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Metabolic syndrome, today affecting more than 20% of the US population, is a group of 5 conditions that often coexist and that strongly predispose to cardiovascular disease. How these conditions are linked mechanistically remains unclear, especially two of these: obesity and elevated blood pressure. Here, we show that high fat consumption in mice leads to the accumulation of lipid droplets in endothelial cells throughout the organism and that lipid droplet accumulation in endothelium suppresses endothelial nitric oxide synthase (eNOS), reduces NO production, elevates blood pressure, and accelerates atherosclerosis. Mechanistically, the accumulation of lipid droplets destabilizes eNOS mRNA and activates an endothelial inflammatory signaling cascade that suppresses eNOS and NO production. Pharmacological prevention of lipid droplet formation reverses the suppression of NO production in cell culture and in vivo and blunts blood pressure elevation in response to a high-fat diet. These results highlight lipid droplets as a critical and unappreciated component of endothelial cell biology, explain how lipids increase blood pressure acutely, and provide a mechanistic account for the epidemiological link between obesity and elevated blood pressure., Introduction Numerous epidemiological studies demonstrate a strong connection between obesity and elevated blood pressure (BP) (1). Lipid loading in humans by i.v. infusion of lipids or by oral fat intake [...]

An inducible gene expression program is a hallmark of the host inflammatory response. Recently, long intergenic non-coding RNAs (lincRNAs) have been shown to regulate the magnitude, duration, and resolution of these responses. Among these is lincRNA-Cox2, a dynamically regulated gene that broadly controls immune gene expression. To evaluate the in vivo functions of this lincRNA, we characterized multiple models of lincRNA-Cox2-deficient mice. LincRNA-Cox2-deficient macrophages and murine tissues had altered expression of inflammatory genes. Transcriptomic studies from various tissues revealed that deletion of the lincRNA-Cox2 locus also strongly impaired the basal and inducible expression of the neighboring gene prostaglandin-endoperoxide synthase (Ptgs2), encoding cyclooxygenase-2, a key enzyme in the prostaglandin biosynthesis pathway. By utilizing different genetic manipulations in vitro and in vivo, we found that lincRNA-Cox2 functions through an enhancer RNA mechanism to regulate Ptgs2. More importantly, lincRNA-Cox2 also functions in trans, independently of Ptgs2, to regulate critical innate immune genes in vivo.

Genome biology approaches have made enormous contributions to our understanding of biological rhythms, particularly in identifying outputs of the clock, including RNAs, proteins, and metabolites, whose abundance oscillates throughout the day. These methods hold significant promise for future discovery, particularly when combined with computational modeling. However, genome-scale experiments are costly and laborious, yielding "big data" that are conceptually and statistically difficult to analyze. There is no obvious consensus regarding design or analysis. Here we discuss the relevant technical considerations to generate reproducible, statistically sound, and broadly useful genome-scale data. Rather than suggest a set of rigid rules, we aim to codify principles by which investigators, reviewers, and readers of the primary literature can evaluate the suitability of different experimental designs for measuring different aspects of biological rhythms. We introduce CircaInSilico, a web-based application for generating synthetic genome biology data to benchmark statistical methods for studying biological rhythms. Finally, we discuss several unmet analytical needs, including applications to clinical medicine, and suggest productive avenues to address them.

The COVID-19 pandemic caused by the SARS-CoV-2 virus has swept the globe with devastating societal consequences and has placed tremendous stress on health care systems. Although severe respiratory disease is [...]

Technological advances in rapid data acquisition have transformed medical biology into a data mining field, where new data sets are routinely dissected and analyzed by statistical models of ever- increasing complexity. Many hypotheses can be generated and tested within a single large data set, and even small effects can be statistically discriminated from a sea of noise. On the other hand, the development of therapeutic interventions moves at a much slower pace. They are determined from carefully randomized and well-controlled experiments with explicitly stated outcomes as the principal mechanism by which a single hypothesis is tested. In this paradigm, only a small fraction of interventions can be tested, and an even smaller fraction are ultimately deemed therapeutically successful. In this Review, we propose strategies to leverage large- cohort data to inform the selection of targets and the design of randomized trials of novel therapeutics. Ultimately, the incorporation of big data and experimental medicine approaches should aim to reduce the failure rate of clinical trials as well as expedite and lower the cost of drug development., Introduction We are experiencing unprecedented growth in the amount of biological and medical information collected from human populations. Large prospective cohorts, such as the UK Biobank (1), the All of [...]

Resistance to immunotherapy is one of the biggest problems of current oncotherapeutics. While T cell abundance is essential for tumor responsiveness to immunotherapy, factors that define the T cell-inflamed tumor microenvironment are not fully understood. We used an unbiased approach to identify tumor-intrinsic mechanisms shaping the immune tumor microenvironment (TME), focusing on pancreatic adenocarcinoma because it is refractory to immunotherapy and excludes T cells from the TME. From human tumors, we identified ephrin-A receptor 2 (EPHA2) as a candidate tumor-intrinsic driver of immunosuppression. Epha2 deletion reversed T cell exclusion and sensitized tumors to immunotherapy. We found that prostaglandin endoperoxide synthase 2 (PTGS2), the gene encoding cyclooxygenase- 2, lies downstream of EPHA2 signaling through TGF-[beta] and is associated with poor patient survival. Ptgs2 deletion reversed T cell exclusion and sensitized tumors to immunotherapy; pharmacological inhibition of PTGS2 was similarly effective. Thus, EPHA2/PTGS2 signaling in tumor cells regulates tumor immune phenotypes; blockade may represent a therapeutic avenue for immunotherapy-refractory cancers. Our findings warrant clinical trials testing the effectiveness of therapies combining EPHA2/TGF-[beta]/PTGS2 pathway inhibitors with antitumor immunotherapy and may change the treatment of notoriously therapy-resistant pancreatic adenocarcinoma., Introduction Immunotherapies, including immune checkpoint blockade (ICB), have led to significant improvement of clinical care for cancer patients (1-4). Patients with melanoma, lung adenocarcinoma, or kidney cancer have a 20%-40% [...]

Inhibitors of microsomal prostaglandin E synthase 1 (mPGES-1) are in the early phase of clinical development. Deletion of mPges-1 in mice confers analgesia, restrains atherogenesis, and fails to accelerate thrombogenesis, while suppressing prostaglandin [E.sub.2] ([PGE.sub.2]), but increasing the biosynthesis of prostacyclin ([PGI.sub.2]). In low-density lipoprotein receptor-deficient ([Ldlr.sup.-/-]) mice, this last effect represents the dominant mechanism by which mPges-1 deletion restrains thrombogenesis, while suppression of [PGE.sub.2] accounts for its antiatherogenic effect. However, the effect of mPges-1 depletion on blood pressure (BP) in this setting remains unknown. Here, we show that mPges-1 depletion significantly increased the BP response to salt loading in male [Ldlr.sup.-/-] mice, whereas, despite the direct vasodilator properties of [PGI.sub.2], deletion of the I prostanoid receptor (Ipr) suppressed this response. Furthermore, combined deletion of the Ipr abrogated the exaggerated BP response in male [mPges-1.sup.-/-] mice. Interestingly, these unexpected BP phenotypes were not observed in female mice fed a high-salt diet (HSD). This is attributable to the protective effect of estrogen in [Ldlr.sup.-/-] mice and in [Ipr.sup.-/-][Ldlr.sup.-/- ] mice. Thus, estrogen compensates for a deficiency in [PGI.sub.2] to maintain BP homeostasis in response to high salt in hyperlipidemic female mice. In male mice, by contrast, the augmented formation of atrial natriuretic peptide (ANP) plays a similar compensatory role, restraining hypertension and oxidant stress in the setting of Ipr depletion. Hence, men with hyperlipidemia on a HSD might be at risk of a hypertensive response to mPGES-1 inhibitors., Introduction Both the adverse cardiovascular events associated with nonsteroidal antiinflammatory drugs (NSAIDs) and the opioid crisis have prompted interest in developing new analgesics (1-4). Several clinical trials have shown that [...]

Lipid peroxidation plays an important role in atherogenesis. Previous studies suggested that autoantibodies against epitopes of oxidized low-density lipoprotein may indicate the extent or rate of progression of atherosclerosis. The aim of this study was to investigate whether autoantibodies to oxidized phospholipids, such as oxidized cardiolipin (OxCL), correlate with levels of isoprostane F(2alpha)-VI, a sensitive marker of in vivo lipid peroxidation, as well as with the extent of atherosclerosis. Two groups of apolipoprotein E-deficient mice were fed chow with or without vitamin E (2000 IU/kg diet) for 16 weeks. In untreated animals, autoantibodies against OxCL and urinary, plasma, and aortic isoprostane F(2alpha)-VI levels increased significantly. Vitamin E treatment significantly reduced antibody titers, isoprostane levels, and atherosclerosis at the end of the study, compared with untreated mice. Autoantibodies to OxCL correlated with aortic isoprostane F(2alpha)-VI levels (r(2) = 0.42, P =.001 for IgG and r(2) = 0.63, P

Since the COVID-19 pandemic swept across the globe, researchers have been trying to understand its origin, life cycle, and pathogenesis. There is a striking variability in the phenotypic response to infection with SARS-CoV-2 that may reflect differences in host genetics and/or immune response. It is known that the human epigenome is influenced by ethnicity, age, lifestyle, and environmental factors, including previous viral infections. This Review examines the influence of viruses on the host epigenome. We describe general lessons and methodologies that can be used to understand how the virus evades the host immune response. We consider how variation in the epigenome may contribute to heterogeneity in the response to SARS-CoV-2 and may identify a precision medicine approach to treatment., Introduction There are millions of nucleotide interactions within a cell, and their alteration by single-nucleotide polymorphisms (SNPs) can result in changes to pathways implicated in disease, such as the response [...]