Plasma proteomics and incident coronary heart disease.

Introduction: DNA methylation patterns used to characterize rate of aging (i.e., epigenetic age acceleration) predict all-cause mortality independently of chronological age and traditional risk factors. It remains unclear how epigenetic age acceleration is associated with cardiovascular disease risk and subclinical atherosclerosis. Hypothesis: Higher epigenetic age acceleration is associated prospectively with greater risk of coronary heart disease (CHD), heart failure (HF), and peripheral arterial disease (PAD) and cross-sectionally with higher carotid intima-medial thickness (IMT). Methods: Age acceleration of blood was estimated by two published methods (Horvath and Hannum) using DNA methylation levels (Illumina 450K array) at 353 and 71 CpG sites in African Americans of the Atherosclerosis Risk in Communities study in 1990-95 (baseline). Among those without prevalent disease at baseline, Cox and linear regression models were used to estimate the association of age acceleration with incident cardiovascular events occurring through 2013 and with carotid IMT cross-sectionally at baseline. Results were stratified by follow-up time for HF due to violation of the proportional hazards assumption. Results: Participants [mean baseline age: 57 years (range: 47-72)] were followed prospectively for a mean 17 years. In fully-adjusted models (Figure), a 1 SD increment in Hannum epigenetic age acceleration was associated with 15-31% greater hazard of incident cardiovascular outcomes, except for HF in later follow-up. Associations using Horvath age acceleration were similar, except it was not associated with myocardial infarction. Cross-sectionally, a 1 SD increment in each age acceleration measure was associated with 0.01 higher baseline carotid IMT (both P ≤ 0.01). Conclusion: This study of African Americans provides evidence that epigenetic age acceleration is associated with greater risk of CHD, HF, and PAD events and higher extent of carotid atherosclerosis, independently of traditional risk factors.

The Framingham Heart Study has contributed importantly to understanding of the causes of coronary heart disease (CHD), stroke, and other cardiovascular diseases. Framingham research has helped define the quantitative and additive nature of these causes or, as they are now called, “cardiovascular risk factors.”1 The National Cholesterol Education Program (NCEP)2 3 has made extensive use of Framingham data in developing its strategy for preventing CHD by controlling high cholesterol levels. The NCEP guidelines2 3 adjust the intensity of cholesterol-lowering therapy with absolute risk as determined by summation of risk factors. The National High Blood Pressure Education Program (NHBPEP) has set forth a parallel approach for blood pressure control. In contrast to the NCEP,2 however, earlier NHBPEP reports issued through the Joint National Committee4 did not match the intensity of therapy to absolute risk for CHD. “Normalization” of blood pressure is the essential goal of therapy regardless of risk status. Blood pressure–lowering therapy is carried out as much for prevention of stroke and other cardiovascular complications as for reduction of CHD risk. Nonetheless, risk assessment could be important for making decisions about type and intensity of therapy for hypertension. Thus, the most recent Joint National Committee report5 gives more attention to risk stratification for adjustment of therapy for hypertension. Although Framingham data have already been influential in the development of national guidelines for risk factor management, the opportunity may exist for both cholesterol and blood pressure programs to draw more extensively from Framingham results when formulating improved risk assessment guidelines and recommending more specific strategies for risk factor modification. The American Heart Association has previously used Framingham risk factor data to prepare charts for estimating CHD risk. Framingham investigators of the National Heart, Lung, and Blood Institute prepared the original charts and have now revised …

BackgroundLow dietary intake of the essential nutrient choline and its metabolite betaine may increase atherogenesis both through effects on homocysteine methylation pathways as well as through choline's antioxidants properties. Nutrient values for many common foods for choline and betaine have recently become available in the U.S. nutrient composition database. Our objective was to assess the association of dietary intake of choline and betaine with incident coronary heart disease (CHD), adjusting for dietary intake measurement error.MethodsWe conducted a prospective investigation of the relation between usual intake of choline and betaine with the risk of CHD in 14,430 middle-aged men and women of the biethnic Atherosclerosis Risk in Communities study. A semi-quantitative food frequency questionnaire was used to assess nutrient intake. Proportional hazard regression models were used to calculate the risk of incident CHD. A regression calibration method was used to adjust for measurement error.ResultsDuring an average 14 years of follow-up (1987–2002), 1,072 incident CHD events were documented. Compared with the lowest quartile of intake, incident CHD risk was slightly and non-significantly higher in the highest quartile of choline and choline plus betaine, HR = 1.22 (0.91, 1.64) and HR = 1.14 (0.85, 1.53), controlling for age, sex, education, total energy intake, dietary intakes of folate, methionine and vitamin B6. No association was found between dietary choline intake and incident CHD when correcting for measurement error.ConclusionHigher intakes of choline and betaine were not protective for incident CHD. Similar investigations in other populations are of interest.

Establishing new approaches for the prevention and treatment of stroke relies on identifying modifiable risk factors that contribute to the development of this complex disease. Mendelian randomization (MR) studies, analogous to naturally occurring randomized trials, can assess causality of potentially modifiable biomarkers and offer new insights into biological pathways. Stroke is the second leading cause of death worldwide and the chief determinant of long-term disability. Stroke is a heterogeneous disease arising from several distinct underlying pathologies and is typically classified as ischemic or hemorrhagic, and further subclassified using imaging data. Ischemic stroke (IS), including its 3 main subtypes: small vessel disease, large vessel disease, and cardioembolic stroke, accounts for ≈80% of stroke and is the result of an interrupted blood supply, leading to localized areas of ischemia in the brain. Small vessel disease may be a consequence of nonatherosclerotic, as well as atherosclerotic, mechanisms that result in an occlusion of the small perforating arteries, whereas large vessel disease results from occlusions or emboli from plaque rupture in larger vessels, such as a carotid artery. Cardioembolic stroke arises typically from emboli from the heart. By contrast, hemorrhagic stroke is a consequence of intracerebral hemorrhage (bleeding into the brain) or subarachnoid hemorrhage (bleeding into the subarachnoid space). These diverse stroke subtypes have distinct underlying pathologies reflecting different risk factor distributions. MR studies, using genetic variants as instrumental variables, afford a powerful approach to assessing causality of risk factors and avoid biases inherent in observational studies, including confounding and reverse causation. This review considers the contribution of MR studies to stroke epidemiology and their relevance to understanding risk factors and new therapeutic targets for stroke. Meta-analyses of large prospective studies have enhanced our knowledge of classical and emerging risk factors for stroke.1–4 Classical risk factors for stroke include nonmodifiable characteristics, …

A single-nucleotide polymorphism on chromosome 9p21, rs10757274 (9p21 allele), has been shown to predict coronary heart disease (CHD) in whites. We evaluated whether adding the 9p21 allele to traditional risk factors (RFs) improved CHD risk prediction in whites from the Atherosclerosis Risk in Communities study and whether changes in risk prediction would modify lipid therapy recommendations. Whites (n=9998) in the Atherosclerosis Risk in Communities study for whom the 9p21 genotype and traditional RF information was available were included. Using Cox proportional hazards models, the Atherosclerosis Risk in Communities Cardiovascular Risk Score, which is based on traditional RFs, was determined. A total of 1349 individuals (13.5%) developed incident CHD events during a period of 14.6 years. Adding the 9p21 allele to traditional RFs was associated with a hazard ratio of incident CHD of 1.2 per allele (P<0.000003) and a significant increase in the area under the curve of the receiver operating characteristic from 0.782 to 0.786 (95% CI, 0.001, 0.007). The 9p21 allele's greatest influence to the Atherosclerosis Risk in Communities Cardiovascular Risk Score was observed in the intermediate-low (>5% to <or=10% 10-year CHD risk) and intermediate-high (>10% to <or=20% 10-year CHD risk) categories, with 12.1% and 12.6% reclassified, respectively. This may impact therapy because 90% of these reclassified individuals had low-density lipoprotein cholesterol >100 mg/dL. Adding the 9p21 allele to traditional RFs in whites in the Atherosclerosis Risk in Communities study modestly improved CHD risk prediction in the intermediate categories.

Background: Dietary protein intake in the U.S. has increased substantially over the past decades, but studies examining the relationship between protein intake and coronary heart disease (CHD) are sparse. Our objective was to assess the relationship of total protein, animal protein, and vegetable protein with risk of CHD in a large, community-based cohort. Research Design and Methods: Participants from the Atherosclerosis Risk in Communities Study (ARIC) who were free of cardiovascular disease at baseline (1987-89) were included in this analysis. Dietary intake was assessed by an interviewer-administered 66-item food frequency questionnaire at baseline and again approximately 6 years later. CHD was defined as a definite or probable myocardial infarction, death from CHD, a cardiac procedure, or electrocardiographic evidence of a silent myocardial infarction. Cox proportional hazards models were used to calculate multivariable hazard ratios and 95% CIs where exposure status was a time-dependent covariate with baseline dietary data used as the exposure for the period between baseline and visit 3, and the average intake of visits 1 and 3 afterwards. Results: With a median follow up time of 19.8 years there were 1,611 CHD events among 10,395 eligible participants. We did not observe significant associations between total protein, animal protein, or vegetable protein intake and incident CHD in either the minimally adjusted or fully adjusted models ( Table ). Similarly, hazard ratios for substituting 50 grams of vegetable protein for animal protein did not result in a significant risk change (HR=0.97, 95% CI: 0.56-1.69). Conclusion: In this large community-based cohort intake of total protein, animal-derived protein, and plant-derived protein were not significantly associated with incident CHD. Studies using whole foods (e.g., chicken, eggs, legumes) as protein exposures may allow for a more nuanced analysis of the protein-CHD relationship. Adjusted hazard ratios (95% CI) for incident CHD by quartile of protein intake at baseline (1987-89) Total Protein Intake Animal Protein Intake Vegetable Protein Intake Grams/Day Incident CHD Cases (n) HR (95% CI) Min Adj ‡ HR (95% CI) Fully Adj * Grams/Day Incident CHD Cases (n) HR (95% CI) Min Adj ‡ HR (95% CI) Fully Adj * Grams/Day Incident CHD Cases (n) HR (95% CI) Min Adj ‡ HR (95% CI) Fully Adj * Q1 &lt;52.3 378 (2,598) 1 (ref) 1 (ref) &lt;37.4 384 (2,599) 1 (ref) 1 (ref) &lt;12.3 354 (2,599) 1 (ref) 1 (ref) Q2 52.3-67.9 369 (2,599) 0.95 (0.82-1.10) 0.94 (0.81-1.10) 37.4-50.4 354 (2,598) 0.85 (0.74-0.98) 0.83 (0.72-0.97) 12.3-16.5 385 (2,598) 0.92 (0.79-1.07) 0.95 (0.81-1.10) Q3 67.9-86.0 418 (2,599) 0.97 (0.82-1.14) 0.95 (0.80-1.13) 50.4-65.9 433 (2,600) 0.91 (0.78-1.06) 0.89 (0.76-1.05) 16.5-21.8 408 (2,599) 1.06 (0.91-1.24) 1.11 (0.95-1.31) Q4 &gt;86.0 446 (2,599) 0.97 (0.79-1.19) 0.90 (0.71-1.14) &gt;65.9 440 (2,598) 1.01 (0.85-1.20) 0.91 (0.74-1.12) &gt;21.8 464 (2,599) 0.91 (0.75-1.10) 0.96 (0.79-1.17) p for trend 0.83 0.47 0.80 0.47 0.76 0.73 ‡ Adjustment for age, sex, and race. * Additional adjustment for center and baseline levels of education, hypertension, type 2 diabetes, LDL, HDL, triglycerides, waist-to-hip ratio, physical activity, smoking status, alcohol intake, and time varying levels of total energy intake, and total carbohydrate intake.

APOL1 renal risk variants are strongly associated with chronic kidney disease in Black adults, but reported associations with cardiovascular disease (CVD) have been conflicting. We examined associations of APOL1 with incident coronary heart disease (n=323), ischemic stroke (n=331), and the composite CVD outcome (n=500) in 10 605 Black participants of the REGARDS study (Reasons for Geographic and Racial Differences in Stroke). Primary analyses compared individuals with APOL1 high-risk genotypes to APOL1 low-risk genotypes in Cox proportional hazards models adjusted for CVD risk factors and African ancestry. APOL1 high-risk participants were younger and more likely to have albuminuria at baseline than APOL1 low-risk participants. The risk of incident stroke, coronary heart disease, or composite CVD end point did not significantly differ by APOL1 genotype status in multivariable models. The association of APOL1 genotype with incident composite CVD differed by diabetes mellitus status (Pinteraction=0.004). In those without diabetes mellitus, APOL1 high-risk genotypes associated with greater risk of incident composite CVD (hazard ratio, 1.67; 95% confidence interval, 1.12-2.47) compared with those with APOL1 low-risk genotypes in multivariable adjusted models. This latter association was driven by ischemic strokes (hazard ratio, 2.32; 95% confidence interval, 1.33-4.07), in particular, those related to small vessel disease (hazard ratio, 5.10; 95% confidence interval, 1.55-16.56). There was no statistically significant association of APOL1 genotypes with incident CVD in subjects with diabetes mellitus. The APOL1 high-risk genotype was associated with higher stroke risk in individuals without but not those with chronic kidney disease in fully adjusted models. APOL1 high-risk status is associated with CVD events in community-dwelling Black adults without diabetes mellitus.

Associations between weight change and coronary heart disease (CHD) have been inconsistent possibly due to differences in length of weight change or follow-up studied. Short-term (ST) decreases in weight close to an event could be unintentional and due to underlying disease, while long-term (LT) increases in adult weight might cause CHD. We examined associations of LT and ST weight change on incident CHD using extant data from 15,689 African Americans and Whites 45–64 years at baseline (1987–89), who were followed through 2005. LT weight change, measured weight at baseline minus recalled weight at age 25, was analyzed excluding events within 3 years after baseline. The effect of ST weight change between two successive visits on CHD events in the subsequent interval was examined using a time-dependent covariate approach. Multivariable adjusted Cox regression was used for analysis. As hypothesized, ST weight loss (>3% of weight) was associated with elevated CHD risk (RR 1.46; 95% CI: 1.18, 1.81) compared to weight maintenance (±3%), however, contrary to our hypothesis LT weight loss was also associated with incident CHD (RR 1.31; 95% CI: 1.00, 1.73). As predicted LT weight gain elevated CHD risk (RR for ≥ 30% gain 1.38; 95% CI: 1.08, 1.76) and ST weight gain was not associated with increased risk. This work illustrates the complex nature of the relationship between the timing of changes in weight and CHD events. Grant Funding Source: National Heart, Lung and Blood Institute [grant number 1RC1HL099429]

Introduction: Ultra-processed food defined as food and drink products formulated through sequences of industrial processes, and generally contain non-culinary used additives. Previous studies have linked higher ultra-processed food intake with several cardiometabolic and cardiovascular diseases. However, longitudinal evidence from US populations remains scarce. Hypothesis: We hypothesized that higher intake of ultra-processed food is associated with higher risk of coronary heart disease (CHD). Methods: We selected 12,607 adults aged 44-66 years in 4 US communities from the ARIC study at baseline. Dietary intake data were collected through a validated 66-item food frequency questionnaire. Ultra-processed foods were defined using the NOVA classification and the level of intake was calculated for each participant. We conducted Cox proportional hazards models to study the association between quartiles of ultra-processed food intake and incident CHD. Nonlinearity was assessed by using restricted cubic spline regression. Results: There were 1,899 incident CHD cases documented after an median follow up of 27 years (291,285.2 person-years). Incidence rates were higher in the highest quartile of ultra-processed food intake (71.6 per 10,000 person-years; 95% CI, 65.8-78.0) compared to the lowest quartile (59.7 per 10,000 person-years; 95% CI, 54.3-65.7). Participants in the highest vs. lowest quartile were associated with a 18% higher risk of CHD (Hazard ratio 1.18 [95% CI, 1.04 - 1.34]; P-trend = 0.010) after adjusting for sociodemographic factors and health behaviors. An approximately linear relationship was observed between ultra-processed food intake and risk of CHD after 4 servings/day ( Figure ). Conclusion: In conclusion, higher ultra-processed food intake was associated with a higher risk of coronary heart disease among middle-aged US adults. Further prospective studies are needed to confirm these findings and to investigate the mechanisms by which ultra-processed food may affect health.

Background— Evidence from in vitro studies indicates that small dense LDL (sd-LDL) is more atherogenic than large buoyant LDL. Previously, sd-LDL has been associated with risk for vascular disease. However, the lack of a standardized sd-LDL assay has hampered its clinical application. Objectives— We tested the hypothesis that elevated plasma sd-LDL-cholesterol (sd-LDL-C) level is associated with risk for incident coronary heart disease (CHD) and stroke in the ARIC cohort. Methods— Plasma sd-LDL-C was measured in 11,419 men and women of the biracial ARIC study using a newly developed automated homogeneous assay. A proportional hazards model was used to examine the relationship between sd-LDL-C, vascular risk factors, and risk for CHD events and stroke over a period of ≈10 years. Results— Mean plasma sd-LDL-C was higher in Caucasians than in African Americans (45.2 vs. 37.4 mg/dL, p&lt;0.0001). Plasma sd-LDL-C levels were strongly correlated with an atherogenic lipid profile and were higher in diabetics vs. non-diabetics (49.6 vs. 42.3 mg/dL, p&lt;0.0001, respectively). sd-LDL-C was associated with incident CHD in a basic model as well as a model that included traditional risk factors and hs-CRP with hazard ratios (HRs) of 1.99 (95%CI: 1.68-2.36) and 1.56 (95%CI: 1.26-1.93) for the highest vs. the lowest quartile, respectively (Table). We did not find a significant association of sd-LDL-C with risk for stroke (Table). Conclusions— sd-LDL-C is associated with incident CHD but does not predict risk for stroke in ARIC participants. Further studies will need to determine whether sd-LDL-C will add value beyond traditional risk factors to cardiovascular risk assessment in clinical practice.

Introduction: Fat infiltration into muscle reduces muscle density and increases the risk for metabolic dysfunction, mobility disability and mortality. We assessed abdominal muscle density and muscle area in relation to incident coronary heart disease (CHD) events. Methods: Adults (mean age 64.6 ± 9.6) from the Multi-Ethnic Study of Atherosclerosis body composition ancillary study had computed tomography (CT)-derived measures of muscle density, muscle area and visceral fat at the L2-L4 spinal column levels between 2002-05 and were followed for incident events. Using sex-stratified Cox proportional hazards regression, associations of muscle density and muscle area (in the same model) with CHD events were assessed using restricted cubic splines with adjustment for confounders including visceral adiposity and BMI. Results: After 10.3±2.9 years of follow up, 924 males had 70 CHD (7.6%) events and 945 females had 44 CHD (4.7%) events. Muscle density was higher in males (44.5±4.9 HU) than females (40.1±5.2 HU), as was muscle area (116.7±23.9 vs. 80.4±23.9 cm 2 , respectively). Among males, and in mutually adjusted models, each incremental SD of muscle density was inversely associated with CHD (HR=0.67; 95%CI=0.49-0.92), while each SD of muscle area was associated with higher risk of CHD (HR=1.75; 95%CI=1.34-2.28; Figure). Overall patterns were similar but less strong among females for density (HR=0.79; 95%CI=0.50-1.22) and area (HR=1.17; 95%CI=0.79-1.73). Conclusions: Greater muscle density is associated with lower CHD risk, while greater muscle size is associated with increased CHD risk. These associations were independent of traditional CHD risk factors and measures of visceral and total body adiposity. Quantity and quality of skeletal muscle may represent distinct aspects of aging and physical functioning that are important in heart health.

The Framingham Heart Study produced sex-specific coronary heart disease (CHD) prediction functions for assessing risk of developing incident CHD in a white middle-class population. Concern exists regarding whether these functions can be generalized to other populations. To test the validity and transportability of the Framingham CHD prediction functions per a National Heart, Lung, and Blood Institute workshop organized for this purpose. Sex-specific CHD functions were derived from Framingham data for prediction of coronary death and myocardial infarction. These functions were applied to 6 prospectively studied, ethnically diverse cohorts (n = 23 424), including whites, blacks, Native Americans, Japanese American men, and Hispanic men: the Atherosclerosis Risk in Communities Study (1987-1988), Physicians' Health Study (1982), Honolulu Heart Program (1980-1982), Puerto Rico Heart Health Program (1965-1968), Strong Heart Study (1989-1991), and Cardiovascular Health Study (1989-1990). The performance, or ability to accurately predict CHD risk, of the Framingham functions compared with the performance of risk functions developed specifically from the individual cohorts' data. Comparisons included evaluation of the equality of relative risks for standard CHD risk factors, discrimination, and calibration. For white men and women and for black men and women the Framingham functions performed reasonably well for prediction of CHD events within 5 years of follow-up. Among Japanese American and Hispanic men and Native American women, the Framingham functions systematically overestimated the risk of 5-year CHD events. After recalibration, taking into account different prevalences of risk factors and underlying rates of developing CHD, the Framingham functions worked well in these populations. The sex-specific Framingham CHD prediction functions perform well among whites and blacks in different settings and can be applied to other ethnic groups after recalibration for differing prevalences of risk factors and underlying rates of CHD events.

In The Lancet Diabetes & Endocrinology, Jon White and colleagues1White J Sofat R Hemani G et al.Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis.Lancet Diabetes Endocrinol. 2016; (published online Jan 15.)http://dx.doi.org/10.1016/S2213-8587(15)00386-1Google Scholar consider the causal role of plasma urate in coronary heart disease, using the technique known as mendelian randomisation. They assess the association between genetic predictors of the risk factor (plasma urate) and the disease outcome (coronary heart disease), noting a statistically robust association between a genetic score based on 31 variants associated with plasma urate and coronary heart disease risk, with a straightforward application of Mendelian randomisation estimating an 18% (95% CI 8-29) relative increase in coronary heart disease risk per 1 SD increase in plasma urate. This positive finding from the mendelian randomisation investigation was in line with the observational epidemiological analysis also reported by the investigators. However, the association of the genetic score with the outcome seems to be at least partly explained by pleiotropic (off-target) associations of the genetic score, and the pattern of associations of the individual genetic variants does not show the characteristic dose–response association that would be expected if the genetic associations were solely driven by the effect of the risk factor on the outcome. Mendelian randomisation is a relatively new, but well established epidemiological technique to assess whether a modifiable risk factor is a worthwhile target for clinical or pharmacological intervention.2Davey Smith G Ebrahim S ‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?.Int J Epidemiol. 2003; 32: 1-22Crossref PubMed Scopus (2488) Google Scholar, 3Burgess S Thompson SG Mendelian randomization: methods for using genetic variants in causal estimation. Chapman & Hall, London2015Crossref Scopus (195) Google Scholar An association between a genetic predictor of the risk factor and the outcome is more likely to reflect that the risk factor has a causal relation with the outcome, compared with an association of the risk factor itself from a traditional epidemiological analysis, for several reasons. First, risk factors tend to be mutually correlated. It is difficult to distinguish whether the risk factor itself is the cause, or if a correlated risk factor is driving the identified association with an outcome. By contrast, most genetic variants tend to be uncorrelated with conventional epidemiological risk factors.4Davey Smith G Lawlor D Harbord R Timpson N Day I Ebrahim S Clustered environments and randomized genes: a fundamental distinction between conventional and genetic epidemiology.PLoS Med. 2007; 4: e352Crossref PubMed Scopus (329) Google Scholar Second, genetic variants are fixed at conception. Hence, a genetic association cannot be affected by external factors that lead to confounded associations. Finally, the associations of genetic variants are not subject to reverse causation. The gene can only ever be the cause, and never the effect. In an ideal mendelian randomisation analysis, the genetic variants have a clear biological link with the risk factor (for example, genetic variants in the CRP gene region for the analysis of C-reactive protein5CRP CHD Genetics CollaborationAssociation between C reactive protein and coronary heart disease: Mendelian randomisation analysis based on individual participant data.BMJ. 2011; 342: d548Crossref PubMed Scopus (210) Google Scholar), and are associated with the risk factor, but not with alternative risk factors. The analysis proceeds analogously to a randomised trial,6Hingorani A Humphries S Nature's randomised trials.Lancet. 2005; 366: 1906-1908Summary Full Text Full Text PDF PubMed Scopus (141) Google Scholar and compares groups of individuals with (on average) genetically raised levels of the risk factor versus those with genetically lowered levels to assess whether the risk factor is a cause of the outcome, and therefore a promising target for prioritisation in drug development. White and colleagues' analysis1White J Sofat R Hemani G et al.Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis.Lancet Diabetes Endocrinol. 2016; (published online Jan 15.)http://dx.doi.org/10.1016/S2213-8587(15)00386-1Google Scholar is far from an ideal mendelian randomisation investigation. This is not a criticism, but a consequence of their investigation of a risk factor that is not a protein biomarker, and so does not have a coding gene region, as in the case of C-reactive protein. However, the consideration of multiple gene regions gives some robustness in the analysis, in that the consistency of any causal finding can be assessed. If multiple independent genetic variants associated with the risk factor are all concordantly associated with the outcome (as in the case of LDL cholesterol with coronary heart disease7Ference BA Yoo W Alesh I et al.Effect of long-term exposure to lower low-density lipoprotein cholesterol beginning early in life on the risk of coronary heart disease: a Mendelian randomization analysis.J Am Coll Cardiol. 2012; 60: 2631-2639Summary Full Text Full Text PDF PubMed Scopus (544) Google Scholar), the separate genetic associations each provide independent evidence for a causal effect of the risk factor on the outcome, strengthening the evidence for a causal finding. Another deficiency is that the composite genetic instrument considered by White and colleagues1White J Sofat R Hemani G et al.Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis.Lancet Diabetes Endocrinol. 2016; (published online Jan 15.)http://dx.doi.org/10.1016/S2213-8587(15)00386-1Google Scholar is not solely associated with urate concentrations, but also shows associations with other risk factors, including blood pressure and lipid fractions. This finding is not necessarily a problem provided that the genetic associations with these factors are mediated by urate concentrations, and so one single causal pathway is represented. However, these associations might reflect pleiotropy of the genetic variants, meaning that there are multiple causal pathways from gene to disease, thereby violating the assumption of mendelian randomisation that an association between gene and disease reflects a causal effect of the risk factor. White and colleagues1White J Sofat R Hemani G et al.Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis.Lancet Diabetes Endocrinol. 2016; (published online Jan 15.)http://dx.doi.org/10.1016/S2213-8587(15)00386-1Google Scholar show a statistically robust association between their 31 variant composite instrument and disease risk. However, the authors are to be commended in not stopping here, as others have done previously, but instead seeking to assess whether potential violations of the instrumental variable assumptions invalidate a causal interpretation for their findings. They use two main statistical approaches: multivariable mendelian randomisation8Burgess S Thompson S Multivariable Mendelian randomization: the use of pleiotropic genetic variants to estimate causal effects.Am J Epidemiol. 2015; 181: 251-260Crossref PubMed Scopus (434) Google Scholar and Egger regression.9Bowden J Davey Smith G Burgess S Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression.Int J Epidemiol. 2015; 44: 512-525Crossref PubMed Scopus (1958) Google Scholar In multivariable mendelian randomisation, alternative risk factors are accounted for by adjusting for the genetic associations with these risk factors in the analysis model. In Egger regression, the assessment is not simply of whether genetic variants that are associated with the risk factor are also associated with the outcome, but whether there is a dose–response relation in these associations—that is, are genetic variants that are more strongly associated with the risk factor also more strongly associated with the outcome? Egger regression also encompasses a test for directional pleiotropy—whether this dose–response relation suggests that a variant having zero association with the risk factor also has zero association with the outcome (as expected if there is no pleiotropy, or balanced pleiotropy). Although multivariable mendelian randomisation does not suggest that measured pleiotropy completely accounts for the causal finding, Egger regression detects pleiotropy among the genetic variants, and provides a weaker causal estimate (a 5% [95% CI −8 to 20] relative increase coronary heart disease risk per 1 SD increase in plasma urate) that is compatible with the null once this pleiotropy is accounted for. Additionally, the genetic associations with the outcome are more variable than would be expected by chance alone; this heterogeneity suggests that the genetic associations with coronary heart disease risk are not solely mediated via plasma urate concentrations. The overall finding is not unequivocal. There is an undeniable association between genetic predictors of plasma urate concentrations and risk of coronary heart disease. However, there are suggestions that the association might represent pleiotropic effects of genetic variants included in the model, rather than a causal effect of urate. In summary, the evidence presented honestly by White and colleagues1White J Sofat R Hemani G et al.Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis.Lancet Diabetes Endocrinol. 2016; (published online Jan 15.)http://dx.doi.org/10.1016/S2213-8587(15)00386-1Google Scholar suggests that urate lowering should be prioritised as a potential mechanism to improve cardiovascular outcomes, but without providing a smoking gun that puts the question of causality beyond doubt. I declare no competing interests. Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysisConventional and multivariate Mendelian randomisation analysis implicates a causal role for urate in the development of coronary heart disease, but these estimates might be inflated by hidden pleiotropy. Egger Mendelian randomisation analysis, which accounts for pleiotropy but has less statistical power, suggests there might be no causal effect. These results might help investigators to determine the priority of trials of urate lowering for the prevention of coronary heart disease compared with other potential interventions. Full-Text PDF Open Access

High-sensitivity cardiac troponin T (hs-cTnT) is a biomarker of cardiovascular risk and could be approved in the United States for clinical use soon. However, data linking long-term temporal change in hs-cTnT to outcomes are limited, particularly in primary prevention settings. To examine the association of 6-year change in hs-cTnT with incident coronary heart disease (CHD), heart failure (HF), and all-cause mortality. This prospective observational cohort study, performed from January 1, 1990, to December 31, 2011, included 8838 participants with biracial representation from the Atherosclerosis Risk in Communities Study who were initially free of CHD and HF and who had hs-cTnT measured twice, 6 years apart. Data analysis was performed from October 28, 2014, to March 9, 2016. Risk factor and temporal hs-cTnT data were collected. Using Cox proportional hazards regression, we examined the association of hs-cTnT change with subsequent CHD, HF, and death during a maximum of 16 years. Improvement in discrimination was determined by the Harrell C statistic. Of the 8838 participants (mean age, 56 years; 5215 female [59.0%]; 1891 black [21.4%]) there were 1157 CHD events, 965 HF events, and 1813 deaths overall. Incident detectable hs-cTnT (baseline, <0.005 ng/mL; follow-up, ≥0.005 ng/mL) was independently associated with subsequent CHD (hazard ratio [HR], 1.4; 95% CI, 1.2-1.6), HF (HR, 2.0; 95% CI, 1.6-2.4), and death (HR, 1.5; 95% CI, 1.3-1.7), relative to an hs-cTnT level less than 0.005 ng/mL at both visits. In addition, HRs as high as 4 for CHD and death and 8 for HF were recorded among individuals with the most marked hs-cTnT increases (eg, baseline, < 0.005 ng/mL; follow-up, ≥0.014 ng/mL). Risk for subsequent outcomes was lower among those with relative hs-cTnT reductions greater than 50% from baseline. Furthermore, information on hs-cTnT change improved discrimination for HF and death when added to a model that included traditional risk factors, N-terminal pro-brain natriuretic peptide, and baseline hs-cTnT level. Among individuals with adjudicated HF hospitalizations, hs-cTnT change appeared to be similarly associated with HF with reduced and preserved ejection fraction. Temporal increases in hs-cTnT, suggestive of progressive myocardial damage, are independently associated with incident CHD, death, and, above all, HF. Serial determination of hs-cTnT trajectory adds clinically relevant information to baseline testing and may be useful in prognostic assessments and the targeting of prevention strategies to high-risk individuals, especially among persons with stage A or B HF.

0017 Few studies have reported the incidence of coronary heart disease and its relationship to risk factors in African-Americans. As part of the Atherosclerosis Risk in Communities Study, baseline risk factors were tested as predictors of incident coronary heart disease over 7-10 years of follow-up, 1987-1997, in four U.S. communities (Forsyth County, North Carolina; Jackson, Mississippi; Minneapolis, Minnesota; and Washington County, Maryland). The sample included 14,026 men and women (2,298 black women [BW]; 5,686 white women [WW]; 1,396 black men [BM]; and 4,682 white men [WM] aged 45-64 who were free of clinical coronary heart disease at baseline. Age-adjusted incidence rates for the 7-10 year period (95% confidence interval) for coronary heart disease were BW 5.0(4.1-6.1), WW 4.0(3.5-4.6), BM 10.7(8.9-12.8), and WM 12.6(11.5-13.8). In multivariate analysis, traditional risk factors were generally predictive in blacks as in whites. Hypertension was a particularly strong risk factor in black women, with hazard rate ratios (HR) being: BW 4.12, WW 2.0, BM 1.85, and WM 1.59. Diabetes was predictive, but HRs were somewhat less in blacks than in whites: BW 1.88, WW 3.34, BM 1.70, and WW 2.14. LDL cholesterol was similarly predictive in all race/gender groups, HR 1.19-1.36 per S.D. LDL cholesterol increment. HDL cholesterol appeared somewhat more protective in whites than in blacks. Although black/white differences in risk factor associations exist, there were more similarities than differences in coronary heart disease risk factors and incidence. Findings from this study, along with clinical trial evidence showing efficacy, support aggressive management of traditional risk factors in blacks as in whites. Understanding of the intriguing racial differences in risk factor prediction may be an important part of further understanding the causes of coronary heart disease and may lead to better methods of prevention and treatment.