A Mendelian randomization study of the effect of type-2 diabetes on coronary heart disease

Mendelian randomisation: A powerful and inexpensive method for identifying and excluding non-genetic risk factors for colorectal cancer

Colorectal cancer (CRC) is the third most common cancer in economically developed countries and a major cause of cancer-related mortality. The importance of lifestyle and diet as major determinants of CRC risk is suggested by differences in CRC incidence between countries and in migration studies. Previous observational epidemiological studies have identified associations between modifiable environmental risk factors and CRC, but these studies can be susceptible to reverse causation and confounding, and their results can therefore conflict. Mendelian randomisation (MR) analysis represents an approach complementary to conventional observational studies examining associations between exposures and disease. The MR strategy employs allelic variants as instrumental variables (IVs), which act as proxies for non-genetic exposures. These allelic variants are randomly assigned during meiosis and can therefore inform on life-long exposure, whilst not being subject to reverse causation. In previous studies MR frameworks have associated several modifiable factors with CRC risk, including adiposity, hyperlipidaemia, fatty acid profile and alcohol consumption. In this review we detail the use of MR to investigate and discover CRC risk factors, and its future applications.

The Genetic Epidemiology of Type 2 Diabetes: Opportunities for Health Translation

PURPOSE OF REVIEW

Genome-wide association studies have delineated the genetic architecture of type 2 diabetes. While functional studies to identify target transcripts are ongoing, new genetic knowledge can be translated directly to health applications. The review covers several translation directions but focuses on genomic polygenic scores for screening and prevention.

RECENT FINDINGS

Over 400 genomic variants associated with T2D and its related quantitative traits are now known. Genetic scores comprising dozens to millions of associated variants can predict incident T2D. However, measurement of body mass index is more efficient than genetic scores to detect T2D risk groups, and knowledge of T2D genetic risk alone seems insufficient to improve health. Genetically determined metabolic sub-phenotypes can be identified by clustering variants associated with physiological axes like insulin resistance. Genetic sub-phenotyping may be a way forward to identify specific individual phenotypes for prevention and treatment. Genomic polygenic scores for T2D can predict incident diabetes but may not be useful to improve health overall. Genetic detection of T2D sub-phenotypes could be useful to personalize screening and care.

Mendelian Randomization Analysis of Hemoglobin A1c as a Risk Factor for Coronary Artery Disease

OBJECTIVE

Observational studies show that higher hemoglobin A1c (A1C) predicts coronary artery disease (CAD). It remains unclear whether this association is driven entirely by glycemia. We used Mendelian randomization (MR) to test whether A1C is causally associated with CAD through glycemic and/or nonglycemic factors.

RESEARCH DESIGN AND METHODS

To examine the association of A1C with CAD, we selected 50 A1C-associated variants (log10 Bayes factor ≥6) from an A1C genome-wide association study (GWAS; n = 159,940) and performed an inverse-variance weighted average of variant-specific causal estimates from CAD GWAS data (CARDIoGRAMplusC4D; 60,801 CAD case subjects/123,504 control subjects). We then replicated results in UK Biobank (18,915 CAD case subjects/455,971 control subjects) and meta-analyzed all results. Next, we conducted analyses using two subsets of variants, 16 variants associated with glycemic measures (fasting or 2-h glucose) and 20 variants associated with erythrocyte indices (e.g., hemoglobin [Hb]) but not glycemic measures. In additional MR analyses, we tested the association of Hb with A1C and CAD.

RESULTS

Genetically increased A1C was associated with higher CAD risk (odds ratio [OR] 1.61 [95% CI 1.40, 1.84] per %-unit, P = 6.9 × 10-12). Higher A1C was associated with increased CAD risk when using only glycemic variants (OR 2.23 [1.73, 2.89], P = 1.0 × 10-9) and when using only erythrocytic variants (OR 1.30 [1.08, 1.57], P = 0.006). Genetically decreased Hb, with concomitantly decreased mean corpuscular volume, was associated with higher A1C (0.30 [0.27, 0.33] %-unit, P = 2.9 × 10-6) per g/dL and higher CAD risk (OR 1.19 [1.04, 1.37], P = 0.02).

CONCLUSIONS

Genetic evidence supports a causal link between higher A1C and higher CAD risk. This relationship is driven not only by glycemic but also by erythrocytic, glycemia-independent factors.

Dysglycemia and the Density of the Coronary Vasa Vasorum

OBJECTIVE

This study was conducted to determine the relationship between dysglycemia and the coronary artery vasa vasorum density.

RESEARCH DESIGN AND METHODS

The left anterior descending coronary artery was removed from 57 deceased individuals during autopsy, and the capillaries in the vessel wall were identified using fluorescent immunohistochemical staining. HbA_1c was determined in postmortem whole blood for each individual. The density of the vasa vasorum in the intima-media and the adventitia was manually quantified and recorded by readers unaware of the individual's other characteristics.

RESULTS

The individuals with diabetes had a lower density of the coronary vasa vasorum than those without diabetes. The higher the HbA_1c, the lower the density of these vessels in the adventitia and entire vessel wall.

CONCLUSIONS

Dysglycemia-induced damage to the vasa vasorum may promote ischemic heart disease in people with diabetes.

Epidemiology of Diabetes Mellitus and Cardiovascular Disease

PURPOSE OF REVIEW

Diabetes mellitus (DM) has become a rising epidemic in the last century, more pressing in the last few decades with the exponential rise of obesity, and has become one of the leading causes of death worldwide.

RECENT FINDINGS

Genetic variants have also been a new field of epidemiology research to determine the underlying genetic component of those risk factors and the association of DM with CVD. In light of its significant prevalence, patients remain unaware of their disease progression that arises from genetic and metabolic risk factors. As compared to non-diabetics, those with type 2 DM carry a higher mortality risk from cardiovascular disease (CVD) across different ethnicity groups and sex. The most common cardiovascular manifestations in those with DM include heart failure, peripheral arterial disease, and coronary heart disease. Although DM does predispose patients to CVD, it in fact is not a risk equivalent, but carries significant heterogeneity in risk for CVD.

The APOE∗3-Leiden Heterozygous Glucokinase Knockout Mouse as Novel Translational Disease Model for Type 2 Diabetes, Dyslipidemia, and Diabetic Atherosclerosis

BACKGROUND

There is a lack of predictive preclinical animal models combining atherosclerosis and type 2 diabetes. APOE∗3-Leiden (E3L) mice are a well-established model for diet-induced hyperlipidemia and atherosclerosis, and glucokinase^+/- (GK^+/-) mice are a translatable disease model for glucose control in type 2 diabetes. The respective mice respond similarly to lipid-lowering and antidiabetic drugs as humans. The objective of this study was to evaluate/characterize the APOE^∗3-Leiden.glucokinase^+/- (E3L.GK^+/-) mouse as a novel disease model to study the metabolic syndrome and diabetic complications.

METHODS

Female E3L.GK^+/-, E3L, and GK^+/- mice were fed fat- and cholesterol-containing diets for 37 weeks, and plasma parameters were measured throughout. Development of diabetic macro- and microvascular complications was evaluated.

RESULTS

Cholesterol and triglyceride levels were significantly elevated in E3L and E3L.GK^+/- mice compared to GK^+/- mice, whereas fasting glucose was significantly increased in E3L.GK^+/- and GK^+/- mice compared to E3L. Atherosclerotic lesion size was increased 2.2-fold in E3L.GK^+/- mice as compared to E3L (p = 0.037), which was predicted by glucose exposure (R ² = 0.636, p = 0.001). E3L and E3L.GK^+/- mice developed NASH with severe inflammation and fibrosis which, however, was not altered by introduction of the defective GK phenotype, whereas mild kidney pathology with tubular vacuolization was present in all three phenotypes.

CONCLUSIONS

We conclude that the E3L.GK^+/- mouse is a promising novel diet-inducible disease model for investigation of the etiology and evaluation of drug treatment on diabetic atherosclerosis.

Age-Related Changes in Glucose Metabolism, Hyperglycemia, and Cardiovascular Risk

Aging and diabetes mellitus are 2 well-known risk factors for cardiovascular disease (CVD). During the past 50 years, there has been an dramatic increase in life expectancy with a simultaneous increase in the prevalence of diabetes mellitus in the older population. This large number of older individuals with diabetes mellitus is problematic given that CVD risk associated with aging and diabetes mellitus. In this review, we summarize epidemiological data relating to diabetes mellitus and CVD, with an emphasis on the aging population. We then present data on hyperglycemia as a risk factor for CVD and review the current knowledge of age-related changes in glucose metabolism. Next, we review the role of obesity in the pathogenesis of age-related glucose dysregulation, followed by a summary of the results from major randomized controlled trials that focus on cardiovascular risk reduction through glycemic control, with a special emphasis on older adults. We then conclude with our proposed model of aging that body composition changes and insulin resistance link possible dysregulation of physiological pathways leading to obesity and diabetes mellitus-both forms of accelerated aging-and risks for CVD.

The Impact of Glycated Hemoglobin (HbA1c) on Cardiovascular Disease Risk: A Mendelian Randomization Study Using UK Biobank

OBJECTIVE

Glycated hemoglobin (HbA_1c) is positively associated with cardiovascular disease (CVD), although evidence is primarily observational. Mendelian randomization studies have only examined its relation with subtypes of CVD. We examined the relation of HbA_1c with CVD and its subtypes in the UK Biobank using Mendelian randomization.

RESEARCH DESIGN AND METHODS

We used 38 genetic variants strongly and independently related to HbA_1c (n = 123,665) applied to the UK Biobank (n = 392,038). We used inverse variance weighting (IVW) to obtain the associations of HbA_1c with CVD, coronary artery disease (CAD), and stroke (overall and stroke subtypes). Sensitivity analyses included Mendelian randomization (MR)-Egger, a weighted median, and exclusion of potentially invalid single nucleotide polymorphisms (SNPs). We also applied the same genetic instruments to CARDIoGRAMplusC4D (Coronary ARtery DIsease Genome wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics) 1000 Genomes-based genome-wide association study (n = 184,305) as a validation for CAD.

RESULTS

In the UK Biobank, HbA_1c was not associated with CVD using IVW (odds ratio [OR] 1.11 per %, 95% CI 0.83-1.48). However, HbA_1c was associated with increased CAD risk (OR 1.50 per %, 95% CI 1.08-2.11) with directionally consistent results from MR-Egger and weighted median. The positive association with CAD was more pronounced when we excluded potentially invalid SNPs (OR 2.24 per %, 95% CI 1.55-3.25). The positive association was replicated in CARDIoGRAM (OR 1.52 per %, 95% CI 1.03-2.26). The association of HbA_1c with stroke and its subtypes was less clear given the low number of cases.

CONCLUSIONS

HbA_1c likely causes CAD. The underlying mechanisms remain to be elucidated.

Genetic Evidence for the Association between Schizophrenia and Breast Cancer

OBJECTIVE

To estimate the potential effect of schizophrenia on breast cancer risk in women, we performed a two-sample Mendelian randomization (MR) study.

METHODS

The instrumental variables comprised 170 uncorrelated and non-pleiotropic single nucleotide polymorphisms (SNPs) that are significantly associated with schizophrenia risk in genome-wide association studies in 105,000 European descent individuals of the Psychiatric Genomics Consortium (http://www.med.unc.edu/pgc/) and the United Kingdom Clozapine Clinic. The association between these SNPs determined schizophrenia and breast cancer risk was estimated in approximately 229,000 European descent females from the Breast Cancer Association Consortium using the inverse-variance weighted and the weighted median MR methods.

RESULTS

We found that the genetically-predicted risk of schizophrenia was associated with increased breast cancer risk (under a random-effects model: odds ratio per 1 unit increase in log odds of schizophrenia = 1.04, 95% confidence interval: 1.02-1.06, p = 5.6 × 10-5). Similar significant associations were observed in analyses using a weighted median model and sensitivity analysis excluding six SNPs with genotype imputation score of less than 0.8, as well as analyses stratified by estrogen receptor status of breast cancer.

CONCLUSION

Our findings implicate a modest increased risk for breast cancer in genetically determined schizophrenic females.

Shared Genetic Contribution of Type 2 Diabetes and Cardiovascular Disease: Implications for Prognosis and Treatment

PURPOSE OF REVIEW

The increased cardiovascular disease (CVD) risk in subjects with type 2 diabetes (T2D) is well established. This review collates the available evidence and assesses the shared genetic background between T2D and CVD: the causal contribution of common risk factors to T2D and CVD and how genetics can be used to improve drug development and clinical outcomes.

RECENT FINDINGS

Large-scale genome-wide association studies (GWAS) of T2D and CVD support a shared genetic background but minimal individual locus overlap. Mendelian randomisation (MR) analyses show that T2D is causal for CVD, but GWAS of CVD, T2D and their common risk factors provided limited evidence for individual locus overlap. Distinct but functionally related pathways were enriched for CVD and T2D genetic associations reflecting the lack of locus overlap and providing some explanation for the variable associations of common risk factors with CVD and T2D from MR analyses.

Mendelian randomisation in type 2 diabetes and coronary artery disease

Type 2 diabetes, coronary artery disease and hypertension are associated with anthropometric and biomarker traits, including waist-to-hip-ratio, body mass index and altered glucose and insulin levels. Clinical trials, for example of weight-loss interventions, show these factors are causal, but lifelong impact of subtle changes in body mass index and body fat distribution are less clear. The use of human genetics can quantify the causal effects of long-term exposure to subtle changes of modifiable risk factors. Mendelian randomisation (MR) uses human genetic variants associated with the risk factor to quantify the relationship between risk factor and disease outcome. The last two years have seen an increase in the number of MR studies investigating the relationship between anthropometric traits and metabolic diseases. This review provides an overview of these recent MR studies in relation to type 2 diabetes, coronary artery disease and hypertension. MR provides evidence for causal associations of waist-to-hip-ratio, body mass index and altered glucose levels with type 2 diabetes, coronary artery disease and hypertension.

Poststatin era in atherosclerosis management: lessons from epidemiologic and genetic studies

PURPOSE OF REVIEW

Cardiovascular diseases (CVD) are the leading cause of death worldwide with over 17 million deaths every year and represent a major public health challenge. The last decade has seen the emergence of novel antiatherogenic therapies.

RECENT FINDINGS

Despite intensive lipid and blood pressure interventions, the burden of CVD is expected to markedly progress because of the global aging of the population and increasing exposure to detrimental lifestyle-related risk. Epidemiologic and genetic studies helped to better apprehend the biology of atherosclerosis and allowed pharmaceutical innovation and recent translational successes. This includes the development of novel lipid and glucose-lowering therapies and the leverage of anti-inflammatory therapies.

SUMMARY

Here, we discuss promises and expectations of emerging scientific and pharmaceutical innovations and translational successes to meet the global therapeutic demand.

Type 1 and type 2 diabetes mellitus and incidence of seven cardiovascular diseases

BACKGROUND

The association between type 1 diabetes mellitus (T1DM) and specific cardiovascular diseases (CVD) is uncertain. Furthermore, data on type 2 diabetes mellitus (T2DM) in relation to risk of aortic valve stenosis, atrial fibrillation, abdominal aortic aneurysm, and intracerebral hemorrhage are scarce and inconclusive. We examined the associations of T1DM and T2DM with incidence of seven CVD outcomes.

METHODS

This study comprised 71,483 Swedish adults from two population-based prospective cohorts. T1DM and T2DM diagnosis and incident CVD cases were ascertained through linkage with the population-based registers.

RESULTS

T1DM was associated with myocardial infarction (hazard ratio [HR] 3.26; 95% confidence interval [CI] 2.47-4.30), heart failure (HR 2.68; 95% CI 1.76-4.09), and ischemic stroke (HR 2.61; 95% CI 1.80-3.79). Increased risk of myocardial infarction, ischemic stroke, and heart failure was also observed in T2DM patients and the magnitude of the associations increased with longer T2DM duration. T2DM was also associated with an increased risk of aortic valve stenosis (HR 1.34; 95% CI 1.05-1.71) and with lower risk of abdominal aortic aneurysm (HR 0.57; 95% CI 0.40-0.82) and intracerebral hemorrhage (HR 0.51; 95% CI 0.30-0.88). Only long-term T2DM (≥20 years) was associated with an increased risk of atrial fibrillation (HR 1.44; 95% CI 1.02-2.04).

CONCLUSION

T1DM and T2DM are associated with increased risk of major CVD outcomes.

TRIAL REGISTRATION

The Cohort of Swedish Men and the Swedish Mammography Cohort are registered at clinicaltrials.gov as NCT01127711 and NCT01127698, respectively.

Impact of atopy on risk of glioma: a Mendelian randomisation study

BACKGROUND

An inverse relationship between allergies with glioma risk has been reported in several but not all epidemiological observational studies. We performed an analysis of genetic variants associated with atopy to assess the relationship with glioma risk using Mendelian randomisation (MR), an approach unaffected by biases from temporal variability and reverse causation that might have affected earlier investigations.

METHODS

Two-sample MR was undertaken using genome-wide association study data. We used single nucleotide polymorphisms (SNPs) associated with atopic dermatitis, asthma and hay fever, IgE levels, and self-reported allergy as instrumental variables. We calculated MR estimates for the odds ratio (OR) for each risk factor with glioma using SNP-glioma estimates from 12,488 cases and 18,169 controls, using inverse-variance weighting (IVW), maximum likelihood estimation (MLE), weighted median estimate (WME) and mode-based estimate (MBE) methods. Violation of MR assumptions due to directional pleiotropy were sought using MR-Egger regression and HEIDI-outlier analysis.

RESULTS

Under IVW, MLE, WME and MBE methods, associations between glioma risk with asthma and hay fever, self-reported allergy and IgE levels were non-significant. An inverse relationship between atopic dermatitis and glioma risk was found by IVW (OR 0.96, 95% confidence interval (CI) 0.93-1.00, P = 0.041) and MLE (OR 0.96, 95% CI 0.94-0.99, P = 0.003), but not by WME (OR 0.96, 95% CI 0.91-1.01, P = 0.114) or MBE (OR 0.97, 95% CI 0.92-1.02, P = 0.194).

CONCLUSIONS

Our investigation does not provide strong evidence for relationship between atopy and the risk of developing glioma, but findings do not preclude a small effect in relation to atopic dermatitis. Our analysis also serves to illustrate the value of using several MR methods to derive robust conclusions.

Association between single nucleotide polymorphism rs11057401 of CCDC92 gene and the risk of coronary heart disease (CHD)

Background

Given that the CCDC92 (coiled-coil domain containing 92) was important in insulin resistance, we sought to investigate whether the CCDC92 rs825476 SNP is associated with the risk of CHD in Chinese Han population.

Methods

Rs11057401 was genotyped for 817 patients with CHD and 724 age- and sex-matched controls using PCR-based Invader assay with the probe sets designed and synthesized by third wave.

Results

Patients were found to have a significantly higher frequency of AA than the controls (23.5% vs. 14.7%, OR = 1.60, p = 0.000), and the frequency of allele A was found to be remarkably higher in the patients than the controls (48.1% vs. 40.3%, OR = 1.19, p = 0.000). Multivariate logistic analysis showed that the incidence of CHD was positively correlated with hyperlipidemia, T2D and rs11057401 AA/AT genotypes. The FPG, TC, and ApoA1 levels in the CHD patients were different among the AA, AT and TT genotypes (P < 0.05), the A allele carriers had higher FPG, TC and lower ApoA1 levels than the A allele non-carriers (P < 0.05).

Conclusion

The genotypic and allelic frequencies of the rs11057401 SNP were significantly different between the patients with CHD and controls. Subjects with AA genotype or A allele were associated with an increased risk of CHD. The AA/AT genotypes were also associated with increased serum FPG, TC and decreased ApoA1 in CHD.

Implementing genome-driven personalized cardiology in clinical practice

Genomics designates the coordinated investigation of a large number of genes in the context of a biological process or disease. It may be long before we attain comprehensive understanding of the genomics of common complex cardiovascular diseases (CVDs) such as inherited cardiomyopathies, valvular diseases, primary arrhythmogenic conditions, congenital heart syndromes, hypercholesterolemia and atherosclerotic heart disease, hypertensive syndromes, and heart failure with preserved/reduced ejection fraction. Nonetheless, as genomics is evolving rapidly, it is constructive to survey now pertinent concepts and breakthroughs. Today, clinical multimodal electronic medical/health records (EMRs/EHRs) incorporating genomic information establish a continuously-learning, vast knowledge-network with seamless cycling between clinical application and research. It can inform insights into specific pathogenetic pathways, guide biomarker-assisted precise diagnoses and individualized treatments, and stratify prognoses. Complex CVDs blend multiple interacting genomic variants, epigenetics, and environmental risk-factors, engendering progressions of multifaceted disease-manifestations, including clinical symptoms and signs. There is no straight-line linkage between genetic cause(s) or causal gene-variant(s) and disease phenotype(s). Because of interactions involving modifier-gene influences, (micro)-environmental, and epigenetic effects, the same variant may actually produce dissimilar abnormalities in different individuals. Implementing genome-driven personalized cardiology in clinical practice reveals that the study of CVDs at the level of molecules and cells can yield crucial clinical benefits. Complementing evidence-based medicine guidelines from large ("one-size fits all") randomized controlled trials, genomics-based personalized or precision cardiology is a most-creditable paradigm: It provides customizable approaches to prevent, diagnose, and manage CVDs with treatments directly/precisely aimed at causal defects identified by high-throughput genomic technologies. They encompass stem cell and gene therapies exploiting CRISPR-Cas9-gene-editing, and metabolomic-pharmacogenomic therapeutic modalities, precisely fine-tuned for the individual patient. Following the Human Genome Project, many expected genomics technology to provide imminent solutions to intractable medical problems, including CVDs. This eagerness has reaped some disappointment that advances have not yet materialized to the degree anticipated. Undoubtedly, personalized genetic/genomics testing is an emergent technology that should not be applied without supplementary phenotypic/clinical information: Genotype≠Phenotype. However, forthcoming advances in genomics will naturally build on prior attainments and, combined with insights into relevant epigenetics and environmental factors, can plausibly eradicate intractable CVDs, improving human health and well-being.

The Genetic Link Between Diabetes and Atherosclerosis

Epidemiological studies have indicated that the risk of atherothrombotic coronary artery disease (CAD) is higher in patients with diabetes, but these results have not been consistently observed across clinical trials. To address this apparent discrepancy, we can apply the results of genome-wide association studies (GWAS) to provide a better understanding of the shared genetic architecture of diabetes and atherothrombotic CAD. For instance, a large GWAS has identified 16 novel loci that are associated with both diabetes and atherothrombotic CAD. These genetic variants may also be used to assess potential causal relationships reported in observational studies and clinical trials through Mendelian randomization analyses. For example, several Mendelian randomization analyses have shown that diabetes is associated with CAD independent of other risk factors (odds ratio [OR]: 1.63, 95% confidence interval [CI]: 1.23-2.07; P = 0.002). Furthermore, Mendelian randomization analyses can provide more insight into the perceived risk of diabetes among patients without diabetes receiving statin therapy. Here, genetically lower activity of HMG-CoA reductase (HMGCR) was associated with a modest increase in diabetes (OR per allele: 1.02, 95% CI: 1.00-1.05). These results highlight the biological mechanisms that link diabetes with the use of statins. In addition, this work illustrates the great potential value of genetic studies to clarify the mechanistic relationships among atherosclerotic vascular disease, dysglycemia, and diabetes. More research is needed to delineate and subsequently better understand the genetic links between diabetes and atherosclerosis.

A Decade of Genetic and Metabolomic Contributions to Type 2 Diabetes Risk Prediction

PURPOSE OF REVIEW

The purpose of this review was to summarize and reflect on advances over the past decade in human genetic and metabolomic discovery with particular focus on their contributions to type 2 diabetes (T2D) risk prediction.

RECENT FINDINGS

In the past 10 years, a combination of advances in genotyping efficiency, metabolomic profiling, bioinformatics approaches, and international collaboration have moved T2D genetics and metabolomics from a state of frustration to an abundance of new knowledge. Efforts to control and prevent T2D have failed to stop this global epidemic. New approaches are needed, and although neither genetic nor metabolomic profiling yet have a clear clinical role, the rapid pace of accumulating knowledge offers the possibility for "multi-omic" prediction to improve health.

The role of glycaemic and lipid risk factors in mediating the effect of BMI on coronary heart disease: a two-step, two-sample Mendelian randomisation study

AIMS/HYPOTHESIS

The extent to which effects of BMI on CHD are mediated by glycaemic and lipid risk factors is unclear. In this study we examined the effects of these traits using genetic evidence.

METHODS

We used two-sample Mendelian randomisation to determine: (1) the causal effect of BMI on CHD (60,801 case vs 123,504 control participants), type 2 diabetes (34,840 case vs 114,981 control participants), fasting glucose (n = 46,186), insulin (n = 38,238), HbA_1c (n = 46,368) and LDL-cholesterol, HDL-cholesterol and triacylglycerols (n = 188,577); (2) the causal effects of glycaemic and lipids traits on CHD; and (3) the extent to which these traits mediate any effect of BMI on CHD.

RESULTS

One SD higher BMI (~ 4.5 kg/m²) was associated with higher risk of CHD (OR 1.45 [95% CI 1.27, 1.66]) and type 2 diabetes (1.96 [95% CI 1.35, 2.83]), higher levels of fasting glucose (0.07 mmol/l [95% CI 0.03, 0.11]), HbA_1c (0.05% [95% CI 0.01, 0.08]), fasting insulin (0.18 log pmol/l [95% CI 0.14, 0.22]) and triacylglycerols (0.20 SD [95% CI 0.14, 0.26]) and lower levels of HDL-cholesterol (-0.23 SD [95% CI -0.32, -0.15]). There was no evidence for a causal relation between BMI and LDL-cholesterol. The causal associations of higher triacylglycerols, HbA_1c and diabetes risk with CHD risk remained after performing sensitivity analyses that considered different models of horizontal pleiotropy. The BMI-CHD effect reduced from 1.45 to 1.16 (95% CI 0.99, 1.36) and to 1.36 (95% CI 1.19, 1.57) with genetic adjustment for triacylglycerols or HbA_1c, respectively, and to 1.09 (95% CI 0.94, 1.27) with adjustment for both.

CONCLUSIONS/INTERPRETATION

Increased triacylglycerol levels and poor glycaemic control appear to mediate much of the effect of BMI on CHD.

Identification of new susceptibility loci for type 2 diabetes and shared etiological pathways with coronary heart disease

To evaluate the shared genetic etiology of type 2 diabetes (T2D) and coronary heart disease (CHD), we conducted a genome-wide, multi-ancestry study of genetic variation for both diseases in up to 265,678 subjects for T2D and 260,365 subjects for CHD. We identify 16 previously unreported loci for T2D and 1 locus for CHD, including a new T2D association at a missense variant in HLA-DRB5 (odds ratio (OR) = 1.29). We show that genetically mediated increase in T2D risk also confers higher CHD risk. Joint T2D-CHD analysis identified eight variants-two of which are coding-where T2D and CHD associations appear to colocalize, including a new joint T2D-CHD association at the CCDC92 locus that also replicated for T2D. The variants associated with both outcomes implicate new pathways as well as targets of existing drugs, including icosapent ethyl and adipocyte fatty-acid-binding protein.

The Genetic Architecture of Coronary Artery Disease: Current Knowledge and Future Opportunities

PURPOSE OF REVIEW

We provide an overview of our current understanding of the genetic architecture of coronary artery disease (CAD) and discuss areas of research that provide excellent opportunities for further exploration.

RECENT FINDINGS

Large-scale studies in human populations, coupled with rapid advances in genetic technologies over the last decade, have clearly established the association of common genetic variation with risk of CAD. However, the effect sizes of the susceptibility alleles are for the most part modest and collectively explain only a small fraction of the overall heritability. By comparison, evidence that rare variants make a substantial contribution to risk of CAD has been somewhat disappointing thus far, suggesting that other biological mechanisms have yet to be discovered. Emerging data suggests that novel pathways involved in the development of CAD can be identified through complementary and integrative systems genetics strategies in mice or humans. There is also convincing evidence that gut bacteria play a previously unrecognized role in the development of CAD, particularly through metabolism of certain dietary nutrients that lead to proatherogenic metabolites in the circulation. A major effort is now underway to functionally understand the newly discovered genetic and biological associations for CAD, which could lead to the development of potentially novel therapeutic strategies. Other important areas of investigation for understanding the pathophysiology of CAD, including epistatic interactions between genes or with either sex and environmental factors, have not been studied on a broad scope and represent additional opportunities for future studies.

Genetic Variation at the Sulfonylurea Receptor, Type 2 Diabetes, and Coronary Heart Disease

Despite widespread clinical use in the treatment of type 2 diabetes, the impact of sulfonylurea therapy on cardiovascular outcomes remains uncertain. Studies of naturally occurring genetic variation can be used to anticipate the expected clinical consequences of a pharmacological therapy. A common missense variant in the gene encoding a component of the sulfonylurea receptor (ABCC8 p.A1369S) promotes closure of the target channel of sulfonylurea therapy and is associated with increased insulin secretion, thus mimicking the effects of sulfonylurea therapy. Using individual-level data from 120,286 participants in the UK Biobank and summary association results from four large-scale genome-wide association studies, we examined the impact of this variant on cardiometabolic traits, type 2 diabetes, and coronary heart disease. The p.A1369S variant was associated with a significantly lower risk of type 2 diabetes (odds ratio [OR] 0.93; 95% CI 0.91, 0.95; P = 1.2 × 10-11). The variant was associated with increased BMI (+0.062 kg/m2; 95% CI 0.037, 0.086; P = 8.1 × 10-7) but lower waist-to-hip ratio adjusted for BMI, a marker of abdominal fat distribution. Furthermore, p.A1369S was associated with a reduced risk of coronary heart disease (OR 0.98; 95% CI 0.96, 0.99; P = 5.9 × 10-4). These results suggest that, despite a known association with increased weight, long-term sulfonylurea therapy may reduce the risk of coronary heart disease.

The Genetics of Ischemic Heart Disease: From Current Knowledge to Clinical Implications

Ischemic heart disease continues to cause high morbidity and mortality. Its prevalence is expected to increase due to population aging, and its prevention is a major goal of health policies. The risk of developing ischemic heart disease is related to a complex interplay between genetic, environmental, and lifestyle factors. In the last decade, considerable progress has been made in knowledge of the genetic architecture of this disease. This narrative review provides an overview of current knowledge of the genetics of ischemic heart disease and of its translation to clinical practice: identification of new therapeutic targets, assessment of the causal relationship between biomarkers and disease, improved risk prediction, and identification of responders and nonresponders to specific drugs (pharmacogenomics).

Genetically Driven Hyperglycemia Increases Risk of Coronary Artery Disease Separately From Type 2 Diabetes

OBJECTIVE

This study tested the hypothesis that genetically raised hyperglycemia increases coronary artery disease (CAD) risk separately from the risk conferred by type 2 diabetes as a whole.

RESEARCH DESIGN AND METHODS

We conducted a Mendelian randomization (MR) analysis using summary-level statistics from the largest published meta-analyses of genome-wide association studies (GWAS) for fasting glucose (FG) (n = 133,010 participants free of diabetes) and CAD (n = 63,746 case subjects and 130,681 control subjects) of predominantly European ancestry. FG-increasing variants associated with type 2 diabetes from the largest GWAS for type 2 diabetes were excluded. Variants with pleiotropic effects on other CAD risk factors (blood lipids, blood pressure, and obesity) were excluded using summary-level data from the largest published GWAS. Data from the Framingham Heart Study were used to validate the MR instrument and to build an FG genetic risk score (GRS).

RESULTS

In an instrumental variable analysis comprising 12 FG-raising variants, a 1 mmol/L increase in FG revealed an effect-size estimate of 1.43 CAD odds (95% CI 1.14-1.79). The association was preserved after excluding variants for heterogeneity and pleiotropic effects on other CAD risk factors (odds ratio [OR] 1.33 [95% CI 1.02-1.73]). The 12 FG-increasing variants did not significantly increase type 2 diabetes risk (OR 1.05 [95% CI 0.91-1.23]), and its prevalence was constant across FG GRS quintiles (P = 0.72).

CONCLUSIONS

Our data support that genetic predisposition to hyperglycemia raises the odds of CAD separately from type 2 diabetes and other CAD risk factors. These findings suggest that modulating glycemia may provide cardiovascular benefit.

A Mendelian Randomization Study of the Effect of Type-2 Diabetes and Glycemic Traits on Bone Mineral Density

Type-2 diabetes (T2D) is associated in observational studies with both higher bone mineral density (BMD) and higher fracture risk for given BMD. These relationships may however be confounded by factors such as body mass index (BMI). Here we used Mendelian randomization (MR) to obtain non-confounded estimates of the effect of T2D and glycemic traits on BMD. We identified genetic variants strongly associated with T2D risk (34,840 T2D cases and 114,981 controls) and fasting glucose (133,010 nondiabetic individuals), but not associated with BMI, and determined the effects of these variants on BMD (up to 83,894 individuals). Using these variants as instrumental variables, we found that a genetically-increased risk of T2D increased femoral neck BMD (+0.034 SD in BMD per unit increase in log-odds of T2D [95% CI, 0.001 to 0.067; p = 0.044]). Genetically-increased fasting glucose also increased femoral neck BMD (+0.13 SD in BMD per mmol/L increase in fasting glucose [95% CI, 0.01 to 0.25; p = 0.034]). Similar nonsignificant trends were observed for the effects of T2D and fasting glucose on lumbar spine BMD. Our results indicate that both genetically-increased T2D risk and genetically-increased fasting glucose have weak positive effects on BMD. © 2016 American Society for Bone and Mineral Research.

Different inverse association of large high-density lipoprotein subclasses with exacerbation of insulin resistance and incidence of type 2 diabetes: The Nagahama study

AIMS

In addition to its antiatherogenic action, high-density lipoprotein (HDL) may also have an antidiabetes function. Although the biological actions of small HDL (HDL3) and large HDL (HDL2) subclasses may be different, evidence in support of that hypothesis is lacking. The aim of this study was to clarify the difference in prognostic significance of HDL subclasses for exacerbation of insulin resistance and incidence of type 2 diabetes in the general population.

METHODS

Study participants included 8365 community residents 52±13years of age not taking lipid lowering drugs. Serum HDL cholesterol subclasses and low-density lipoprotein subclasses, were measured by a homogeneous assay. Insulin resistance was assessed by homeostasis model assessment of insulin resistance (HOMA-IR).

RESULTS

Cross-sectional analysis adjusted for possible covariates found that HDL2 cholesterol (HDL2-C) levels were inversely associated with HOMA-IR (β=-0.169, p<0.001), whereas HDL3-C had the opposite association (β=0.054, p<0.001). Similar results were found in an analysis for type 2 diabetes (HDL2-C, odds ratio=0.96, p=0.001; HDL3-C, odds ratio=1.04, p=0.181). In a longitudinal analysis with 5.0years of follow-up, HDL2-C was inversely associated with exacerbation of insulin resistance (β=-0.163, p<0.001); HDL3-C had the opposite association (β=0.026, p=0.037). During follow-up, 205 individuals were newly diagnosed with diabetes, and HDL2-C level was associated with an inverse risk of type 2 diabetes incidence (odds ratio=0.98, p=0.006).

CONCLUSIONS

HDL may have an antidiabetic function; the prognostic value of HDL2-C for diabetes and insulin resistance might be better than that of HDL3-C.

Relationship between salivary/pancreatic amylase and body mass index: a systems biology approach

BACKGROUND

Salivary (AMY1) and pancreatic (AMY2) amylases hydrolyze starch. Copy number of AMY1A (encoding AMY1) was reported to be higher in populations with a high-starch diet and reduced in obese people. These results based on quantitative PCR have been challenged recently. We aimed to re-assess the relationship between amylase and adiposity using a systems biology approach.

METHODS

We assessed the association between plasma enzymatic activity of AMY1 or AMY2, and several metabolic traits in almost 4000 French individuals from D.E.S.I.R. longitudinal study. The effect of the number of copies of AMY1A (encoding AMY1) or AMY2A (encoding AMY2) measured through droplet digital PCR was then analyzed on the same parameters in the same study. A Mendelian randomization analysis was also performed. We subsequently assessed the association between AMY1A copy number and obesity risk in two case-control studies (5000 samples in total). Finally, we assessed the association between body mass index (BMI)-related plasma metabolites and AMY1 or AMY2 activity.

RESULTS

We evidenced strong associations between AMY1 or AMY2 activity and lower BMI. However, we found a modest contribution of AMY1A copy number to lower BMI. Mendelian randomization identified a causal negative effect of BMI on AMY1 and AMY2 activities. Yet, we also found a significant negative contribution of AMY1 activity at baseline to the change in BMI during the 9-year follow-up, and a significant contribution of AMY1A copy number to lower obesity risk in children, suggesting a bidirectional relationship between AMY1 activity and adiposity. Metabonomics identified a BMI-independent association between AMY1 activity and lactate, a product of complex carbohydrate fermentation.

CONCLUSIONS

These findings provide new insights into the involvement of amylase in adiposity and starch metabolism.

Mendelian Randomization and Type 2 Diabetes

Type 2 diabetes (T2DM) is a common, complex disease that poses a substantial burden on individual and population health, but we have relatively limited understanding of its underlying pathophysiology. Observational studies have highlighted large numbers of risk factors for T2DM, some of which are modifiable through behavioural or pharmacological intervention. Determining which of these risk factors plays a causal role in the development of T2DM has been a challenge, but Mendelian randomisation (MR) studies are harnessing genetic data in population studies to offer new insights. Using evolving analytical methods, MR studies continue to address questions of causality related to T2DM, including exploring the roles of adiposity, blood lipids and inflammation. The causal roles of a number of important modifiable risk factors have been confirmed by MR studies, while the relevance of others has been called into question. As more MR studies are conducted, methods are developed and refined in order to make the most efficient and reliable use of available genetic and phenotypic data. In this review, the design and findings of some important MR studies related to T2DM are explored and their relevance for translation to clinical practice considered.

A 19-SNP coronary heart disease gene score profile in subjects with type 2 diabetes: the coronary heart disease risk in type 2 diabetes (CoRDia study) study baseline characteristics

Background

The coronary risk in diabetes (CoRDia) trial (n = 211) compares the effectiveness of usual diabetes care with a self-management intervention (SMI), with and without personalised risk information (including genetics), on clinical and behavioural outcomes. Here we present an assessment of randomisation, the cardiac risk genotyping assay, and the genetic characteristics of the recruits.

Methods

Ten-year coronary heart disease (CHD) risk was calculated using the UKPDS score. Genetic CHD risk was determined by genotyping 19 single nucleotide polymorphisms (SNPs) using Randox’s Cardiac Risk Prediction Array and calculating a gene score (GS). Accuracy of the array was assessed by genotyping a subset of pre-genotyped samples (n = 185).

Results

Overall, 10-year CHD risk ranged from 2–72 % but did not differ between the randomisation groups (p = 0.13). The array results were 99.8 % concordant with the pre-determined genotypes. The GS did not differ between the Caucasian participants in the CoRDia SMI plus risk group (n = 66) (p = 0.80) and a sample of UK healthy men (n = 1360). The GS was also associated with LDL-cholesterol (p = 0.05) and family history (p = 0.03) in a sample of UK healthy men (n = 1360).

Conclusions

CHD risk is high in this group of T2D subjects. The risk array is an accurate genotyping assay, and is suitable for estimating an individual’s genetic CHD risk.

Trial registration This study has been registered at ClinicalTrials.gov; registration identifier NCT01891786

The effect of hematocrit and hemoglobin on the risk of ischemic heart disease: A Mendelian randomization study

Hematocrit and hemoglobin affect viscosity, and have been considered as risk factors for ischemic heart disease (IHD), although observations are inconsistent; randomized controlled trials targeting hematocrit or hemoglobin have not been definitive. To clarify their role, the risk of IHD was assessed according to genetically determined hematocrit and hemoglobin. We applied single nucleotide polymorphisms (SNPs) strongly determining hematocrit and hemoglobin, from a genome wide association study, to a large case (64,746) control (130,681) study of coronary artery disease, CARDIoGRAMplusC4D, to obtain unconfounded estimates using instrumental variable analysis by combining the Wald estimators for each SNP taking into account any correlation between SNPs using weighted generalized linear regression. Hematocrit was positively associated with IHD, odds ratio (OR) 1.07 per %, 95% confidence interval (CI) 1.03 to 1.11, before and after excluding SNPs from gene regions directly functionally relevant to IHD. However, hematocrit was not associated with IHD (OR 0.99, 0.94 to 1.04) after also excluding SNPs associated with lipids at genome wide significance. Hemoglobin was not associated with IHD (OR 1.06 per g/dL, 0.97 to 1.15) which was similar (OR 1.02, 0.94 to 1.11) after excluding SNPs from gene regions directly functionally relevant to IHD. Hemoglobin was negatively associated with IHD after also excluding SNPs associated with lipids at genome wide significance (OR 0.86, 0.78 to 0.94). In conclusion, hematocrit shares genetic determinants with IHD, but whether the genes contribute to IHD via hematocrit or other mechanisms is not entirely clear. Higher Hemoglobin is unlikely to cause IHD.

Mendelian randomization analysis in three Japanese populations supports a causal role of alcohol consumption in lowering low-density lipid cholesterol levels and particle numbers

BACKGROUND AND AIMS

While alcohol consumption is known to increase plasma high-density lipoprotein (HDL) cholesterol levels, its relationship with low-density lipoprotein (LDL) cholesterol levels is unclear. Aldehyde dehydrogenase 2 (ALDH2) is a rate-controlling enzyme in alcohol metabolism, but a large number of Japanese people have the inactive allele. Here, we conducted a Mendelian randomization analysis using the ALDH2 genotype to clarify a causal role of alcohol on circulating cholesterol levels and lipoprotein particle numbers.

METHODS

This study was conducted in three independent general Japanese populations (men, n = 2289; women, n = 1940; mean age 63.3 ± 11.2 years). Alcohol consumption was assessed using a questionnaire. Lipoprotein particle numbers were determined by nuclear magnetic resonance spectroscopy.

RESULTS

Alcohol consumption increased linearly in proportion to the number of subjects carrying the enzymatically active *1 allele in men (p < 0.001). The *1 allele was also positively associated with HDL cholesterol level (adjusted mean ± standard error, *1*1: 60 ± 0.5, *1*2: 56 ± 0.6, *2*2: 55 ± 1.3 mg/dl, p < 0.001) and inversely associated with LDL cholesterol level (116 ± 0.9, 124 ± 1.1, 130 ± 2.6 mg/dl, p < 0.001). The *1 allele was also positively associated with HDL particle numbers (per-allele: 2.60 ± 0.32 μmol/l, p < 0.001) and inversely associated with LDL particle numbers (-67.8 ± 19.6 nmol/l, p = 0.001). Additional Mendelian randomization analysis failed to clarify the involvement of cholesteryl ester transfer protein in alcohol-related changes in lipoprotein cholesterol levels. No significant association was observed in women, presumably due to their small amount of alcohol intake.

CONCLUSIONS

Alcohol consumption has a causal role in not only increasing HDL cholesterol levels but also decreasing LDL cholesterol levels and particle numbers.

Polyunsaturated fatty acids and prostate cancer risk: a Mendelian randomisation analysis from the PRACTICAL consortium

BACKGROUND

Prostate cancer is a common cancer worldwide with no established modifiable lifestyle factors to guide prevention. The associations between polyunsaturated fatty acids (PUFAs) and prostate cancer risk have been inconsistent. Using Mendelian randomisation, we evaluated associations between PUFAs and prostate cancer risk.

METHODS

We used individual-level data from a consortium of 22 721 cases and 23 034 controls of European ancestry. Externally-weighted PUFA-specific polygenic risk scores (wPRSs), with explanatory variation ranging from 0.65 to 33.07%, were constructed and used to evaluate associations with prostate cancer risk per one standard deviation (s.d.) increase in genetically-predicted plasma PUFA levels using multivariable-adjusted unconditional logistic regression.

RESULTS

No overall association was observed between the genetically-predicted PUFAs evaluated in this study and prostate cancer risk. However, risk reductions were observed for short-chain PUFAs, linoleic (ORLA=0.95, 95%CI=0.92, 0.98) and α-linolenic acids (ORALA=0.96, 95%CI=0.93, 0.98), among men <62 years; whereas increased risk was found among men ⩾62 years for LA (ORLA=1.04, 95%CI=1.01, 1.07). For long-chain PUFAs (i.e., arachidonic, eicosapentaenoic, and docosapentaenoic acids), increased risks were observed among men <62 years (ORAA=1.05, 95%CI=1.02, 1.08; OREPA=1.04, 95%CI=1.01, 1.06; ORDPA=1.05, 95%CI=1.02, 1.08).

CONCLUSION

Results from this study suggest that circulating ω-3 and ω-6 PUFAs may have a different role in the aetiology of early- and late-onset prostate cancer.

Variant rs10911021 that associates with coronary heart disease in type 2 diabetes, is associated with lower concentrations of circulating HDL cholesterol and large HDL particles but not with amino acids

AIMS

An intergenic locus on chromosome 1 (lead SNP rs10911021) was previously associated with coronary heart disease (CHD) in type 2 diabetes (T2D). Using data from the UCLEB consortium we investigated the relationship between rs10911021 and CHD in T2D, whether rs10911021 was associated with levels of amino acids involved in the γ-glutamyl cycle or any conventional risk factors (CRFs) for CHD in the T2D participants.

METHODS

Four UCLEB studies (n = 6531) had rs10911021 imputation, CHD in T2D, CRF and metabolomics data determined using a nuclear magnetic resonance based platform.

RESULTS

The expected direction of effect between rs10911021 and CHD in T2D was observed (1377 no CHD/160 CHD; minor allele OR 0.80, 95 % CI 0.60-1.06) although this was not statistically significant (p = 0.13). No association between rs10911021 and CHD was seen in non-T2D participants (11218 no CHD/1274 CHD; minor allele OR 1.00 95 % CIs 0.92-1.10). In T2D participants, while no associations were observed between rs10911021 and the nine amino acids measured, rs10911021 was associated with HDL-cholesterol (p = 0.0005) but the minor "protective" allele was associated with lower levels (-0.034 mmol/l per allele). Focusing more closely on the HDL-cholesterol subclasses measured, we observed that rs10911021 was associated with six large HDL particle measures in T2D (all p < 0.001). No significant associations were seen in non-T2D subjects.

CONCLUSIONS

Our findings are consistent with a true association between rs10911021 and CHD in T2D. The protective minor allele was associated with lower HDL-cholesterol and reductions in HDL particle traits. Our results indicate a complex relationship between rs10911021 and CHD in T2D.

Diabetes and Risk of Arterial Stiffness: A Mendelian Randomization Analysis

We aimed to explore the causal association between type 2 diabetes (T2D) and increased arterial stiffness. We performed a Mendelian randomization (MR) analysis in 11,385 participants from a well-defined community study in Shanghai during 2011-2013. We genotyped 34 T2D-associated common variants identified in East Asians and created a genetic risk score (GRS). We assessed arterial stiffness noninvasively with the measurement of brachial-ankle pulse wave velocity (baPWV). We used the instrumental variable (IV) estimator to qualify the causal relationship between T2D and increased arterial stiffness. We found each 1-SD increase in T2D_GRS was associated with 6% higher risk in increased arterial stiffness (95% CI 1.01, 1.12), after adjustment of other metabolic confounders. Using T2D_GRS as the IV, we demonstrated a causal relationship between T2D and arterial stiffening (odds ratio 1.24, 95% CI 1.06, 1.47; P = 0.008). When categorizing the genetic loci according to their effect on insulin secretion or resistance, we found genetically determined decrease in insulin secretion was associated with increase in baPWV (βIV = 122.3 cm/s, 95% CI 41.9, 204.6; P = 0.0005). In conclusion, our results provide evidence supporting a causal association between T2D and increased arterial stiffness in a Chinese population.

A Mendelian Randomization Study of Plasma Homocysteine and Multiple Myeloma

Observational studies have demonstrated an association between elevated homocysteine (Hcy) level and risk of multiple myeloma (MM). However, it remains unclear whether this relationship is causal. We conducted a Mendelian randomization (MR) study to evaluate whether genetically increased Hcy level influences the risk of MM. We used the methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism as an instrumental variable, which affects the plasma Hcy levels. Estimate of its effect on plasma Hcy level was based on a recent genome-wide meta-analysis of 44,147 individuals, while estimate of its effect on MM risk was obtained through meta-analysis of case-control studies with 2,092 cases and 4,954 controls. By combining these two estimates, we found that per one standard-deviation (SD) increase in natural log-transformed plasma Hcy levels conferred a 2.67-fold increase in risk for MM (95% confidence interval (CI): 1.12–6.38; P = 2.7 × 10⁻²). Our study suggests that elevated Hcy levels are causally associated with an increased risk of developing MM. Whether Hcy-lowering therapy can prevent MM merits further investigation in long-term randomized controlled trials (RCTs).

Type 2 Diabetes Genetic Predisposition, Obesity, and All-Cause Mortality Risk in the U.S.: A Multiethnic Analysis

OBJECTIVE

Type 2 diabetes (T2D) is associated with increased mortality in ethnically diverse populations, although the extent to which this association is genetically determined is unknown. We sought to determine whether T2D-related genetic variants predicted all-cause mortality, even after accounting for BMI, in the Third National Health and Nutrition Examination Survey.

RESEARCH DESIGN AND METHODS

We modeled mortality risk using a genetic risk score (GRS) from a weighted sum of risk alleles at 38 T2D-related single nucleotide polymorphisms. In age-, sex-, and BMI-adjusted logistic regression models, accounting for the complex survey design, we tested the association with mortality in 6,501 participants. We repeated the analysis within ethnicities (2,528 non-Hispanic white [NHW], 1,979 non-Hispanic black [NHB], and 1,994 Mexican American [MA]) and within BMI categories (<25, 25-30, and ≥30 kg/m(2)). Significance was set at P < 0.05.

RESULTS

Over 17 years, 1,556 participants died. GRS was associated with mortality risk (OR 1.04 [95% CI 1.00-1.07] per T2D-associated risk allele, P = 0.05). Within ethnicities, GRS was positively associated with mortality risk in NHW and NHB, but not in MA (0.95 [0.90-1.01], P = 0.07). The negative trend in MA was largely driven by those with BMI <25 kg/m(2) (0.91 [0.82-1.00]). In NHW, the positive association was strongest among those with BMI ≥30 kg/m(2) (1.07 [1.02-1.12]).

CONCLUSIONS

In the U.S., a higher T2D genetic risk was associated with increased mortality risk, especially among obese NHW. The underlying genetic basis for mortality likely involves complex interactions with factors related to ethnicity, T2D, and body weight.

Type 2 Diabetes, Diabetes Genetic Score and Risk of Decreased Renal Function and Albuminuria: A Mendelian Randomization Study

BACKGROUND

Type 2 diabetes (T2D) is a risk factor for dysregulation of glomerular filtration rate (GFR) and albuminuria. However, whether the association is causal remains unestablished.

RESEARCH DESIGN AND METHODS

We performed a Mendelian Randomization (MR) analysis in 11,502 participants aged 40 and above, from a well-defined community in Shanghai during 2011-2013, to explore the causal association between T2D and decreased estimated GFR (eGFR) and increased urinary albumin-to-creatinine ratio (uACR). We genotyped 34 established T2D common variants in East Asians, and created a T2D-genetic risk score (GRS). We defined decreased eGFR as eGFR<90ml/min/1.73m(2) and increased uACR as uACR≥30mg/g. We used the T2D_GRS as the instrumental variable (IV) to quantify the causal effect of T2D on decreased eGFR and increased uACR.

RESULTS

Each 1-standard deviation (SD, 3.90 points) increment in T2D_GRS was associated with decreased eGFR: odds ratio (OR)=1.18 (95% confidence interval [CI]: 1.01, 1.30). In the MR analysis, we demonstrated a causal relationship between genetically determined T2D and decreased eGFR (OR=1.47, 95% CI: 1.15, 1.88, P=0.0003). When grouping the genetic loci according to their relations with either insulin secretion (IS) or insulin resistance (IR), we found both IS_GRS and IR_GRS were significantly related to decreased eGFR (both P<0.02). In addition, T2D_GRS and IS_GRS were significantly associated with Log-uACR (both P=0.04).

CONCLUSION

Our results provide novel evidence for a causal association between T2D and decreased eGFR by using MR approach in a Chinese population.