, these markers only modestly improve cardiovascular risk prediction beyond traditional risk factors.
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AIMS: Resting heart rate is a promising modifiable cardiovascular risk marker in older adults, but the mechanisms linking heart rate to cardiovascular disease are not fully understood. We aimed to assess the association between resting heart rate and incident heart failure (HF) and cardiovascular mortality, and to examine whether these associations might be attributable to systemic inflammation and endothelial dysfunction. METHODS AND RESULTS: We studied 4084 older adults aged 70-82 years with known cardiovascular risk factors or previous cardiovascular disease, without pre-existing HF or beta-blockers in the PROSPER study. Over a 3.2-year follow-up period, we examined incident HF hospitalization and cardiovascular mortality according to resting heart rate, along with C-reactive protein (CRP), interleukin-6 (IL-6), tissue plasminogen activator (tPA), and von Willebrand factor (vWf). Mean heart rate was 67 b.p.m. for men and 70 b.p.m. for women. CRP, IL-6, tPA, and vWf levels were all positively correlated with heart rate. After multivariate adjustment, heart rate was associated with HF hospitalization [hazard ratio (HR) 1.78 for highest vs. lowest distribution third, 95% confidence interval (CI) 1.21-2.63, P= 0.003] and cardiovascular mortality (HR 1.74, 95% CI 1.23-2.47, P= 0.002). Further adjustment for both IL-6 and vWf levels decreased HR to 1.60 (95% CI 1.08-2.38, P= 0.020) for HF and to 1.50 (95% CI 1.04-2.15, P= 0.028) for cardiovascular mortality. CONCLUSION: Increased heart rate is associated with increased systemic inflammation and endothelial dysfunction. These factors are likely to contribute to, but do not fully explain, the risk of HF and cardiovascular death associated with increased heart rate in older age.
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BACKGROUND: Several markers of atherosclerosis and of inflammation have been shown to predict coronary heart disease (CHD) individually. However, the utility of markers of atherosclerosis and of inflammation on prediction of CHD over traditional risk factors has not been well established, especially in the elderly. METHODS: We studied 2202 men and women, aged 70-79, without baseline cardiovascular disease over 6-year follow-up to assess the risk of incident CHD associated with baseline noninvasive measures of atherosclerosis (ankle-arm index [AAI], aortic pulse wave velocity [aPWV]) and inflammatory markers (interleukin-6 [IL-6], C-reactive protein [CRP], tumor necrosis factor-a [TNF-a]). CHD events were studied as either nonfatal myocardial infarction or coronary death ("hard" events), and "hard" events plus hospitalization for angina, or the need for coronary-revascularization procedures (total CHD events). RESULTS: During the 6-year follow-up, 283 participants had CHD events (including 136 "hard" events). IL-6, TNF-a and AAI independently predicted CHD events above Framingham Risk Score (FRS) with hazard ratios [HR] for the highest as compared with the lowest quartile for IL-6 of 1.95 (95%CI: 1.38-2.75, p for trend<0.001), TNF-a of 1.45 (95%CI: 1.04-2.02, p for trend 0.03), of 1.66 (95%CI: 1.19-2.31) for AAI £0.9, as compared to AAI 1.01-1.30. CRP and aPWV were not independently associated with CHD events. Results were similar for "hard" CHD events. Addition of IL-6 and AAI to traditional cardiovascular risk factors yielded the greatest improvement in the prediction of CHD; C-index for "hard"/total CHD events increased from 0.62/0.62 for traditional risk factors to 0.64/0.64 for IL-6 addition, 0.65/0.63 for AAI, and 0.66/0.64 for IL-6 combined with AAI. Being in the highest quartile of IL-6 combined with an AAI £ 0.90 or >1.40 yielded an HR of 2.51 (1.50-4.19) and 4.55 (1.65-12.50) above FRS, respectively. With use of CHD risk categories, risk prediction at 5 years was more accurate in models that included IL-6, AAI or both, with 8.0, 8.3 and 12.1% correctly reclassified respectively. CONCLUSIONS: Among older adults, markers of atherosclerosis and of inflammation, particularly IL-6 and AAI, are independently associated with CHD. However, these markers only modestly improve cardiovascular risk prediction beyond traditional risk factors. Acknowledgments: This study was supported by Contracts NO1-AG-6-2101, NO1-AG-6- 2103, and NO1-AG-6-2106 of the National Institute on Aging. This research was supported in part by the Intramural Research Program of the NIH, National Institute on Aging.
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Recent progresses in genetics have opened new avenues to further our understanding of the pathophysiological mechanisms underlying cardiovascular disease, raising, new expectations in the field of personalized medicine. Genetic tests may have a high predictive value for rare monogenic diseases. The situation is very different for common polygenic diseases, such as myocardial infarction, type 2 diabetes or stroke. The results from recent genome-wide association studies have provided useful information for research, but have not yet been proven to be clinically useful. It is therefore currently not recommended to conducted genetic testing to guide cardiovascular prevention neither in clinical nor in public health settings.
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AIMS: Common carotid artery intima-media thickness (CCIMT) is widely used as a surrogate marker of atherosclerosis, given its predictive association with cardiovascular disease (CVD). The interpretation of CCIMT values has been hampered by the absence of reference values, however. We therefore aimed to establish reference intervals of CCIMT, obtained using the probably most accurate method at present (i.e. echotracking), to help interpretation of these measures. METHODS AND RESULTS: We combined CCIMT data obtained by echotracking on 24 871 individuals (53% men; age range 15-101 years) from 24 research centres worldwide. Individuals without CVD, cardiovascular risk factors (CV-RFs), and BP-, lipid-, and/or glucose-lowering medication constituted a healthy sub-population (n = 4234) used to establish sex-specific equations for percentiles of CCIMT across age. With these equations, we generated CCIMT Z-scores in different reference sub-populations, thereby allowing for a standardized comparison between observed and predicted ('normal') values from individuals of the same age and sex. In the sub-population without CVD and treatment (n = 14 609), and in men and women, respectively, CCIMT Z-scores were independently associated with systolic blood pressure [standardized βs 0.19 (95% CI: 0.16-0.22) and 0.18 (0.15-0.21)], smoking [0.25 (0.19-0.31) and 0.11 (0.04-0.18)], diabetes [0.19 (0.05-0.33) and 0.19 (0.02-0.36)], total-to-HDL cholesterol ratio [0.07 (0.04-0.10) and 0.05 (0.02-0.09)], and body mass index [0.14 (0.12-0.17) and 0.07 (0.04-0.10)]. CONCLUSION: We estimated age- and sex-specific percentiles of CCIMT in a healthy population and assessed the association of CV-RFs with CCIMT Z-scores, which enables comparison of IMT values for (patient) groups with different cardiovascular risk profiles, helping interpretation of such measures obtained both in research and clinical settings.
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CONTEXT: Plasma levels of C-reactive protein (CRP) are independently associated with risk of coronary heart disease, but whether CRP is causally associated with coronary heart disease or merely a marker of underlying atherosclerosis is uncertain. OBJECTIVE: To investigate association of genetic loci with CRP levels and risk of coronary heart disease. DESIGN, SETTING, AND PARTICIPANTS: We first carried out a genome-wide association (n = 17,967) and replication study (n = 13,615) to identify genetic loci associated with plasma CRP concentrations. Data collection took place between 1989 and 2008 and genotyping between 2003 and 2008. We carried out a mendelian randomization study of the most closely associated single-nucleotide polymorphism (SNP) in the CRP locus and published data on other CRP variants involving a total of 28,112 cases and 100,823 controls, to investigate the association of CRP variants with coronary heart disease. We compared our finding with that predicted from meta-analysis of observational studies of CRP levels and risk of coronary heart disease. For the other loci associated with CRP levels, we selected the most closely associated SNP for testing against coronary heart disease among 14,365 cases and 32,069 controls. MAIN OUTCOME MEASURE: Risk of coronary heart disease. RESULTS: Polymorphisms in 5 genetic loci were strongly associated with CRP levels (% difference per minor allele): SNP rs6700896 in LEPR (-14.8%; 95% confidence interval [CI], -17.6% to -12.0%; P = 6.2 x 10(-22)), rs4537545 in IL6R (-11.5%; 95% CI, -14.4% to -8.5%; P = 1.3 x 10(-12)), rs7553007 in the CRP locus (-20.7%; 95% CI, -23.4% to -17.9%; P = 1.3 x 10(-38)), rs1183910 in HNF1A (-13.8%; 95% CI, -16.6% to -10.9%; P = 1.9 x 10(-18)), and rs4420638 in APOE-CI-CII (-21.8%; 95% CI, -25.3% to -18.1%; P = 8.1 x 10(-26)). Association of SNP rs7553007 in the CRP locus with coronary heart disease gave an odds ratio (OR) of 0.98 (95% CI, 0.94 to 1.01) per 20% lower CRP level. Our mendelian randomization study of variants in the CRP locus showed no association with coronary heart disease: OR, 1.00; 95% CI, 0.97 to 1.02; per 20% lower CRP level, compared with OR, 0.94; 95% CI, 0.94 to 0.95; predicted from meta-analysis of the observational studies of CRP levels and coronary heart disease (z score, -3.45; P < .001). SNPs rs6700896 in LEPR (OR, 1.06; 95% CI, 1.02 to 1.09; per minor allele), rs4537545 in IL6R (OR, 0.94; 95% CI, 0.91 to 0.97), and rs4420638 in the APOE-CI-CII cluster (OR, 1.16; 95% CI, 1.12 to 1.21) were all associated with risk of coronary heart disease. CONCLUSION: The lack of concordance between the effect on coronary heart disease risk of CRP genotypes and CRP levels argues against a causal association of CRP with coronary heart disease.