Fasting glucose and insulin are intermediate traits for type 2 diabetes. Here we explore the role of coding variation on these traits by analysis of variants on the HumanExome BeadChip in 60,564 non-diabetic individuals and in 16,491 T2D cases and 81,877 controls. We identify a novel association of a low-frequency nonsynonymous SNV in GLP1R (A316T; rs10305492; MAF=1.4%) with lower FG (β=−0.09±0.01 mmol l⁻¹, P=3.4 × 10⁻¹²), T2D risk (OR[95%CI]=0.86[0.76–0.96], P=0.010), early insulin secretion (β=−0.07±0.035 pmol_insulin mmol_glucose⁻¹, P=0.048), but higher 2-h glucose (β=0.16±0.05 mmol l⁻¹, P=4.3 × 10⁻⁴). We identify a gene-based association with FG at G6PC2 (p_SKAT=6.8 × 10⁻⁶) driven by four rare protein-coding SNVs (H177Y, Y207S, R283X and S324P). We identify rs651007 (MAF=20%) in the first intron of ABO at the putative promoter of an antisense lncRNA, associating with higher FG (β=0.02±0.004 mmol l⁻¹, P=1.3 × 10⁻⁸). Our approach identifies novel coding variant associations and extends the allelic spectrum of variation underlying diabetes-related quantitative traits and T2D susceptibility.

Aims 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). Methods and results We studied a multinational cohort of 6926 hospitalized patients with acute HF enrolled in the European Society of Cardiology (ESC) and Heart Failure Association (HFA) Long‐Term Registry, of whom 49.4% (n = 3422) had known or previously undiagnosed diabetes (defined as self‐reported history, or medication use, or fasting glucose levels ≥7.0 mmol/L or haemoglobin A_1c ≥6.5%). Compared with those without diabetes, patients with known or previously undiagnosed diabetes had higher cumulative rates of in‐hospital mortality, 1‐year mortality, and 1‐year HF re‐hospitalization that occurred independently of multiple clinical risk factors: in‐hospital mortality [6.8 vs. 4.4%; adjusted hazard ratio (HR) 1.774; 95% confidence interval (CI) 1.282–2.456, P < 0.001], 1‐year all‐cause mortality (27.5 vs. 24%; adjusted HR 1.162; 95% CI 1.020–1.325, P = 0.024), and 1‐year hospital re‐admissions for HF (23.2 vs. 18.5%; adjusted HR 1.320; 95% CI 1.139–1.530, P < 0.001). Moreover, elevated admission blood glucose concentrations were powerfully prognostic for in‐hospital mortality, but not for 1‐year mortality or re‐hospitalizations, in both patients with and without diabetes. Conclusions Among patients hospitalized for acute HF, the presence of diabetes is independently associated with an increased risk of in‐hospital mortality, 1‐year all‐cause mortality, and 1‐year re‐hospitalizations for HF, underscoring the need for more effective and personalized treatments of diabetes in this particularly high‐risk patient population.

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 (GRS_t) improves T2D prediction compared with previous less inclusive GRS_t; 2) separate GRS for β-cell (GRS_β) and insulin resistance (GRS_IR) independently predict T2D; and 3) the relationships between T2D and GRS_t, GRS_β, or GRS_IR 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 GRS_t was significantly associated with incident T2D in all three groups. In FOS but not CARDIA, the 62-locus GRS_t improved the model C statistic (0.698 and 0.726 for models without and with GRS_t, respectively; P < 0.001) but did not materially improve risk reclassification in either study. Results were similar among blacks compared with whites. The GRS_β but not GRS_IR 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.

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.