Trained Immunity-Promoting Nanobiologic Therapy Suppresses Tumor Growth and Potentiates Checkpoint Inhibition.

Trained immunity, a functional state of myeloid cells, has been proposed as a compelling immune-oncological target. Its efficient induction requires direct engagement of myeloid progenitors in the bone marrow. For this purpose, we developed a bone marrow-avid nanobiologic platform designed specifically to induce trained immunity. We established the potent anti-tumor capabilities of our lead candidate MTP10-HDL in a B16F10 mouse melanoma model. These anti-tumor effects result from trained immunity-induced myelopoiesis caused by epigenetic rewiring of multipotent progenitors in the bone marrow, which overcomes the immunosuppressive tumor microenvironment. Furthermore, MTP10-HDL nanotherapy potentiates checkpoint inhibition in this melanoma model refractory to anti-PD-1 and anti-CTLA-4 therapy. Finally, we determined MTP10-HDL's favorable biodistribution and safety profile in non-human primates. In conclusion, we show that rationally designed nanobiologics can promote trained immunity and elicit a durable anti-tumor response either as a monotherapy or in combination with checkpoint inhibitor drugs.

Clonally expanded CD8 T cells characterize amyotrophic lateral sclerosis-4.

Amyotrophic lateral sclerosis (ALS) is a heterogenous neurodegenerative disorder that affects motor neurons and voluntary muscle control1. ALS heterogeneity includes the age of manifestation, the rate of progression and the anatomical sites of symptom onset. Disease-causing mutations in specific genes have been identified and define different subtypes of ALS1. Although several ALS-associated genes have been shown to affect immune functions2, whether specific immune features account for ALS heterogeneity is poorly understood. Amyotrophic lateral sclerosis-4 (ALS4) is characterized by juvenile onset and slow progression3. Patients with ALS4 show motor difficulties by the time that they are in their thirties, and most of them require devices to assist with walking by their fifties. ALS4 is caused by mutations in the senataxin gene (SETX). Here, using Setx knock-in mice that carry the ALS4-causative L389S mutation, we describe an immunological signature that consists of clonally expanded, terminally differentiated effector memory (TEMRA) CD8 T cells in the central nervous system and the blood of knock-in mice. Increased frequencies of antigen-specific CD8 T cells in knock-in mice mirror the progression of motor neuron disease and correlate with anti-glioma immunity. Furthermore, bone marrow transplantation experiments indicate that the immune system has a key role in ALS4 neurodegeneration. In patients with ALS4, clonally expanded TEMRA CD8 T cells circulate in the peripheral blood. Our results provide evidence of an antigen-specific CD8 T cell response in ALS4, which could be used to unravel disease mechanisms and as a potential biomarker of disease state.

Inhibiting Inflammation with Myeloid Cell-Specific Nanobiologics Promotes Organ Transplant Acceptance.

Inducing graft acceptance without chronic immunosuppression remains an elusive goal in organ transplantation. Using an experimental transplantation mouse model, we demonstrate that local macrophage activation through dectin-1 and toll-like receptor 4 (TLR4) drives trained immunity-associated cytokine production during allograft rejection. We conducted nanoimmunotherapeutic studies and found that a short-term mTOR-specific high-density lipoprotein (HDL) nanobiologic treatment (mTORi-HDL) averted macrophage aerobic glycolysis and the epigenetic modifications underlying inflammatory cytokine production. The resulting regulatory macrophages prevented alloreactive CD8+ T cell-mediated immunity and promoted tolerogenic CD4+ regulatory T (Treg) cell expansion. To enhance therapeutic efficacy, we complemented the mTORi-HDL treatment with a CD40-TRAF6-specific nanobiologic (TRAF6i-HDL) that inhibits co-stimulation. This synergistic nanoimmunotherapy resulted in indefinite allograft survival. Together, we show that HDL-based nanoimmunotherapy can be employed to control macrophage function in vivo. Our strategy, focused on preventing inflammatory innate immune responses, provides a framework for developing targeted therapies that promote immunological tolerance.

Cortico-limbic interactions and carotid atherosclerotic burden during chronic stress exposure.

BACKGROUND AND AIMS: Chronic stress associates with cardiovascular disease, but mechanisms remain incompletely defined. Advanced imaging was used to identify stress-related neural imaging phenotypes associated with atherosclerosis. METHODS: Twenty-seven individuals with post-traumatic stress disorder (PTSD), 45 trauma-exposed controls without PTSD, and 22 healthy controls underwent 18F-fluorodeoxyglucose positron emission tomography/magnetic resonance imaging (18F-FDG PET/MRI). Atherosclerotic inflammation and burden were assessed using 18F-FDG PET (as maximal target-to-background ratio, TBR max) and MRI, respectively. Inflammation was assessed using high-sensitivity C-reactive protein (hsCRP) and leucopoietic imaging (18F-FDG PET uptake in spleen and bone marrow). Stress-associated neural network activity (SNA) was assessed on 18F-FDG PET as amygdala relative to ventromedial prefrontal cortex (vmPFC) activity. MRI diffusion tensor imaging assessed the axonal integrity (AI) of the uncinate fasciculus (major white matter tract connecting vmPFC and amygdala). RESULTS: Median age was 37 years old and 54% of participants were female. There were no significant differences in atherosclerotic inflammation between participants with PTSD and controls; adjusted mean difference in TBR max (95% confidence interval) of the aorta 0.020 (-0.098, 0.138), and of the carotids 0.014 (-0.091, 0.119). Participants with PTSD had higher hsCRP, spleen activity, and aorta atherosclerotic burden (normalized wall index). Participants with PTSD also had higher SNA and lower AI. Across the cohort, carotid atherosclerotic burden (standard deviation of wall thickness) associated positively with SNA and negatively with AI independent of Framingham risk score. CONCLUSIONS: In this study of limited size, participants with PTSD did not have higher atherosclerotic inflammation than controls. Notably, impaired cortico-limbic interactions (higher amygdala relative to vmPFC activity or disruption of their intercommunication) associated with carotid atherosclerotic burden. Larger studies are needed to refine these findings.

Trained immunity suppression determines kidney allograft survival.

The innate immune system plays an essential role in regulating the immune responses to kidney transplantation, but the mechanisms through which innate immune cells influence long-term graft survival are unclear. The current study highlights the vital role of trained immunity in kidney allograft survival. Trained immunity describes the epigenetic and metabolic changes that innate immune cells undergo following an initial stimulus, allowing them have a stronger inflammatory response to subsequent stimuli. We stimulated healthy peripheral blood mononuclear cells with pretransplant and posttransplant serum of kidney transplant patients and immunosuppressive drugs in an in vitro trained immunity assay and measured tumor necrosis factor and interleukin 6 cytokine levels in the supernatant as a readout for trained immunity. We show that the serum of kidney transplant recipients collected 1 week after transplantation can suppress trained immunity. Importantly, we found that kidney transplant recipients whose serum most strongly suppressed trained immunity rarely experienced graft loss. This suppressive effect of posttransplant serum is likely mediated by previously unreported effects of immunosuppressive drugs. Our findings provide mechanistic insights into the role of innate immunity in kidney allograft survival, uncovering trained immunity as a potential therapeutic target for improving graft survival.

Association of the multi-biomarker disease activity score with arterial 18-fluorodeoxyglucose uptake in rheumatoid arthritis.

OBJECTIVES: Rheumatoid arthritis (RA) and atherosclerosis share many common inflammatory pathways. We studied whether a multi-biomarker panel for RA disease activity (MBDA) would associate with changes in arterial inflammation in an interventional trial. METHODS: In the TARGET Trial, RA patients with active disease despite methotrexate were randomly assigned to the addition of either a TNF inhibitor or sulfasalazine+hydroxychloroquine (triple therapy). Baseline and 24-week follow-up 18F-fluorodeoxyglucose (FDG) positron emission tomography/computed tomography scans were assessed for change in arterial inflammation measured as the maximal arterial target-to-blood background ratio of FDG uptake in the most diseased segment of the carotid arteries or aorta (MDS-TBRmax). The MBDA test, measured at baseline and weeks 6, 18, and 24, was assessed for its association with the change in MDS-TBRmax. RESULTS: Interpretable scans were available at baseline and week 24 for n = 112 patients. The MBDA score at week 24 was significantly correlated with the change in MDR-TBRmax (Spearman's rho = 0.239; p= 0.011) and remained significantly associated after adjustment for relevant confounders. Those with low MBDA at week 24 had a statistically significant adjusted reduction in arterial inflammation of 0.35 units vs no significant reduction in those who did not achieve low MBDA. Neither DAS28-CRP nor CRP predicted change in arterial inflammation. The MBDA component with the strongest association with change in arterial inflammation was serum amyloid A (SAA). CONCLUSIONS: Among treated RA patients, achieved MBDA predicts of changes in arterial inflammation. Achieving low MBDA at 24 weeks was associated with clinically meaningful reductions in arterial inflammation, regardless of treatment.

A review of self-supervised, generative, and few-shot deep learning methods for data-limited magnetic resonance imaging segmentation.

Magnetic resonance imaging (MRI) is a ubiquitous medical imaging technology with applications in disease diagnostics, intervention, and treatment planning. Accurate MRI segmentation is critical for diagnosing abnormalities, monitoring diseases, and deciding on a course of treatment. With the advent of advanced deep learning frameworks, fully automated and accurate MRI segmentation is advancing. Traditional supervised deep learning techniques have advanced tremendously, reaching clinical-level accuracy in the field of segmentation. However, these algorithms still require a large amount of annotated data, which is oftentimes unavailable or impractical. One way to circumvent this issue is to utilize algorithms that exploit a limited amount of labeled data. This paper aims to review such state-of-the-art algorithms that use a limited number of annotated samples. We explain the fundamental principles of self-supervised learning, generative models, few-shot learning, and semi-supervised learning and summarize their applications in cardiac, abdomen, and brain MRI segmentation. Throughout this review, we highlight algorithms that can be employed based on the quantity of annotated data available. We also present a comprehensive list of notable publicly available MRI segmentation datasets. To conclude, we discuss possible future directions of the field-including emerging algorithms, such as contrastive language-image pretraining, and potential combinations across the methods discussed-that can further increase the efficacy of image segmentation with limited labels.

PTSD increases risk for major adverse cardiovascular events through neural and cardio-inflammatory pathways.

While posttraumatic stress disorder (PTSD) is known to associate with an elevated risk for major adverse cardiovascular events (MACE), few studies have examined mechanisms underlying this link. Recent studies have demonstrated that neuro-immune mechanisms, (manifested by heightened stress-associated neural activity (SNA), autonomic nervous system activity, and inflammation), link common stress syndromes to MACE. However, it is unknown if neuro-immune mechanisms similarly link PTSD to MACE. The current study aimed to test the hypothesis that upregulated neuro-immune mechanisms increase MACE risk among individuals with PTSD. This study included N = 118,827 participants from a large hospital-based biobank. Demographic, diagnostic, and medical history data collected from the biobank. SNA (n = 1,520), heart rate variability (HRV; [n = 11,463]), and high sensitivity C-reactive protein (hs-CRP; [n = 15,164]) were obtained for a subset of participants. PTSD predicted MACE after adjusting for traditional MACE risk factors (hazard ratio (HR) [95 % confidence interval (CI)] = 1.317 [1.098, 1.580], ß = 0.276, p = 0.003). The PTSD-to-MACE association was mediated by SNA (CI = 0.005, 0.133, p < 0.05), HRV (CI = 0.024, 0.056, p < 0.05), and hs-CRP (CI = 0.010, 0.040, p < 0.05). This study provides evidence that neuro-immune pathways may play important roles in the mechanisms linking PTSD to MACE. Future studies are needed to determine if these markers are relevant targets for PTSD treatment and if improvements in SNA, HRV, and hs-CRP associate with reduced MACE risk in this patient population.

Implications of the Use of Artificial Intelligence Predictive Models in Health Care Settings : A Simulation Study.

BACKGROUND: Substantial effort has been directed toward demonstrating uses of predictive models in health care. However, implementation of these models into clinical practice may influence patient outcomes, which in turn are captured in electronic health record data. As a result, deployed models may affect the predictive ability of current and future models. OBJECTIVE: To estimate changes in predictive model performance with use through 3 common scenarios: model retraining, sequentially implementing 1 model after another, and intervening in response to a model when 2 are simultaneously implemented. DESIGN: Simulation of model implementation and use in critical care settings at various levels of intervention effectiveness and clinician adherence. Models were either trained or retrained after simulated implementation. SETTING: Admissions to the intensive care unit (ICU) at Mount Sinai Health System (New York, New York) and Beth Israel Deaconess Medical Center (Boston, Massachusetts). PATIENTS: 130 000 critical care admissions across both health systems. INTERVENTION: Across 3 scenarios, interventions were simulated at varying levels of clinician adherence and effectiveness. MEASUREMENTS: Statistical measures of performance, including threshold-independent (area under the curve) and threshold-dependent measures. RESULTS: At fixed 90% sensitivity, in scenario 1 a mortality prediction model lost 9% to 39% specificity after retraining once and in scenario 2 a mortality prediction model lost 8% to 15% specificity when created after the implementation of an acute kidney injury (AKI) prediction model; in scenario 3, models for AKI and mortality prediction implemented simultaneously, each led to reduced effective accuracy of the other by 1% to 28%. LIMITATIONS: In real-world practice, the effectiveness of and adherence to model-based recommendations are rarely known in advance. Only binary classifiers for tabular ICU admissions data were simulated. CONCLUSION: In simulated ICU settings, a universally effective model-updating approach for maintaining model performance does not seem to exist. Model use may have to be recorded to maintain viability of predictive modeling. PRIMARY FUNDING SOURCE: National Center for Advancing Translational Sciences.

Nanotherapeutic Heterogeneity: Sources, Effects, and Solutions.

Nanomaterials have revolutionized medicine by enabling control over drugs' pharmacokinetics, biodistribution, and biocompatibility. However, most nanotherapeutic batches are highly heterogeneous, meaning they comprise nanoparticles that vary in size, shape, charge, composition, and ligand functionalization. Similarly, individual nanotherapeutics often have heterogeneously distributed components, ligands, and charges. This review discusses nanotherapeutic heterogeneity's sources and effects on experimental readouts and therapeutic efficacy. Among other topics, it demonstrates that heterogeneity exists in nearly all nanotherapeutic types, examines how nanotherapeutic heterogeneity arises, and discusses how heterogeneity impacts nanomaterials' in vitro and in vivo behavior. How nanotherapeutic heterogeneity skews experimental readouts and complicates their optimization and clinical translation is also shown. Lastly, strategies for limiting nanotherapeutic heterogeneity are reviewed and recommendations for developing more reproducible and effective nanotherapeutics provided.

Reducing cardiovascular risk with immunomodulators: a randomised active comparator trial among patients with rheumatoid arthritis.

OBJECTIVE: Recent large-scale randomised trials demonstrate that immunomodulators reduce cardiovascular (CV) events among the general population. However, it is uncertain whether these effects apply to rheumatoid arthritis (RA) and if certain treatment strategies in RA reduce CV risk to a greater extent. METHODS: Patients with active RA despite use of methotrexate were randomly assigned to addition of a tumour necrosis factor (TNF) inhibitor (TNFi) or addition of sulfasalazine and hydroxychloroquine (triple therapy) for 24 weeks. Baseline and follow-up 18F-fluorodeoxyglucose-positron emission tomography/CT scans were assessed for change in arterial inflammation, an index of CV risk, measured as an arterial target-to-background ratio (TBR) in the carotid arteries and aorta. RESULTS: 115 patients completed the protocol. The two treatment groups were well balanced with a median age of 58 years, 71% women, 57% seropositive and a baseline disease activity score in 28 joints of 4.8 (IQR 4.0, 5.6). Baseline TBR was similar across the two groups. Significant TBR reductions were observed in both groups-ΔTNFi: -0.24 (SD=0.51), Δtriple therapy: -0.19 (SD=0.51)-without difference between groups (difference in Δs: -0.02, 95% CI -0.19 to 0.15, p=0.79). While disease activity was significantly reduced across both treatment groups, there was no association with change in TBR (ß=0.04, 95% CI -0.03 to 0.10). CONCLUSION: We found that addition of either a TNFi or triple therapy resulted in clinically important improvements in vascular inflammation. However, the addition of a TNFi did not reduce arterial inflammation more than triple therapy. TRIAL REGISTRATION NUMBER: NCT02374021.

Self-gated, dynamic contrast-enhanced magnetic resonance imaging with compressed-sensing reconstruction for evaluating endothelial permeability in the aortic root of atherosclerotic mice.

High-risk atherosclerotic plaques are characterized by active inflammation and abundant leaky microvessels. We present a self-gated, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) acquisition with compressed sensing reconstruction and apply it to assess longitudinal changes in endothelial permeability in the aortic root of Apoe-/- atherosclerotic mice during natural disease progression. Twenty-four, 8-week-old, female Apoe-/- mice were divided into four groups (n = 6 each) and imaged with self-gated DCE-MRI at 4, 8, 12, and 16 weeks after high-fat diet initiation, and then euthanized for CD68 immunohistochemistry for macrophages. Eight additional mice were kept on a high-fat diet and imaged longitudinally at the same time points. Aortic-root pseudo-concentration curves were analyzed using a validated piecewise linear model. Contrast agent wash-in and washout slopes (b1 and b2 ) were measured as surrogates of aortic root endothelial permeability and compared with macrophage density by immunohistochemistry. b2 , indicating contrast agent washout, was significantly higher in mice kept on an high-fat diet for longer periods of time (p = 0.03). Group comparison revealed significant differences between mice on a high-fat diet for 4 versus 16 weeks (p = 0.03). Macrophage density also significantly increased with diet duration (p = 0.009). Spearman correlation between b2 from DCE-MRI and macrophage density indicated a weak relationship between the two parameters (r = 0.28, p = 0.20). Validated piecewise linear modeling of the DCE-MRI data showed that the aortic root contrast agent washout rate is significantly different during disease progression. Further development of this technique from a single-slice to a 3D acquisition may enable better investigation of the relationship between in vivo imaging of endothelial permeability and atherosclerotic plaques' genetic, molecular, and cellular makeup in this important model of disease.

The combined effect of air and transportation noise pollution on atherosclerotic inflammation and risk of cardiovascular disease events.

BACKGROUND: Air pollution and noise exposures individually associate with major adverse cardiovascular events (MACE) via a mechanism involving arterial inflammation (ArtI); however, their combined impact on ArtI and MACE remains unknown. We tested whether dual (vs. one or neither) exposure associates with greater ArtI and MACE risk and whether MACE risk is mediated via ArtI. METHODS: Individuals (N = 474) without active cancer or known cardiovascular disease with clinical 18F-FDG-PET/CT imaging were followed for 5 years for MACE. ArtI was measured. Average air pollution (particulate matter ≤ 2.5 µm, PM2.5) and transportation noise exposure were determined at individual residences. Higher exposures were defined as noise > 55 dBA (World Health Organization cutoff) and PM2.5 ≥ sample median. RESULTS: At baseline, 46%, 46%, and 8% were exposed to high levels of neither, one, or both pollutants; 39 experienced MACE over a median 4.1 years. Exposure to an increasing number of pollutants associated with higher ArtI (standardized ß [95% CI: .195 [.052, .339], P = .008) and MACE (HR [95% CI]: 2.897 [1.818-4.615], P < .001). In path analysis, ArtI partially mediated the relationship between pollutant exposures and MACE (P < .05). CONCLUSION: Air pollution and transportation noise exposures contribute incrementally to ArtI and MACE. The mechanism linking dual exposure to MACE involves ArtI.

Targeting Trained Innate Immunity With Nanobiologics to Treat Cardiovascular Disease.

[Figure: see text].

Scan-rescan measurement repeatability of 18F-FDG PET/MR imaging of vascular inflammation.

Non-invasive positron emission tomography (PET) of vascular inflammation and atherosclerotic plaque by identifying increased uptake of 18F-fluordeoxyglucose (18F-FDG) is a powerful tool for monitoring disease activity, progression, and its response to therapy. 18F-FDG PET/computed tomography (PET/CT) of the aorta and carotid arteries has become widely used to assess changes in inflammation in clinical trials. However, the recent advent of hybrid PET/magnetic resonance (PET/MR) scanners has advantages for vascular imaging due to the reduction in radiation exposure and improved soft tissue contrast of MR compared to CT. Important for research and clinical use is an understanding of the scan-rescan repeatability of the PET measurement. While this has been studied for PET/CT, no data is currently available for vascular PET/MR imaging. In this study, we determined the scan-rescan measurement repeatability of 18F-FDG PET/MR in the aorta and carotid arteries was less than 5%, comparable to similar findings for 18F-FDG PET/CT.

18F-fluoride PET/MR in cardiac amyloid: A comparison study with aortic stenosis and age- and sex-matched controls.

OBJECTIVES: Cardiac MR is widely used to diagnose cardiac amyloid, but cannot differentiate AL and ATTR subtypes: an important distinction given their differing treatments and prognoses. We used PET/MR imaging to quantify myocardial uptake of 18F-fluoride in ATTR and AL amyloid patients, as well as participants with aortic stenosis and age/sex-matched controls. METHODS: In this prospective multicenter study, patients were recruited in Edinburgh and New York and underwent 18F-fluoride PET/MR imaging. Standardized volumes of interest were drawn in the septum and areas of late gadolinium enhancement to derive myocardial standardized uptake values (SUV) and tissue-to-background ratio (TBRMEAN) after correction for blood pool activity in the right atrium. RESULTS: 53 patients were scanned: 18 with cardiac amyloid (10 ATTR and 8 AL), 13 controls, and 22 with aortic stenosis. No differences in myocardial TBR values were observed between participants scanned in Edinburgh and New York. Mean myocardial TBRMEAN values in ATTR amyloid (1.13 ± 0.16) were higher than controls (0.84 ± 0.11, P = .0006), aortic stenosis (0.73 ± 0.12, P < .0001), and those with AL amyloid (0.96 ± 0.08, P = .01). TBRMEAN values within areas of late gadolinium enhancement provided discrimination between patients with ATTR (1.36 ± 0.23) and all other groups (e.g., AL [1.06 ± 0.07, P = .003]). A TBRMEAN threshold >1.14 in areas of LGE demonstrated 100% sensitivity (CI 72.25 to 100%) and 100% specificity (CI 67.56 to 100%) for ATTR compared to AL amyloid (AUC 1, P = .0004). CONCLUSION: Quantitative 18F-fluoride PET/MR imaging can distinguish ATTR amyloid from other similar phenotypes and holds promise in improving the diagnosis of this condition.

Novel non-invasive assessment of upper airway inflammation in obstructive sleep apnea using positron emission tomography/magnetic resonance imaging.

PURPOSE: To develop a novel non-invasive technique to quantify upper airway inflammation using positron emission tomography/magnetic resonance imaging (PET/MRI) in patients with obstructive sleep apnea (OSA). METHODS: Patients with treatment naïve moderate-to-severe OSA underwent [18F]-fluoro-2-deoxy-D-glucose (FDG) PET/MRI. Three readers independently performed tracings of the pharyngeal soft tissue on MRI. Standardized uptake values (SUV) were generated from region of interest (ROI) tracings on corresponding PET images. Background SUV was measured from the sternocleidomastoid muscle. SUV and target-to-background (TBR) were compared across readers using intraclass correlation coefficient (ICC) analyses. SUV from individual image slices were compared between each reader using Bland-Altman plots and Pearson correlation coefficients. All tracings were repeated by one reader for assessment of intra-reader reliability. RESULTS: Five participants completed our imaging protocol and analysis. Median age, body mass index, and apnea-hypopnea index were 41 years (IQR 40.5-68.5), 32.7 kg/m2 (IQR 28.1-38.1), and 30.7 event per hour (IQR 19.5-48.1), respectively. The highest metabolic activity regions were consistently localized to palatine or lingual tonsil adjacent mucosa. Twenty-five ICC met criteria for excellent agreement. The remaining three were TBR measurements which met criteria for good agreement. Head-to-head comparisons revealed strong correlation between each reader. CONCLUSIONS: Our novel imaging technique demonstrated reliable quantification of upper airway FDG avidity. This technology has implications for future work exploring local airway inflammation in individuals with OSA and exposure to pollutants. It may also serve as an assessment tool for response to OSA therapies.