Genetic Predictors of Cardiovascular Mortality During Intensive Glycemic Control in Type 2 Diabetes: Findings From the ACCORD Clinical Trial

Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People With Type 2 Diabetes

OBJECTIVE

To identify genetic risk factors for incident cardiovascular disease (CVD) among people with type 2 diabetes (T2D).

RESEARCH DESIGN AND METHODS

We conducted a multiancestry time-to-event genome-wide association study for incident CVD among people with T2D. We also tested 204 known coronary artery disease (CAD) variants for association with incident CVD.

RESULTS

Among 49,230 participants with T2D, 8,956 had incident CVD events (event rate 18.2%). We identified three novel genetic loci for incident CVD: rs147138607 (near CACNA1E/ZNF648, hazard ratio [HR] 1.23, P = 3.6 × 10-9), rs77142250 (near HS3ST1, HR 1.89, P = 9.9 × 10-9), and rs335407 (near TFB1M/NOX3, HR 1.25, P = 1.5 × 10-8). Among 204 known CAD loci, 5 were associated with incident CVD in T2D (multiple comparison-adjusted P < 0.00024, 0.05/204). A standardized polygenic score of these 204 variants was associated with incident CVD with HR 1.14 (P = 1.0 × 10-16).

CONCLUSIONS

The data point to novel and known genomic regions associated with incident CVD among individuals with T2D.

Lessons and Applications of Omics Research in Diabetes Epidemiology

PURPOSE OF REVIEW

Recent advances in genomic technology and molecular techniques have greatly facilitated the identification of disease biomarkers, advanced understanding of pathogenesis of different common diseases, and heralded the dawn of precision medicine. Much of these advances in the area of diabetes have been made possible through deep phenotyping of epidemiological cohorts, and analysis of the different omics data in relation to detailed clinical information. In this review, we aim to provide an overview on how omics research could be incorporated into the design of current and future epidemiological studies.

RECENT FINDINGS

We provide an up-to-date review of the current understanding in the area of genetic, epigenetic, proteomic and metabolomic markers for diabetes and related outcomes, including polygenic risk scores. We have drawn on key examples from the literature, as well as our own experience of conducting omics research using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank, as well as other cohorts, to illustrate the potential of omics research in diabetes. Recent studies highlight the opportunity, as well as potential benefit, to incorporate molecular profiling in the design and set-up of diabetes epidemiology studies, which can also advance understanding on the heterogeneity of diabetes. Learnings from these examples should facilitate other researchers to consider incorporating research on omics technologies into their work to advance the field and our understanding of diabetes and its related co-morbidities. Insights from these studies would be important for future development of precision medicine in diabetes.

The Inclusion of Underrepresented Populations in Cardiovascular Genetics and Epidemiology

Novel genetic risk markers have helped us to advance the field of cardiovascular epidemiology and refine our current understanding and risk stratification paradigms. The discovery and analysis of variants can help us to tailor prognostication and management. However, populations underrepresented in cardiovascular epidemiology and cardiogenetics research may experience inequities in care if prediction tools are not applicable to them clinically. Therefore, the purpose of this article is to outline the barriers that underrepresented populations can face in participating in genetics research, to describe the current efforts to diversify cardiogenetics research, and to outline strategies that researchers in cardiovascular epidemiology can implement to include underrepresented populations. Mistrust, a lack of diverse research teams, the improper use of sensitive biodata, and the constraints of genetic analyses are all barriers for including diverse populations in genetics studies. The current work is beginning to address the paucity of ethnically diverse genetics research and has already begun to shed light on the potential benefits of including underrepresented and diverse populations. Reducing barriers for individuals, utilizing community-driven research processes, adopting novel recruitment strategies, and pushing for organizational support for diverse genetics research are key steps that clinicians and researchers can take to develop equitable risk stratification tools and improve patient care.

Time-to-Event Genome-Wide Association Study for Incident Cardiovascular Disease in People with Type 2 Diabetes Mellitus

BACKGROUND

Type 2 diabetes mellitus (T2D) confers a two- to three-fold increased risk of cardiovascular disease (CVD). However, the mechanisms underlying increased CVD risk among people with T2D are only partially understood. We hypothesized that a genetic association study among people with T2D at risk for developing incident cardiovascular complications could provide insights into molecular genetic aspects underlying CVD.

METHODS

From 16 studies of the Cohorts for Heart & Aging Research in Genomic Epidemiology (CHARGE) Consortium, we conducted a multi-ancestry time-to-event genome-wide association study (GWAS) for incident CVD among people with T2D using Cox proportional hazards models. Incident CVD was defined based on a composite of coronary artery disease (CAD), stroke, and cardiovascular death that occurred at least one year after the diagnosis of T2D. Cohort-level estimated effect sizes were combined using inverse variance weighted fixed effects meta-analysis. We also tested 204 known CAD variants for association with incident CVD among patients with T2D.

RESULTS

A total of 49,230 participants with T2D were included in the analyses (31,118 European ancestries and 18,112 non-European ancestries) which consisted of 8,956 incident CVD cases over a range of mean follow-up duration between 3.2 and 33.7 years (event rate 18.2%). We identified three novel, distinct genetic loci for incident CVD among individuals with T2D that reached the threshold for genome-wide significance (P<5.0×10-8): rs147138607 (intergenic variant between CACNA1E and ZNF648) with a hazard ratio (HR) 1.23, 95% confidence interval (CI) 1.15 - 1.32, P=3.6×10-9, rs11444867 (intergenic variant near HS3ST1) with HR 1.89, 95% CI 1.52 - 2.35, P=9.9×10-9, and rs335407 (intergenic variant between TFB1M and NOX3) HR 1.25, 95% CI 1.16 - 1.35, P=1.5×10-8. Among 204 known CAD loci, 32 were associated with incident CVD in people with T2D with P<0.05, and 5 were significant after Bonferroni correction (P<0.00024, 0.05/204). A polygenic score of these 204 variants was significantly associated with incident CVD with HR 1.14 (95% CI 1.12 - 1.16) per 1 standard deviation increase (P=1.0×10-16).

CONCLUSIONS

The data point to novel and known genomic regions associated with incident CVD among individuals with T2D.

Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Association of a Multiancestry Genome-Wide Blood Pressure Polygenic Risk Score With Adverse Cardiovascular Events

BACKGROUND

Traditional cardiovascular risk factors and the underlying genetic risk of elevated blood pressure (BP) determine an individual's composite risk of developing adverse cardiovascular events. We sought to evaluate the relative contributions of the traditional cardiovascular risk factors to the development of adverse cardiovascular events in the context of varying BP genetic risk profiles.

METHODS

Genome-wide polygenic risk score (PRS) was computed using multiancestry genome-wide association estimates among US adults who underwent whole-genome sequencing in the Trans-Omics for Precision program. Individuals were stratified into high, intermediate, and low genetic risk groups (>80th, 20-80th, and <20th centiles of systolic BP [SBP] PRS). Based on the ACC/AHA Pooled Cohort Equations, participants were stratified into low and high (10 year-atherosclerotic cardiovascular disease [CVD] risk: <10% or ≥10%) cardiovascular risk factor profile groups. The primary study outcome was incident cardiovascular event (composite of incident heart failure, incident stroke, and incident coronary heart disease).

RESULTS

Among 21 897 US adults (median age: 56 years; 56.0% women; 35.8% non-White race/ethnicity), 1 SD increase in the SBP PRS, computed using 1.08 million variants, was associated with SBP (β: 4.39 [95% CI, 4.13-4.65]) and hypertension (odds ratio, 1.50 [95% CI, 1.46-1.55]), respectively. This association was robustly seen across racial/ethnic groups. Each SD increase in SBP PRS was associated with a higher risk of the incident CVD (multivariable-adjusted hazards ratio, 1.07 [95% CI, 1.04-1.10]) after controlling for ACC/AHA Pooled Cohort Equations risk scores. Among individuals with a high SBP PRS, low atherosclerotic CVD risk was associated with a 58% lower hazard for incident CVD (multivariable-adjusted hazards ratio, 0.42 [95% CI, 0.36-0.50]) compared to those with high atherosclerotic CVD risk. A similar pattern was noted in intermediate and low genetic risk groups.

CONCLUSIONS

In a multiancestry cohort of >21 000 US adults, genome-wide SBP PRS was associated with BP traits and adverse cardiovascular events. Adequate control of modifiable cardiovascular risk factors may reduce the predisposition to adverse cardiovascular events among those with a high SBP PRS.

Questionnaire-based exposome-wide association studies (ExWAS) reveal expected and novel risk factors associated with cardiovascular outcomes in the Personalized Environment and Genes Study

While multiple factors are associated with cardiovascular disease (CVD), many environmental exposures that may contribute to CVD have not been examined. To understand environmental effects on cardiovascular health, we performed an exposome-wide association study (ExWAS), a hypothesis-free approach, using survey data on endogenous and exogenous exposures at home and work and data from health and medical histories from the North Carolina-based Personalized Environment and Genes Study (PEGS) (n = 5015). We performed ExWAS analyses separately on six cardiovascular outcomes (cardiac arrhythmia, congestive heart failure, coronary artery disease, heart attack, stroke, and a combined atherogenic-related outcome comprising angina, angioplasty, atherosclerosis, coronary artery disease, heart attack, and stroke) using logistic regression and a false discovery rate of 5%. For each CVD outcome, we tested 502 single exposures and built multi-exposure models using the deletion-substitution-addition (DSA) algorithm. To evaluate complex nonlinear relationships, we employed the knockoff boosted tree (KOBT) algorithm. We adjusted all analyses for age, sex, race, BMI, and annual household income. ExWAS analyses revealed novel associations that include blood type A (Rh-) with heart attack (OR[95%CI] = 8.2[2.2:29.7]); paint exposures with stroke (paint related chemicals: 6.1[2.2:16.0], acrylic paint: 8.1[2.6:22.9], primer: 6.7[2.2:18.6]); biohazardous materials exposure with arrhythmia (1.8[1.5:2.3]); and higher paternal education level with reduced risk of multiple CVD outcomes (stroke, heart attack, coronary artery disease, and combined atherogenic outcome). In multi-exposure models, trouble sleeping and smoking remained important risk factors. KOBT identified significant nonlinear effects of sleep disorder, regular intake of grapefruit, and a family history of blood clotting problems for multiple CVD outcomes (combined atherogenic outcome, congestive heart failure, and coronary artery disease). In conclusion, using statistics and machine learning, these findings identify novel potential risk factors for CVD, enable hypothesis generation, provide insights into the complex relationships between risk factors and CVD, and highlight the importance of considering multiple exposures when examining CVD outcomes.

Pharmacogenetics of Cardiovascular Prevention in Diabetes: From Precision Medicine to Identification of Novel Targets

Pharmacogenetics—a branch of precision medicine—holds the promise of becoming a novel tool to reduce the social and healthcare burdens of cardiovascular disease (CVD) and coronary artery disease (CAD) in diabetes. The improvement in cardiovascular risk stratification resulting from adding genetic characteristics to clinical data has moved from the modest results obtained with genetic risk scores based on few genetic variants, to the progressively better performances of polygenic risk scores based on hundreds to millions of variants (CAD-PGRS). Similarly, over the past few years, the number of studies investigating the use of CAD-PGRS to identify different responses to cardio-preventive treatment has progressively increased, yielding striking results for lipid-lowering drugs such as proprotein convertase subtilisin/kexin type 9 (PCSK9) inhibitors and statins. The use of CAD-PGRS to stratify patients based on their likely response to diabetes-specific interventions has been less successful, but promising results have been obtained with regard to specific genetic variants modulating the effects of interventions such as intensive glycemic control and fenofibrate. The finding of diabetes-specific CAD-loci, such as GLUL, has also led to the identification of promising new targets that might hopefully result in the development of specific therapies to reduce CVD burden in patients with diabetes. As reported in consensus statements from international diabetes societies, some of these pharmacogenetic approaches are expected to be introduced in clinical practice over the next decade. For this to happen, in addition to continuing to improve and validate these tools, it will be necessary to educate physicians and patients about the opportunities and limits of pharmacogenetics, as summarized in this review.

Polygenic Risk Scores for Cardiovascular Disease: A Scientific Statement From the American Heart Association

Cardiovascular disease is the leading contributor to years lost due to disability or premature death among adults. Current efforts focus on risk prediction and risk factor mitigation' which have been recognized for the past half-century. However, despite advances, risk prediction remains imprecise with persistently high rates of incident cardiovascular disease. Genetic characterization has been proposed as an approach to enable earlier and potentially tailored prevention. Rare mendelian pathogenic variants predisposing to cardiometabolic conditions have long been known to contribute to disease risk in some families. However, twin and familial aggregation studies imply that diverse cardiovascular conditions are heritable in the general population. Significant technological and methodological advances since the Human Genome Project are facilitating population-based comprehensive genetic profiling at decreasing costs. Genome-wide association studies from such endeavors continue to elucidate causal mechanisms for cardiovascular diseases. Systematic cataloging for cardiovascular risk alleles also enabled the development of polygenic risk scores. Genetic profiling is becoming widespread in large-scale research, including in health care-associated biobanks, randomized controlled trials, and direct-to-consumer profiling in tens of millions of people. Thus, individuals and their physicians are increasingly presented with polygenic risk scores for cardiovascular conditions in clinical encounters. In this scientific statement, we review the contemporary science, clinical considerations, and future challenges for polygenic risk scores for cardiovascular diseases. We selected 5 cardiometabolic diseases (coronary artery disease, hypercholesterolemia, type 2 diabetes, atrial fibrillation, and venous thromboembolic disease) and response to drug therapy and offer provisional guidance to health care professionals, researchers, policymakers, and patients.

Systematic Heritability and Heritability Enrichment Analysis for Diabetes Complications in UK Biobank and ACCORD Studies

Diabetes-related complications reflect longstanding damage to small and large vessels throughout the body. In addition to the duration of diabetes and poor glycemic control, genetic factors are important contributors to the variability in the development of vascular complications. Early heritability studies found strong familial clustering of both macrovascular and microvascular complications. However, they were limited by small sample sizes and large phenotypic heterogeneity, leading to less accurate estimates. We take advantage of two independent studies-UK Biobank and the Action to Control Cardiovascular Risk in Diabetes trial-to survey the single nucleotide polymorphism heritability for diabetes microvascular (diabetic kidney disease and diabetic retinopathy) and macrovascular (cardiovascular events) complications. Heritability for diabetic kidney disease was estimated at 29%. The heritability estimate for microalbuminuria ranged from 24 to 60% and was 41% for macroalbuminuria. Heritability estimates of diabetic retinopathy ranged from 6 to 33%, depending on the phenotype definition. More severe diabetes retinopathy possessed higher genetic contributions. We show, for the first time, that rare variants account for much of the heritability of diabetic retinopathy. This study suggests that a large portion of the genetic risk of diabetes complications is yet to be discovered and emphasizes the need for additional genetic studies of diabetes complications.

Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Diabetes mellitus correlates with increased biological age as indicated by clinical biomarkers

Chronological age (CA) is determined by time of birth, whereas biological age (BA) is based on changes on a cellular level and strongly correlates with morbidity, mortality, and longevity. Type 2 diabetes (T2D) associates with increased morbidity and mortality; thus, we hypothesized that BA would be increased and calculated it from biomarkers collected at routine clinical visits. Deidentified data was obtained from three cohorts of patients (20–80 years old)—T2D, type 1 diabetes (T1D), and prediabetes—and compared to gender- and age-matched non-diabetics. Eight clinical biomarkers that correlated with CA in people without diabetes were used to calculate BA using the Klemera and Doubal method 1 (KDM1) and multiple linear regression (MLR). The phenotypic age (PhAge) formula was used with its predetermined biomarkers. BA of people with T2D was, on average, 12.02 years higher than people without diabetes (p < 0.0001), while BA in T1D was 16.32 years higher (p < 0.0001). Results were corroborated using MLR and PhAge. The biomarkers with the strongest correlation to increased BA in T2D using KDM were A1c (R² = 0.23, p < 0.0001) and systolic blood pressure (R² = 0.21, p < 0.0001). BMI had a positive correlation to BA in non-diabetes subjects but disappeared in those with diabetes. Mortality data using the ACCORD trial was used to validate our results and showed a significant correlation between higher BA and decreased survival. In conclusion, BA is increased in people with diabetes, irrespective of pathophysiology, and to a lesser extent in prediabetes.

Genetics of macrovascular complications in type 2 diabetes

Type 2 diabetes mellitus (T2DM) is a metabolic disorder that currently affects more than 400 million worldwide and is projected to cause 552 million cases by the year 2030. Long-term vascular complications, such as coronary artery disease, myocardial infarction, stroke, are the leading causes of morbidity and mortality among diabetic patients. The recent advances in genome-wide technologies have given a powerful impetus to the study of risk markers for multifactorial diseases. To date, the role of genetic and epigenetic factors in modulating susceptibility to T2DM and its vascular complications is being successfully studied that provides the accumulation of genomic knowledge. In the future, this will provide an opportunity to reveal the pathogenetic pathways in the development of the disease and allow to predict the macrovascular complications in T2DM patients. This review is focused on the evidence of the role of genetic variants and epigenetic changes in the development of macrovascular pathology in diabetic patients.

A Type 2 Diabetes Subtype Responsive to ACCORD Intensive Glycemia Treatment

OBJECTIVE

Current type 2 diabetes (T2D) management contraindicates intensive glycemia treatment in patients with high cardiovascular disease (CVD) risk and is partially motivated by evidence of harms in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial. Heterogeneity in response to intensive glycemia treatment has been observed, suggesting potential benefit for some individuals.

RESEARCH DESIGN AND METHODS

ACCORD was a randomized controlled trial that investigated whether intensively treating glycemia in individuals with T2D would reduce CVD outcomes. Using a novel approach to cluster HbA1c trajectories, we identified groups in the intensive glycemia arm with modified CVD risk. Genome-wide analysis and polygenic score (PS) were developed to predict group membership. Mendelian randomization was performed to infer causality.

RESULTS

We identified four clinical groupings in the intensive glycemia arm, and clinical group 4 (C4) displayed fewer CVD (hazard ratio [HR] 0.34; P = 2.01 × 10-3) and microvascular outcomes (HR 0.86; P = 0.015) than those receiving standard treatment. A single-nucleotide polymorphism, rs220721, in MAS1 reached suggestive significance in C4 (P = 4.34 × 10-7). PS predicted C4 with high accuracy (area under the receiver operating characteristic curve 0.98), and this predicted C4 displayed reduced CVD risk with intensive versus standard glycemia treatment (HR 0.53; P = 4.02 × 10-6), but not reduced risk of microvascular outcomes (P < 0.05). Mendelian randomization indicated causality between PS, on-trial HbA1c, and reduction in CVD outcomes (P < 0.05).

CONCLUSIONS

We found evidence of a T2D clinical group in ACCORD that benefited from intensive glycemia treatment, and membership in this group could be predicted using genetic variants. This study generates new hypotheses with implications for precision medicine in T2D and represents an important development in this landmark clinical trial warranting further investigation.

Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease.

RESULTS

Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Haptoglobin Phenotype Modifies the Influence of Intensive Glycemic Control on Cardiovascular Outcomes

BACKGROUND

Whereas there exists a direct relationship between glycated hemoglobin and cardiovascular disease (CVD), clinical trials targeting glycated hemoglobin to near-normal levels using intensive therapy have failed to prevent CVD and have even increased mortality, making clinical decision making difficult. A common polymorphism at the haptoglobin (Hp) genetic locus is associated with CVD, especially coronary heart disease, in the setting of hyperglycemia.

OBJECTIVES

This study sought to determine whether the treatment difference of intensive versus standard glucose-lowering therapy on risk of CVD events in the ACCORD (Action to Control Cardiovascular Risk in Diabetes) study depended on Hp phenotype.

METHODS

Hp phenotype was measured within 5,806 non-Hispanic white ACCORD participants using a validated assay. Adjusted hazard ratios (aHR) with 95% confidence intervals (CI) estimated from stratified Cox regression models were used to quantify the association between intensive therapy and incident CVD for the 2 different Hp phenotype groups (Hp2-2, Hp1 carriers).

RESULTS

Compared with standard therapy, intensive therapy was associated with a lower risk of incident coronary heart disease among participants with the Hp2-2 phenotype (n = 2,133; aHR: 0.71; 95% CI: 0.55 to 0.91; p = 0.006), but not among the other 2 phenotypes (Hp1 allele carriers) (n = 3,673; aHR: 0.95; 95% CI: 0.79 to 1.13; p = 0.550). The same pattern was observed for CVD. Conversely, intensive therapy was associated with an increased risk of fatal CVD (aHR: 1.50; 95% CI: 1.00 to 2.25; p = 0.049) and total mortality (aHR: 1.40; 95% CI: 1.08 to 1.81; p = 0.011) among the Hp1 carriers, whereas this risk was not increased in the Hp2-2 phenotype (fatal CVD: aHR: 1.02; 95% CI: 0.59 to 1.77; p = 0.931; total mortality: aHR: 0.98; 95% CI: 0.68 to 1.41; p = 0.908).

CONCLUSIONS

Intensive glucose-lowering therapy was effective at preventing incident coronary heart disease and CVD events in ACCORD study participants with the Hp2-2 phenotype but not in Hp1 carriers, who had increased mortality risk from intensive therapy.

Genetics of diabetes mellitus and diabetes complications

Diabetes is one of the fastest growing diseases worldwide, projected to affect 693 million adults by 2045. Devastating macrovascular complications (cardiovascular disease) and microvascular complications (such as diabetic kidney disease, diabetic retinopathy and neuropathy) lead to increased mortality, blindness, kidney failure and an overall decreased quality of life in individuals with diabetes. Clinical risk factors and glycaemic control alone cannot predict the development of vascular complications; numerous genetic studies have demonstrated a clear genetic component to both diabetes and its complications. Early research aimed at identifying genetic determinants of diabetes complications relied on familial linkage analysis suited to strong-effect loci, candidate gene studies prone to false positives, and underpowered genome-wide association studies limited by sample size. The explosion of new genomic datasets, both in terms of biobanks and aggregation of worldwide cohorts, has more than doubled the number of genetic discoveries for both diabetes and diabetes complications. We focus herein on genetic discoveries for diabetes and diabetes complications, empowered primarily through genome-wide association studies, and emphasize the gaps in research for taking genomic discovery to the next level.

Evaluation and management of residual cardiovascular risk in patients with diabetes

Presence of diabetes (types 1 and 2) increases the risk of atherosclerotic cardiovascular disease. Despite adequate metabolic control and treatment of vascular risk factors until the goals recommended by the clinical practice guidelines are achieved, residual cardiovascular risk may be very high in some patients with diabetes. Stratifying the vascular risk for each patient as precisely as possible is therefore necessary. Consolidated strategies to improve patient prognosis include aggressive reduction of LDL cholesterol, blood pressure control, achievement of the best HbA1c control possible without inducing hypoglycemia, use of hypoglycemic drugs shown to have cardiovascular benefits, and use of platelet aggregation inhibitors in patients with greater initial risk. Emerging strategies for patients with very high or extreme risk would include use of drugs intended to decrease triglyceride-rich lipoproteins and inflammation.

PPARA Polymorphism Influences the Cardiovascular Benefit of Fenofibrate in Type 2 Diabetes: Findings From ACCORD-Lipid

The cardiovascular benefits of fibrates have been shown to be heterogeneous and to depend on the presence of atherogenic dyslipidemia. We investigated whether genetic variability in the PPARA gene, coding for the pharmacological target of fibrates (PPAR-α), could be used to improve the selection of patients with type 2 diabetes who may derive cardiovascular benefit from addition of this treatment to statins. We identified a common variant at the PPARA locus (rs6008845, C/T) displaying a study-wide significant influence on the effect of fenofibrate on major cardiovascular events (MACE) among 3,065 self-reported white subjects treated with simvastatin and randomized to fenofibrate or placebo in the ACCORD-Lipid trial. T/T homozygotes (36% of participants) experienced a 51% MACE reduction in response to fenofibrate (hazard ratio 0.49; 95% CI 0.34-0.72), whereas no benefit was observed for other genotypes (P interaction = 3.7 × 10-4). The rs6008845-by-fenofibrate interaction on MACE was replicated in African Americans from ACCORD (N = 585, P = 0.02) and in external cohorts (ACCORD-BP, ORIGIN, and TRIUMPH, total N = 3059, P = 0.005). Remarkably, rs6008845 T/T homozygotes experienced a cardiovascular benefit from fibrate even in the absence of atherogenic dyslipidemia. Among these individuals, but not among carriers of other genotypes, fenofibrate treatment was associated with lower circulating levels of CCL11-a proinflammatory and atherogenic chemokine also known as eotaxin (P for rs6008845-by-fenofibrate interaction = 0.003). The GTEx data set revealed regulatory functions of rs6008845 on PPARA expression in many tissues. In summary, we have found a common PPARA regulatory variant that influences the cardiovascular effects of fenofibrate and that could be used to identify patients with type 2 diabetes who would derive benefit from fenofibrate treatment, in addition to those with atherogenic dyslipidemia.

Genome-wide association study on coronary artery disease in type 1 diabetes suggests beta-defensin 127 as a risk locus

AIMS

Diabetes is a known risk factor for coronary artery disease (CAD). There is accumulating evidence that CAD pathogenesis differs for individuals with type 1 diabetes (T1D). However, the genetic background has not been extensively studied. We aimed to discover genetic loci increasing CAD susceptibility, especially in T1D, to examine the function of these discoveries and to study the role of the known risk loci in T1D.

METHODS AND RESULTS

We performed the largest genome-wide association study to date for CAD in T1D, comprising 4869 individuals with T1D (cases/controls: 941/3928). Two loci reached genome-wide significance, rs1970112 in CDKN2B-AS1 [odds ratio (OR) = 1.32, P = 1.50 × 10-8], and rs6055069 on DEFB127 promoter (OR = 4.17, P = 2.35 × 10-9), with consistent results in survival analysis. The CDKN2B-AS1 variant replicated (P = 0.04) when adjusted for diabetic kidney disease in three additional T1D cohorts (cases/controls: 434/3123). Furthermore, we explored the function of the lead discoveries with a cardio-phenome-wide analysis. Among the eight suggestive loci (P < 1 × 10-6), rs70962766 near B3GNT2 associated with central blood pressure, rs1344228 near CNTNAP5 with intima media thickness, and rs2112481 on GRAMD2B promoter with serum leucocyte concentration. Finally, we calculated genetic risk scores for individuals with T1D with the known susceptibility loci. General population risk variants were modestly but significantly associated with CAD also in T1D (P = 4.21 × 10-7).

CONCLUSION

While general population CAD risk loci had limited effect on the risk in T1D, for the first time, variants at the CDKN2B-AS1 locus were robustly associated with CAD in individuals with T1D. The novel finding on β-defensin DEFB127 promoter provides a link between diabetes, infection susceptibility, and CAD, although pending on future confirmation.

Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association

BACKGROUND

The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2020 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals.

RESULTS

Each of the 26 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

A Genetic Locus on Chromosome 2q24 Predicting Peripheral Neuropathy Risk in Type 2 Diabetes: Results From the ACCORD and BARI 2D Studies

Genetic factors have been postulated to be involved in the etiology of diabetic peripheral neuropathy (DPN), but their identity remains mostly unknown. The aim of this study was to conduct a systematic search for genetic variants influencing DPN risk using two well-characterized cohorts. A genome-wide association study (GWAS) testing 6.8 million single nucleotide polymorphisms was conducted among participants of the Action to Control Cardiovascular Risk in Diabetes (ACCORD) clinical trial. Included were 4,384 white case patients with type 2 diabetes (T2D) and prevalent or incident DPN (defined as a Michigan Neuropathy Screening Instrument clinical examination score >2.0) and 784 white control subjects with T2D and no evidence of DPN at baseline or during follow-up. Replication of significant loci was sought among white subjects with T2D (791 DPN-positive case subjects and 158 DPN-negative control subjects) from the Bypass Angioplasty Revascularization Investigation in Type 2 Diabetes (BARI 2D) trial. Association between significant variants and gene expression in peripheral nerves was evaluated in the Genotype-Tissue Expression (GTEx) database. A cluster of 28 SNPs on chromosome 2q24 reached GWAS significance (P < 5 × 10-8) in ACCORD. The minor allele of the lead SNP (rs13417783, minor allele frequency = 0.14) decreased DPN odds by 36% (odds ratio [OR] 0.64, 95% CI 0.55-0.74, P = 1.9 × 10-9). This effect was not influenced by ACCORD treatment assignments (P for interaction = 0.6) or mediated by an association with known DPN risk factors. This locus was successfully validated in BARI 2D (OR 0.57, 95% CI 0.42-0.80, P = 9 × 10-4; summary P = 7.9 × 10-12). In GTEx, the minor, protective allele at this locus was associated with higher tibial nerve expression of an adjacent gene (SCN2A) coding for human voltage-gated sodium channel NaV1.2 (P = 9 × 10-4). To conclude, we have identified and successfully validated a previously unknown locus with a powerful protective effect on the development of DPN in T2D. These results may provide novel insights into DPN pathogenesis and point to a potential target for novel interventions.

Current Status and Future Directions for Electronic Point-of-Care Clinical Decision Support to Improve Diabetes Management in Primary Care

In the past decade there have been major improvements in the design, use, and effectiveness of point-of-care clinical decision support (CDS) systems to improve quality of care for patients with diabetes and related conditions. Advances in data exchange, data security, and human factors research have driven these improvements. Current diabetes CDS systems have high use rates, high clinician/user satisfaction rates, and have measurably improved glucose control, blood pressure control, and cardiovascular risk trajectories in adults with diabetes. As diabetes care increasingly relies on complex biomarker-driven risk prediction methods to optimize care goals and prioritize treatment options based on potential benefit to an individual patient, CDS systems will become indispensable tools to guide clinician and patient decision-making. In this study we describe specific challenges that must be addressed further to improve the design, implementation, and effectiveness of primary care diabetes CDS systems in coming years.

Leveraging Genetics to Improve Cardiovascular Health in Diabetes: The 2018 Edwin Bierman Award Lecture

The past decade has witnessed an exponential increase in our ability to search the genome for genetic factors predisposing to cardiovascular disease (CVD) and in particular coronary heart disease (CHD). Identifying these genes could lead to the development of innovative strategies to prevent the cardiovascular complications of diabetes by allowing us to 1) create predictive algorithms for the identification of patients at especially high risk of CVD so that these individuals can undergo preventive interventions early in the natural history of the disease; 2) discover as yet unknown disease pathways linking diabetes to atherosclerosis, which can be used as targets for the development of new CVD-preventing drugs specifically directed at subjects with diabetes; and 3) devise personalized programs increasing the cost-effectiveness of preventive interventions by tailoring them to the genetic background of each patient. Substantial progress has been made in each of these three areas as exemplified by the recent development of a CHD genetic risk score improving CHD prediction among subjects with type 2 diabetes, the discovery of a diabetes-specific CHD locus on 1q25 pointing to glutamine synthase (GLUL) and the γ-glutamyl cycle as key regulators of CHD risk in diabetes, and the identification of two genetic loci allowing the selection of patients with type 2 diabetes who may especially benefit from intensive glycemic control. Translating these discoveries into clinical practice will not be without challenges, but the potential rewards, from the perspective of public health as well as that of persons with diabetes, make this goal worth pursuing.

New approach to diabetes care: from blood glucose to cardiovascular disease

Diabetes, a metabolic disease with vascular consequences due to accelerated atherosclerosis, is one of the 21st century's most prevalent chronic diseases. Characterized by inability to produce or use insulin, leading to hyperglycemia and insulin deficiency, diabetes causes a variety of microvascular (such as retinopathy and kidney disease) and macrovascular complications (including myocardial infarction and stroke) which reduce the quality of life and life expectancy of individuals with diabetes. We describe the close relationship between diabetes, cardiovascular risk factors, and cardiovascular disease, and examine multifactorial approaches to diabetes treatment, including reducing cardiovascular risk in individuals with type 2 diabetes. Finally, we analyze new prospects for the treatment of type 2 diabetes, resulting from the development of novel antidiabetic drugs. The aim of this review is that the clinician should assume the crucial role of guiding individuals with diabetes in the control of their disease, in order to improve their quality of life and prognosis. In view of the currently available evidence, the emergence of new glucose-reducing therapies with proven cardiovascular benefit means that the best therapeutic strategy for diabetes must go beyond reducing hyperglycemia and aim to reduce cardiovascular risk.

Regional differences in the incidence of diabetic cardiovascular events reflect the quality of care

OBJECTIVES

Diabetic patients have two-fold excess risk of cardiovascular complications (CVCs). To compare the treatment quality of diabetic patients we compared the incidence of CVCs between the five university hospital districts (UHDs) in Finland.

DESIGN

The study population comprised all persons with diabetes in Finland since 1964. They were followed up for the incidence of first acute coronary syndrome (ACS) and first ischemic stroke (IS) using the National Hospital Discharge Register and the National Causes of Death Register data between the years 2000 and 2011. Incidence differences among diabetic patients were also compared with corresponding results in the total population. The main analysis tool was Poisson regression adjusted for age, sex and study year. The UHD of Helsinki was used as the reference category.

RESULTS

In the diabetic population the risk for ACS exceeded the reference significantly in three UHDs ranging from 1.03 (95% CI 0.89-1.19) to 1.70 (1.46-1.97). The incidence of IS exceeded the reference in two UHDs ranging from 1.01 (0.89-1.15) to 1.36 (1.18-1.56). These differences were similar to the corresponding figures in the total population. Differences between the UHDs remained stable over time.

CONCLUSIONS

We found major and stable differences in the incidence of ACS and IS between the UHDs among patients with diabetes. The differences result from several factors influencing the risk of these complications, including the treatment. These differences tended to be larger than the corresponding differences in the total population, which suggests that there is potential to prevent CVCs by improving diabetes care.

Genetic Tools for Coronary Risk Assessment in Type 2 Diabetes: A Cohort Study From the ACCORD Clinical Trial

OBJECTIVE

We evaluated whether the increasing number of genetic loci for coronary artery disease (CAD) identified in the general population could be used to predict the risk of major CAD events (MCE) among participants with type 2 diabetes at high cardiovascular risk.

RESEARCH DESIGN AND METHODS

A weighted genetic risk score (GRS) derived from 204 variants representative of all the 160 CAD loci identified in the general population as of December 2017 was calculated in 5,360 and 1,931 white participants in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) and Outcome Reduction With Initial Glargine Intervention (ORIGIN) studies, respectively. The association between GRS and MCE (combining fatal CAD events, nonfatal myocardial infarction, and unstable angina) was assessed by Cox proportional hazards regression.

RESULTS

The GRS was associated with MCE risk in both ACCORD and ORIGIN (hazard ratio [HR] per SD 1.27, 95% CI 1.18-1.37, P = 4 × 10-10, and HR per SD 1.35, 95% CI 1.16-1.58, P = 2 × 10-4, respectively). This association was independent from interventions tested in the trials and persisted, though attenuated, after adjustment for classic cardiovascular risk predictors. Adding the GRS to clinical predictors improved incident MCE risk classification (relative integrated discrimination improvement +8%, P = 7 × 10-4). The performance of this GRS was superior to that of GRS based on the smaller number of CAD loci available in previous years.

CONCLUSIONS

When combined into a GRS, CAD loci identified in the general population are associated with CAD also in type 2 diabetes. This GRS provides a significant improvement in the ability to correctly predict future MCE, which may increase further with the discovery of new CAD loci.

Precision medicine in the management of type 2 diabetes

The study of type 2 diabetes has been driven by advances in human genetics, epigenetics, biomarkers, mechanistic studies, and large clinical trials, enabling new insights into disease susceptibility, pathophysiology, progression, and development of complications. Simultaneously, several new drug classes with different mechanisms of action have been introduced over the past two decades, accompanied by data about cardiovascular safety and non-glycaemic outcomes. In this Review, we critically examine the progress and integration of this new science into clinical practice, and review opportunities for enabling the use of precision medicine in the diagnosis and treatment of type 2 diabetes. We contrast the success in delivering personalised medicine for monogenic diabetes with the greater challenge of providing a precision medicine approach for type 2 diabetes, highlighting gaps, limitations, and areas requiring further study.

Genetic Variants in HSD17B3, SMAD3, and IPO11 Impact Circulating Lipids in Response to Fenofibrate in Individuals With Type 2 Diabetes

Individuals with type 2 diabetes (T2D) and dyslipidemia are at an increased risk of cardiovascular disease. Fibrates are a class of drugs prescribed to treat dyslipidemia, but variation in response has been observed. To evaluate common and rare genetic variants that impact lipid responses to fenofibrate in statin-treated patients with T2D, we examined lipid changes in response to fenofibrate therapy using a genomewide association study (GWAS). Associations were followed-up using gene expression studies in mice. Common variants in SMAD3 and IPO11 were marginally associated with lipid changes in black subjects (P < 5 × 10-6 ). Rare variant and gene expression changes were assessed using a false discovery rate approach. AKR7A3 and HSD17B13 were associated with lipid changes in white subjects (q < 0.2). Mice fed fenofibrate displayed reductions in Hsd17b13 gene expression (q < 0.1). Associations of variants in SMAD3, IPO11, and HSD17B13, with gene expression changes in mice indicate that transforming growth factor-beta (TGF-β) and NRF2 signaling pathways may influence fenofibrate effects on dyslipidemia in patients with T2D.

Genetic basis of diabetic kidney disease and other diabetic complications

Diabetic kidney disease and other long-term complications are common in diabetes, and comprise the main cause of co-morbidity and premature mortality in individuals with diabetes. While familial clustering and heritability have been reported for all diabetic complications, the genetic background and the molecular mechanisms remain poorly understood. In recent years, genome-wide association studies have identified a few susceptibility loci for the renal complications as well as for diabetic retinopathy, diabetic cardiovascular disease and mortality. As for many complex diseases, the genetic factors increase the risk of complications in concert with the environment, and certain associations seem specific for particular conditions, for example, SP3-CDCA7 associated with end-stage renal disease only in women, or MGMT and variants on chromosome 5q13 associated with cardiovascular mortality only under tight glycaemic control. The characterization of the phenotypes is one of the main challenges for genetic research on diabetic complications, in addition to an urgent need to increase the number of individuals with diabetes with high quality phenotypic data to be included in future genetic studies.

Modulation of GLP-1 Levels by a Genetic Variant That Regulates the Cardiovascular Effects of Intensive Glycemic Control in ACCORD

OBJECTIVE

A genome-wide association study in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial identified two markers (rs57922 and rs9299870) that were significantly associated with cardiovascular mortality during intensive glycemic control and could potentially be used, when combined into a genetic risk score (GRS), to identify patients with diabetes likely to derive benefit from intensive control rather than harm. The aim of this study was to gain insights into the pathways involved in the modulatory effect of these variants.

RESEARCH DESIGN AND METHODS

Fasting levels of 65 biomarkers were measured at baseline and at 12 months of follow-up in the ACCORD-Memory in Diabetes (ACCORD-MIND) MRI substudy (n = 562). Using linear regression models, we tested the association of the GRS with baseline and 12-month biomarker levels, and with their difference (Δ), among white subjects, with genotype data (n = 351) stratified by intervention arm.

RESULTS

A significant association was observed between GRS and ΔGLP-1 (glucagon-like peptide 1, active) in the intensive arm (P = 3 × 10-4). This effect was driven by rs57922 (P = 5 × 10-4). C/C homozygotes, who had been found to derive cardiovascular benefits from intensive treatment, showed a 22% increase in GLP-1 levels during follow-up. By contrast, T/T homozygotes, who had been found to experience increased cardiac mortality with intensive treatment, showed a 28% reduction in GLP-1 levels. No association between ΔGLP-1 and GRS or rs57922 was observed in the standard treatment arm.

CONCLUSIONS

Differences in GLP-1 axis activation may mediate the modulatory effect of variant rs57922 on the cardiovascular response to intensive glycemic control. These findings highlight the importance of GLP-1 as a cardioprotective factor.

Progress in Defining the Genetic Basis of Diabetic Complications

PURPOSE OF REVIEW

Diabetic complications affecting the kidneys, retina, nerves, and the cardiovasculature are the major causes of morbidity and mortality in diabetes. This paper aims to review the current understanding of the genetic basis of these complications, based on recent findings especially from genome-wide association studies.

RECENT FINDINGS

Variants in or near AFF3, RGMA-MCTP2, SP3-CDCA7, GLRA3, CNKSR3, and UMOD have reached genome-wide significance (p value <5 × 10^-8) for association with diabetic kidney disease, and recently, GRB2 was reported to be associated at genome-wide significance with diabetic retinopathy. While some loci affecting cardiovascular disease in the general population have been replicated in diabetes, GLUL affects the risk of cardiovascular disease specifically in diabetic subjects. Genetic findings are emerging for diabetic complications, although the studies remain relatively small compared to those for type 1 and type 2 diabetes. In addition to pinpointing specific loci, the studies also reveal biological information on correlated traits and pathways.