Brigham And Women'S Hospital

NIH Research Projects · FY 2025 · 2023-07

ABSTRACT In a recent study published in Nature Nanotechnology, we demonstrated that cancer cells form physical nanoscales tentacles (nanotubes) to connect with and harvest mitochondria from immune cells. Such mitochondria hijacking metabolically depleted the immune cells and augmented the cancer cells. These findings have significant implications as it emerges as a novel mechanism of immune evasion by cancer cells, which can limit the efficacy of immune checkpoint inhibitors. Here we propose to develop next- generation immunotherapies that can perturb this novel immune evasion phenomenon. We are specifically developing novel small molecule inhibitors of the exocyst complex, which we have implicated in the above phenomenon. Our preliminary results show that such small molecules can exert a powerful antitumor efficacy, augment classical immune checkpoint inhibitors and display an excellent safety profile. In Aim 1. We will synthesize and characterize exocyst inhibitors in vitro to test the hypothesis that rationally designed small molecule inhibitors of the exocyst complex can inhibit nanotube assembly. In Aim. 2. We will establish the safety pharmacology of exocyst inhibitors in vivo. In Aim 3, we will test the hypothesis that exocyst inhibitors can improve antitumor outcomes with immune checkpoint inhibitors. Achieving these aims will lead to fundamental insights into a new mechanism of cancer-immune cell communication. Our preliminary results indicate exocyst inhibitors can emerge as a new class of immunotherapy.

NIH Research Projects · FY 2024 · 2023-07

Since the onset of the COVID-19 pandemic, the practice of “boarding” patients admitted to the hospital in the Emergency Department (ED) has reached unprecedented levels. For critically ill patients including those with acute decompensated heart failure (ADHF), ED boarding worsens outcomes as patients spend hours in the ED waiting to be transferred to the appropriate inpatient ward for specialized care. Given the unabated increase in ED boarding, length of ED stay, and subsequent time to specialist evaluation and management, developing new technologies to enable rapid reassessment of ADHF patients during these protracted ED stays is critical for improved care and patient outcomes. In a typical workflow in the Emergency Department, physicians perform bedside lung ultrasound once, at time of initial patient presentation, and use the presence or absence of ‘B- Lines’ in the images as a biomarker for pulmonary congestion. Often assessed by ED physicians in a binary manner, the presence of B-lines is used in conjunction with a clinical exam and blood tests to rule in acute ADHF. While detecting B-lines can be as easy as looking at two lung zones to make a clinical decision of ADHF, counting B-lines requires both skill and training in B-line identification, and in aggregating B-line counts over 8+ lung zones for accuracy. For a busy ED physician this is prohibitive given constraints on time, training, and cognitive load. To ease this problem, ED physicians need tools that can automatically count and aggregate the B-lines to quantify the severity of the congestion. Without this automation, it is entirely possible that either suboptimal or even no treatment will be initiated for ADHF patients in the ED leading to increased hospital length of stay, further perpetuating the ED boarding. The creation of tools for automatic quantification has the potential to enable workflows with reassessment to meet the changing patient care needs. Our long-term goals are to develop computational tools that mitigate the operator-dependence endemic to ultrasound image acquisition and interpretation. The objective of this Trailblazer R21 application is to develop and validate computational methods for quantifying pulmonary congestion from bedside lung ultrasound in the ED, which will be achieved by (1) developing and evaluating explainable tools for automated quantification of pulmonary congestion using retrospective lung ultrasound data and (2) validating the performance of the trained models in a workflow demonstrated by a prospective observational study in which patients presenting to the ED with ADHF will be assessed with lung ultrasound both pre-and post-therapeutic intervention, and findings typically used to measure pulmonary congestion on inpatient services will be recorded for both time points.

NIH Research Projects · FY 2026 · 2023-07

Hospital Systems Serving Health Disparity Populations (HSSHDPs) deliver needed services to racial and ethnic minority groups and other communities. HSSHDPs may experience long-term effects of natural and man-made disasters that in turn could affect health outcomes. Using the framework of the disaster management cycle (mitigation, preparedness, response, and recovery), this project proposes to conduct a mixed methods study of the long-term effects of pandemics on US hospitals across four critical domains (quality, workforce, finances, and innovation), with a special focus on HSSHDPs and on the health disparity populations they serve. This project will be the first major national investigation of the effects of national disasters on HSSHDPs. This rigorous mixed methods study will be significant in identifying HSSDHPS most and least affected by pandemics and will deepen the understanding of the contributing factors that led to successes and challenges. The study will identify actionable best practices and challenges to HSSHDPs’ operations before, during and after pandemics. The specific aims of this study are: Aim 1. Describe the long-term effects of pandemics on hospitals and the perceived usefulness of disaster management planning activities (including interactions with Coalitions). In partnership with the American Hospital Association and America’s Essential Hospitals a nationally representative survey of 2000 hospitals will be conducted to examine variation by HSSHDP status and other characteristics. Aim 2. Analyze changes over time (2018-2024) in hospital-level quality, service levels, and finances, and in patient-level outcomes. Using secondary data sources, the study will focus on differences among HSSHDPs and non-HSSHDPs. Aim 3. Explore the innovations undertaken by HSSHDPs to mitigate the effects of pandemics. The study will include 10 in-depth case studies, using purposive sampling to select HSSHDPs and non-HSSHDPs. Semi-structured interviews with stakeholders will be used to more fully understand existing structures, challenges, interactions with Coalitions, and other disaster management strategies. Aim 4. Develop prioritized policy recommendations to enhance resilience of our most critical public health systems for future disasters. A national Delphi consensus panel in conjunction with the National Academy of Science Engineering and Medicine will be conducted.

NIH Research Projects · FY 2025 · 2023-07

PROJECT SUMMARY Tumor cells and infiltrating immune cells co-evolve during the course of tumor progression, with the immune system progressively losing its efficacy as tumors advance. Immune cells are highly dependent on cellular metabolism to manifest their effector functions, but in the tumor microenvironment (TME), ‘metabolic competition’ with rapidly proliferating cancer cells leads to nutrient deprivation alongside increased metabolic waste, both of which negatively impact immune cell function. Moreover, ‘metabolic symbiosis’ between cancer and immune cells can promote the acquisition of suppressive immune cell phenotypes, ultimately disfavoring anti-tumor immunity. These dynamic metabolic interactions are shaped by the niches occupied by cells within the TME. Thus, the metabolic cross talk between tumor and immune cells over the course of tumor progression can be a major determinant of immune cell function and, consequently, response to immune-targeted therapies. Unfortunately, the study of immune cell metabolism and crosstalk in the TME has been very challenging due to reliance on methods that analyze metabolism in bulk cell populations, which obscures individual cellular diversity, difficulties in predicting downstream outcomes of metabolic perturbations because of the complexity of the metabolic network, and the lack of tools to map metabolic alterations in situ. To overcome these challenges, we developed Compass, a flux balance analysis (FBA) algorithm that applies a network-based analytical approach to single-cell RNA-sequencing (scRNA-seq) data to predict metabolic states of individual cells in tissue1. We have applied Compass as well as standard computational methods to the analysis of longitudinal scRNA-seq data from a pre-clinical murine model of melanoma with the goal of determining the temporal- and tumor-size- based metabolic alterations in both tumor and infiltrating immune cells during tumor progression. Our preliminary data indicate that polyamine metabolism is a key hub of metabolic crosstalk between tumor and immune cells that are either static or dynamic over the course of melanoma tumor progression and that may occupy distinct tissue niches. We find that CD4+ regulatory T cells (Treg), exhausted CD8+ T cells, and suppressive myeloid cells upregulate spermine/spermidine acetyltransferase (Sat1), which catalyzes acetylation of polyamines, with tumor progression. Conversely, a subset of c-Met+ melanoma cells that has features of stemness is high for polyamine recycling genes. Based on these observations, we hypothesize that that systems-based analysis of the alterations and crosstalk involving polyamine metabolism in tumor and immune cells during tumor progression will uncover novel means for therapeutic intervention. We propose to: 1) Dissect the functional role of polyamine metabolism in immune cells and tumor cells during tumor progression; 2) Construct a high resolution spatial map of tumor:immune metabolic crosstalk via the polyamine pathway.

NIH Research Projects · FY 2025 · 2023-07

Antibody-mediated rejection (AMR) in kidney transplantation remains a major cause of kidney graft loss and a critical hurdle to improve long term allograft survival, with no approved therapy. Antibody responses are tightly controlled through T follicular helper (Tfh) cells. Understanding the role of Tfh in kidney transplant and developing clinically translatable strategies to control AMR holds promise to improve long term outcomes. Our group has identified that Qa-1(HLA-E in human) restricted CD8 Tregs are critical regulators of Tfh, the key modulators of B cell differentiation in the germinal center (GC) in kidney transplantation. CD8 Tregs are confined to <5% of CD8 T cells that express a triad of surface receptors– CD44, CD122 and Ly49. Our recently published data (Choi et al. PNAS, Dec 2020) and preliminary data describe a novel role for CD8 Treg in regulating Tfh in allo-immunity. These CD8 Tregs express T cell receptors (TCRs) that recognize Qa-1, a non-classical class-Ib MHC molecule with limited polymorphism. We show that alloreactive activated CD4 T cells, especially Tfh, upregulate their Qa-1 expression, making them a target for CD8 Treg suppression. Disrupting the peptide Qa-1 (pQa-1)-TCR interaction via a point mutation in the Qa-1 gene while sparing the binding of pQa-1 to the inhibitory NKG2A receptor on CD8 Treg leads to the uncontrolled proliferation of Tfh, B Cell maturation, increased donor specific antibodies (DSA), increased allograft complement activation, and accelerated allograft rejection. Our preliminary data show that mobilization and activation of CD8 Treg by specific peptide FL9 agonists dampen Tfh-dependent anti-graft Ab-mediated injury and prolong fully mismatched kidney allograft survival. Since HLA-E and Qa-1 are expressed as only 1 of 2 alleles, this approach is applicable to large groups of patients and avoids the problems of MHC class Ia diversity. The clinical feasibility of FL9 peptide therapy to AMR has high translational potential in AMR and highlights the significance of this approach. Our hypothesis is that during alloimmune T cell activation in kidney transplantation, alloreactive T cells, primarily Tfh, upregulate Qa-1- stress peptide complexes, mostly FL9 on their surface, allowing tight control by Qa1 restricted CD8 Treg. Furthermore, LY49 expressed on CD8 Treg serve as a coinhibitory signal. Identifying peptides critical for the control of alloreactive T cells by antigen specific CD8 Tregs and the positive and negative signals critical for their function will lead to novel targeted therapeutic strategies in allo-immunity and will be investigated here. To test our hypothesis, we developed multiple new tools that are unique to our group. We generated super agonists for the stress peptides to optimize in vivo CD8 Tregs expansion. We also generated a new transgenic mouse where CD8 T cells express TCR that specifically recognize FL9-Qa1 peptide complex. While LY49 may have inhibitory function on CD8 Tregs, we will study its role in allo-immunity through a newly generated knockout mouse and blocking antibodies developed in our laboratory. We will test this hypothesis in murine kidney transpant model that leads to cellular and antibody mediated rejection similar to human rejection.

NIH Research Projects · FY 2025 · 2023-07

Abstract The broad goal of this project is to determine whether shifting the temporal distribution of macronutrient intake impacts metabolic markers of health, which holds great translational value for vulnerable populations, including night shift workers. Night work is increasingly prevalent and a risk factor for type 2 diabetes (T2D). We and others have shown that circadian misalignment itself, i.e., the misalignment between the eating/fasting cycle and the central circadian timing system, leads to impaired glucose tolerance and decreased insulin sensitivity, even in chronic shift workers. Circadian misalignment is thus a likely mechanism contributing to the increased T2D risk in night workers. Because night work is not likely to go away anytime soon, countermeasures against these adverse metabolic effects are desperately needed. Our preliminary data from stringently-controlled circadian experiments suggests that glucose tolerance, beta-cell function, and diet-induced thermogenesis are increased in the circadian morning compared to the circadian evening, and that—in contrast—fat tolerance is increased in the circadian evening compared to the circadian morning. Based on these insights, we have developed a novel and translational approach that combines the concepts of the importance of WHAT we eat with the importance of WHEN we eat: scheduling high-carb intake for the circadian morning and high-fat intake for the circadian evening (C/F; expected to be favorable) as compared to vice versa (F/C, high-fat for circadian morning and high-carb for circadian evening), without changing 24-h caloric or macronutrient intake. Using two highly-controlled, within-subject, randomized, crossover protocols (one under circadian alignment, one under circadian misalignment), we will test the hypotheses that high-carb intake during the biological morning and high-fat intake during the biological evening (C-F) compared to vice versa (F-C) leads to: higher glucose tolerance (Aim 1); higher diet-induced thermogenesis (Aim 2); and higher fat tolerance (Exploratory Aim 3). We will test these aims in a robust and sophisticated study design: (1) without disturbing sleep during the day; (2) without requiring extended fasting during wakefulness at night; (3) without changing the caloric content per meal; and (4) without changing 24-h caloric or 24-h macronutrient intake. Knowledge on the health impacts of macronutrient intake timing is not only important for shift workers but also for the general population. Therefore, these questions will not only be addressed under circadian misalignment but also circadian alignment.

NIH Research Projects · FY 2025 · 2023-07

PROJECT SUMMARY Multiple Sclerosis (MS) is an autoimmune disease of the central nervous system (CNS) that constitutes the leading cause of neurologic disability in young adults. Astrocytes, microglia and monocytes play important roles in MS and its model, experimental autoimmune encephalomyelitis (EAE), but the mechanisms that regulate their activity are poorly understood. The study of astrocyte and microglia regulation may identify mechanisms of pathogenesis and therapeutic targets in MS, particularly for the progressive phase of the disease. Our long-term goal is to develop therapies to limit astrocyte pathogenic activities in MS. During the course of our studies we made the following preliminary observations: 1) SigmaR1-IRE1a signaling activates the transcription factor XBP1 in astrocytes, promoting microglial activation, monocyte recruitment to the CNS and disease pathology during EAE; 2) Astrocyte-specific XBP1 knockdown ameliorates EAE; 3) XBP1 is activated in an astrocyte subset in EAE and MS; 4) XBP1 activation in astrocytes is associated to increased VEGF-B signaling 5) Microglia and CNS-recruited monocytes produce VEGF-B during EAE; and 6) VEGF-B produced by microglia boost astrocyte pro-inflammatory activities. We hypothesize that active XBP1 (XBP1s) drives a pathogenic astrocyte subset (XBP1s+ astrocytes) in MS and EAE, which is controlled by microglia- and monocyte-produced VEGF-B. Thus, we propose to study the role of SigmaR1-IRE1a-XBP1 signaling in astrocytes in EAE and MS, and its potential as a therapeutic target. Our specific aims are: SPECIFIC AIM 1: Does XBP1 activation define a subset of pathogenic astrocytes? We propose to: 1) Characterize XBP1s+ astrocytes in EAE using Focused Interrogation of cells by Nucleic acid Detection and Sequencing (FIND-seq) a method, which we developed to study cell subsets in-depth, and 2) Generate a spatiotemporal map of the localization, regulation and cell interactions of XBP1s+ astrocytes and other cell subsets in EAE and MS using MERFISH (Multiplexed error robust fluorescence in situ hybridization). SPECIFIC AIM 2: How do microglia and monocytes control XBP1s+ astrocytes? We propose to: 1) Define the role of VEGF-B produced by microglia and monocytes on the control of XBP1s+ and other astrocyte subsets during EAE, and 2) Identify by NICHE-seq additional pathways involved in the control of XBP1s+ and other astrocyte subsets by microglia and monocytes during EAE. SPECIFIC AIM 3: Is SigmaR1 a therapeutic target to modulate CNS inflammation? We propose to: 1) Evaluate the therapeutic value of the clinical-grade CNS penetrant SigmaR1 antagonist S1RA on EAE, and 2) Define the effects of S1RA on XBP1s+ astrocytes, and other cell subsets in the CNS in EAE. IN SUMMARY, this project studies a novel astrocyte subset, the molecular and cellular mechanisms that control it, its distribution and cell interactions throughout the CNS, and its potential as a therapeutic target in MS.

NIH Research Projects · FY 2024 · 2023-07

Project Summary Diffusion MRI (dMRI) is a leading in-vivo imaging methodology for investigating subtle microstructural changes in the brain’s white matter, which often requires multi-site collaborations for data collection. Decentralized processing approaches are becoming the preferred approach for multi-site data collection because they support improved personal data protection and are scalable. Using a decentralized approach, The Enhancing Neuro Imaging Genetics through Meta Analysis (ENIGMA) studies produced seminal findings across different disorders. However, the dMRI pipeline established for decentralized ENIGMA dMRI studies is not automatic, not user friendly, and requires each site to have strong programming and dMRI expertise, which is not the case in many clinical sites. The goal of this project is to help alleviate the site-level technical burdens, which would promote decentralized studies by enabling the addition of more sites. Decentralized multi-site studies are needed for rigorous and statistically robust identification of subtle neurological changes, but the technical difficulties which make decentralized dMRI analysis highly resource- intensive, are impeding research sites from participating. The technical difficulties include the installation of multiple software tools and their software dependencies, analysis instructions that include multiple scripting steps that are hard to follow for novice users, and quality control (QC) steps that require expertise in dMRI. The central goal of this application is to develop a user-friendly dMRI analysis platform for decentralized studies which will facilitate the processing and QC by pursuing two specific aims: 1) develop an automated dMRI processing pipeline with extensive data QC steps; and 2) provide dashboard function and containerize the pipeline. Under the first aim, various neuroimaging and image processing utilities will be linked together to automatize the dMRI processing pipeline while estimating extensive QC measures, which will be curated for non-dMRI experts to help intuitively understand the data quality. For the second aim, a web-server will be developed to provide a dashboard that is used to interact with the pipeline and visualize the outputs. Also, all the components will be containerized as a single package for easier dissemination and deployment using docker. The innovative approaches proposed in this application will simplify the dMRI analysis, enable optimal user experience requiring minimal manual user-interventions in the installation and operation of the containerized pipeline, and will facilitate a dashboard for intuitive user interaction. Our new and substantively different approach is significant because it is expected to resolve much of the technical burden impeding the collaborative investigation of brain changes in a decentralized approach, encouraging more sites to participate in multi-site dMRI studies.

NIH Research Projects · FY 2025 · 2023-07

PROJECT SUMMARY Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease that causes obstructed airflow from the lungs. As a common complex disease, COPD has high global morbidity and mortality. Indeed, deaths due to respiratory disease numbered nearly four million, which was mostly contributed by COPD. There is a clear demand to improve our understanding of COPD pathogenesis and develop interventions to prevent and treat COPD. Yet, a complex disease phenotype is usually determined by various pathobiological processes that interact in a network, rather than induced by the abnormality in a single effector gene product. Extensive evidence implies that disease-associated proteins have distinct interactions within the human protein-protein interaction (PPI) network (a.k.a. the human interactome), and the pathobiological processes of a complex disease are associated with perturbation within specific disease neighborhoods of the interactome, often referred to as the disease module. Comprehensive understanding of the COPD pathogenesis and predicting disease genes to inform therapeutic treatment require advanced tools to identify its disease module. Although many disease module detection methods have been reported in the literature, they all have fundamental limitations. More importantly, existing methods do not fully leverage the advantage of multi-omics data. In this application, a statistical physics and network-based framework will be developed to detect disease modules for complex human diseases using multi-omics data. This framework will be systematically validated with synthetic data. Then it will be applied to the rich multi-omics data (SNP genotyping, DNA methylation, mRNA and miRNA expression) in two large COPD cohorts. Dr. Wang’s training in statistical physics, network science and deep learning have prepared him well for his proposed research. However, understanding and interpreting the molecular basis of complex diseases and the statistical analysis of multi-omics data are still arduous tasks that will require further training in specific areas. Dr. Wang will leverage the excellent intellectual environment of Harvard Medical School and its teaching hospitals and will have access to extensive computational resources through the Channing Division of Network Medicine and Harvard Medical School. Through the guidance of a mentoring and advisory team with complementary expertise, together with formal coursework and workshops, Dr. Wang will immerse himself in a training program focusing on statistical genetics, epigenetics, multi-omics integration, and the biology of pulmonary diseases. Dr. Wang will also participate in regular meetings with his mentors and advisory committee members, allowing him to share his progress and receive timely feedback. Altogether, Dr. Wang’s training and research plan will enable him to expand his current skillset to include the ability to address the challenges of analyzing the complex genomic and epigenomic data of large epidemiological cohorts, identify open questions in the systems biology of COPD, and ultimately contribute to the precision medicine of lung diseases.

NIH Research Projects · FY 2026 · 2023-07

About 80% of Americans experience periodontitis in their lifetime. Alveolar bone loss leads to loosening or loss of teeth or dental implants that disrupts the most basic daily functions, such as eating and speaking. Various bone grafts are being used to restore alveolar bone loss, but poor prognosis remains a long-standing problem. Autografts are considered the gold standard, but these grafts exhibit significant volume loss in inflammatory conditions. The available amount of material for autografts is limited, and surgical harvesting procedures are often complex and associated with morbidity, pain, and infection at the donor site. Allografts and xenografts have less bone formation capacity than autografts, while they are also associated with risks of infection, disease transmission, and immunological rejection by the host. Synthetic bone grafts such as hydroxyapatite (HAP) and beta-tricalcium phosphate (β-TCP) have also been widely used, mostly in granule or block form. However, none of the existing synthetic bone graft materials exhibit sufficient bone formation capacity to restore inflammatory alveolar bone loss to pre-disease levels. There is a significant unmet medical need for the development of a next-generation bone implant that can effectively regenerate alveolar bone in chronic inflammatory conditions. Alveolar bone almost never spontaneously regenerates in the presence of chronic inflammation. Excess inflammation destroys tissues and supports the growth of pathogens leading to the realization that effective control of microbiome dysbiosis in periodontitis cannot be achieved without effective control of inflammation. Inflammation can be resolved by specialized pro-resolving lipid mediators (SPMs) that can rapidly restore tissue homeostasis to stop the negative feedback loop of infection-inflammation and boost bone regeneration. SPMs effectively regulate inflammation in utero through early childhood, but their production and effectiveness diminish with age. In many instances, chronic inflammatory diseases such as periodontitis are associated with a failure of natural resolution pathways. Here, we aim to develop an innovative 3D printed customized biomimetic and immunomodulatory alveolar bone implant that can provide targeted key biological factors for inflammation modulation and bone regeneration. We will use whitlockite (WH) nanoparticles, the second most abundant bone mineral in humans with excellent bone formation capacity, to develop SPM-delivering bone-mimetic ink material for 3D printing a customized, personalized bone implant that can stably fit into alveolar bone defects to effectively resolve inflammation and boost bone regeneration. During this research project, we will establish a novel bioengineering process for preparing this innovative alveolar bone implant that can later be used by clinicians. The therapeutic effectiveness of the SPM-delivering bone-mimetic implant will be evaluated in a periodontitis model with alveolar bone loss. We envisage that the proposed biomimetic immunomodulatory 3D printed bone implant will significantly improve alveolar bone regeneration in severe inflammatory periodontitis or peri- implantitis and lead to a breakthrough in the treatment of non-healing inflammatory skeletal defects.

NIH Research Projects · FY 2025 · 2023-07

PROJECT SUMMARY/ABSTRACT There is a critical need for effective pharmacotherapy for the management of non-alcoholic fatty liver disease (NAFLD). The proposed research is to conduct early-stage preclinical validation of new therapeutic leads that target thioesterase superfamily member 1 (Them1; synonym Acyl-CoA thioesterase 11), a key enzyme of fatty acid metabolism that becomes maladaptive in NAFLD. The long-term goal is to develop inhibitors of Them1 as a therapeutic modality in the management of human NAFLD. The objective of this research is to optimize the drug-like properties of small molecule inhibitors in order to create lead compounds, and to demonstrate their safety, efficacy and specificity in cell-based assays and in experimental NAFLD using mice. Targeting Them1 with optimized small molecule inhibitors is expected to mitigate NAFLD by: 1) Increasing energy expenditure in thermogenic brown and beige adipose tissue; 2) Decreasing hepatic steatosis, as well as glucose production by the liver; and 3) Reducing inflammation in white adipose tissue. The rationale is that a lead compound that addresses these three independent pathogenic contributions of Them1 should prove effective in NAFLD. We have completed a high-throughput small molecule screen that has identified promising inhibitors targeting the fatty acyl-CoA thioesterase activity of Them1. Motivated by extensive mechanistic data on the contributions of Them1 to NAFLD pathogenesis, the development of inhibitors into lead compounds will be accomplished in three specific aims: 1) To optimize the potency and specificity of Them1 small molecule inhibitors; 2) To establish drug-like properties and efficacy in cell culture of early lead compounds; and 3) To evaluate therapeutic lead compounds in experimental NAFLD using mice. In Aim 1, small molecule inhibitors will be optimized by medicinal chemistry strategies to improve potency, specificity and drug-like properties. These efforts will be guided by structure-activity relationships based on in vitro enzymatic assays, as well as biophysical and structural determinants of Them1-inhibitor interactions. Aim 2 will evaluate early lead compounds for drug-like properties, as well as cytotoxicity. Selected early leads will then be tested for efficacy in primary cultured mouse and human cells for their capacities to increase fatty acid oxidation in brown adipocytes and hepatocytes, to reduce hepatic glucose production in hepatocytes and to decrease production of inflammatory mediators by white adipocytes. Specificity will be assessed using cells cultured from Them1-/- mice. In Aim 3, lead compounds will be tested in mice for pharmacokinetics and tolerability. Upon establishing dosing routes and schedules, efficacy to prevent and to reverse NAFLD will be assessed in mouse models. Off-target effects will be evaluated using Them1-/- mice. The expected outcome of these studies is the development and pre-clinical validation of optimized lead Them1 inhibitors that leverage novel mechanisms of energy homeostasis, fatty acid and glucose metabolism, as well as inflammation in the medical management of NAFLD.

NIH Research Projects · FY 2025 · 2023-07

Contemporary new technologies such as optogenetics and single cell genomics show that electrically active neurons stimulate growth of adult and pediatric gliomas. Conversely, cancers and cancer therapies alter nervous system form and function (e.g., cancer therapy-related cognitive impairment colloquially known as “chemobrain” or “chemofog”). The two-way dialogue between tumors and the nervous system defines an emerging new scientific discipline termed “Cancer Neuroscience”. The Department of Neurology at Brigham and Women’s Hospital (BWH), together with the Department of Neurobiology at Harvard Medical School (HMS), propose an integrative, first-in-kind postdoctoral training program in this new field. The Program will be co-led by a clinician scientist, Tracy Batchelor, M.D. (Chair of Neurology at BWH) and a basic scientist Michael Greenberg, Ph.D. (co-director, Harvard Brain Science Initiative). A faculty of 29 mentors will be drawn from the Dana-Farber/Harvard Cancer Center and from the Harvard Brain Science Initiative. This will be a basic science program. Candidates with Ph.D. and/or M.D. degrees will be eligible but there will be no clinical training. We request support for 6 postdoctoral fellows per year to serve 2-year appointments. The Program will foster both scientific development and professional development of these trainees. For Scientific Development, the Program will bring doctorate level basic scientists with skill sets in neural development, electrophysiology, neural circuitry, optogenetics, brain metabolism and neurochemistry into the laboratories of clinical/translational investigators working on primary and also metastatic cancers of the brain. For laboratory research, fellows will be taught to identify important questions and approaches that will move the field forward and provide translational opportunities to impact cancer treatment. For professional development, we will provide trainees with (i) opportunities to refine and enhance their grantsmanship and scientific communication skills; (ii) individual Development Plans; (iii) individual postdoctoral mentoring committees, and (iv) customized opportunities for trainees to acquire experience in mentoring and teaching depending on their career goals. The program Director and co-Director will work closely with a Training Oversight Committee and an External Advisory Board. Collaborative relationships with academic institutions will help support trainee recruitment and program development. Strategies to measure trainee satisfaction, track outcomes, and evaluate program effectiveness will include annual surveys from trainees and mentors, as well as exit and alumni interviews. Institutional resources and funding will support training activities and annual advisory meetings.

NIH Research Projects · FY 2026 · 2023-07

Summary Genome wide associations studies (GWAS) have produced a multitude of candidate genes and loci for a wide range of complex disease and phenotypic traits, but often have not resulted in sufficient mechanistic insight to lead to actionable changes in prevention, diagnosis, or treatment of disease. This is a consequence of key attributes of the underlying genetic effects which can prove difficult to model, specifically: combinatorial interactions between multiple loci, a preponderance of regulatory effects which may act at different times and in in different tissues or organs, and the integration of lifelong multidimensional risk in many of the mapped disease traits. As the field evolves, so other contributions have begun to be recognized at specific loci including; modification of the effects of existing Mendelian genes, more complex gene-gene or gene-environment interactions and a role for somatic variation contributing to diverse chronic diseases. We have successfully overcome these challenges in our existing Zebrafish GWAS Community Resource by creating a pipeline which exploits the strengths of rapid scalability, functional relevance and genomic conservation of the zebrafish model system to generate useful functional annotation of over 100 genes and regulatory loci over the last 7 years. We have defined the disease gene(s) for multiple GWAS loci in parallel and moved the field forward to early mechanistic studies. We now propose to extend this Community Resource, continuing our existing activities while adding key capabilities in a) modeling gene-gene and gene environment interactions to further explore the complex genetics of numerous common diseases and the b) definitive modeling of somatic variation including efficient transplantation studies to fully understand the role of somatic variation in disease. These new capabilities also directly address ongoing requests from the human genetics community for which the resource was originally developed. As a consortium, we will continue to push forward the capabilities of the zebrafish as a model organism in this field and as costs drop, the number of diseases/loci that we will be able to functionally annotate will only grow through the duration of the proposal. Importantly, we will be able to deliver a comprehensive package of annotated candidate genes and interactions back to our collaborators in the human genetics community to enhance the impact and insight derived from their studies. For this renewal application, we propose the following Specific Aims: Aim 1 - Functionally analyze loci from multiple GWAS studies on blood, liver, heart and vessel traits, optimizing assay development and gene editing using CRISPR-Cas9 technology in zebrafish. Aim 2 - Quantitatively characterize gene-gene and gene-environment interactions where these have been implicated in human genetics Aim 3 - Modeling the role of somatic variation at GWAS loci in chronic disease

NIH Research Projects · FY 2026 · 2023-06

In this 5-year R01 project titled “Mapping of the intrinsic and extrinsic cerebellar connectome at ultra high resolution with expert neuroanatomical curation,” we propose to create the first detailed atlas of the human cerebellar connectome using sub-millimeter ultra-high-resolution diffusion MRI (dMRI). The human cerebellar connectome is affected in multiple conditions including autism, schizophrenia, Down's syndrome, Alzheimer's disease, Parkinson's disease, cerebellar mutism, and neurodegeneration. The complex anatomy of the cerebellar structural connectome includes intricate connections between the tightly foliated cerebellar cortex, the deep cerebellar nuclei, and structures external to the cerebellum including the spinal cord, brainstem, thalamus, and cerebral cortex. Remarkably, the cerebellum contains 80% of all neurons in the brain. Yet, a complete map of the intrinsic and extrinsic structural connectome of the human cerebellum is still lacking. Several challenges have prevented detailed mapping of the cerebellar structural connectome. First, the limited spatial resolution of current state-of-the-art dMRI data prevents mapping of intricate connections between the cerebellar cortex and small nuclei in the deep cerebellum, brainstem, and thalamus. Second, cerebellar connectome mapping is further limited by abundant anatomical errors in existing dMRI tractography algorithms, which do not respect known synapses and decussations or key nuclei. Third, our understanding of human neuroanatomy relies heavily on the results of invasive tracer studies in monkeys, but the detailed neuroanatomy of the cerebellar connectome in monkeys has not yet been systematically mined and compiled. We propose to address these challenges to create the most comprehensive description of the cerebellar connectome to date. Our strategy includes fast and distortion-free ultra-high-resolution dMRI acquisitions, novel anatomically constrained and curated cerebellar tractography, deep learning joint parcellation of fibers and nuclei for fine-grained atlasing, and expert neuroanatomical generation of the intrinsic and extrinsic cerebellar connectivity matrices from non-human primate tracer studies. Overall, these steps will enable robust in-vivo tracing of the cerebellar connectome of the human brain at an unprecedented spatial resolution. Our final deliverable will be a comprehensive, anatomically curated atlas of the human cerebellar connectome, which will enable the study of the cerebellar connectome in health and disease. We will publicly release the atlas, the monkey connectivity matrices, all extracted fascicles, all acquired images, and all software as open source.

NIH Research Projects · FY 2025 · 2023-06

In this 5-year R01 project titled “Mapping of the intrinsic and extrinsic cerebellar connectome at ultra high resolution with expert neuroanatomical curation,” we propose to create the first detailed atlas of the human cerebellar connectome using sub-millimeter ultra-high-resolution diffusion MRI (dMRI). The human cerebellar connectome is affected in multiple conditions including autism, schizophrenia, Down's syndrome, Alzheimer's disease, Parkinson's disease, cerebellar mutism, and neurodegeneration. The complex anatomy of the cerebellar structural connectome includes intricate connections between the tightly foliated cerebellar cortex, the deep cerebellar nuclei, and structures external to the cerebellum including the spinal cord, brainstem, thalamus, and cerebral cortex. Remarkably, the cerebellum contains 80% of all neurons in the brain. Yet, a complete map of the intrinsic and extrinsic structural connectome of the human cerebellum is still lacking. Several challenges have prevented detailed mapping of the cerebellar structural connectome. First, the limited spatial resolution of current state-of-the-art dMRI data prevents mapping of intricate connections between the cerebellar cortex and small nuclei in the deep cerebellum, brainstem, and thalamus. Second, cerebellar connectome mapping is further limited by abundant anatomical errors in existing dMRI tractography algorithms, which do not respect known synapses and decussations or key nuclei. Third, our understanding of human neuroanatomy relies heavily on the results of invasive tracer studies in monkeys, but the detailed neuroanatomy of the cerebellar connectome in monkeys has not yet been systematically mined and compiled. We propose to address these challenges to create the most comprehensive description of the cerebellar connectome to date. Our strategy includes fast and distortion-free ultra-high-resolution dMRI acquisitions, novel anatomically constrained and curated cerebellar tractography, deep learning joint parcellation of fibers and nuclei for fine-grained atlasing, and expert neuroanatomical generation of the intrinsic and extrinsic cerebellar connectivity matrices from non-human primate tracer studies. Overall, these steps will enable robust in-vivo tracing of the cerebellar connectome of the human brain at an unprecedented spatial resolution. Our final deliverable will be a comprehensive, anatomically curated atlas of the human cerebellar connectome, which will enable the study of the cerebellar connectome in health and disease. We will publicly release the atlas, the monkey connectivity matrices, all extracted fascicles, all acquired images, and all software as open source.

NIH Research Projects · FY 2024 · 2023-06

ABSTRACT Recent clinical success of mRNA vaccines for COVID-19 has sparked enormous interest in mRNA therapy for a wide range of biomedical applications including protein replacement therapy. However, one unique challenge associated with mRNA therapy is dealing with the transient efficacy due to its relatively short half-life. Current nanoparticles including FDA-approved lipid nanoparticles (LNPs) could significantly improve mRNA translation efficiency, but the duration of in vivo protein expression by these mRNA NPs is generally short (limited to a few days), thus requiring frequent re-dosing. The main objective of this project is to advance a new transformative LNP technology enabling long-acting mRNA replacement therapy of genetic disorders associated with loss of function of a particular protein. In our recent studies, we developed a new generation of LNPs and performed the head-to-head comparison in vitro and in vivo to the benchmark LNP formulations composed of FDA-approved ionizable lipids. We observed a dramatic increase of the duration of model protein expression in vitro and in vivo by our new mRNA LNPs. Preliminary safety studies showed that our mRNA LNPs were well tolerated without observable adverse events in vivo. With the proof-of-concept demonstration of our long-acting mRNA LNPs, this project aims to i) further optimize the mRNA LNP technology for longer-term, high level protein expression, and ii) rigorously validate this transformative mRNA delivery platform using hemophilia A as a model disease. We expect that with successful validation in normal and hemophilia A mice, this long-acting mRNA LNP platform could be readily moved into clinical testing for hemophilia and expanded to other genetic diseases that require restoration of normal protein functions.

NIH Research Projects · FY 2026 · 2023-06

PROJECT SUMMARY/ABSTRACT Traumatic injuries from burns, blasts, or major surgery dysregulates immune system function predisposing the injured people to life-threatening opportunistic infections or persistent critical illness. Targeted immunotherapies for traumatic injuries to restore immune system function and homeostasis have not yet been developed and are urgently needed. The immunophenotypic diversity in humans provides a solid justification to target evolutionarily conserved innate immunoregulatory networks that are less heterogenous for treatment. As such, the reprogramming of innate immune cells by a process called “trained immunity” is a promising concept for targeting therapeutics to reduce the morbidity and mortality from trauma-induced complications. Trained immunity can occur in short-lived innate immune cells by epigenetically modifying accessibility to immune regulatory genes in hematopoietic stem cells (HSC), which are then passed on by differentiation to innate effector cells, leaving them better poised to respond to infection. We have developed Toll-like receptor 9 (TLR9) agonists – unmethylated CpG-DNA sequences, which are naturally found in bacterial DNA and eukaryotic cell mitochondria - as immunotherapeutic medical countermeasures to promote immune system recovery after radiation and traumatic injuries. We recently discovered that mesenchymal stromal cells (MSCs), which are critical cellular residents in the bone marrow hematopoietic stem cell (HSC) niche, express high TLR9 levels, strongly react to CpG-DNA stimulation, and mediate emergency granulopoiesis responses to infection in neutropenic mice. This discovery prompted us to consider trained immunity as a central mechanism contributing to the immune protection from systemic CpG-DNA treatment in our burn trauma and infection model. Here, we address the hypothesis that TLR9 agonist therapy mediates protective immunity and restores immune homeostasis by trained immunity mechanisms involving bone marrow MSCs and HSCs. To test this hypothesis, we propose the following specific aims: 1) To delineate hematopoietic and peripheral immune consequences of trauma with CpG-DNA therapeutic intervention, 2) To identify transcriptional and epigenetic changes in bone marrow MSCs and HSCs from injured and uninjured mice treated with CpG-DNA, and 3) To generate and use chimeric mouse models to delineate injury and CpG-DNA induced trained immunity phenotypes transferred by HSCs. We anticipate that the results from this research program will provide pre-clinical mechanistic insights towards translating CpG-DNA as an immunotherapeutic strategy for trauma-induced immune dysregulation.

NIH Research Projects · FY 2025 · 2023-06

PROJECT SUMMARY / ABSTRACT Idiopathic pulmonary fibrosis (IPF) is a fatal disease characterized by excessive deposition of extracellular ma- trix. Myofibroblasts are the primary effector cells of lung fibrogenesis. Identifying molecular mechanisms medi- ating myofibroblast differentiation will increase our understanding of IPF pathobiology and identify new targets for antifibrotic therapies. Metabolic reprogramming is one such molecular mechanism essential, yet the con- nections between metabolism, myofibroblast differentiation, and pulmonary fibrosis are unknown. Our objective is to define how a new metabolic approach, lactate transporter (MCT) inhibition, prevents myofibroblast differ- entiation in vitro and in vivo. Our preliminary data implicate lactate transport in IPF pathobiology by showing increased expression of lactate transporters MCT1 and MCT4 in IPF lung explants. We show that inhibition of these transporters decreases bleomycin-induced pulmonary fibrosis and myofibroblast differentiation. Lactate transporter inhibition promotes cellular respiration and mitochondrial efficiency. Transcription factor enrichment analyses suggest that MCT inhibitors reverse TGFβ-stimulated expression of pro-fibrotic BRD4 target genes. Together, these data support our central hypothesis that lactate transport inhibition reprograms fibroblast me- tabolism to attenuate ROS production and BRD4 activation, thereby preventing myofibroblast differentiation and pulmonary fibrosis. To test this, we will pursue three specific aims: (1) Determine the metabolic conse- quences of lactate transport inhibition, (2) Determine how lactate transport inhibition alters myofibroblast gene transcription, and (3) Identify the cellular therapeutic target of lactate transport inhibitors in vivo. In Aim 1, we will test that MCT inhibition promotes cellular respiration, decreases mitochondrial membrane potential, and decreases fibrogenic ROS production using metabolic flux analyses, molecular biosensors, and novel meta- bolic manipulations. In Aim 2, we will test that decreased BRD4 activity is the novel molecular mechanism link- ing MCT inhibition and myofibroblast differentiation using a gain- and loss-of-function strategy applied to MCT and BRD4 activity coupled to ChIP-qPCR analyses of BRD4 target gene engagement and myofibroblast phe- notypic readouts. In Aim 3, we will test that MCT expression is essential for myofibroblast differentiation and pulmonary fibrosis in vivo using MCT1 and MCT4 conditional knockout animals combined with imaging mass spectrometry to interrogate fibroblast metabolism in vivo and scRNAseq to quantify fibroblast differentiation. The rationale for this work is that defining mechanistic links between metabolism, myofibroblast differentiation, and pulmonary fibrosis will advance the prospects of metabolic therapies for the treatment of IPF. The pro- posed research is innovative because it focuses on the essential role of lactate transporters in myofibroblast differentiation in IPF. The research contributions will be significant because they will establish the mechanistic basis for the efficacy of lactate transporter inhibitors in pulmonary fibrosis.

NIH Research Projects · FY 2026 · 2023-06

Summary A majority of patients with Tuberous Sclerosis Complex (TSC) develop benign kidney tumors known as renal angiomyolipoma (AML) that can cause renal insufficiency and spontaneous life-threatening hemorrhages. The main therapy for AML is everolimus, a rapamycin analog inhibitor of the kinase mTOR with cytostatic activity that only partially reduces tumor size. AMLs become stable over time, and tumor re-growth is often occurs after treatment is interrupted due to side effects. Therefore, there is an urgent need to elucidate mechanisms of tumor resistance for the development of more efficacious therapies. Efforts to recapitulate AML experimentally have failed for the past 20+ years, precluding the study of AML biology. To address this problem, we have used genetically engineered patient-derived induced pluripotent stem cells (iPSCs) to generate AML organoids. Organoids generated from iPSCs carrying biallelic inactivating mutations in the TSC2 locus (i.e. TSC2-/-) faithfully recapitulated key anatomical and molecular features of human kidney AML (reported in Hernandez JOR et al. Nat Commun. 2021 Nov 11;12(1):6496). Some of those features included the presence of myomelanocytic AML-like cells co-expressing smooth muscle and melanocyte markers, and the transcriptional activation of signaling pathways shared with kidney AML. Transplantation of TSC2-/- AML organoids into the kidneys of immunodeficient rodents resulted in fully vascularized human AML xenografts for mechanistic studies and for drug testing testing in vivo. Using these novel tools we identified potential mechanisms of tumor resistance driven by p21CIP1 and by BCL-2 apoptosis modulators, preventing AML cell death induced by rapalogs. Our in vivo experiments also indicated that drug delivery via nanocarriers may increase the efficacy of anti-tumor therapy while reducing undesired effects in other tissues. The objective of this proposal is to elucidate anti-apoptotic mechanisms driven by p21CIP1 and BCL-2 proteins for the development of novel anti-tumor therapies combining BCL-2 protein inhibitor drugs and rapalogs, that can be co-delivered using tissue-targeting nanoparticles. Our long-term goal is to design new therapies for AML with increased efficacy and specificity. The central hypothesis is that antiapoptotic mechanisms driven by p21CIP1 and BCL-2 apoptosis inhibitors sustain AML cell survival promoting tumor resistance to rapalog therapy. Our three aims are: Aim 1: To investigate anti-apoptotic mechanisms of tumor resistance driven by p21CIP1 in renal AML; Aim 2: To elucidate the role of IGFBP2 in stabilizing p21CIP1 promoting AML cell survival; Aim 3: To study the contribution of BCL-2 proteins to AML cell survival through pharmacologic blockage of BH3 domain interaction. Collectively, these studies will provide much needed insight into the mechanisms of AML and will assess the efficacy of BCL-2 inhibitor therapy alone or in combination with rapalogs in AML-targeting nanoparticles.

NIH Research Projects · FY 2026 · 2023-06

Among community-living older adults, falls are a leading cause of injury, disability, injury-related death, and high medical costs. Despite decades of research, the proportion of older adults who fall has not declined. Identifying older adults at risk of falls remains a major public health priority. Exercise and other interventions can lower fall risk; however, new tools are needed to determine who is most likely to benefit from early interventions. Early research linking fall risk to gait measures obtained in the clinic (e.g., average speed, stride variability) contributed significantly to the understanding of the prediction of fall risk. Studies have also shown that older adults who are more active have reduced risks of falls and fall-related injury. However, critical gaps remain. Exciting advances in digital medicine and remote monitoring using wearable devices have afforded new and more widely accessible opportunities for evaluating the relationships between Daily Living Gait (DLG) and Daily Living Physical Activity (DLPA) to injurious falls in older adults. Measures of DLG (e.g., gait speed, cadence, variability, and how these vary throughout the week) and measures of DLPA (e.g., activity levels and activity fragmentation) can all be derived from a single accelerometer worn for 1 week. While growing evidence suggests that DLG and DLPA do a better job at predicting falls than conventional in-clinic measures, studies to date have been relatively small and have not focused on the prediction of injurious falls. Moreover, little is known about the utility of combining DLG and DLPA measures to predict injurious falls. To address these gaps, we will leverage: 1) an existing large dataset of older women enrolled in the Women’s Health Study (WHS) and 2) advances in wearable technology and machine learning. From 2011 to 2015, 17,466 WHS women wore a tri-axial accelerometer during waking hours for a week; they also regularly self-reported their physical activity levels and health history. We propose to evaluate, for the first time, if and how DLG and DLPA measures predict fall-related injuries in this aging cohort (average age=72 years at the time of accelerometer wear) using records of injurious falls from the Centers for Medicare & Medicaid Services (CMS). Primary Aims 1 and 2 will evaluate which specific measures of DLG and DLPA are associated with the risk of injurious falls in the subsequent year after assessment, using statistical and machine learning approaches that use time-to-event analyses (with and without adjustments for covariates). Primary Aim 3 will evaluate whether utilizing measures of both DLG and DLPA is more strongly associated with the risk of injurious falls than utilizing each of these measures alone. We will also determine if self-reported exercise history is associated with DLG and DLPA, and explore whether markers of DLG and DLPA are associated with risks of injurious falls over more extended periods of 5 and 10 years, as secondary and exploratory aims. By taking advantage of a unique, large dataset, our multi-disciplinary team will identify potential “signatures” to identify high-risk adults who may benefit from early fall prevention strategies and markedly accelerate the potential of using digital markers of fall risk.

NIH Research Projects · FY 2025 · 2023-06

PROJECT SUMMARY Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease, with varying contributions of emphysema and large and small airway disease. COPD heterogeneity is also manifest in variable responses to treatments, including inhaled corticosteroids (ICS). There is an unmet need for biomarkers for COPD outcomes. Our group has led RNA-sequencing on blood samples collected at the Phase 2 (5 year) visit in the Genetic Epidemiology of COPD Study (COPDGene). We found that a type 1 interferon-stimulated gene expression signature in whole blood was associated with airway measures from quantitative analysis of chest computed tomography (CT) scans. A score summarizing the expression of these genes was associated with reduced lung function and COPD exacerbations. The association between the interferon gene score and airway disease was abolished in ICS users. Our hypothesis is that interferon pathway blood gene expression could be used to define an endotype of COPD characterized by airway disease, which will serve as a predictive biomarker for COPD exacerbations and progression and can be targeted with ICS therapy. We will address the following Specific Aims: (1) Airway-interferon predictor of exacerbations and progression: Using COPDGene Phase 3 (10 year) clinical and imaging data, we will use the interferon airway gene signature as a biomarker to develop prediction models for acute exacerbations and disease progression in subjects with and without COPD. The gene signature prediction will be validated in additional COPD studies. (2) Airway-interferon endotype of COPD: We will perform RNA-sequencing in blood samples from the COPDGene Phase 3 visit to test for stability vs. change of gene expression signatures and clinical phenotypes over a five-year interval. To identify lung tissue correlates of the blood gene expression, we will analyze RNA-seq data in resected lung samples from smokers with and without COPD from the Lung Tissue Research Consortium (LTRC), testing for associations between interferon signature genes with chest CT scan-defined airway disease and COPD phenotypes. (3) Response to inhaled corticosteroids: In COPDGene and LTRC, we will test whether the associations between the interferon gene signature and COPD phenotypes of airway disease, exacerbations, and lung function decline are altered in ICS users compared to non-users. We will measure expression of interferon signature genes in a previously completed 12-week clinical trial of ICS in COPDGene subjects, and test whether ICS use affects the interferon- stimulated gene expression pattern. We will re-analyze the clinical trial to test whether the interferon signature predicts response to ICS. This proposal will complement the ongoing analyses in COPDGene by developing a biomarker for COPD outcomes and targeted ICS prescription, which can be used for a future pharmacogenomics clinical trial. Understanding the airway disease interferon gene signature can guide future mechanistic studies and research into targeted therapies beyond ICS.

NIH Research Projects · FY 2026 · 2023-05

Project Summary. Vascular smooth muscle cells (VSMCs) of a synthetic phenotype meet their energy requirements largely via aerobic glycolysis. Hypoxia-inducible factor-1α (Hif-1α) induces a complex transcriptional program that facilitates glycolysis in the setting of low oxygen tension. In normoxia, Hif-1α undergoes proteasomal degradation via prolyl hydroxylation and ubiquitination. In VSMCs engaged in aerobic glycolysis, however, Hif-1α is stabilized by mechanisms that remain unclear. Preliminary data provide insight into the mechanism of this normoxic stabilization of Hif-1α, showing that Hif-1α-dependent aerobic glycolysis remains the primary source of ATP; that conditioned media obtained from VSMCs contains low-molecular-weight factors that stabilize Hif-1α; and that initial identification of these factors indicates that they comprise the family of branched-chain keto-acids (BCKAs), α-ketoisocaproate (KIC), α- keto-β-methylvalerate (KMV), and α-ketoisovalerate (KIV), derived from their parent branched-chain essential amino acids (BCAAs), leucine, valine, and isoleucine, respectively. Given these preliminary results, the central hypothesis of this proposal is that synthetic VSMCs engage in aerobic glycolysis through the effect of BCKAs on Hif-1α stabilization. To address this hypothesis, we propose the following specific aims: 1) we will examine the determinants of BCKA synthesis in VSMCs and their regulation; 2) we will examine the effect of BCKAs on Hif-1α stabilization and explore potential underlying molecular mechanisms; and 3) we will examine the effect of BCKAs on VSMC phenotype and examine the relationship between phenotype switching and metabolic re-programming. The role of BCKAs on VSMC phenotype and metabolism will also be studied in animal models of pulmonary hypertension. The results of these studies should provide useful insight into molecular mechanisms underlying Hif-1α stabilization and aerobic glycolysis in VSMCs, the role of BCKAs in that process, and the relationship between BCKA- dependent aerobic glycolysis and VSMC phenotype and pathophenotype.

NIH Research Projects · FY 2025 · 2023-05

Project Summary/Abstract All tumors contain a mixture of different cell types. Within the malignant cell population, clonal evolution leads to the emergence of clones with different genetic lesions, and various biological processes shape the co-occurrence of different cell states that are characterized by specific transcriptional/epigenetic landscapes. This heterogeneity underlies the persistence of small populations of tumor cells through treatment, leading to disease recurrence, which is a major clinical challenge. To better understand clonal structures and transcriptional/epigenetic states in primary human tumors, there is an unmet need for technologies that comprehensively profile these modalities at single-cell resolution. The PI/PDs Peter van Galen and Vijay Sankaran have pioneered the use of mitochondrial DNA (mtDNA) variants as naturally occurring cell barcodes to reconstruct clonal relationships between cells, and demonstrate simultaneous profiling of transcriptional (scRNA-seq) and epigenetic (scATAC-seq) cell states. As such, they are uniquely positioned to realize the potential of these technologies to illuminate the complex tumor ecosystem and identify vulnerabilities of different malignant cell types. The long-term goal of this research is to guide new therapeutic approaches that can effectively eradicate heterogeneous tumor cells. The overall objective is to establish enabling technologies that can be used across a wide range of tumors to transform our understanding of cancer biology. Drs. Van Galen and Sankaran, supported by a strong network of collaborators, will jointly work towards this objective through two specific aims: 1) Advance and validate experimental methods to simultaneously dissect the transcriptome, epigenome, and clonal structures in cancer and 2) Proof-of-principle profiling of acute myeloid leukemia clones at diagnosis that subsequently drive recurrence. In the first Aim, the investigators will build on their recent accomplishments to establish optimized and validated procedures for multi-omic analysis of primary human cancer cells with clear performance measures. In the second Aim, paired diagnosis-relapse samples from a well-defined cohort of acute myeloid leukemia patients will be analyzed to demonstrate the simultaneous dissection of longitudinal patterns of clonal evolution with transcriptional/epigenetic cell states - a key proof-of-principle for this technology. The approach is innovative by leveraging naturally occurring mtDNA variants to layer clonal relationships onto current state-of-the-art assays for single-cell analysis. The proposed research is significant because the successful completion of the project would equip the scientific community with new tools for the comprehensive molecular/cellular characterization of cancer. The expected output is a repeatable, reliable approach for single-cell analysis of primary human cancer cells at three core modalities, yielding transcriptional, epigenetic, and clonal resolution. This will be enabling for NCI-funded projects in a range of tumor systems.

NIH Research Projects · FY 2026 · 2023-05

Recent successes of artificial intelligence and machine learning (especially deep learning) in analyzing electronic health record (EHR) data have not only stimulated excitement in stakeholders but have also raised concerns about potential biased and inaccurate clinical decision making facilitated by machine learning systems. A number of evaluation metrics have been proposed. However, they underappreciate the persistent systematic differences between the data distributions of different patient groups. Hence, when used to develop machine learning methods, they may lead to models that perform inconsistently across groups and reduce the overall reliability of the trained machine learning models. The situation can be further complicated by missing values that are common in EHR data, which can further degrade model performance if not handled properly. In this project, we aim to develop a novel evaluation methodology (Aim 1) and incorporate it into the development of innovative machine learning models and techniques to reduce systematic errors and increase interpretability (Aim 2). To better handle missing values, we will develop new machine learning models that contain trainable in-process missing value imputation components and new algorithms to train them with constraints defined by our proposed evaluation method (Aim 3). In addition, we will develop proactive machine learning techniques to advance healthcare quality (Aim 4). We will evaluate and improve our proposed evaluation metrics and machine learning techniques in the context of facilitating clinical decision making (Aim 5). Large datasets from two of the largest US healthcare systems will be used in carrying out the proposed research.

NIH Research Projects · FY 2026 · 2023-05

PROJECT SUMMARY The ability to measure extremely low levels of biomolecules accurately and rapidly is essential for diagnosing and monitoring many diseases. While sufficient for certain biomarkers, the sensitivities of most existing diagnostic systems are inadequate for measuring many protein biomarkers that exist in easily accessible biofluids at concentrations below the picomolar range. In this application, we propose to engineer and refine a new ultrasensitive single molecule protein analysis platform that will be able to routinely measure attomolar protein concentrations, which we call Molecular On-bead Signal Amplification for Individual Counting (MOSAIC). MOSAIC transforms single molecule measurements into a simplified assay format via on-bead signal localization, which has the potential to be integrated into a point of care (POC) device. In MOSAIC, a non- diffusible signal is generated on each bead carrying a target molecule, creating an on-bead signal that remains attached for prolonged periods of time, thereby enabling alternative detection schemes to be employed that do not require bead confinement into microwells or droplets to localize signals. A key challenge to be addressed in the proposed work will be to ensure that this MOSAIC platform can consistently outperform current ultrasensitive protein detection technologies in sensitivity by one to two orders of magnitude across many protein analytes, which in turn lays the foundation for future work in translating this enhanced analytical sensitivity to improved clinical sensitivity and specificity for diagnostic applications. In Aims 1 and 2, we will optimize signal generation and readout methods for MOSAIC and expand its multiplexing capabilities. In Aim 3, we will evaluate the diagnostic utility of MOSAIC in a proof-of-principle clinical application to detect very low abundance Mycobacterium tuberculosis antigens in urine as a potential triage test for tuberculosis. The resulting biosensing technology will provide an ultrasensitive diagnostic platform that will open up protein analysis to previously inaccessible biomarkers and also be readily and affordably utilized across both research and clinical laboratories using common laboratory instruments.