Heart failure is a leading cause of cardiovascular morbidity and mortality. However, the contribution of common genetic variation to heart failure risk has not been fully elucidated, particularly in comparison to other common cardiometabolic traits. We report a multi-ancestry genome-wide association study meta-analysis of all-cause heart failure including up to 115,150 cases and 1,550,331 controls of diverse genetic ancestry, identifying 47 risk loci. We also perform multivariate genome-wide association studies that integrate heart failure with related cardiac magnetic resonance imaging endophenotypes, identifying 61 risk loci. Gene-prioritization analyses including colocalization and transcriptome-wide association studies identify known and previously unreported candidate cardiomyopathy genes and cellular processes, which we validate in gene-expression profiling of failing and healthy human hearts. Colocalization, gene expression profiling, and Mendelian randomization provide convergent evidence for the roles of BCKDHA and circulating branch-chain amino acids in heart failure and cardiac structure. Finally, proteome-wide Mendelian randomization identifies 9 circulating proteins associated with heart failure or quantitative imaging traits. These analyses highlight similarities and differences among heart failure and associated cardiovascular imaging endophenotypes, implicate common genetic variation in the pathogenesis of heart failure, and identify circulating proteins that may represent cardiomyopathy treatment targets.

Pharmacologic clinical trials for heart failure with preserved ejection fraction have been largely unsuccessful as compared to those for heart failure with reduced ejection fraction. Whether differences in the genetic underpinnings of these major heart failure subtypes may provide insights into the disparate outcomes of clinical trials remains unknown. We utilize a large, uniformly phenotyped, single cohort of heart failure sub-classified into heart failure with reduced and with preserved ejection fractions based on current clinical definitions, to conduct detailed genetic analyses of the two heart failure sub-types. We find different genetic architectures and distinct genetic association profiles between heart failure with reduced and with preserved ejection fraction suggesting differences in underlying pathobiology. The modest genetic discovery for heart failure with preserved ejection fraction (one locus) compared to heart failure with reduced ejection fraction (13 loci) despite comparable sample sizes indicates that clinically defined heart failure with preserved ejection fraction likely represents the amalgamation of several, distinct pathobiological entities. Development of consensus sub-phenotyping of heart failure with preserved ejection fraction is paramount to better dissect the underlying genetic signals and contributors to this highly prevalent condition.

We conduct a large-scale meta-analysis of heart failure genome-wide association studies (GWAS) consisting of over 90,000 heart failure cases and more than 1 million control individuals of European ancestry to uncover novel genetic determinants for heart failure. Using the GWAS results and blood protein quantitative loci, we perform Mendelian randomization and colocalization analyses on human proteins to provide putative causal evidence for the role of druggable proteins in the genesis of heart failure. We identify 39 genome-wide significant heart failure risk variants, of which 18 are previously unreported. Using a combination of Mendelian randomization proteomics and genetic cis-only colocalization analyses, we identify 10 additional putatively causal genes for heart failure. Findings from GWAS and Mendelian randomization-proteomics identify seven (CAMK2D, PRKD1, PRKD3, MAPK3, TNFSF12, APOC3 and NAE1) proteins as potential targets for interventions to be used in primary prevention of heart failure.

Background: Sepsis is one of the leading causes of hospital mortality, and diabetes is a risk factor for the development of infections. Although strong evidence has shown an association between metformin and reduced risk of infections, the risk of developing infections with newer classes of oral anti-diabetic drugs (OADs) has been less certain. Our study aims to examine the association between outpatient OAD use and hospital admissions for infections. Methods: The study cohort included 1.39 million adults with diabetes utilizing the Veterans Health Affairs Corporate Data Warehouse. Multivariate logistic regression was used to estimate the effect of each drug class on hospital admission for infection while adjusting for covariates. Results: After adjusting for covariates, those who took metformin during the study period had 3.3% lower odds of hospital admission for infection compared to those who were never on metformin (OR 0.97, 95% CI 0.95-0.98). OADs that were associated with a statistically significant increased odds of being admitted included meglitinides (OR 1.22, 95% CI 1.07-1.38), SGLT2 inhibitors (OR 1.16, 95% CI 1.08-1.24), alpha-glucosidase inhibitors (OR 1.09, 95% CI 1.04-1.15), and DPP4 inhibitors (OR 1.04, 95% CI 1.01-1.06). Conclusions: Metformin was associated with lower odds of hospital admission for infection while meglitinides, SGLT2 inhibitors, alpha-glucosidase inhibitors, and DPP4 inhibitors were associated with higher odds of admission for infection.

Aims: To assess the prevalence and clinical implications of “mismatches” between HbA1c and glucose levels in the United States across the life course. Methods: Participants ages 12–79 years from U.S. National Health and Nutrition Examination Survey (NHANES) 2005–2016 without known diagnosis of diabetes and who had a 75 g oral glucose tolerance test were included. Previously undiagnosed diabetes (DM), prediabetes, and normal glucose metabolism (NGM) were defined using American Diabetes Association cut-points. Mismatches were defined by the hemoglobin glycation index (HGI). Results: In 10,361 participants, 5% and 41% had diabetes and prediabetes, respectively, by fasting or 2-hour glucose criteria. By HbA1c criteria, the high HGI tertile consisted of mostly abnormal classification (3% DM, 52% prediabetes) and the low HGI tertile contained mostly normal classification (78% NGM). Across all ages, 15% (weighted: 30 million individuals) had clinically significant mismatches of HGI magnitude ≥+0.5% (i.e., high mismatch) or ≤−0.5% (low mismatch). Mismatch was most common in older adults and non-Hispanic Black participants. Conclusions: Mismatches of clinically significant magnitude could lead to HbA1c-related misdiagnosis or inappropriate management in up to 30 million Americans. Older adults, non-Hispanic Black individuals, and others with high mismatches may benefit from complementing HbA1c with additional diagnostic and management strategies.

Background: Supplemental melatonin may ameliorate metabolic syndrome (MetS) components, but data from placebo-controlled trials are lacking. Methods: We conducted a double-blind, placebo-controlled, crossover, Phase II randomized pilot clinical trial to estimate the effects of melatonin supplementation on MetS components and the overall prevalence of MetS. We randomized 39 subjects with MetS to receive 8.0 mg oral melatonin or matching placebo nightly for 10 weeks. After a 6-week washout, subjects received the other treatment for 10 more weeks. We measured waist circumference, triglycerides, HDL cholesterol, fasting glucose, and blood pressure (BP) in each subject at the beginning and end of both 10-week treatment periods. The primary outcome was the mean 10-week change in each MetS component, and a secondary outcome was the proportion of subjects free from MetS, after melatonin versus placebo. Results: The mean 10-week change for most MetS components favored melatonin over placebo (except fasting glucose): waist circumference -0.9 vs. +1.0 cm (p = 0.15); triglycerides -66.3 vs.-4.2 mg/dL (p = 0.17); HDL cholesterol -0.2 vs.-1.1 mg/dL (p = 0.59); fasting glucose +0.3 vs.-3.1 mg/dL (p = 0.29); systolic BP -2.7 vs. +4.7 mmHg (p = 0.013); and diastolic BP -1.1 vs. +1.1 mmHg (p = 0.24). Freedom from MetS tended to be more common following melatonin versus placebo treatment (after the first 10 weeks, 35.3% vs. 15.0%, p = 0.25; after the second 10 weeks, 45.0% vs. 23.5%, p = 0.30). Melatonin was well-Tolerated. Conclusions: Melatonin supplementation modestly improved most individual MetS components compared with placebo, and tended to increase the proportion of subjects free from MetS after treatment.

Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (nDM = 178,691, nnoDM = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM.

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Aims: To examine the association of HbA1c and glucose levels with incident diabetic retinopathy according to black African or white European ancestry. Methods: In this retrospective cohort study of 202 500 US Veterans with diabetes (2000–2014), measures included HbA1c, outpatient random serum/plasma glucose, and incident retinopathy [conversion from negative to ≥2 positive evaluations (ICD-9 codes), without a subsequent negative]. Results: At baseline, the study population had a mean age of 59.3 years, their mean BMI was 31.9 kg/m2, HbA1c level was 57 mmol/mol (7.4%) and glucose level was 8.8 mmol/l, and 77% were of white European ancestry (white individuals) and 21% of black African ancestry (black individuals). HbA1c was 0.3% higher in black vs white individuals (P < 0.001), adjusting for baseline age, sex, BMI, estimated glomerular filtration rate (eGFR), haemoglobin, and average systolic blood pressure and glucose. Over 11 years, incident retinopathy occurred in 9% of black and 7% of white individuals, but black individuals had higher HbA1c, glucose, and systolic blood pressure (all P < 0.001); adjusted for these factors, incident retinopathy was reduced in black vs white individuals (P < 0.001). The population incidence of retinopathy (7%) was associated with higher mean baseline HbA1c in individuals with black vs white ancestry [63 mmol/mol (7.9%) vs 58 mmol/mol (7.5%); P < 0.001)], but with similar baseline glucose levels (9.0 vs 9.0 mmol/l; P = 0.660, all adjusted for baseline age, sex and BMI). Conclusions: Since retinopathy occurs at higher HbA1c levels in black people for a given level of average plasma glucose, strategies may be needed to individualize the interpretation of HbA1c measurements.

OBJECTIVE Therapeutic inertia threatens the potential long-term benefits of achieving early glycemic control after type 2 diabetes diagnosis. We evaluated temporal trends in second-line diabetes medication initiation among individuals initially treated with metformin. RESEARCH DESIGN AND METHODS We included data from 199,042 adults with type 2 diabetes in the U.S. Department of Veterans Affairs health care system initially treated with metformin monotherapy from 2005 to 2013. We used multivariable Cox proportional haz-ards and linear regression to estimate associations of year of metformin mono-therapy initiation with time to second-line diabetes treatment over 5 years of follow-up (primary outcome) and with hemoglobin A1c (HbA1c) at the time of sec-ond-line diabetes treatment initiation (secondary outcome). RESULTS The cumulative 5-year incidence of second-line medication initiation declined from 47% among metformin initiators in 2005 to 36% in 2013 counterparts (P < 0.0001) despite a gradual increase in mean HbA1c at the end of follow-up (from 6.94 ± 1.28% to 7.09 ± 1.42%, Ptrend < 0.0001). In comparisons with metformin monotherapy initiators in 2005, adjusted hazard ratios for 5-year initiation of sec-ond-line diabetes treatment ranged from 0.90 (95% CI 0.87, 0.92) for 2006 met-formin initiators to 0.68 (0.66, 0.70) for 2013 counterparts. Among those receiving second-line treatment within 5 years of metformin initiation, HbA1c at second-line medication initiation increased from 7.74 ± 1.66% in 2005 metformin initiators to 8.55 ± 1.92% in 2013 counterparts (Ptrend < 0.0001). CONCLUSIONS We observed progressive delays in diabetes treatment intensification consistent with therapeutic inertia. Process-of-care interventions early in the diabetes disease course may be needed to reverse adverse temporal trends in diabetes care.