Yu, Yue

Abstract Objectives Heart failure (HF) impacts millions of patients worldwide, yet the variability in treatment responses remains a major challenge for healthcare professionals. The current treatment strategies, largely derived from population based evidence, often fail to consider the unique characteristics of individual patients, resulting in suboptimal outcomes. This study aims to develop computational models that are patient-specific in predicting treatment outcomes, by utilizing a large Electronic Health Records (EHR) database. The goal is to improve drug response predictions by identifying specific HF patient subgroups that are likely to benefit from existing HF medications. Materials and Methods A novel, graph-based model capable of predicting treatment responses, combining Graph Neural Network and Transformer was developed. This method differs from conventional approaches by transforming a patient's EHR data into a graph structure. By defining patient subgroups based on this representation via K-Means Clustering, we were able to enhance the performance of drug response predictions. Results Leveraging EHR data from 11 627 Mayo Clinic HF patients, our model significantly outperformed traditional models in predicting drug response using NT-proBNP as a HF biomarker across five medication categories (best RMSE of 0.0043). Four distinct patient subgroups were identified with differential characteristics and outcomes, demonstrating superior predictive capabilities over existing HF subtypes (best mean RMSE of 0.0032). Discussion These results highlight the power of graph-based modeling of EHR in improving HF treatment strategies. The stratification of patients sheds light on particular patient segments that could benefit more significantly from tailored response predictions. Conclusions Longitudinal EHR data have the potential to enhance personalized prognostic predictions through the application of graph-based AI techniques.

The natriuretic peptide system (NPS) and renin-angiotensin-aldosterone system (RAAS) function oppositely at multiple levels. While it has long been suspected that angiotensin II (ANGII) may directly suppress NPS activity, no clear evidence to date supports this notion. This study was designed to systematically investigate ANGII–NPS interaction in humans, in vivo, and in vitro. Circulating atrial, b-type, and c-type natriuretic peptides (ANP, BNP, CNP), cyclic guanosine monophosphate (cGMP), and ANGII were simultaneously investigated in 128 human subjects. Prompted hypothesis was validated in vivo to determine the influence of ANGII on ANP actions. The underlying mechanisms were further explored via in vitro approaches. In humans, ANGII demonstrated an inverse relationship with ANP, BNP, and cGMP. In regression models predicting cGMP, adding ANGII levels and the interaction term between ANGII and natriuretic peptides increased the predictive accuracy of the base models constructed with either ANP or BNP, but not CNP. Importantly, stratified correlation analysis further revealed a positive association between cGMP and ANP or BNP only in subjects with low, but not high, ANGII levels. In rats, co-infusion of ANGII even at a physiological dose attenuated cGMP generation mediated by ANP infusion. In vitro, we found the suppressive effect of ANGII on ANP-stimulated cGMP requires the presence of ANGII type-1 (AT1) receptor and mechanistically involves protein kinase C (PKC), as this suppression can be substantially rescued by either valsartan (AT1 blocker) or Go6983 (PKC inhibitor). Using surface plasmon resonance (SPR), we showed ANGII has low binding affinity to the guanylyl cyclase A (GC-A) receptor compared to ANP or BNP. Our study reveals ANGII is a natural suppressor for the cGMP-generating action of GC-A via AT1/PKC dependent manner and highlights the importance of dual-targeting RAAS and NPS in maximizing beneficial properties of natriuretic peptides in cardiovascular protection.

Abstract Infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can result in a cytokine storm that is associated with poor outcomes in patients. The activation of a NOD-like receptor pyrin domain containing 3 (NLRP3) inflammasome following SARS-CoV-2 infection has been shown to play a major role in inflammatory immune responses. In this study, we show that open reading frame 8 (ORF8) protein is abundantly secreted as a glycoprotein in vitro. The glycosylated ORF8 stimulates human CD14+/CD16+ monocytes to cause upregulation of proinflammatory cytokine production and cell surface marker expression within 24 hours. The data suggests that stimulation of human monocytes by ORF8 is not receptor mediated. Rather, ORF8 is likely phagocytosed by human monocytes. ORF8 then stimulates the monocytes by independently binding to the NACHT and LRR domains of the NLRP3 protein. Pharmacologic inhibition of NLRP3 significantly diminished the production of pro-inflammatory cytokines from ORF8-stimulated human monocytes. Finally, this study shows that the ORF8 protein is also secreted in patients with newly diagnosed coronavirus disease 2019 (COVID-19). Levels of ORF8 in the blood of patients diagnosed with COVID-19 correlated with disease mortality and trajectory of disease. ORF8 stimulation of monocytes causes pro-inflammatory cytokine production that leads to the development of severe COVID-19.

Introduction: The atrial natriuretic peptide (ANP) regulates blood pressure (BP) and cardiorenal homeostasis via activation of guanylyl cyclase A (GC-A) receptor and second messenger cGMP. We recently demonstrated the safety, tolerability, and BP-lowering properties of MANP, an ANP analog and best-in-class GC-A activator, in subjects with essential hypertension (HTN). However, the effects of MANP on human metabolome during HTN remains undefined. Hypothesis: A single subcutaneous (SQ) administration of MANP can trigger metabolomic changes in humans. Methods: Twenty-two patients with HTN and metabolic syndrome (MetS) were randomized to receive placebo (N=5) or MANP (N=17, 2.5 μg/kg). Untargeted liquid chromatography mass spectrometry-based metabolomics and informatics were conducted on plasma of all subjects at baseline, 1 h post injection (hpi), and 6 hpi. Top circulating metabolites associated with MANP treatment were identified via a comparison of abundance between before and after MANP administration. Results: Compared to placebo, MANP resulted in the most prominent cGMP increase at 1 hpi and BP lowering effect at 6 hpi. With untargeted approach, we identified totally 1384 circulating metabolites. Principal component analysis supported distinct metabolic signatures at baseline, 1 hpi and 6 hpi in subjects receiving MANP. In MANP group, we found 31 metabolites at 1 hpi and 148 metabolites at 6 hpi showing significant change in abundance (adjusted P value < 0.05) compared to baseline. By contrast, <10 metabolites with difference in circulating abundance at either 1 hpi or 6 hpi compared to baseline were found in placebo group. Specifically, 8 annotated metabolites were identified with significant and progressive changes at both 1 and 6 hpi after treatment of MANP but not placebo, which included spisulosine, paecilaminol, quinine ethyl carbonate, thyrotropin releasing hormone, 3-epideoxycholic acid, hellicoside, pentanorvitamin D3, and tetracosanal. Conclusion: SQ administration of MANP triggers changes in a wide range of circulating metabolites beyond cGMP activation and BP reduction in humans. The biological outcome and clinical impact of these MANP-associated metabolites may help guide a precision medicine approach in HTN with MetS.

RXRA is an endothelial- and early stage–predominant therapeutic target for treating anthracycline-induced cardiotoxicity.