...in the Multi-Ethnic Study of Atherosclerosis, diabetes was among the risk factors that were associated with risk overestimation in a single-variable analysis.2 Since the early 2000s, the New ...Zealand Ministry of Health has recommended the use of cardiovascular disease risk prediction to inform preventive treatment decisions, and that recommendation resulted in an increase in screening for diabetes status. ...in 2012, only 50% of eligible adults had been screened for diabetes. ...New Zealand created a new national initiative to increase screening for diabetes in the eligible population, which replaced fasting blood glucose with non-fasting glycated haemoglobin (HbA1c) as the recommended screening test. Global diabetes prevalence is increasing from the rise in obesity, unhealthy diets, and widespread physical inactivity due in part to growing urbanisation and its impact on lifestyle factors.4 This increasing prevalence, in addition to the adoption of cardiovascular disease risk estimation by many countries that require screening for diabetes, will increase the heterogeneity of the cardiovascular disease risk profile among individuals with diabetes. Since many primary prevention guidelines from national organisations around the world consider patients with diabetes at high cardiovascular risk, these guidelines require re-examination when diabetes screening levels are high.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
1. The most important way to prevent atherosclerotic vascular disease, heart failure, and atrial fibrillation is to promote a healthy lifestyle throughout life.
2. A team-based care approach is an ...effective strategy for the prevention of cardiovascular disease. Clinicians should evaluate the social determinants of health that affect individuals to inform treatment decisions.
3. Adults who are 40 to 75 years of age and are being evaluated for cardiovascular disease prevention should undergo 10-year atherosclerotic cardiovascular disease (ASCVD) risk estimation and have a clinician–patient risk discussion before starting on pharmacological therapy, such as antihypertensive therapy, a statin, or aspirin. The presence or absence of additional risk-enhancing factors can help guide decisions about preventive interventions in select individuals, as can coronary artery calcium scanning.
4. All adults should consume a healthy diet that emphasizes the intake of vegetables, fruits, nuts, whole grains, lean vegetable or animal protein, and fish and minimizes the intake of
trans
fats, processed meats, refined carbohydrates, and sweetened beverages. For adults with overweight and obesity, counseling and caloric restriction are recommended for achieving and maintaining weight loss.
5. Adults should engage in at least 150 minutes per week of accumulated moderate-intensity physical activity or 75 minutes per week of vigorous-intensity physical activity.
6. For adults with type 2 diabetes mellitus, lifestyle changes, such as improving dietary habits and achieving exercise recommendations are crucial. If medication is indicated, metformin is first-line therapy, followed by consideration of a sodium-glucose cotransporter 2 inhibitor or a glucagon-like peptide-1 receptor agonist.
7. All adults should be assessed at every healthcare visit for tobacco use, and those who use tobacco should be assisted and strongly advised to quit.
8. Aspirin should be used infrequently in the routine primary prevention of ASCVD because of lack of net benefit.
9. Statin therapy is first-line treatment for primary prevention of ASCVD in patients with elevated low-density lipoprotein cholesterol levels (≥190 mg/dL), those with diabetes mellitus, who are 40 to 75 years of age, and those determined to be at sufficient ASCVD risk after a clinician–patient risk discussion.
10. Nonpharmacological interventions are recommended for all adults with elevated blood pressure or hypertension. For those requiring pharmacological therapy, the target blood pressure should generally be <130/80 mm Hg.
Recent data suggest that visit-to-visit variability of blood pressure is associated with stroke incidence. Correlates of increased visit-to-visit variability in blood pressure and the relationship ...between variability and all-cause mortality were examined using data on US adults ≥20 years of age from the Third National Health and Nutrition Examination Survey (n=956). Three consecutive blood pressure readings were taken during 3 separate study visits from 1988 to 1994. Based on the mean of the second and third measurements from each visit, visit-to-visit blood pressure variability for each participant was defined using the standard deviation and coefficient of variation across visits. Mortality was assessed through December 31, 2006 (median follow-up=14 years; n=240 deaths). The mean of the standard deviation for systolic blood pressure across visits was 7.7 mm Hg. After multivariable adjustment, older age, female gender, history of myocardial infarction, higher mean systolic blood pressure and pulse pressure, and use of angiotensin converting enzyme inhibitors were associated with higher standard deviation in systolic blood pressure. The multivariable adjusted hazard ratios for all-cause mortality associated with a standard deviation of systolic blood pressure of 4.80 to 8.34 mm Hg and ≥8.35 mm Hg, versus <4.80 mm Hg, were 1.57 (95% CI, 1.07 to 2.18) and 1.50 (95% CI, 1.03 to 2.18), respectively. Results were similar when coefficient of variation for systolic blood pressure was evaluated. Visit-to-visit variability for diastolic blood pressure was not associated with mortality. In this population-based study of US adults, higher levels of short-term visit-to-visit variability in systolic blood pressure were associated with increased all-cause mortality.
Nomograms to predict normal aortic root diameter for body surface area (BSA) in broad ranges of age have been widely used but are limited by lack of consideration of gender effects, jumps in upper ...limits of aortic diameter among age strata, and data from older teenagers. Sinus of Valsalva diameter was measured by American Society of Echocardiography convention in normal-weight, nonhypertensive, nondiabetic subjects ≥15 years old without aortic valve disease from clinical or population-based samples. Analyses of covariance and linear regression with assessment of residuals identified determinants and developed predictive models for normal aortic root diameter. In 1,207 apparently normal subjects ≥15 years old (54% women), aortic root diameter was 2.1 to 4.3 cm. Aortic root diameter was strongly related to BSA and height (r = 0.48 for the 2 comparisons), age (r = 0.36), and male gender (+2.7 mm adjusted for BSA and age, p <0.001 for all comparisons). Multivariable equations using age, gender, and BSA or height predicted aortic diameter strongly (R = 0.674 for the 2 comparisons, p <0.001) with minimal relation of residuals to age or body size: for BSA 2.423 + (age years × 0.009) + (BSA square meters × 0.461) − (gender 1 = man, 2 = woman × 0.267), SEE 0.261 cm; for height 1.519 + (age years × 0.010) + (height centimeters × 0.010) − (gender 1 = man, 2 = woman × 0.247), SEE 0.215 cm. In conclusion, aortic root diameter is larger in men and increases with body size and age. Regression models incorporating body size, age, and gender are applicable to adolescents and adults without limitations of previous nomograms.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
Obesity is an important component of the pathophysiology of chronic diseases. Identifying epigenetic modifications associated with elevated adiposity, including DNA methylation variation, may point ...to genomic pathways that are dysregulated in numerous conditions. The Illumina 450K Bead Chip array was used to assay DNA methylation in leukocyte DNA obtained from 2097 African American adults in the Atherosclerosis Risk in Communities (ARIC) study. Mixed-effects regression models were used to test the association of methylation beta value with concurrent body mass index (BMI) and waist circumference (WC), and BMI change, adjusting for batch effects and potential confounders. Replication using whole-blood DNA from 2377 White adults in the Framingham Heart Study and CD4+ T cell DNA from 991 Whites in the Genetics of Lipid Lowering Drugs and Diet Network Study was followed by testing using adipose tissue DNA from 648 women in the Multiple Tissue Human Expression Resource cohort. Seventy-six BMI-related probes, 164 WC-related probes and 8 BMI change-related probes passed the threshold for significance in ARIC (P < 1 × 10(-7); Bonferroni), including probes in the recently reported HIF3A, CPT1A and ABCG1 regions. Replication using blood DNA was achieved for 37 BMI probes and 1 additional WC probe. Sixteen of these also replicated in adipose tissue, including 15 novel methylation findings near genes involved in lipid metabolism, immune response/cytokine signaling and other diverse pathways, including LGALS3BP, KDM2B, PBX1 and BBS2, among others. Adiposity traits are associated with DNA methylation at numerous CpG sites that replicate across studies despite variation in tissue type, ethnicity and analytic approaches.
Essential hypertension is a common, complex disorder affecting ≤1 billion adults globally. Blood pressure is a highly heritable trait, with ≤50% of the variation between individuals accounted for by ...familial relationships. Despite this strong heritability, determining the genetic architecture of hypertension in humans has proved challenging. Recent technological and methodological developments have given rise to what is now known as omics—a domain of study that includes genomics, as well as epigenomics, transcriptomics, proteomics, and metabolomics. For complex traits like hypertension, which involve multiple pathways and organs, omic approaches offer the advantage of allowing identification of novel hypertensive mechanisms to help further dissect and characterize the disorder’s pathophysiology. This review provides a primer on the genomics, transcriptomics, proteomics, and metabolomics of blood pressure and hypertension. We provide an introduction to each approach with examples chosen to illustrate its potential. We conclude with a brief assessment of current methods aimed at integrating multiomic data. A review of the literature found genomic, epigenomic, transcriptomic, proteomic, and metabolomic methods have been applied to dissect the pathophysiology of blood pressure and hypertension. Omic methods and integration of multiomic data represent a potentially fruitful approach to illuminating the complex pathophysiology of hypertension and, ultimately, may point to novel diagnostics and treatments.
Mixed linear model (MLM) methods have proven useful in controlling for population structure and relatedness within genome-wide association studies. However, MLM-based methods can be computationally ...challenging for large datasets. We report a compression approach, called 'compressed MLM', that decreases the effective sample size of such datasets by clustering individuals into groups. We also present a complementary approach, 'population parameters previously determined' (P3D), that eliminates the need to re-compute variance components. We applied these two methods both independently and combined in selected genetic association datasets from human, dog and maize. The joint implementation of these two methods markedly reduced computing time and either maintained or improved statistical power. We used simulations to demonstrate the usefulness in controlling for substructure in genetic association datasets for a range of species and genetic architectures. We have made these methods available within an implementation of the software program TASSEL.
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DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, UILJ, UKNU, UL, UM, UPUK
Genome-wide association studies (GWASs) have identified many genetic variants underlying complex traits. Many detected genetic loci harbor variants that associate with multiple—even distinct—traits. ...Most current analysis approaches focus on single traits, even though the final results from multiple traits are evaluated together. Such approaches miss the opportunity to systemically integrate the phenome-wide data available for genetic association analysis. In this study, we propose a general approach that can integrate association evidence from summary statistics of multiple traits, either correlated, independent, continuous, or binary traits, which might come from the same or different studies. We allow for trait heterogeneity effects. Population structure and cryptic relatedness can also be controlled. Our simulations suggest that the proposed method has improved statistical power over single-trait analysis in most of the cases we studied. We applied our method to the Continental Origins and Genetic Epidemiology Network (COGENT) African ancestry samples for three blood pressure traits and identified four loci (CHIC2, HOXA-EVX1, IGFBP1/IGFBP3, and CDH17; p < 5.0 × 10−8) associated with hypertension-related traits that were missed by a single-trait analysis in the original report. Six additional loci with suggestive association evidence (p < 5.0 × 10−7) were also observed, including CACNA1D and WNT3. Our study strongly suggests that analyzing multiple phenotypes can improve statistical power and that such analysis can be executed with the summary statistics from GWASs. Our method also provides a way to study a cross phenotype (CP) association by using summary statistics from GWASs of multiple phenotypes.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Known genetic susceptibility loci for type 2 diabetes (T2D) explain only a small proportion of heritable T2D risk. We hypothesize that DNA methylation patterns may contribute to variation in ...diabetes-related risk factors, and this epigenetic variation across the genome can contribute to the missing heritability in T2D and related metabolic traits. We conducted an epigenome-wide association study for fasting glucose, insulin, and homeostasis model assessment of insulin resistance (HOMA-IR) among 837 nondiabetic participants in the Genetics of Lipid Lowering Drugs and Diet Network study, divided into discovery (N = 544) and replication (N = 293) stages. Cytosine guanine dinucleotide (CpG) methylation at ∼470,000 CpG sites was assayed in CD4(+) T cells using the Illumina Infinium HumanMethylation 450 Beadchip. We fit a mixed model with the methylation status of each CpG as the dependent variable, adjusting for age, sex, study site, and T-cell purity as fixed-effects and family structure as a random-effect. A Bonferroni corrected P value of 1.1 × 10(-7) was considered significant in the discovery stage. Significant associations were tested in the replication stage using identical models. Methylation of a CpG site in ABCG1 on chromosome 21 was significantly associated with insulin (P = 1.83 × 10(-7)) and HOMA-IR (P = 1.60 × 10(-9)). Another site in the same gene was significant for HOMA-IR and of borderline significance for insulin (P = 1.29 × 10(-7) and P = 3.36 × 10(-6), respectively). Associations with the top two signals replicated for insulin and HOMA-IR (P = 5.75 × 10(-3) and P = 3.35 × 10(-2), respectively). Our findings suggest that methylation of a CpG site within ABCG1 is associated with fasting insulin and merits further evaluation as a novel disease risk marker.
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