Chronic Alcohol Intake Compromises Lung Immunity by Altering Immunometabolism in Humans and Mouse Models.

Chronic alcohol consumption disrupts lung immunity and host defense mechanisms, rendering individuals with alcohol use disorder more susceptible to developing inflammatory lung conditions with poor prognoses. Here, we focused on investigating the molecular and cellular effects of alcohol ingestion on lung immunity in male and female subjects using population-based human lung transcriptomics analysis and an experimental mouse model of chronic alcohol drinking using the NIAAA alcohol feeding model. Flow cytometry and transcriptomics analyses in lungs revealed a sexually dimorphic effect of chronic alcohol drinking on lung immunity of both human and mouse. The male lungs were more sensitive to chronic alcohol drinking-induced dysregulation of lung immunity compared to the females. Furthermore, comparative transcriptomics analysis using lungs and liver samples from matched human and mouse subjects exhibited that lungs were more sensitive than the liver to the effects of alcohol in down-regulating immune-related genes and pathways. Furthermore, the transcriptomics analysis provided evidence that immunometabolic change is a central driver in lung alteration by downregulating the immune pathways and upregulating metabolic pathways. Chronic alcohol consumption resulted in reduced mTOR signaling and decreased immune cell populations. mTOR signaling axis may serve as an upstream regulator of alcohol-induced dysregulation in lung immunity.

Machine learning-based marker for coronary artery disease: derivation and validation in two longitudinal cohorts.

BACKGROUND: Binary diagnosis of coronary artery disease does not preserve the complexity of disease or quantify its severity or its associated risk with death; hence, a quantitative marker of coronary artery disease is warranted. We evaluated a quantitative marker of coronary artery disease derived from probabilities of a machine learning model. METHODS: In this cohort study, we developed and validated a coronary artery disease-predictive machine learning model using 95 935 electronic health records and assessed its probabilities as in-silico scores for coronary artery disease (ISCAD; range 0 [lowest probability] to 1 [highest probability]) in participants in two longitudinal biobank cohorts. We measured the association of ISCAD with clinical outcomes-namely, coronary artery stenosis, obstructive coronary artery disease, multivessel coronary artery disease, all-cause death, and coronary artery disease sequelae. FINDINGS: Among 95 935 participants, 35 749 were from the BioMe Biobank (median age 61 years [IQR 18]; 14 599 [41%] were male and 21 150 [59%] were female; 5130 [14%] were with diagnosed coronary artery disease) and 60 186 were from the UK Biobank (median age 62 [15] years; 25 031 [42%] male and 35 155 [58%] female; 8128 [14%] with diagnosed coronary artery disease). The model predicted coronary artery disease with an area under the receiver operating characteristic curve of 0·95 (95% CI 0·94-0·95; sensitivity of 0·94 [0·94-0·95] and specificity of 0·82 [0·81-0·83]) and 0·93 (0·92-0·93; sensitivity of 0·90 [0·89-0·90] and specificity of 0·88 [0·87-0·88]) in the BioMe validation and holdout sets, respectively, and 0·91 (0·91-0·91; sensitivity of 0·84 [0·83-0·84] and specificity of 0·83 [0·82-0·83]) in the UK Biobank external test set. ISCAD captured coronary artery disease risk from known risk factors, pooled cohort equations, and polygenic risk scores. Coronary artery stenosis increased quantitatively with ascending ISCAD quartiles (increase per quartile of 12 percentage points), including risk of obstructive coronary artery disease, multivessel coronary artery disease, and stenosis of major coronary arteries. Hazard ratios (HRs) and prevalence of all-cause death increased stepwise over ISCAD deciles (decile 1: HR 1·0 [95% CI 1·0-1·0], 0·2% prevalence; decile 6: 11 [3·9-31], 3·1% prevalence; and decile 10: 56 [20-158], 11% prevalence). A similar trend was observed for recurrent myocardial infarction. 12 (46%) undiagnosed individuals with high ISCAD (≥0·9) had clinical evidence of coronary artery disease according to the 2014 American College of Cardiology/American Heart Association Task Force guidelines. INTERPRETATION: Electronic health record-based machine learning was used to generate an in-silico marker for coronary artery disease that can non-invasively quantify atherosclerosis and risk of death on a continuous spectrum, and identify underdiagnosed individuals. FUNDING: National Institutes of Health.

Discovery of a NAPE-PLD inhibitor that modulates emotional behavior in mice.

N-acylethanolamines (NAEs), which include the endocannabinoid anandamide, represent an important family of signaling lipids in the brain. The lack of chemical probes that modulate NAE biosynthesis in living systems hamper the understanding of the biological role of these lipids. Using a high-throughput screen, chemical proteomics and targeted lipidomics, we report here the discovery and characterization of LEI-401 as a CNS-active N-acylphosphatidylethanolamine phospholipase D (NAPE-PLD) inhibitor. LEI-401 reduced NAE levels in neuroblastoma cells and in the brain of freely moving mice, but not in NAPE-PLD KO cells and mice, respectively. LEI-401 activated the hypothalamus-pituitary-adrenal axis and impaired fear extinction, thereby emulating the effect of a cannabinoid CB1 receptor antagonist, which could be reversed by a fatty acid amide hydrolase inhibitor. Our findings highlight the distinctive role of NAPE-PLD in NAE biosynthesis in the brain and suggest the presence of an endogenous NAE tone controlling emotional behavior.

The Heterogeneity of Lipid Metabolism in Cancer.

The study of cancer cell metabolism has traditionally focused on glycolysis and glutaminolysis. However, lipidomic technologies have matured considerably over the last decade and broadened our understanding of how lipid metabolism is relevant to cancer biology [1-3]. Studies now suggest that the reprogramming of cellular lipid metabolism contributes directly to malignant transformation and progression [4, 5]. For example, de novo lipid synthesis can supply proliferating tumor cells with phospholipid components that comprise the plasma and organelle membranes of new daughter cells [6, 7]. Moreover, the upregulation of mitochondrial ß-oxidation can support tumor cell energetics and redox homeostasis [8], while lipid-derived messengers can regulate major signaling pathways or coordinate immunosuppressive mechanisms [9-11]. Lipid metabolism has, therefore, become implicated in a variety of oncogenic processes, including metastatic colonization, drug resistance, and cell differentiation [10, 12-16]. However, whether we can safely and effectively modulate the underlying mechanisms of lipid metabolism for cancer therapy is still an open question.

Bleomycin Induces Drug Efflux in Lungs. A Pitfall for Pharmacological Studies of Pulmonary Fibrosis.

ATP-binding cassette (ABC) transporters are evolutionarily conserved membrane proteins that pump a variety of endogenous substrates across cell membranes. Certain subfamilies are known to interact with pharmaceutical compounds, potentially influencing drug delivery and treatment efficacy. However, the role of drug resistance-associated ABC transporters has not been examined in idiopathic pulmonary fibrosis (IPF) or its animal model: the bleomycin (BLM)-induced murine model. Here, we investigate the expression of two ABC transporters, P-gp (permeability glycoprotein) and BCRP (breast cancer resistance protein), in human IPF lung tissue and two different BLM-induced mouse models of pulmonary fibrosis. We obtained human IPF specimens from patients during lung transplantation and administered BLM to male C57BL/6J mice either by oropharyngeal aspiration (1 U/kg) or subcutaneous osmotic infusion (100 U/kg over 7 d). We report that P-gp and BCRP expression in lungs of patients with IPF was comparable to controls. However, murine lungs expressed increased levels of P-gp and BCRP after oropharyngeal and subcutaneous BLM administration. We localized this upregulation to multiple pulmonary cell types, including alveolar fibroblasts, endothelial cells, and type 2 epithelial cells. Functionally, this effect reduced murine lung exposure to nintedanib, a U.S. Food and Drug Administration-approved IPF therapy known to be a P-gp substrate. The study reveals a discrepancy between IPF pathophysiology and the common animal model of lung fibrosis. BLM-induced drug efflux in the murine lungs may present an uncontrolled confounding variable in the preclinical study of IPF drug candidates, and these findings will facilitate disease model validation and enhance new drug discoveries that will ultimately improve patient outcomes.

Combination therapy with BPTES nanoparticles and metformin targets the metabolic heterogeneity of pancreatic cancer.

Targeting glutamine metabolism via pharmacological inhibition of glutaminase has been translated into clinical trials as a novel cancer therapy, but available drugs lack optimal safety and efficacy. In this study, we used a proprietary emulsification process to encapsulate bis-2-(5-phenylacetamido-1,2,4-thiadiazol-2-yl)ethyl sulfide (BPTES), a selective but relatively insoluble glutaminase inhibitor, in nanoparticles. BPTES nanoparticles demonstrated improved pharmacokinetics and efficacy compared with unencapsulated BPTES. In addition, BPTES nanoparticles had no effect on the plasma levels of liver enzymes in contrast to CB-839, a glutaminase inhibitor that is currently in clinical trials. In a mouse model using orthotopic transplantation of patient-derived pancreatic tumor tissue, BPTES nanoparticle monotherapy led to modest antitumor effects. Using the HypoxCR reporter in vivo, we found that glutaminase inhibition reduced tumor growth by specifically targeting proliferating cancer cells but did not affect hypoxic, noncycling cells. Metabolomics analyses revealed that surviving tumor cells following glutaminase inhibition were reliant on glycolysis and glycogen synthesis. Based on these findings, metformin was selected for combination therapy with BPTES nanoparticles, which resulted in significantly greater pancreatic tumor reduction than either treatment alone. Thus, targeting of multiple metabolic pathways, including effective inhibition of glutaminase by nanoparticle drug delivery, holds promise as a novel therapy for pancreatic cancer.

Network analyses identify liver-specific targets for treating liver diseases.

We performed integrative network analyses to identify targets that can be used for effectively treating liver diseases with minimal side effects. We first generated co-expression networks (CNs) for 46 human tissues and liver cancer to explore the functional relationships between genes and examined the overlap between functional and physical interactions. Since increased de novo lipogenesis is a characteristic of nonalcoholic fatty liver disease (NAFLD) and hepatocellular carcinoma (HCC), we investigated the liver-specific genes co-expressed with fatty acid synthase (FASN). CN analyses predicted that inhibition of these liver-specific genes decreases FASN expression. Experiments in human cancer cell lines, mouse liver samples, and primary human hepatocytes validated our predictions by demonstrating functional relationships between these liver genes, and showing that their inhibition decreases cell growth and liver fat content. In conclusion, we identified liver-specific genes linked to NAFLD pathogenesis, such as pyruvate kinase liver and red blood cell (PKLR), or to HCC pathogenesis, such as PKLR, patatin-like phospholipase domain containing 3 (PNPLA3), and proprotein convertase subtilisin/kexin type 9 (PCSK9), all of which are potential targets for drug development.

Cannabinoid-1 receptor deletion in podocytes mitigates both glomerular and tubular dysfunction in a mouse model of diabetic nephropathy.

AIMS: To determine the specific role of podocyte-expressed cannabinoid-1 receptor (CB1 R) in the development of diabetic nephropathy (DN), relative to CB1 R in other renal cell types. MATERIAL AND METHODS: We developed a mouse model with a podocyte-specific deletion of CB1 R (pCB1Rko) and challenged this model with streptozotocin (STZ)-induced type-1 DN. We also assessed the podocyte response to high glucose in vitro and its effects on CB1 R activation. RESULTS: High glucose exposure for 48 hours led to an increase in CB1 R gene expression (CNR1) and endocannabinoid production in cultured human podocytes. This was associated with podocyte injury, reflected by decreased podocin and nephrin expression. These changes could be prevented by Cnr1-silencing, thus identifying CB1R as a key player in podocyte injury. After 12 weeks of chronic hyperglycaemia, STZ-treated pCB1Rko mice showed elevated blood glucose similar to that of their wild-type littermates. However, they displayed less albuminuria and less podocyte loss than STZ-treated wild-type mice. Unexpectedly, pCB1Rko mice also have milder tubular dysfunction, fibrosis and reduction of cortical microcirculation compared to wild-type controls, which is mediated, in part, by podocyte-derived endocannabinoids acting via CB1 R on proximal tubular cells. CONCLUSIONS: Activation of CB1 R in podocytes contributes to both glomerular and tubular dysfunction in type-1 DN, which highlights the therapeutic potential of peripheral CB1 R blockade.

The Heterogeneity of Lipid Metabolism in Cancer.

KEY POINTS: The study of cancer cell metabolism has traditionally focused on glycolysis and glutaminolysis. However, lipidomic technologies have matured considerably over the last decade and broadened our understanding of how lipid metabolism is relevant to cancer biology [1­3]. Studies now suggest that the reprogramming of cellular lipid metabolism contributes directly to malignant transformation and progression [4, 5]. For example, de novo lipid synthesis can supply proliferating tumor cells with phospholipid components that comprise the plasma and organelle membranes of new daughter cells [6, 7]. Moreover, the upregulation of mitochondrial ß-oxidation can support tumor cell energetics and redox homeostasis [8], while lipid-derived messengers can regulate major signaling pathways or coordinate immunosuppressive mechanisms [9­11]. Lipid metabolism has therefore become implicated in a variety of oncogenic processes, including metastatic colonization, drug resistance, and cell differentiation [10, 12­16]. However, whether we can safely and effectively modulate the underlying mechanisms for cancer therapy is still an open question.

Genome-first evaluation with exome sequence and clinical data uncovers underdiagnosed genetic disorders in a large healthcare system.

Population-based genomic screening may help diagnose individuals with disease-risk variants. Here, we perform a genome-first evaluation for nine disorders in 29,039 participants with linked exome sequences and electronic health records (EHRs). We identify 614 individuals with 303 pathogenic/likely pathogenic or predicted loss-of-function (P/LP/LoF) variants, yielding 644 observations; 487 observations (76%) lack a corresponding clinical diagnosis in the EHR. Upon further investigation, 75 clinically undiagnosed observations (15%) have evidence of symptomatic untreated disease, including familial hypercholesterolemia (3 of 6 [50%] undiagnosed observations with disease evidence) and breast cancer (23 of 106 [22%]). These genetic findings enable targeted phenotyping that reveals new diagnoses in previously undiagnosed individuals. Disease yield is greater with variants in penetrant genes for which disease is observed in carriers in an independent cohort. The prevalence of P/LP/LoF variants exceeds that of clinical diagnoses, and some clinically undiagnosed carriers are discovered to have disease. These results highlight the potential of population-based genomic screening.

Muesli Intake May Protect Against Coronary Artery Disease: Mendelian Randomization on 13 Dietary Traits.

BACKGROUND: Diet is a key modifiable risk factor of coronary artery disease (CAD). However, the causal effects of specific dietary traits on CAD risk remain unclear. With the expansion of dietary data in population biobanks, Mendelian randomization (MR) could help enable the efficient estimation of causality in diet-disease associations. OBJECTIVES: The primary goal was to test causality for 13 common dietary traits on CAD risk using a systematic 2-sample MR framework. A secondary goal was to identify plasma metabolites mediating diet-CAD associations suspected to be causal. METHODS: Cross-sectional genetic and dietary data on up to 420,531 UK Biobank and 184,305 CARDIoGRAMplusC4D individuals of European ancestry were used in 2-sample MR. The primary analysis used fixed effect inverse-variance weighted regression, while sensitivity analyses used weighted median estimation, MR-Egger regression, and MR-Pleiotropy Residual Sum and Outlier. RESULTS: Genetic variants serving as proxies for muesli intake were negatively associated with CAD risk (OR: 0.74; 95% CI: 0.65-0.84; P = 5.385 × 10-4). Sensitivity analyses using weighted median estimation supported this with a significant association in the same direction. Additionally, we identified higher plasma acetate levels as a potential mediator (OR: 0.03; 95% CI: 0.01-0.12; P = 1.15 × 10-4). CONCLUSIONS: Muesli, a mixture of oats, seeds, nuts, dried fruit, and milk, may causally reduce CAD risk. Circulating levels of acetate, a gut microbiota-derived short-chain fatty acid, could be mediating its cardioprotective effects. These findings highlight the role of gut flora in cardiovascular health and help prioritize randomized trials on dietary interventions for CAD.

Exome sequence analysis identifies rare coding variants associated with a machine learning-based marker for coronary artery disease.

Coronary artery disease (CAD) exists on a spectrum of disease represented by a combination of risk factors and pathogenic processes. An in silico score for CAD built using machine learning and clinical data in electronic health records captures disease progression, severity and underdiagnosis on this spectrum and could enhance genetic discovery efforts for CAD. Here we tested associations of rare and ultrarare coding variants with the in silico score for CAD in the UK Biobank, All of Us Research Program and BioMe Biobank. We identified associations in 17 genes; of these, 14 show at least moderate levels of prior genetic, biological and/or clinical support for CAD. We also observed an excess of ultrarare coding variants in 321 aggregated CAD genes, suggesting more ultrarare variant associations await discovery. These results expand our understanding of the genetic etiology of CAD and illustrate how digital markers can enhance genetic association investigations for complex diseases.

Anandamide is an Early Blood Biomarker of Hermansky-Pudlak Syndrome Pulmonary Fibrosis.

Hermansky-Pudlak syndrome (HPS) is a group of rare genetic disorders, with several subtypes leading to fatal adult-onset pulmonary fibrosis (PF) and no effective treatment. Circulating biomarkers detecting early PF have not been identified. We investigated whether endocannabinoids could serve as blood biomarkers of PF in HPS. We measured endocannabinoids in the serum of HPS, IPF, and healthy human subjects and in a mouse model of HPSPF. Pulmonary function tests (PFT) were correlated with endocannabinoid measurements. In a pale ear mouse model of bleomycin-induced HPSPF, serum endocannabinoid levels were measured with and without treatment with zevaquenabant (MRI-1867), a peripheral CB1R and iNOS antagonist. In three separate cohorts, circulating anandamide levels were increased in HPS-1 patients with or without PF, compared to healthy volunteers. This increase was not observed in IPF patients or in HPS-3 patients, who do not have PF. Circulating anandamide (AEA) levels were negatively correlated with PFT. Furthermore, a longitudinal study over the course of 5-14 years with HPS-1 patients indicated that circulating AEA levels begin to increase with the fibrotic lung process even at the subclinical stages of HPSPF. In pale ear mice with bleomycin-induced HpsPF, serum AEA levels were significantly increased in the earliest stages of PF and remained elevated at a later fibrotic stage. Zevaquenabant treatment reduced the increased AEA levels and attenuated progression in bleomycin-induced HpsPF. Circulating AEA may be a prognostic blood biomarker for PF in HPS-1 patients. Further studies are indicated to evaluate endocannabinoids as potential surrogate biomarkers in progressive fibrotic lung diseases.

Development of a human genetics-guided priority score for 19,365 genes and 399 drug indications.

Studies have shown that drug targets with human genetic support are more likely to succeed in clinical trials. Hence, a tool integrating genetic evidence to prioritize drug target genes is beneficial for drug discovery. We built a genetic priority score (GPS) by integrating eight genetic features with drug indications from the Open Targets and SIDER databases. The top 0.83%, 0.28% and 0.19% of the GPS conferred a 5.3-, 9.9- and 11.0-fold increased effect of having an indication, respectively. In addition, we observed that targets in the top 0.28% of the score were 1.7-, 3.7- and 8.8-fold more likely to advance from phase I to phases II, III and IV, respectively. Complementary to the GPS, we incorporated the direction of genetic effect and drug mechanism into a directional version of the score called the GPS with direction of effect. We applied our method to 19,365 protein-coding genes and 399 drug indications and made all results available through a web portal.

An Integrative Multiomics Framework for Identification of Therapeutic Targets in Pulmonary Fibrosis.

Pulmonary fibrosis (PF) is a heterogeneous disease with a poor prognosis. Therefore, identifying additional therapeutic modalities is required to improve outcome. However, the lack of biomarkers of disease progression hampers the preclinical to clinical translational process. Here, this work assesses and identifies progressive alterations in pulmonary function, transcriptomics, and metabolomics in the mouse lung at 7, 14, 21, and 28 days after a single dose of oropharyngeal bleomycin. By integrating multi-omics data, this work identifies two central gene subnetworks associated with multiple critical pathological changes in transcriptomics and metabolomics as well as pulmonary function. This work presents a multi-omics-based framework to establish a translational link between the bleomycin-induced PF model in mice and human idiopathic pulmonary fibrosis to identify druggable targets and test therapeutic candidates. This work also indicates peripheral cannabinoid receptor 1 (CB1 R) antagonism as a rational therapeutic target for clinical translation in PF. Mouse Lung Fibrosis Atlas can be accessed freely at https://niaaa.nih.gov/mouselungfibrosisatlas.

A machine learning model identifies patients in need of autoimmune disease testing using electronic health records.

Systemic autoimmune rheumatic diseases (SARDs) can lead to irreversible damage if left untreated, yet these patients often endure long diagnostic journeys before being diagnosed and treated. Machine learning may help overcome the challenges of diagnosing SARDs and inform clinical decision-making. Here, we developed and tested a machine learning model to identify patients who should receive rheumatological evaluation for SARDs using longitudinal electronic health records of 161,584 individuals from two institutions. The model demonstrated high performance for predicting cases of autoantibody-tested individuals in a validation set, an external test set, and an independent cohort with a broader case definition. This approach identified more individuals for autoantibody testing compared with current clinical standards and a greater proportion of autoantibody carriers among those tested. Diagnoses of SARDs and other autoimmune conditions increased with higher model probabilities. The model detected a need for autoantibody testing and rheumatology encounters up to five years before the test date and assessment date, respectively. Altogether, these findings illustrate that the clinical manifestations of a diverse array of autoimmune conditions are detectable in electronic health records using machine learning, which may help systematize and accelerate autoimmune testing.

In vitro and in vivo pharmacokinetic characterization, chiral conversion and PBPK scaling towards human PK simulation of S-MRI-1867, a drug candidate for Hermansky-Pudlak syndrome pulmonary fibrosis.

Hermansky-Pudlak syndrome (HPS) is a rare autosomal recessive disorder that affects lysosome-related organelles, often leading to fatal pulmonary fibrosis (PF). The search for a treatment for HPS pulmonary fibrosis (HPSPF) is ongoing. S-MRI-1867, a dual cannabinoid receptor 1 (CB1R)/inducible nitric oxide synthase (iNOS) inhibitor, has shown great promise for the treatment of several fibrotic diseases, including HPSPF. In this study, we investigated the in vitro ADME characteristics of S-MRI-1867, as well as its pharmacokinetic (PK) properties in mice, rats, dogs, and monkeys. S-MRI-1867 showed low aqueous solubility (< 1 µg/mL), high plasma protein binding (>99%), and moderate to high metabolic stability. In its preclinical PK studies, S-MRI-1867 exhibited moderate to low plasma clearance (CLp) and high steady-state volume of distribution (Vdss) across all species. Despite the low solubility and P-gp efflux, S-MRI-1867 showed great permeability and metabolic stability leading to a moderate bioavailability (21-60%) across mouse, rat, dog, and monkey. Since the R form of MRI-1867 is CB1R-inactive, we investigated the potential conversion of S-MRI-1867 to R-MRI-1867 in mice and found that the chiral conversion was negligible. Furthermore, we developed and validated a PBPK model that adequately fits the PK profiles of S-MRI-1867 in mice, rats, dogs, and monkeys using various dosing regimens. We employed this PBPK model to simulate the human PK profiles of S-MRI-1867, enabling us to inform human dose selection and support the advancement of this promising drug candidate in the treatment of HPSPF.

Phenome-wide Mendelian randomization study of plasma triglyceride levels and 2600 disease traits.

Background: Causality between plasma triglyceride (TG) levels and atherosclerotic cardiovascular disease (ASCVD) risk remains controversial despite more than four decades of study and two recent landmark trials, STRENGTH, and REDUCE-IT. Further unclear is the association between TG levels and non-atherosclerotic diseases across organ systems. Methods: Here, we conducted a phenome-wide, two-sample Mendelian randomization (MR) analysis using inverse-variance weighted (IVW) regression to systematically infer the causal effects of plasma TG levels on 2600 disease traits in the European ancestry population of UK Biobank. For replication, we externally tested 221 nominally significant associations (p<0.05) in an independent cohort from FinnGen. To account for potential horizontal pleiotropy and the influence of invalid instrumental variables, we performed sensitivity analyses using MR-Egger regression, weighted median estimator, and MR-PRESSO. Finally, we used multivariable MR (MVMR) controlling for correlated lipid fractions to distinguish the independent effect of plasma TG levels. Results: Our results identified seven disease traits reaching Bonferroni-corrected significance in both the discovery (p<1.92 × 10-5) and replication analyses (p<2.26 × 10-4), suggesting a causal relationship between plasma TG levels and ASCVDs, including coronary artery disease (OR 1.33, 95% CI 1.24-1.43, p=2.47 × 10-13). We also identified 12 disease traits that were Bonferroni-significant in the discovery or replication analysis and at least nominally significant in the other analysis (p<0.05), identifying plasma TG levels as a novel potential risk factor for nine non-ASCVD diseases, including uterine leiomyoma (OR 1.19, 95% CI 1.10-1.29, p=1.17 × 10-5). Conclusions: Taking a phenome-wide, two-sample MR approach, we identified causal associations between plasma TG levels and 19 disease traits across organ systems. Our findings suggest unrealized drug repurposing opportunities or adverse effects related to approved and emerging TG-lowering agents, as well as mechanistic insights for future studies. Funding: RD is supported by the National Institute of General Medical Sciences of the National Institutes of Health (NIH) (R35-GM124836) and the National Heart, Lung, and Blood Institute of the NIH (R01-HL139865 and R01-HL155915).

Peripheral Hybrid CB1R and iNOS Antagonist MRI-1867 Displays Anti-Fibrotic Efficacy in Bleomycin-Induced Skin Fibrosis.

Scleroderma, or systemic sclerosis, is a multi-organ connective tissue disease resulting in fibrosis of the skin, heart, and lungs with no effective treatment. Endocannabinoids acting via cannabinoid-1 receptors (CB1R) and increased activity of inducible NO synthase (iNOS) promote tissue fibrosis including skin fibrosis, and joint targeting of these pathways may improve therapeutic efficacy. Recently, we showed that in mouse models of liver, lung and kidney fibrosis, treatment with a peripherally restricted hybrid CB1R/iNOS inhibitor (MRI-1867) yields greater anti-fibrotic efficacy than inhibiting either target alone. Here, we evaluated the therapeutic efficacy of MRI-1867 in bleomycin-induced skin fibrosis. Skin fibrosis was induced in C57BL/6J (B6) and Mdr1a/b-Bcrp triple knock-out (KO) mice by daily subcutaneous injections of bleomycin (2 IU/100 µL) for 28 days. Starting on day 15, mice were treated for 2 weeks with daily oral gavage of vehicle or MRI-1867. Skin levels of MRI-1867 and endocannabinoids were measured by mass spectrometry to assess target exposure and engagement by MRI-1867. Fibrosis was characterized histologically by dermal thickening and biochemically by hydroxyproline content. We also evaluated the potential increase of drug-efflux associated ABC transporters by bleomycin in skin fibrosis, which could affect target exposure to test compounds, as reported in bleomycin-induced lung fibrosis. Bleomycin-induced skin fibrosis was comparable in B6 and Mdr1a/b-Bcrp KO mice. However, the skin level of MRI-1867, an MDR1 substrate, was dramatically lower in B6 mice (0.023 µM) than in Mdr1a/b-Bcrp KO mice (8.8 µM) due to a bleomycin-induced increase in efflux activity of MDR1 in fibrotic skin. Furthermore, the endocannabinoids anandamide and 2-arachidonylglycerol were elevated 2-4-fold in the fibrotic vs. control skin in both mouse strains. MRI-1867 treatment attenuated bleomycin-induced established skin fibrosis and the associated increase in endocannabinoids in Mdr1a/b-Bcrp KO mice but not in B6 mice. We conclude that combined inhibition of CB1R and iNOS is an effective anti-fibrotic strategy for scleroderma. As bleomycin induces an artifact in testing antifibrotic drug candidates that are substrates of drug-efflux transporters, using Mdr1a/b-Bcrp KO mice for preclinical testing of such compounds avoids this pitfall.

CB1 R and iNOS are distinct players promoting pulmonary fibrosis in Hermansky-Pudlak syndrome.

Hermansky-Pudlak syndrome (HPS) is a rare genetic disorder which, in its most common and severe form, HPS-1, leads to fatal adult-onset pulmonary fibrosis (PF) with no effective treatment. We evaluated the role of the endocannabinoid/CB1 R system and inducible nitric oxide synthase (iNOS) for dual-target therapeutic strategy using human bronchoalveolar lavage fluid (BALF), lung samples from patients with HPS and controls, HPS-PF patient-derived lung fibroblasts, and bleomycin-induced PF in pale ear mice (HPS1ep/ep ). We found overexpression of CB1 R and iNOS in fibrotic lungs of HPSPF patients and bleomycin-infused pale ear mice. The endocannabinoid anandamide was elevated in BALF and negatively correlated with pulmonary function parameters in HPSPF patients and pale ear mice with bleomycin-induced PF. Simultaneous targeting of CB1 R and iNOS by MRI-1867 yielded greater antifibrotic efficacy than inhibiting either target alone by attenuating critical pathologic pathways. Moreover, MRI-1867 treatment abrogated bleomycin-induced increases in lung levels of the profibrotic interleukin-11 via iNOS inhibition and reversed mitochondrial dysfunction via CB1 R inhibition. Dual inhibition of CB1 R and iNOS is an effective antifibrotic strategy for HPSPF.