Marco Dauriz

Polygenic type 2 diabetes prediction at the limit of common variant detection.

Genome-wide association studies (GWAS) may have reached their limit of detecting common type 2 diabetes (T2D)–associated genetic variation. We evaluated the performance of current polygenic T2D prediction. Using data from the Framingham Offspring (FOS) and the Coronary Artery Risk Development in Young Adults (CARDIA) studies, we tested three hypotheses: 1) a 62-locus genotype risk score (GRSt) improves T2D prediction compared with previous less inclusive GRSt; 2) separate GRS for β-cell (GRSβ) and insulin resistance (GRSIR) independently predict T2D; and 3) the relationships between T2D and GRSt, GRSβ, or GRSIR do not differ between blacks and whites. Among 1,650 young white adults in CARDIA, 820 young black adults in CARDIA, and 3,471 white middle-aged adults in FOS, cumulative T2D incidence was 5.9%, 14.4%, and 12.9%, respectively, over 25 years. The 62-locus GRSt was significantly associated with incident T2D in all three groups. In FOS but not CARDIA, the 62-locus GRSt improved the model C statistic (0.698 and 0.726 for models without and with GRSt, respectively; P < 0.001) but did not materially improve risk reclassification in either study. Results were similar among blacks compared with whites. The GRSβ but not GRSIR predicted incident T2D among FOS and CARDIA whites. At the end of the era of common variant discovery for T2D, polygenic scores can predict T2D in whites and blacks but do not outperform clinical models. Further optimization of polygenic prediction may require novel analytic methods, including less common as well as functional variants.

Metabolite Traits and Genetic Risk Provide Complementary Information for the Prediction of Future Type 2 Diabetes

OBJECTIVE A genetic risk score (GRS) comprised of single nucleotide polymorphisms (SNPs) and metabolite biomarkers have each been shown, separately, to predict incident type 2 diabetes. We tested whether genetic and metabolite markers provide complementary information for type 2 diabetes prediction and, together, improve the accuracy of prediction models containing clinical traits. RESEARCH DESIGN AND METHODS Diabetes risk was modeled with a 62-SNP GRS, nine metabolites, and clinical traits. We fit age- and sex-adjusted logistic regression models to test the association of these sources of information, separately and jointly, with incident type 2 diabetes among 1,622 initially nondiabetic participants from the Framingham Offspring Study. The predictive capacity of each model was assessed by area under the curve (AUC). RESULTS Two hundred and six new diabetes cases were observed during 13.5 years of follow-up. The AUC was greater for the model containing the GRS and metabolite measurements together versus GRS or metabolites alone (0.820 vs. 0.641, P < 0.0001, or 0.820 vs. 0.803, P = 0.01, respectively). Odds ratios for association of GRS or metabolites with type 2 diabetes were not attenuated in the combined model. The AUC was greater for the model containing the GRS, metabolites, and clinical traits versus clinical traits only (0.880 vs. 0.856, P = 0.002). CONCLUSIONS Metabolite and genetic traits provide complementary information to each other for the prediction of future type 2 diabetes. These novel markers of diabetes risk modestly improve the predictive accuracy of incident type 2 diabetes based only on traditional clinical risk factors.

Non-alcoholic fatty liver disease is associated with an increased prevalence of atrial fibrillation in hospitalized patients with Type 2 diabetes

NAFLD (non-alcoholic fatty liver disease) and AF (atrial fibrillation) are two pathological conditions that are highly prevalent in developed countries and share multiple risk factors. The relationship between NAFLD and AF in Type 2 diabetes is currently unknown. We studied a hospital-based sample of 702 patients with Type 2 diabetes discharged from our Division of Endocrinology during 2007-2011. The diagnosis of AF was confirmed in affected participants on the basis of ECGs and medical history by experienced cardiologists. NAFLD was defined by ultrasonographic detection of hepatic steatosis in the absence of other liver diseases. Of the 702 hospitalized patients included in the study, 514 (73.2%) of them had NAFLD and 85 (12.1%) had persistent or permanent AF. NAFLD was associated with an increased risk of prevalent AF {OR (odds ratio), 3.04 [95% CI (confidence interval), 1.54-6.02]; P<0.001}. Adjustments for age, sex, systolic BP (blood pressure), HbA1c, (glycated haemoglobin), estimated GFR (glomerular filtration rate), total cholesterol, electrocardiographic LVH (left ventricular hypertrophy), COPD (chronic obstructive pulmonary disease), and prior history of HF (heart failure), VHD (valvular heart disease) or hyperthyroidism did not attenuate the association between NAFLD and AF [adjusted OR, 5.88 (95% CI, 2.72-12.7); P<0.001]. In conclusion, our results show that ultrasound-diagnosed NAFLD is strongly associated with an increased prevalence of persistent or permanent AF in patients with Type 2 diabetes, independently of several clinical risk factors for AF. The potential impact of NAFLD on AF deserves particular attention, especially with respect to the implications for screening and surveillance strategies in the growing number of patients with NAFLD.

In-hospital and 1-year mortality associated with diabetes in patients with acute heart failure: results from the ESC-HFA Heart Failure Long-Term Registry

The aim of this study was to evaluate the in‐hospital and 1‐year prognostic impact of diabetes and elevated blood glucose levels at hospital admission in patients with acute heart failure (HF).

Heart valve calcification in patients with type 2 diabetes and nonalcoholic fatty liver disease

PURPOSE Aortic valve sclerosis (AVS) and mitral annulus calcification (MAC) are two powerful predictors of adverse cardiovascular outcomes in patients with type 2 diabetes, but the etiology of valvular calcification is uncertain. Nonalcoholic fatty liver disease (NAFLD) is an emerging cardiovascular risk factor and is very common in type 2 diabetes, but whether NAFLD is associated with valvular calcification in this group of patients is presently unknown. METHODS We undertook a cross-sectional study of 247 consecutive type 2 diabetic outpatients with no previous history of heart failure, valvular heart diseases (aortic stenosis, mitral stenosis, moderate or severe aortic and mitral regurgitation) or hepatic diseases. Presence of MAC and AVS was detected by echocardiography. NAFLD was diagnosed by ultrasonography. RESULTS Overall, 139 (56.3%) patients had no heart valve calcification (HVC-0), 65 (26.3%) patients had one valve affected (HVC-1) and 43 (17.4%) patients had both valves affected (HVC-2). 175 (70.8%) patients had NAFLD and the prevalence of this disease markedly increased in patients with HVC-2 compared with either HVC-1 or HVC-0 (86.1% vs. 83.1% vs. 60.4%, respectively; p < 0.001). NAFLD was significantly associated with AVS and/or MAC (unadjusted-odds ratio 3.51, 95% CI 1.89-6.51, p < 0.001). Adjustments for age, sex, waist circumference, smoking, blood pressure, hemoglobin A1c, LDL-cholesterol, kidney function parameters, medication use and echocardiographic variables did not appreciably weaken this association (adjusted-odds ratio 2.70, 95% CI 1.23-7.38, p < 0.01). CONCLUSIONS Our results show that NAFLD is an independent predictor of cardiac calcification in both the aortic and mitral valves in patients with type 2 diabetes.

Prognostic impact of in-hospital hyperglycemia in hospitalized patients with acute heart failure: Results of the IN-HF (Italian Network on Heart Failure) Outcome registry.

OBJECTIVES Although diabetes mellitus is frequently associated with heart failure (HF), the association between elevated admission glucose levels and adverse outcomes has not been well established in hospitalized patients with acute HF. METHODS We prospectively evaluated in-hospital mortality, post-discharge 1-year mortality and 1-year re-hospitalization rates in the Italian Network on Heart Failure (IN-HF) Outcome registry cohort of 1776 patients hospitalized with acute HF and stratified by their admission glucose levels (i.e., known diabetes, newly diagnosed hyperglycemia, no diabetes). RESULTS Compared with those without diabetes (n = 586), patients with either known diabetes (n = 749) (unadjusted-odds ratio [OR] 1.64, 95%CI 0.99–2.70) or newly diagnosed hyperglycemia (n = 441) (unadjusted-OR 2.34, 95%CI 1.39–3.94) had higher in-hospital mortality, but comparable post-discharge 1-year mortality rates. After adjustment for age, sex, systolic blood pressure, estimated glomerular filtration rate, left ventricular ejection fraction, HF etiology and HF worsening/de novo presentation, the results remained unchanged in patients with known diabetes (adjusted-OR 1.86, 95%CI 1.01–3.42), while achieved borderline significance in those with newly diagnosed hyperglycemia (adjusted-OR 1.81, 95%CI 0.95–3.45). One-year re-hospitalization rates were lower in patients with newly diagnosed hyperglycemia (adjusted-hazard ratio 0.74, 95%CI 0.56–0.96) than in other groups. CONCLUSIONS Elevated admission blood glucose levels are associated with poorer in-hospital survival outcomes in patients with acute HF, especially in those with previously known diabetes. This finding further highlights the importance of tight glycemic control during hospital stay and address the need of dedicated intervention studies to identify customized clinical protocols to improve in-hospital survival of these high-risk patients.

Current Insights into the Joint Genetic Basis of Type 2 Diabetes and Coronary Heart Disease

The large-scale genome-wide association studies conducted so far identified numerous allelic variants associated with type 2 diabetes (T2D), coronary heart disease (CHD) and related cardiometabolic traits. Many T2D- and some CHD-risk loci are also linked with metabolic traits that are hallmarks of insulin resistance (lipid profile, abdominal adiposity). Chromosome 9p21.3 and 2q36.3 are the most consistently replicated loci appearing to share genetic risk for both T2D and CHD. Although many glucose- or insulin-related trait variants are also linked with T2D risk, none of them is associated with CHD. Hence, while T2D and CHD are strongly clinically linked together, further ongoing analyses are needed to clarify the existence of a shared underlying genetic signature of these complex traits. The present review summarizes an updated picture of T2D-CHD genetics as of 2013, aiming to provide a platform for targeted studies dissecting the contribution of genetics to the phenotypic heterogeneity of T2D and CHD.

Association Between Diabetes and 1-Year Adverse Clinical Outcomes in a Multinational Cohort of Ambulatory Patients With Chronic Heart Failure: Results From the ESC-HFA Heart Failure Long-Term Registry

OBJECTIVE Diabetes mellitus is associated with an increased risk of cardiovascular disease (CVD) and death. Because the prevalence of diabetes is rising worldwide and chronic heart failure (CHF) is becoming increasingly common with the aging population, it is timely to examine the impact of diabetes per se on 1-year adverse outcomes in patients with CHF. RESEARCH DESIGN AND METHODS We prospectively assessed whether diabetes status independently affected the 1-year risk of all-cause and CVD mortality and first hospitalization for worsening heart failure (HF) in a multinational cohort of 9,428 outpatients with CHF enrolled in the European Society of Cardiology and Heart Failure Association Long-Term Registry. RESULTS Compared with those patients without diabetes, patients with diabetes (n = 3,440, 36.5%) had higher cumulative rates of 1-year all-cause death (9.4% vs. 7.2%; adjusted hazard ratio [HR] 1.28; 95% CI 1.07–1.54), CVD death (4.8% vs. 3.8%; adjusted HR 1.28; 95% CI 0.99–1.66), and HF hospitalization (13.8% vs. 9.3%; adjusted HR 1.37; 95% CI 1.17–1.60), all independent of age, sex, BMI, smoking, systolic blood pressure, estimated glomerular filtration rate, hemoglobin, HF etiology, left ventricular ejection fraction, hypertension, statin use, and prior stroke or chronic obstructive pulmonary disease. Among CHF patients with HbA1c measurements available at baseline (n = 2,567), there was a significant and independent association between increasing HbA1c levels and the risk of 1-year survival outcomes. CONCLUSIONS The presence of diabetes markedly increases the risk of 1-year adverse clinical outcomes in outpatients with CHF independent of multiple common risk factors. More effective and personalized treatment for diabetes should be considered in this particularly high-risk patient population.

Prevalence of Cardiovascular Autonomic Neuropathy in a Cohort of Patients With Newly Diagnosed Type 2 Diabetes: The Verona Newly Diagnosed Type 2 Diabetes Study (VNDS).

OBJECTIVE Cardiovascular autonomic diabetic neuropathy (CAN) is a serious complication of diabetes. No reliable data on the prevalence of CAN among patients with newly diagnosed type 2 diabetes are available. Therefore, the aim of this study was to estimate the prevalence of CAN among patients with newly diagnosed type 2 diabetes. RESEARCH DESIGN AND METHODS A cohort of 557 patients with newly diagnosed type 2 diabetes with cardiovascular autonomic test results available was selected. Early and confirmed neuropathy were assessed using a standardized methodology and their prevalences determined. A multivariate logistic regression analysis was modeled to study the factors associated with CAN. RESULTS In the entire cohort, the prevalence of confirmed CAN was 1.8%, whereas that of early CAN was 15.3%. Prevalence did not differ between men and women. In the multivariate analyses BMI results were independently and significantly associated with CAN after adjusting for age, sex, hemoglobin A1c, pulse pressure, triglyceride-to-HDL cholesterol ratio, kidney function parameters, and antihypertensive treatment. CONCLUSIONS CAN could be detected very early in type 2 diabetes. This study may suggest the importance of performing standardized cardiovascular autonomic tests after diagnosis of type 2 diabetes.

Prognostic impact of diabetes and prediabetes on survival outcomes in patients with chronic heart failure: A post-hoc analysis of the GISSI-HF (Gruppo Italiano per lo Studio della Sopravvivenza nella Insufficienza Cardiaca-Heart Failure) trial

Background The independent prognostic impact of diabetes mellitus (DM) and prediabetes mellitus (pre‐DM) on survival outcomes in patients with chronic heart failure has been investigated in observational registries and randomized, clinical trials, but the results have been often inconclusive or conflicting. We examined the independent prognostic impact of DM and pre‐DM on survival outcomes in the GISSI‐HF (Gruppo Italiano per lo Studio della Sopravvivenza nella Insufficienza Cardiaca‐Heart Failure) trial. Methods and Results We assessed the risk of all‐cause death and the composite of all‐cause death or cardiovascular hospitalization over a median follow‐up period of 3.9 years among the 6935 chronic heart failure participants of the GISSI‐HF trial, who were stratified by presence of DM (n=2852), pre‐DM (n=2013), and non‐DM (n=2070) at baseline. Compared with non‐DM patients, those with DM had remarkably higher incidence rates of all‐cause death (34.5% versus 24.6%) and the composite end point (63.6% versus 54.7%). Conversely, both event rates were similar between non‐DM patients and those with pre‐DM. Cox regression analysis showed that DM, but not pre‐DM, was associated with an increased risk of all‐cause death (adjusted hazard ratio, 1.43; 95% CI, 1.28–1.60) and of the composite end point (adjusted hazard ratio, 1.23; 95% CI, 1.13–1.32), independently of established risk factors. In the DM subgroup, higher hemoglobin A1c was also independently associated with increased risk of both study outcomes (all‐cause death: adjusted hazard ratio, 1.21; 95% CI, 1.02–1.43; and composite end point: adjusted hazard ratio, 1.14; 95% CI, 1.01–1.29, respectively). Conclusions Presence of DM was independently associated with poor long‐term survival outcomes in patients with chronic heart failure. Clinical Trial Registration URL: http://www.clinicaltrials.gov. Unique identifier: NCT00336336.