Unraveling the relationships between alpha- and beta-adrenergic modulation and the risk of heart failure.

Background: The effects of α and ß adrenergic receptor modulation on the risk of developing heart failure (HF) remains uncertain due to a lack of randomized controlled trials. This study aimed to estimate the effects of α and ß adrenergic receptors modulation on the risk of HF and to provide proof of principle for genetic target validation studies in HF. Methods: Genetic variants within the cis regions encoding the adrenergic receptors α1A, α2B, ß1, and ß2 associated with blood pressure in a 757,601-participant genome-wide association study (GWAS) were selected as instruments to perform a drug target Mendelian randomization study. Effects of these variants on HF risk were derived from the HERMES GWAS (542,362 controls; 40,805 HF cases). Results: Lower α1A or ß1 activity was associated with reduced HF risk: odds ratio (OR) 0.83 (95% CI 0.74-0.93, P = 0.001) and 0.95 (95% CI 0.93-0.97, P = 8 × 10-6). Conversely, lower α2B activity was associated with increased HF risk: OR 1.09 (95% CI 1.05-1.12, P = 3 × 10-7). No evidence of an effect of lower ß2 activity on HF risk was found: OR 0.99 (95% CI 0.92-1.07, P = 0.95). Complementary analyses showed that these effects were consistent with those on left ventricular dimensions and acted independently of any potential effect on coronary artery disease. Conclusions: This study provides genetic evidence that α1A or ß1 receptor inhibition will likely decrease HF risk, while lower α2B activity may increase this risk. Genetic variant analysis can assist with drug development for HF prevention.

Transforming drug discovery with a high-throughput AI-powered platform: A 5-year experience with Patrimony.

High-throughput computational platforms are being established to accelerate drug discovery. Servier launched the Patrimony platform to harness computational sciences and artificial intelligence (AI) to integrate massive multimodal data from internal and external sources. Patrimony has enabled researchers to prioritize therapeutic targets based on a deep understanding of the pathophysiology of immuno-inflammatory diseases. Herein, we share our experience regarding main challenges and critical success factors faced when industrializing the platform and broadening its applications to neurological diseases. We emphasize the importance of integrating such platforms in an end-to-end drug discovery process and engaging human experts early on to ensure a transforming impact.

Sex differences in the generalizability of randomized clinical trials in heart failure with reduced ejection fraction.

AIMS: In order to understand how sex differences impact the generalizability of randomized clinical trials (RCTs) in patients with heart failure (HF) and reduced ejection fraction (HFrEF), we sought to compare clinical characteristics and clinical outcomes between RCTs and HF observational registries stratified by sex. METHODS AND RESULTS: Data from two HF registries and five HFrEF RCTs were used to create three subpopulations: one RCT population (n = 16 917; 21.7% females), registry patients eligible for RCT inclusion (n = 26 104; 31.8% females), and registry patients ineligible for RCT inclusion (n = 20 810; 30.2% females). Clinical endpoints included all-cause mortality, cardiovascular mortality, and first HF hospitalization at 1 year. Males and females were equally eligible for trial enrolment (56.9% of females and 55.1% of males in the registries). One-year mortality rates were 5.6%, 14.0%, and 28.6% for females and 6.9%, 10.7%, and 24.6% for males in the RCT, RCT-eligible, and RCT-ineligible groups, respectively. After adjusting for 11 HF prognostic variables, RCT females showed higher survival compared to RCT-eligible females (standardized mortality ratio [SMR] 0.72; 95% confidence interval [CI] 0.62-0.83), while RCT males showed higher adjusted mortality rates compared to RCT-eligible males (SMR 1.16; 95% CI 1.09-1.24). Similar results were also found for cardiovascular mortality (SMR 0.89; 95% CI 0.76-1.03 for females, SMR 1.43; 95% CI 1.33-1.53 for males). CONCLUSION: Generalizability of HFrEF RCTs differed substantially between the sexes, with females having lower trial participation and female trial participants having lower mortality rates compared to similar females in the registries, while males had higher than expected cardiovascular mortality rates in RCTs compared to similar males in registries.

Generalizability of randomized controlled trials in heart failure with reduced ejection fraction.

BACKGROUND: Heart failure (HF) trials have stringent inclusion and exclusion criteria, but limited data exist regarding generalizability of trials. We compared patient characteristics and outcomes between patients with HF and reduced ejection fraction (HFrEF) in trials and observational registries. METHODS AND RESULTS: Individual patient data for 16 922 patients from five randomized clinical trials and 46 914 patients from two HF registries were included. The registry patients were categorized into trial-eligible and non-eligible groups using the most commonly used inclusion and exclusion criteria. A total of 26 104 (56%) registry patients fulfilled the eligibility criteria. Unadjusted all-cause mortality rates at 1 year were lowest in the trial population (7%), followed by trial-eligible patients (12%) and trial-non-eligible registry patients (26%). After adjustment for age and sex, all-cause mortality rates were similar between trial participants and trial-eligible registry patients [standardized mortality ratio (SMR) 0.97; 95% confidence interval (CI) 0.92-1.03] but cardiovascular mortality was higher in trial participants (SMR 1.19; 1.12-1.27). After full case-mix adjustment, the SMR for cardiovascular mortality remained higher in the trials at 1.28 (1.20-1.37) compared to RCT-eligible registry patients. CONCLUSION: In contemporary HF registries, over half of HFrEF patients would have been eligible for trial enrolment. Crude clinical event rates were lower in the trials, but, after adjustment for case-mix, trial participants had similar rates of survival as registries. Despite this, they had about 30% higher cardiovascular mortality rates. Age and sex were the main drivers of differences in clinical outcomes between HF trials and observational HF registries.

Retropath: automated pipeline for embedded metabolic circuits.

Metabolic circuits are a promising alternative to other conventional genetic circuits as modular parts implementing functionalities required for synthetic biology applications. To date, metabolic design has been mainly focused on production circuits. Emergent applications such as smart therapeutics, however, require circuits that enable sensing and regulation. Here, we present RetroPath, an automated pipeline for embedded metabolic circuits that explores the circuit design space from a given set of specifications and selects the best circuits to implement based on desired constraints. Synthetic biology circuits embedded in a chassis organism that are capable of controlling the production, processing, sensing, and the release of specific molecules were enumerated in the metabolic space through a standard procedure. In that way, design and implementation of applications such as therapeutic circuits that autonomously diagnose and treat disease, are enabled, and their optimization is streamlined.