Brigham And Women'S Hospital

NIH Research Projects · FY 2025 · 2025-09

SUMMARY: This R01 application is to continue NIH funding for the Ante-Amyloid treatment of Alzheimer’s disease (A3) Trial and the Alzheimer Plasma Extension (APEX) Study. The A3 Trial is one of the sister trials of the AHEAD 3-45 Study testing lecanemab, a potent amyloid-removing monoclonal antibody, at the asymptomatic or “preclinical” stage of AD. The overall goal of these studies is to build a “bridging chain of evidence” that will link the removal of very early amyloid-beta (Aβ) to slowing the spread of early AD tauopathy and ultimately to the prevention of cognitive decline that occurs in the later stages of AD. The A3 testing is low dose lecanemab, prior (“ante”) to elevated brain amyloidosis, defined by intermediate levels (20-40 Centiloids) on screening Aβ PET. A3 runs in parallel with “A45” Trial, testing higher dose lecanemab in participants at later stages of preclinical AD (>40CL). The A3 Trial is the first prevention trial to test an amyloid-lowering therapeutic at the intermediate amyloid stage of sporadic AD and will contribute essential knowledge about the optimal window for efficacy and safety of anti-amyloid monotherapy. A3 is primarily an imaging and biofluid Phase IIb Study at a very early stage of AD pathophysiology, and will require longer term cognitive and functional assessments, paired with biofluid and imaging outcomes, through the Open-Label Extension. This A3 evidence will serve to elucidate the links between Aβ, tau, and the cognitive decline expected at the later preclinical stages studied in the A45 trial. The AHEAD 3-45 Study screened over 20,000 individuals ages 55- 80, and recently completed randomization of (N=441) and A45 (N=1146), utilizing a novel plasma screening algorithm. The APEX Study, funded as a supplement to the A3 R01, will follow 1000 participants with subtle plasma abnormalities, but were not eligible for randomization due to amyloid PET below the A3 threshold (<20CL). APEX is oversampling from a large group of individuals from minoritized racial and/or ethnic underrepresented groups (URG), who showed disproportionate rates of ineligibility on screening Aβ and tau markers. APEX (currently >50% URG enrollment) provides an unparalleled opportunity to evaluate longitudinal trajectories of AD biomarkers across ethnoracial groups to inform future primary AD prevention trials. Furthermore, across APEX and A3-45, we will evaluate Social Determinants of Health, and novel markers of vascular and inflammatory processes to evaluate independent (and Aβ interactive) contributions to cognitive decline. This will lay the foundation for future prevention trials in more representative populations in whom Aβ may not be the primary driver of dementia. Completing these public-private-philanthropic ACTC partnership projects will provide critical information to the field, in particular whether lowering Aβ at this much earlier stage of disease can halt the spread of tauopathy and have a greater impact on cognitive decline. These studies will serve to chart the path forward towards primary prevention of AD, as well as combination prevention trials to address the multiple contributors to cognitive decline in older individuals.

NIH Research Projects · FY 2026 · 2025-09

Project Summary Neutrophils are major players in the innate immune system, known for their role in fighting infections by engulfing and destroying invading pathogens, including those in the lungs. Neutrophil heterogeneity is a key component in innate immune regulation. Distinct mature neutrophil subpopulations, defined by their signature gene expression profiles, phenotypes, behaviors, and functional states, exist even prior to encountering pathogens. Understanding the unique features and origins of these functional subpopulations will enable the effective and safe manipulation of their specific functions for personalized medicine. The objective of this proposed project is to investigate the origin and characterize the functional state of the lung interstitial neutrophil (LIN) subset. Preliminary scRNA-Seq analysis revealed a tightly regulated neutrophil reprogramming trajectory during lung infection and inflammation, based on gene expression patterns. The preliminary studies identified the functional heterogeneity of neutrophils across three different lung compartments: the vasculature, the interstitium, and the alveoli, and discovered that neutrophils lodged in the interstitium for an extended period before migrating to the alveoli. Based on these findings, it was hypothesized that transcriptional reprogramming leads to the formation of a specialized LIN subset defined by its unique gene expression profile. These neutrophils are highly specialized, with significant bactericidal activity, making the lung interstitium a primary site for bacterial elimination. Accordingly, expanding the LIN population could be a viable therapeutic strategy for enhancing neutrophil-mediated host defense, while potentially detrimental in sterile inflammation-induced acute lung injury. To advance the understanding of the function, fate, pathophysiological role, and origin of LINs and explore their therapeutic potential, three specific aims will be investigated: Aim 1 will characterize the functions and fate of LINs. In addition, neutrophil- mediated bacterial killing in the interstitium will be visualized and confirmed by fluorescent imaging. Aim 2 will elucidate the pathophysiological role of LINs in lung infection and inflammation. The LIN population will be expanded by inhibiting CCR2-mediated neutrophil transepithelial migration, and its effect on host bactericidal activity and lung injury will be tested in a neutropenia-related bacterial pneumonia model and an acid aspiration-induced acute lung injury (AA-ALI) model. Aim 3 will further investigate the microenvironment- induced transcriptional reprogramming that confers specialized functions to LINs. Additional scRNA-Seq analyses will be performed to gain a deeper understanding of neutrophil reprogramming in the interstitium and to reveal potential temporal and stimulus-specific reprogramming schemes. Together, the results from this study will establish LINs as a specialized neutrophil subpopulation with unique phenotype and function, and as a novel therapeutic target for treating lung infections and inflammation.

NIH Research Projects · FY 2025 · 2025-09

Project Summary: Deep learning methods toward resolving uncertain variant classifications Genomic sequencing can substantially improve clinical management, by optimizing surveillance and treatment options, and improving risk assessment. As the interpretation of genetic variants increases, thousands of new variant interpretations are entering variant databases each month. Most variants in these databases have insufficient evidence to be classified as pathogenic or benign, and as a result are classified as Variants of Uncertain Significance (VUSs). Despite potentially increasing risk, information about these variants cannot be communicated to providers or patients due to a lack of structured evidence. This translational gap is preventing many patients who collectively carry such variants from benefiting from genomic medicine. ClinVar, a large diagnostic variant database contains a unique abundance of predictive information that has been curated by clinical experts over many years. This includes over 1.1 million plaintext diagnostic reports that often describe case data, literature review, and an analysis of computational predictions or functional assay data. We will use these clinical reports to make predictions of pathogenicity, and to identify which specific sources of evidence of pathogenicity are provided in each report. This project will enhance the value of data in ClinVar, a public resource used by thousands of investigators, clinicians, and bioinformatic pipelines. We will first optimize a text classification model to make predictions from diagnostic summaries, evaluating and fine-tuning a set of large language models which have been trained on different text corpora. Using clinical reports and known classifications from ClinVar variant submissions, we will evaluate different filtering criteria used in the training process. We measure performance on high confidence labeled data which have been previously reviewed by expert panels, as well as on bona fide VUSs, using expert panel curated variant interpretations as ground truth validation data. Next, we identify the information from these reports which drive predictions using post-hoc explainability methods (attention mapping, representation probing, and causal mediation analysis), and then map this evidence to biomedical concepts related to variant interpretation and pathogenicity, using a knowledge graph which is refined to highlight these concepts relevant to diagnostic review criteria. Finally, we will measure the extent to which these approaches can identify complementary evidence across variant reports generated by different clinical labs related to the same variant, which can be used to re-classify VUS or resolve a variant with conflicting interpretations. We will manually review a set of clinical reports to evaluate accuracy of the sources of information that have been recovered. If evidence is sufficient, we will identify up to 100 variants which are carried by participants in the Mass General Brigham biobank, and attempt to update their variant classifications so that these results can be communicated to patients.

NIH Research Projects · FY 2025 · 2025-09

Obstructive Sleep Apnea (OSA), characterized by recurrent pharyngeal obstructive events during sleep, affects as many as 38% of adults, most of whom are not diagnosed and treated, and thus at potential risk for daytime impairment and long-term health problems. Efforts to implement evidence-based approaches for improving diagnosis and treatment have been impeded by the lack of data from longitudinal studies and clinical trials that address which patients are at greatest risk for cardiovascular disease and other health problems, and who is most likely to benefit from intervention. Notably, the standard disease-defining metric, the Apnea Hypopnea Index (AHI), the number of breathing pauses during sleep, does not characterize the heterogeneity of OSA mechanisms, the physiological impact of the breathing disturbances, risk for adverse outcomes, and likelihood of responding to treatment. Our multi-disciplinary team will address this gap by integrating multiple data sources to derive physiologically informative individual and composite metrics of OSA and characterize their associations with mechanistic traits, symptoms, risk factors, molecular markers, and clinical outcomes. We will cost-effectively utilize data from: a) existing large prospective research cohorts (including data within the National Sleep Research Resource and Trans-Omics in Precision Medicine; n≈29,000; b) newly ingested sleep and clinical outcome data from a large clinical biobank; n≈30,000; and c) a prospective study of patients with OSA recruited to examine the short-term reproducibility of OSA metrics. In Aim1, we will quantify the reproducibility of OSA severity markers (i.e., that quantify ventilatory reduction and hypoxia, heart rate, and sleep fragmentation responses to obstructive events) in a diverse sample of patients with a range of AHI studied twice over ≈ 2 weeks with polysomnography. Using the most reproducible metrics, we will derive OSA composites that are potentially more informative than individual metrics and describe OSA subtypes. In Aim 2, we aim to further characterize the clinical and physiological heterogeneity of individual OSA metrics and composites by describing their associations with symptoms and socio-demographic, health-related, metabolomic, and endotypic markers. We will use genetic instruments and Mendelian Randomization to study associations of OSA metrics/composites with each other and with common co-morbidities (e.g., obesity, diabetes, hypertension, etc) and candidate biological pathways (inflammation, lung function, etc) - clarifying which associations reflect shared genetics, indirect effects, and/or direct causal effects. In Aim 3, we will use existing longitudinal and clinical trial data to evaluate which OSA metrics/composites predict long term health outcomes and OSA treatment response. Scalability will be addressed by identifying parsimonious sets of metrics that can be most readily incorporated into clinical practice. With professional society and patient input, we will develop and disseminate a foundational OSA classification (taxonomy), annotated for relevance by sex and social determinants of health, with the goal of improving the understanding of the heterogeneity of OSA, providing a foundation for OSA precision medicine.

NIH Research Projects · FY 2025 · 2025-09

Project Summary Abstract: The skin is a barrier tissue that is impacted by all types of external radiation events and is accessible to non- invasive testing. Tape stripping of the skin is an effective, well established, and non-invasive method for sampling both protein and RNA biomarkers in human skin. We have developed a model of studying radiation injury in human skin by irradiating living human skin grafts carried by immunodeficient NSG mice. Our model recapitulates both the early inflammatory and late fibrotic changes in skin observed in patients after radiation exposure. We present pilot spatial profiling and immunostaining data demonstrating that superficial keratinocytes, the cell population sampled by non-invasive tape stripping, upregulate RNA and protein biomarkers within 24 hours of radiation exposure and that different biomarkers have the potential to discriminate between 1, 2 and 5 Gy radiation. In this proposal, we will identify optimal keratinocyte biomarkers of radiation exposure and develop a point-of-care test to measure them using non-invasive tape stripping. In Aim 1, we will identify, validate and measure the expression kinetics of keratinocyte biomarkers of radiation exposure (0, 1, 2, 5 Gy) in human skin grafts carried by NSG mice. Xenium 5000 plex spatial transcriptional profiling will be used to identify candidate biomarkers (Aim 1A), followed by single cell proteomic measurement of candidate biomarkers using cyclic immunofluorescence (CyCIF) in both discovery and validation sample cohorts (Aim 1B,C). The kinetics of protein biomarker expression will then be evaluated via CyCIF on days 1, 2, 3, 5, and 7 after 1, 2, or 5 Gy irradiation (Aim 1D). In Aim 2, we will use NSG mice grafted with neonatal foreskin and skin obtained from aged patients (>65 years) to study the utility of identified biomarkers in pediatric and aged individuals. In Aim 3, we will develop and test a point-of-care test to measure biomarkers using non-invasive tape stripping of the skin. These studies will generate validated, human cutaneous biomarkers of radiation exposure and a non-invasive test to measure them that is immediately applicable to the care of humans exposed to radiation.

NIH Research Projects · FY 2025 · 2025-09

Title: Training Program in Patient-Oriented Research in Cardiovascular Endocrinology Abstract For some time, keen observers of the academic scene have been sounding alarm over an impending manpower crisis in patient-oriented research reflected in steadily declining numbers of clinical investigators since 2000, potentially jeopardizing a highly successful national enterprise of clinical medicine and drug discovery. In spite of these concerns, the number of T32 programs in patient-oriented research (~3% of funded T32 grants) has dwindled and today, few programs are aimed at patient-oriented research in cardiometabolic disorders. This new Training Program in Patient-Oriented Research in Cardiovascular Endocrinology aims to bridge this gap by providing comprehensive, curriculum- and mentor-based training in all aspects of patient-oriented research. The program is founded upon 4 pillars: 1) 16 dedicated NIH-funded primary mentors committed to individualized mentoring; 2) motivated trainees committed to lifelong careers as academic investigators in patient-oriented research; 3) 3 NIH-funded early career investigators committed to developing careers as research mentors; and 4) 6 scientists with expertise in the relevant content areas who will serve as content experts within the trainee's mentoring team. The program's implementation is led by two co-directors (Adler and Bhasin), and 2 committees: Operations Committee (responsible for program administration/ direction, trainee selection, and program evaluation); Career Development / Mentoring Committee (CDMC, responsible for trainee mentoring and career development). The program includes: 1) a didactic curriculum-based learning; 2) research training in setting of mentored research project/s; and 3) an individualized career development plan. Each trainee develops an Individual Development Plan with the guidance of their Mentoring Team, which includes primary mentor, co- mentor, content expert, and CDMC advisor. The curriculum-based learning includes training in ethics in research, genetics and epigenetics, biostatistics and statistical genetics, endocrinology, nutrition and obesity, and cardiovascular endocrinology. Trainees are encouraged to create a trainee-specific curriculum utilizing courses at Mass General Brigham and affiliated academic medical centers. All trainees are required to complete coursework in patient-oriented translational research, biostatistics, Omics technologies, and a specific course in cardiovascular endocrinology. The Program includes structured evaluations of trainees, mentors and the program. Trainee selection is based on recommendation letters, previous training, research interests, commitment to patient-oriented research, and a personal interview. The program's strengths include 2 experienced program co-directors and outstanding mentors with NIH funding, a stellar publication record, and success in training mentees who have advanced to successful academic careers and NIH funding; outstanding institutional infrastructure to support research and training, and a large pool of qualified candidates at Brigham and Women’s Hospital and affiliated academic medical centers.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY This K23 award will support career development for the candidate to become an independent acupuncturist- scientist, focused on mechanisms of acupuncture and point specificity. BACKGROUND. Acupoints represent one of the core tenets of acupuncture, yet their underlying scientific basis remains poorly understood. This gap poses challenges in advancing the fundamental science of acupuncture and determining whether point specificity is an essential, therapeutic component of acupuncture. Recent basic animal studies have provided compelling evidence that cutaneous neurogenic inflammation may be a potential physiological correlate of acupoints in the context of visceral diseases. They demonstrated that (1) experimental induction of visceral diseases (e.g., rodent models of colitis) causes cutaneous neurogenic inflammation, the distribution of which overlaps with the locations of specific acupoints, and (2) acupuncture at these sensitized locations is more effective in improving the corresponding diseases. To date, no studies have been done to validate these findings in human subjects. Thus, the goal of this K23 is to bridge this gap by conducting clinical and translational (C/T) research in human subjects, using inflammatory bowel disease (IBD) as the disease model. Key features of neurogenic inflammation include increased blood flow and hypersensitivity, so cutaneous blood perfusion and pressure pain threshold (PPT) will be collected as proxy measures, using laser speckle contrast imaging and pressure algometry. SPECIFIC AIMS. The proposal will consist of two independent, yet interrelated studies: a translational study comparing cutaneous blood perfusion and PPT between IBD patients and healthy control participants across multiple prespecified acupoints and sham points (Aim 1), and a pilot RCT in IBD patients to collect feasibility measures that will inform the design of a larger scale RCT, evaluating whether cutaneous sensitization of acupoints and/or sham points used in acupuncture treatment affects clinical outcomes (Aim 2). LONG-TERM GOAL. The candidate’s long-term career goal as an acupuncturist-scientist is to advance the science of acupuncture and translate scientific evidence to inform clinical practice to ultimately improve patient care. With the mentored research and training activities proposed in this K23, she will develop expertise in C/T research methodologies, learn more about IBD pathophysiology, deepen her understanding of biomedical imaging and biomarker science, and gain competence in longitudinal analysis. MENTORSHIP. The candidate will be supported an interdisciplinary mentoring team with expertise in acupuncture research, IBD, biomedical imaging and physiological signal analyses, and biostatistics: Drs. Peter Wayne and Vitaly Napadow (co-primary mentors) and Drs. Joshua Korzenik, Ted Kaptchuk, Weidong Lu, Andrew Ahn, and Pamela Rist (collaborators and secondary mentors). IMPACT. This K23 proposal addresses a critical gap in the field of acupuncture research surrounding the scientific basis of acupoints and aligns with NCCIH’s objective to advance the fundamental science and methods development relevant to acupuncture research.

NIH Research Projects · FY 2025 · 2025-09

Project Summary Alzheimer’s disease (AD) and related dementias (ADRD) pose significant challenges with a growing societal impact. Addressing these challenges requires comprehensive research into the neurobiology of the diseases, leading to innovative biomedical concepts, approaches, and molecular targets. A central factor in these disorders is the protein tau, whose misregulated homeostasis, aggregation, and intercellular spread contribute to AD, Frontotemporal dementia (FTD), and other tauopathies. Tau-containing neurofibrillary tangles (NFTs) from AD brains are known to contain RNA, and it is proposed that tau-RNA interactions may facilitate tau aggregation and modulate neuronal vulnerability to stress. However, the specific RNA species involved in tau pathology remain unidentified. Our data suggest a novel class of small RNA transcripts—tRNA-derived fragments (tRFs)—that accumulate in AD, potentially binding tau and promoting its misfolding and aggregation. Regulated by disease-related neuronal stress, tRFs are enriched in extracellular spaces and body fluids, including cerebrospinal fluid (CSF), and can be taken up by recipient neurons. Our research aims to investigate the role of specific tRFs in tau aggregation, pathology propagation, and neurodegeneration in ADRD through the following Specific Aims. Specific Aim 1: Characterize the small RNA landscape, with a focus on tRFs, at different stages of AD pathology using an optimized RNA sequencing platform. Examine the RNA binding capacity of intracellular and extracellular tau variants and mutants using human induced pluripotent stem cell (iPSC)-derived neurons and rodent primary neurons. Identify tRFs within pathological tau aggregates and visualize their colocalization with tau pathology in human AD brains. Specific Aim 2: Investigate the impact of selected tRFs and tRF-enriched extracellular complexes on tau homeostasis and pathology using gain- and loss-of-function approaches in neuronal cell models. Specific Aim 3: Examine the effects of specific tRFs on tau pathology and behavioral phenotypes in WT mice and a humanized Tau P301S/PS19 mouse model of tauopathy and neurodegeneration. Assess neuroprotective effects of targeting specific tRFs in the brain. This collaborative R01 project seeks to unravel the complex molecular mechanisms underlying ADRD and explore the cellular and extracellular biology of these disorders. Findings may reveal a new class of potential therapeutic targets and biomarkers.

NIH Research Projects · FY 2025 · 2025-08

ABSTRACT Abdominal aortic aneurysms (AAAs) are a significant healthcare challenge, particularly among the elderly. The presence of intraluminal thrombus (ILT) is common in AAAs, yet its precise role in aneurysm progression remains a topic of ongoing debate. Emerging evidence suggests that ILT substantially contributes to AAA growth by creating an environment that promotes proteolytic activity, leading to the degradation of elastin and collagen in the arterial wall. Despite recognition of the role of blood flow patterns in ILT formation and AAA progression, a systematic approach to understanding these relationships is lacking. This study aims to bridge this gap by investigating both gross and local blood flow characteristics to uncover the mechanisms underlying ILT initiation and subsequent AAA rupture risk. Leveraging my expertise in computational modeling, along with new training in deep-learning-based image processing and statistical analysis, this research will examine the spatiotemporal dynamics of hemodynamics and their correlations with ILT development. Machine learning (ML) algorithms will be utilized to analyze global flow indices and near-wall flow characteristics, enhancing our ability to predict ILT formation and AAA rupture risk. The study will first identify general blood flow characteristics linked to ILT development, followed by an in- depth analysis of local hemodynamics in distinct sub-regions of the aneurysm to reveal their specific roles in localized ILT formation and AAA expansion. Finally, both global and local flow characteristics will be integrated using ML to establish a relationship between hemodynamics, ILT accumulation, and rupture risk. Through this comprehensive exploration, the study seeks to provide a more coherent understanding of AAA severity and the interplay between blood flow, ILT, and rupture risk. Overall, this project aims to bridge the gap between aneurysmal hemodynamics, ILT formation, and AAA rupture risk, offering new insights for clinical management and risk assessment of AAA patients. This fellowship will further enhance my expertise in AI-driven medical image processing and statistical analysis while fostering collaboration with clinical experts to advance my career in vascular research.

NIH Research Projects · FY 2025 · 2025-08

Nearly 1 in 2 US adults has hypertension, and it is a leading cause of myocardial infarction, stroke, and death. Despite the importance of hypertension and the widespread availability of medication treatment, less than half of patients have blood pressures that are controlled. This is in part due to the way in which we deliver care, and new strategies are needed to achieve better blood pressure control. Team-based care with medication titration by a non-physician is a promising approach, but the cost and infrastructure required make this option less feasible. An alternative strategy is to have patients self-manage their own hypertension by checking blood pressures and following an algorithm, pre-planned between the patient and primary care doctor, to intensify their medications at home. Despite evidence for the safety, effectiveness and cost- effectiveness of this approach, it has not yet been incorporated into routine care. Prior to a large-scale trial of this intervention in the US, several key factors need to be tested. First, the sociodemographic characteristics of patients with hypertension in the US, patient preferences, practice patterns, perspectives of US providers and regulatory environment are different from the original trials. Our preliminary work has demonstrated that US patients and providers are enthusiastic about antihypertensive self- titration, and that adaptation of the intervention to the US context will require specific prioritization of diverse patient participation. Moreover, usual care has evolved, and an adapted intervention will need to optimally utilize the electronic health record and consider use of connected home blood pressure cuffs. Thus, in this project we will complete key preparatory steps to ensure the intervention is adapted to and implementable in the US primary care context. In Aim 1 we will refine our process to identify patients with uncontrolled hypertension to incorporate home blood pressure measurements. In Aim 2 we will develop and refine recruitment and intervention materials and processes based on feedback from a diverse group of healthcare team members and patients. We will then pilot test all aspects of the intervention in clinical care for 30 patients to determine reach, adoption, feasibility and fidelity (Aim 3). Upon completion of this work all materials and procedures will be proven ready for the successful conduct of a randomized trial testing antihypertensive self-titration in the US primary care context.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY/ABSTRACT Chronic kidney disease (CKD) is associated with accelerated cardiovascular (CV) aging including maladaptive myocardial and vascular remodeling, ultimately increasing cardiovascular risk independent of traditional risk factors. Microcirculatory dysfunction plays a key role in the early stages of myocardial injury and dysfunction. Specifically, a decline in myocardial flow reserve (MFR) - a well-validated quantitative marker of vascular health assessed using positron emission tomography (PET) – is linked to maladaptive myocardial remodeling and adverse outcomes. Chronic systemic and vascular inflammation, which is highly prevalent in CKD, is linked to endothelial dysfunction, dysregulated angiogenesis, atherosclerosis, myocardial dysfunction, and abnormalities in the coronary microcirculation. Kidney transplantation offers a unique observational model to examine the impact of reducing CKD-related inflammation on CV outcomes, including coronary microvascular function and myocardial mechanics. The goal of the proposal, based on the observational study RESTORE (Impact of Renal Transplant on Coronary Microvascular Function in Patients with Advanced Chronic Kidney Disease), is to mechanistically explore cardiovascular health before and after transplant, focusing on the interplay between inflammation, angiogenesis, myocardial perfusion and myocardial function. We hypothesize that systemic inflammation and dysregulated angiogenesis contribute to abnormal myocardial blood flow, measured by PET, and abnormal myocardial mechanics, assessed by echocardiography, in patients with advanced CKD on the transplant waitlist (Specific Aim 1). Leveraging transplantation as an observational intervention, we further hypothesize that kidney transplant will be associated with improved myocardial blood flow and myocardial mechanics (Specific Aim 2), and that reductions in inflammation and dysregulated angiogenesis after transplant will be associated with improved myocardial blood flow and function (Specific Aim 3). By gaining a mechanistic understanding of how CKD, its associated inflammation and dysregulated angiogenesis, and kidney transplant influence myocardial blood flow and function, this study may lead to targeted preventive therapies in the future, such as immunomodulatory treatments, including IL-6 inhibitors. The proposal will be accomplished within a comprehensive career development plan designed to provide the award applicant Dr. Huck, who is a cardiovascular imaging specialist and early career investigator, the skills to become an independent R01-funded clinical-translational investigator and academic leader performing mechanistic and therapeutic clinical trials with imaging endpoints in people with kidney disease. Dr. Huck has an expert mentorship team of multidisciplinary researchers in coronary microvascular dysfunction, kidney transplant, clinical trials and state-of-the-art cardiovascular imaging and a superb environment for early career development at Brigham and Women’s Hospital and Harvard Medical School. He is ideally supported for a transition to scientific independence over the course of the award period.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY This Mentored Research Scientist Development Award (K01) application is submitted by Jason Brian Gibbons, PhD, an assistant professor in the Department of Health Systems, Management, and Policy at the University of Colorado Anschutz Medical Campus. Dr. Gibbons's long-term goal is to improve the quality of care for patients with opioid use disorders (OUD) and reduce overdose deaths. Over the past few years, Dr. Gibbons has focused his research on studying the effectiveness of OUD treatment and policies and programs aimed at expanding OUD treatment service access, use, and adherence. As part of this proposal, Dr. Gibbons aims to obtain rigorous training in novel machine learning-based dynamic treatment regime methods (DTRs) and optimization trial designs to study the dynamic and heterogeneous nature of OUD severity and treatment response with the ultimate goal of using study findings to optimize OUD treatment delivery. He proposes a 5-year program of career development and mentored research to accomplish this research objective. Dr. Gibbons will work with an interdisciplinary team of mentors from the University of Colorado Anschutz Medical Campus, Brigham and Women's Hospital, and the University of Michigan, who have international reputations in the areas of his proposed training. The overarching objective of his proposal is to develop dynamic, personalized treatment recommendations using machine learning-based DTRs. DTRs can use high-dimensional data on patient's medical and social characteristics to assess the relationship between factors and treatment responses over time. The DTR then uses these relationships to craft optimal treatment decision rules. The DTRs will incorporate extensive health records from a national Behavioral Health Care Services provider, Discovery Behavioral Health, and linked all-payer claims and death records. Once the treatment decision rules have been constructed using several DTRs, a single model will be identified as “best- performing” based on its ability to generate decision rules that minimize patient risk of opioid overdose and hospitalization. A pilot hybrid factorial sequential multiple assignment randomized trial (SMART) will then be conducted to assess the acceptability and feasibility of a future full-scale trial (R01) that will evaluate the effectiveness of the generated treatment decision rules from the best-performing DTR. This research can potentially mark a paradigm shift in OUD treatment by moving towards individualized, data-driven treatment and aligns with NIDA's broader public health goals and strategic priorities. This research and Dr. Gibbons's planned training activities will prepare him to develop and test adaptive treatment strategies that may be able to improve OUD treatment outcomes. Training and research from this proposal will also be relevant to his interests in optimizing treatment for other chronic substance use and mental health disorders. Finally, the research and training will give Dr. Gibbons the solid foundation he needs to become an independent investigator and future leader in mental health and substance use disorder treatment quality research.

NIH Research Projects · FY 2025 · 2025-08

Project Summary Glioblastoma (GBM) is the most common type of malignant primary brain tumor found in adults and is fatal in all cases with a median survival time of only 14-16 months. Therapeutic targeting of classic cancer growth factor pathways in glioma has had limited success, suggesting that gliomas have unique growth mechanisms. Increasing evidence has implicated the neurotransmitter glutamate (Glu) as playing a critical role in driving glioma growth and invasion. GBM cells downregulate excitatory amino acid transporter-2 (EAAT2) and upregulate system Xc transporter (xCT) activity, increasing the extracellular Glu. Increased Glu causes excitotoxicity, healthy cell death, and autocrine Glu receptor stimulation to enhance GBM cell migration and growth. xCT exchange of Glu for cystine increases glutathione (GSH) synthesis to better resist oxidative stress and chemical insult. Novel therapeutics that target Glu metabolism have shown early promise. In particular, the drug riluzole disrupts GSH synthesis, promotes oxidative stress by inhibiting Glu export via xCT, and promotes astrocytic Glu uptake for reconversion to glutamine (Gln). Riluzole has been shown to be effective in treating in vitro GBM cell lines and preclinical GBM mouse models and the pro-drug troriluzole is under clinical investigation in GBM patients (ClinicalTrials.gov: NCT03970447 and NCT06552260). Similarly, IDH1-mutant glioma cells have been shown to have altered glutamate metabolism compared to wild type cells. Changes in Glu levels have been observed in clinical IDH1-mutant gliomas in response to IDH1-inhibitor therapies. The central role of Glu in these processes strongly suggests that noninvasive, high-resolution Glu imaging would help optimize drugs targeting this critical pathway and improve tumor treatment monitoring. Current methods for measuring glutamate either suffer from low sensitivity or low specificity. We propose to overcome this challenge by developing and optimizing a novel glutamate Chemical Exchange Spin Lock (GluCESL) magnetic resonance fingerprinting (MRF) method that enables accurate quantification of glutamate concentration with high specificity and sensitivity. We hypothesize that the GluCESL-MRF method will enable the acquisition of accurate, high-resolution glutamate concentration maps in acquisition times of less than 10 minutes. To test this hypothesis, we will first optimize the GluCESL-MRF acquisition schedule to maximize the accuracy of the glutamate maps using a deep learning approach for optimizing the glutamate fingerprinting acquisition schedule (Aim 1.2). Next, we will validate the GluCESL-MRF glutamate maps with low resolution glutamate maps obtained from magnetic resonance spectroscopy (Aim 1.3). The reproducibility of the glutamate maps will then be examined in test-retest studies performed at different time points and MRI scanners (Aim 1.4). Finally, the ability of GluCESL-MRF to monitor response to novel glioma therapies that target the glutamate metabolic pathway will be evaluated in two small pilot studies looking at response to troriluzole (Aim 2.1) or the IDH1-inhibitor vorasidenib (Aim 2.2).

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY/ABSTRACT Calcium pyrophosphate deposition disease (CPPD) is a painful inflammatory crystalline arthritis that afflicts 8-10 million Americans, but targeted treatments do not currently exist and there are very few studies on this common arthritis. Some patients with CPPD report improved joint symptoms with long-term colchicine 0.6mg daily (FDA-approved dose for gout), though we currently lack tools to predict which CPPD patients will benefit. The NLRP3 inflammasome plays a key role in the pathophysiology of CPPD and cardiovascular (CV) disease, and CV risk is up to two-fold higher in patients with CPPD than matched comparators. Understanding colchicine's impact on the NLRP3 inflammasome and downstream pathways will provide critical knowledge about mechanisms by which colchicine reduces CPPD symptoms and has tremendous

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY There is an urgent need for translational virologists and physician scientists, who are trained in translational patient-oriented research, have expertise across clinical/laboratory science, and can bridge the gaping divide that often occurs between purely clinical and laboratory-focused researchers. Translational HIV virologists are instrumental to the success of clinical trials networks, collaboratories, and for our goal to translate basic laboratory findings into novel therapeutics. However, it has become increasingly clear to me that the pipeline for translational HIV researchers has slowed to a trickle. The primary goal of this project will be to provide mentorship to trainees and early career investigators in clinical studies and cutting-edge translational virology techniques in key priority areas of HIV. Among the top priorities of the HIV field is the determination of the mechanisms behind HIV persistence, the search for therapeutic interventions that can lead to sustained antiretroviral therapy (ART)-free HIV post-treatment control, and the impact of HIV drug resistance to newer antiretroviral agents (ARVs). Trainees will have the opportunity to both lead and study participants from high- priority cohorts, such as the Low-V cohort of participants with non-suppressible viremia, the Control of HIV after Antiretroviral Medication Pause (CHAMP) study, the largest study of post-treatment controllers world- wide, and new HIV cure and treatment trials from the ACTG. This will be paired with training in cutting-edge laboratory techniques like the Matched Integration Site and Proviral Sequencing (MIP-Seq) and single-cell techniques for an in-depth analysis of the molecular circuits of HIV persistence and reservoir control. This is also an exciting time for HIV therapeutics with the rollout of dolutegravir in Africa and the introduction of long- acting injectables in the US. However, progress could be reversed with increasing drug resistance. We have developed robust next-generation sequencing platforms for HIV resistance sequencing and will use cohorts from the ACTG and sub-Saharan Africa to evaluate the prevalence and clinical impact of antiviral drug resistance mutations. Trainees will also have access to individualized training in virology, clinical trial design and implementation, biostatistics, and bioinformatics courses and co-mentors. With the successful completion of this project, we will have 1) trained the next generation of investigators to provide leadership and virology support for clinical studies focused on HIV; 2) advanced our understanding of the mechanisms of HIV persistence and control in PTCs, with implications for the design of HIV curative strategies for all individuals living with HIV, and 3) defined the impact of antiviral drug resistance and viral evolution to our newest ARVs.

NIH Research Projects · FY 2025 · 2025-08

Project Summary/Abstract Myocardial fibrosis is commonplace in the aging heart. Accelerated extracellular matrix remodeling and collagen deposition, triggered by chronic myocardial tissue injury, are associated with pathologic myocardial fibrosis, and contribute to the rising burden of cardiovascular disease. Although the initiating triggers for myocardial tissue injury are disease-specific, they activate a highly consistent set of core pathways of fibrosis that lead to accumulation of myofibroblasts and fibrotic tissue remodeling. Unraveling the mechanisms that contribute to myocardial fibrosis will enable prevention of myocardial fibrosis progression and design of therapeutic interventions that could have a wide-ranging impact on multiple cardiovascular diseases. Cardiac magnetic resonance imaging (MRI) with T1 mapping is a non-invasive histologically validated quantitative method for assessment of myocardial fibrosis. Genome-wide association analysis is a powerful analytical approach that can identify biological pathways linked to cardiovascular traits. However, adequately powered genome-wide association studies of myocardial fibrosis in humans require large sample sizes with combined genomic, cardiac MRI and clinical outcome data, which to date have been elusive. The UK Biobank (UKB) is a unique longitudinal prospective cohort comprising ~500,000 participants with comprehensive phenotyping, imaging, and multiple genomic data types. Approximately 100,000 participants have contributed to the UKB imaging study, offering paired cardiac MRI and whole genome sequence data, with 60,000 participants undergoing repeat cardiac MRI during follow-up. The current proposal aims to: (1) harness machine learning to measure, at an unprecedented scale in 100,000 individuals in the UKB, myocardial segment-specific fibrosis burden and tissue heterogeneity and examine the clinical relevance of these measured traits by examining their association with cardiovascular, metabolic and inflammatory diseases; (2) leverage whole genome sequence data to identify coding and non-coding genomic loci associated with myocardial fibrosis for potential therapeutic targeting; and (3) examine clinical and genetic factors that contribute to myocardial fibrosis progression in the subset with repeat cardiac MRI. This work will benefit from the robust scientific and computational infrastructure at the Cardiovascular Medicine Division at the Brigham and Women's Hospital and the Cardiovascular Disease Initiative (CVDI) at the Broad Institute of Massachusetts Institute of Technology (MIT) and Harvard. Dr. Nauffal will be mentored by Dr. Patrick T. Ellinor, the Director of the CVDI and an expert in defining the molecular basis of cardiac fibrosis using genetics. By completing the research and training aims outlined in this proposal, Dr. Nauffal will acquire proficiency in deep learning methods, human genetic discovery, fibrosis imaging and longitudinal data analysis. These skills are critical to achieve his goal of becoming an independent R01-funded computational cardiovascular geneticist.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY Essential tremor (ET) is one of the most common neurological diseases, with an estimated seven million affected persons in the USA. The disease is chronic and progressive. It is poorly served by currently available medications that initially were approved for other indications. Here, we describe a new approach to discovering novel compounds tailored explicitly toward the hypothesized underlying causes of ET. Although the etiology and pathophysiology of ET are not yet fully understood, human data strongly implicates: i) endogenous β-carbolines (e.g., harmane) in the etiology of ET and (ii) a disturbance of the GABAergic system in the pathophysiology of ET. Harmane is a negative allosteric modulator (NAM) that reduces the maximal functional response elicited by GABA and binds at an allosteric site different from the benzodiazepine site. Indeed, exogenous administration of harmine causes tremors in humans. We have identified a mechanistically unique strategy to treat ET and restore GABAA functional tone to a normal state while avoiding the side effects typically associated with excessive GABAA potentiation. Our preliminary studies identified both (i) GABAA precision PAMs and (ii) dual GABAA precision PAM/β2-adrenergic receptor antagonists that were efficacious in the harmaline model of ET without sedation. With optimized PK and brain exposure, we believe that a GABAA precision PAM will restore proper motor function in brain regions affected in ET without the side effects of excessive GABAA potentiation (e.g., sedation). Our Aims are as follows: AIM 1: Medicinal chemistry optimization and in vitro characterization of novel β-carboline GABAA PAMs. ZK-95962 was a promising GABAA partial agonist, but high clearance, poor oral bioavailability, and sedation halted its clinical development. We propose that (i) the cause of the poor PK of ZK-95962 (e.g., ester hydrolysis) can be successfully addressed, and (ii) its excessive GABA potentiation can be fine-tuned by appropriate substitution. Therefore, this aim aims to identify novel β-carboline GABAA precision PAMs and significantly improve these compounds' metabolic stability and PK properties. AIM 2: In vivo evaluation of lead molecules in the harmaline model of ET. Three GABAA precision PAMs and three dual-acting compounds (e.g., β2-ADR antagonist/GABA precision PAM) that satisfy the stringent criteria defined in Table 3 will be scaled up for evaluation in the harmaline model. Efficacious compounds will be tested in three models (righting reflex, rotarod, and SLA) that can detect different indicators of sedation. For a compound to advance, it must in all three safety models, demonstrate a NOAEL ≥30X above its ED50 in the harmaline ET efficacy model. Compounds with a NOAEL ≥100X will be preferred. A positive result will provide mechanistic support for the proposition that a precision GABAA PAM can eliminate tremors in the harmaline model of ET without sedative side effects and the identification of compounds suitable for advancement into preclinical safety testing.

NIH Research Projects · FY 2025 · 2025-08

Abstract Micronutrients are critical for healthy brain development and growth, but deficiencies are common in countries with high rates of undernutrition. Early infancy, a particularly sensitive period for brain development, is a time when many infants fully depend on the micronutrient content of mother’s milk to meet their ongoing dietary requirements. Inadequate micronutrient status in a mother may lead to deficiencies of certain micronutrients in breast milk, such as vitamin B6 or B12, and may jeopardize an infant’s neurodevelopment. It is possible this problem may be prevented by providing lactating mothers with daily micronutrient supplementation. The central hypothesis of the proposed research is that maternal MMS during lactation will improve infant neurodevelopment, partly due to higher levels of B-complex vitamin in maternal milk. I propose the following specific aims: 1) to determine if maternal multiple micronutrient supplementation during lactation improves infant neurodevelopment, 2) to quantify the effect of maternal multiple micronutrient supplementation during lactation on B-complex vitamin content in milk, and 3) to measure the association between B-complex vitamin content in milk and neurodevelopment. I will accomplish this through two parent studies, a clinical trial of multiple micronutrient supplementation among lactating mothers in Ethiopia (R01HD107475) and an established observational lactation cohort in Bangladesh. Knowledge gained from this study will address a critical global gap related to maternal micronutrient supplementation during lactation and provide data needed to inform global guidelines. This K23 Career Development Award is being proposed by Dr. Krysten North, a neonatologist and physician- scientist studying nutrition interventions to optimize neurodevelopment among infants in resource-limited settings. Dr. North’s training aims are to develop expertise related to 1) global clinical trials, 2) human milk composition, 3) advanced statistical analysis of correlated data, and 4) infant neurodevelopmental assessment. Her mentorship team includes Dr. Anne CC Lee (primary mentor; global maternal-newborn clinical trials), Dr. Christopher Duggan (co-secondary mentor; micronutrients among children in low-resource settings), and Dr. Mandy Belfort (co-secondary mentor; effects of infant nutrition on neurodevelopment). The candidate is positioned in an ideal environment at Brigham and Women’s Hospital and Harvard Medical School, with rich resources for training and collaboration. She has crafted a detailed career development and training plan that includes an expert scientific advisory committee, mentored research, didactic coursework, and a timeline for manuscript and R01 development. After this K23 period, Dr. North will transition to independence as a researcher and leader in the field of nutrition interventions to improve neurodevelopment for vulnerable infants in resource- limited settings.

NIH Research Projects · FY 2025 · 2025-08

Project Summary Antimicrobial-resistant (AMR) infections are a global health crisis, causing nearly 5 million deaths annually, with the highest burden in low- and middle-income countries (LMICs). Carbapenem-resistant Enterobacterales (CRE) are among the most dangerous AMR pathogens because they are resistant to nearly all antibiotics. CRE acquire this resistance mainly through two mechanisms: i) carbapenemase production and ii) changes in their cell structure (porin deficiency) that prevent antibiotics from entering the bacteria. Although porin deficiency causes about 15% of CRE, the exact impact of different porin mutations—especially in regions like Latin America—remains poorly understood. Additionally, the lack of rapid, affordable diagnostic tools in these areas delays effective treatment, leading to higher mortality, especially in cases of bloodstream infections. To address these challenges, I developed BADLOCK, a CRISPR-based diagnostic test that can rapidly identify bacterial species and AMR genes from blood cultures. BADLOCK is affordable, portable, and designed for resource-limited settings, aligning with World Health Organization recommendations. Preliminary data show it can accurately detect common bacteria and resistance genes, making it a promising tool for use in LMICs. This proposal focuses on characterizing porin mutations and expanding BADLOCK’s capabilities. I will sequence the genomes of a completed cohort of over 500 Enterobacterales isolates from Peru to identify porin mutations (among other AMR determinants), assess their contribution to resistance through genomic comparisons with other CRE cohorts, and conduct lab experiments to confirm the role of these mutations. CRISPR guides will be developed using novel computational strategies to target diverse species, common AMR genes, and validated porin mutations, thereby improving BADLOCK’s utility. Finally, it will be piloted in Peruvian hospitals to evaluate its performance in real-world settings. This project will improve diagnostic capacity in resource-limited settings and create the first catalog of isogenic strains with porin mutations. Additionally, it will provide critical insights into resistance mechanisms and support more effective management of bacterial infections in LMICs. As an infectious disease physician with an extensive background in bacterial genomics, I am well-poised to carry out these research goals. However, this proposal includes an ambitious training and career development plan that will further enhance the molecular biology and global health research skills necessary to launch my career as an independent, R01-funded investigator. The robust scientific and educational resources of Harvard Medical School and the Broad Institute provide an excellent training environment, and I have built a mentorship team consisting of world leaders in bacterial genomics, infectious disease diagnostics, and global health – all of whom are committed to supporting me in my success as an independent researcher.

NIH Research Projects · FY 2025 · 2025-08

Project Summary/Abstract The complex variations of the liver during surgical resection present a significant challenge for surgical navigation in minimally invasive liver surgery (MILS). This proposal aims to revolutionize MILS navigation by leveraging novel computer vision and deep learning algorithms to integrate multiple imaging modalities, including regular and near-infrared (NIR) laparoscopy, ultrasound, and MR/CT. Our first objective is to develop a pioneering dynamic simultaneous localization and mapping (SLAM) approach, enabling real-time tracking of liver surface variations from stereo laparoscopic videos. To mitigate the accumulative errors during lengthy procedures, we will utilize near-infrared tattoo technology to establish easily recognizable artificial landmarks. Our second objective is to develop an efficient 3D ultrasound volumetric reconstruction method and a comprehensive registration method between SLAM, ultrasound, and MR/CT data to improve the accuracy of localizing internal vessels and tumors, as well as minimize accumulative errors. Preliminary results have shown promise, validating the feasibility of our approach. Moving forward, we will integrate these algorithms into the 3D Slicer software to provide an intuitive interface to surgeons and validate our navigation system using both ex vivo and in vivo porcine livers. Our project benefits from a strong research team. Dr. Haoyin Zhou (PI) has extensive expertise in computer vision and deep learning, underpinning our innovative SLAM approaches. Dr. Jayender Jagadeesan (co-investigator) brings invaluable experience in surgical navigation, while Dr. Sandy Wells (co-investigator) is a renowned authority in ultrasound image registration and segmentation. Dr. Jiping Wang (Other Significant Contributor) contributes extensive expertise as an experienced general surgeon. Together, our team from Brigham and Women's Hospital, Harvard Medical School, is poised to make significant strides in advancing MILS navigation.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY/ABSTRACT The bacterium Staphylococcus aureus (S. aureus) is the second-leading infectious cause of death in the world. S. aureus spreads through the bloodstream, causing disseminated infections that can persist for weeks and are associated with high mortality. The ability of S. aureus to evade clearance by the immune system is a major barrier to the treatment of disseminated S. aureus infections. Upon dissemination, S. aureus can adopt a noncytotoxic phenotype. The presence of noncytotoxic bacteria is associated with non-resolving infections and with increased patient mortality during bloodstream infections. Despite mounting evidence that noncytotoxic S. aureus plays a major role during infection of humans, most research on S. aureus-immune interactions has focused on cytotoxic bacteria. It not clear how noncytotoxic S. aureus restricts immune responses, and how these activities impact the outcomes of infection. The research detailed in this proposal aims to determine how noncytotoxic S. aureus evades detection by the innate immune system. To address this knowledge gap, Dr. Jastrab developed a macrophage infection model using noncytotoxic S. aureus. This model demonstrated that a cell wall modification previously implicated in immune evasion, peptidoglycan (PGN) O-acetylation, blunts release of the inflammatory cytokine IL-1b. Release of IL-1b required a second cell wall modification, glycosylation of the cell wall component wall teichoic acid (WTA). Thus, these cell wall modifications have competing effects on immune signaling during noncytotoxic S. aureus infection. IL-1b release required activation of the cytosolic DNA receptor Absent in Melanoma 2 (AIM2). These data support the hypothesis that PGN O-acetylation and WTA glycosylation alter the availability of cytosolic DNA within macrophages to modulate immunity. The research described in this proposal explores key features of this hypothesis by defining the origin of AIM2-associated DNA, determining how cell wall modifications impact immunity during bloodstream infection, and identifying host factors that regulate AIM2 activation. Dr. Jastrab’s research will be supported by a team of mentors committed to fostering his scientific development. His primary mentor, Dr. Jonathan Kagan, is a world-renowned immunologist who will provide hands-on scholarly and technical training in molecular immunology. Dr. Kagan has a proven track record of successful mentorship, having supervised numerous trainees currently in tenure-track faculty positions. Drs. Jastrab and Kagan have devised a Career Development Plan that will ensure important professional benchmarks are met. To augment Dr. Kagan’s mentorship, Dr. Jastrab has assembled an Advisory Committee of scientists with expertise in microbiology, immunology, and clinical infectious diseases to provide scientific and professional guidance. The support of this K08 award will facilitate Dr. Jastrab’s transition to a role as an independent investigator characterizing molecular mechanisms of bacteria-immune interactions during infection.

NIH Research Projects · FY 2025 · 2025-08

STAT-CAT Project Summary / Abstract (maximum 30 lines) Oncology patients are at high risk for life-threatening venous thromboembolism (VTE) yet rarely receive anticoagulant prophylaxis due to bleeding risks. Thus, effective prophylaxis in oncology requires a method to reduce VTE without increasing hemorrhage. The primary aim of the proposed Statins to Prevent Cancer Associated Venous Thromboembolism (STAT-CAT) trial is to test whether rosuvastatin 20 mg daily for 12 months compared to placebo can safely prevent VTE in patients with newly diagnosed or recently relapsed cancer who are at increased thrombotic risk, are not planned to be anticoagulated, and who neither take nor otherwise qualify for statin therapy. Randomized trial data strongly support the core STAT-CAT hypothesis; as independently demonstrated in both the large-scale JUPITER and HOPE-3 trials, random allocation to rosuvastatin as compared to placebo resulted in a 47% reduction in VTE risk (HR 0.53, 95%CI 0.37-0.75) without any increase in bleeding. STAT-CAT is also supported by mechanistic studies which demonstrate decreased prothrombotic potential in those taking rosuvastatin through lipid independent pathways that include anti-inflammatory effects. STAT- CAT will enroll up to 4000 participants with recently diagnosed or relapsed cancer who have moderate- to-high VTE risk using an innovative pre-screening computable phenotype tool that will efficiently enable study coordinators to electronically pre-define potential trial participants at all sites in an identical manner while reducing subjectivity and enhancing applicability and generalizability. STAT-CAT will enroll through a proven “hub-and-spoke” engagement plan with committed high-volume academic cancer centers who have strong community partnerships to ensure a broad and generalizable tumor base with adequate representation of both sexes and of underrepresented populations; these sites see more than 75,000 STAT-CAT eligible patients annually. The primary endpoint of STAT-CAT is the incidence of pulmonary embolus, deep vein thrombosis of the upper or lower extremities, or fatal VTE during 12 months of active therapy or matching placebo. Secondary and tertiary aims include the impact of rosuvastatin on the composite rate of venous and arterial thrombosis, as well as evaluating safety with a focus on bleeding, transaminitis and myositis. Streamlined trial operations and pragmatic participant follow-up assessments will be used to minimize site burden while allowing virtually all other trial activities, including drug delivery, to be performed centrally in a consistent and cost-efficient manner. We believe the likelihood is high that generic rosuvastatin can significantly reduce rates of VTE in an oncology setting with no increase in bleeding; if successful, STAT-CAT will markedly improve thrombotic outcomes for large numbers of oncology patients with a safe and inexpensive intervention that avoids the hemorrhagic complications of conventional anticoagulation.

NIH Research Projects · FY 2025 · 2025-08

Project Summary Pulmonary hypertension (PH) is a heterogeneous disorder characterized by elevated pulmonary artery pressure. PH is a frequent complication of chronic lung diseases, most commonly chronic obstructive pulmonary disease (COPD-PH). Despite significant mortality risk associated with COPD-PH, diagnosis often occurs at an advanced disease stage and there are no approved therapies. Clinical trials evaluating the efficacy of pulmonary arterial hypertension (PAH) therapy in COPD-PH have by-and-large demonstrated no consistent benefit. However, cumulative data suggest a signal towards clinical improvement in certain COPD-PH subgroups. Heterogeneity of patient inclusion in these trials limit understanding of which COPD-PH patients may benefit from repurposing existing PAH therapies. Therefore, efforts to identify earlier disease, sub-phenotype COPD-PH patients and decipher clinical features associated with treatment response are critical to improving outcomes. To date, quantitative data from chest computed tomography (CT), a non-invasive and frequently performed diagnostic test in COPD patients, remains an underutilized resource poised to inform research for this morbid disease. To this end, I propose the study, “Computed tomography for early detection and phenotyping of pulmonary hypertension associated with chronic obstructive pulmonary disease with implications for treatment.” This study includes three foundational steps: 1) identify and validate quantitative CT imaging features for early detection of COPD-PH 2) apply advanced machine learning analytics to identify novel COPD-PH sub-phenotypes that inform mortality risk and 3) associate COPD-PH patient CT characteristics with therapeutic response to pulmonary vasodilator therapy. These aims are directly in line with a major NHLBI research priority, to identify disease sub- phenotypes and patients likely to respond to disease-specific treatments. Completion of this proposal will advance the field of COPD-PH by identifying imaging features predictive of early disease, novel disease sub- phenotypes with differential survival trajectories and CT characteristics predictive of response to the PAH therapy, Tadalafil, which is frequently used off-label in this population. The skills I anticipate gaining through this mentored project across three academic institutions, Brigham and Women’s Hospital/Harvard Medical School, the VA Boston Healthcare System and the T.H. Chan School of Public Health, will advance my career goal of becoming an independent investigator focused on PH phenotyping and clinical trial enrichment.

NIH Research Projects · FY 2025 · 2025-08

Project Summary Because randomized controlled trials often severely underrepresent frail and complex patients, it is pivotal to inform physicians’ treatment choices with drug safety and effectiveness studies based on real-world data. Electronic health records (EHR) contain rich clinical information and are among the most commonly used real- world data for causal effect estimation for pharmacotherapies. However, much of the essential data is embedded in the free-text clinical notes and reports (unstructured EHR). However, the traditional natural language processing (NLP) approaches require a labor-intensive process of knowledge acquisition and training dataset creation for each phenotype. This makes it not scalable for the large numbers of outcome phenotypes, risk stratification factors, and potential confounders (often>200) that need to be created for a typical pharmacoepidemiologic study. In contrast, developing Large Language Models (LLMs) is a more scalable approach because LLMs can be used to predict phenotypes not defined during the training stage. Yet, existing LLMs were not tailored for determining essential phenotypes for causal effect estimation of pharmacotherapies. Our objective is to build an LLM-based causal analytical platform for drug safety and effectiveness using two large multi-center EHR systems linked with Centers for Medicare & Medicaid Services (CMS) utilization, clinical assessment, and pharmacy dispensing data covering>1.3 million lives from 2000-2024. Our central working hypothesis is that our novel LLMs have robust performance in determining a wide variety of clinical phenotypes, including those not originally targeted during the training stage, and they can be used to reduce missing data for pharmacoepidemiology causal analysis. In Aim 1, we will train novel LLMs for phenotypes commonly used in drug safety and effectiveness causal analysis building on existing general-purpose LLMs. The reference standard of the target phenotypes will be provided by large-scale annotation based on structured data in the linked external clinical data. The targeted phenotypes include cognitive function, mental and functional status, pain levels, mood symptoms, adherence to chronic medications, and healthcare utilization outside of study EHR. In Aim 2, we will assess the generalizability of the novel LLMs to predict eight new categories of phenotypes (not already targeted in Aim 1) in an independent dataset. We will further optimize the LLMs based on the performance in the validation dataset. In Aim 3, we will determine the impact of LLM-derived features on causal effect estimation in three categories of highly relevant empirical drug safety and effectiveness studies in terms of bias and variance reduction. This LLM-based causal analytical platform can be used to generate a wide range of high-validity clinical features that enable causal effect estimation with adequate patient outcome phenotyping, confounding adjustment, and treatment effect heterogeneity evaluation, which is required for high-quality evidence for individualized prescribing.

NIH Research Projects · FY 2025 · 2025-08

STAT-CAT Project Summary / Abstract (maximum 30 lines) Oncology patients are at high risk for life-threatening venous thromboembolism (VTE) yet rarely receive anticoagulant prophylaxis due to bleeding risks. Thus, effective prophylaxis in oncology requires a method to reduce VTE without increasing hemorrhage. The primary aim of the proposed Statins to Prevent Cancer Associated Venous Thromboembolism (STAT-CAT) trial is to test whether rosuvastatin 20 mg daily for 12 months compared to placebo can safely prevent VTE in patients with newly diagnosed or recently relapsed cancer who are at increased thrombotic risk, are not planned to be anticoagulated, and who neither take nor otherwise qualify for statin therapy. Randomized trial data strongly support the core STAT-CAT hypothesis; as independently demonstrated in both the large-scale JUPITER and HOPE-3 trials, random allocation to rosuvastatin as compared to placebo resulted in a 47% reduction in VTE risk (HR 0.53, 95%CI 0.37-0.75) without any increase in bleeding. STAT-CAT is also supported by mechanistic studies which demonstrate decreased prothrombotic potential in those taking rosuvastatin through lipid independent pathways that include anti-inflammatory effects. STAT- CAT will enroll up to 4000 participants with recently diagnosed or relapsed cancer who have moderate- to-high VTE risk using an innovative pre-screening computable phenotype tool that will efficiently enable study coordinators to electronically pre-define potential trial participants at all sites in an identical manner while reducing subjectivity and enhancing applicability and generalizability. STAT-CAT will enroll through a proven “hub-and-spoke” engagement plan with committed high-volume academic cancer centers who have strong community partnerships to ensure a broad and generalizable tumor base with adequate representation of both sexes and of underrepresented populations; these sites see more than 75,000 STAT-CAT eligible patients annually. The primary endpoint of STAT-CAT is the incidence of pulmonary embolus, deep vein thrombosis of the upper or lower extremities, or fatal VTE during 12 months of active therapy or matching placebo. Secondary and tertiary aims include the impact of rosuvastatin on the composite rate of venous and arterial thrombosis, as well as evaluating safety with a focus on bleeding, transaminitis and myositis. Streamlined trial operations and pragmatic participant follow-up assessments will be used to minimize site burden while allowing virtually all other trial activities, including drug delivery, to be performed centrally in a consistent and cost-efficient manner. We believe the likelihood is high that generic rosuvastatin can significantly reduce rates of VTE in an oncology setting with no increase in bleeding; if successful, STAT-CAT will markedly improve thrombotic outcomes for large numbers of oncology patients with a safe and inexpensive intervention that avoids the hemorrhagic complications of conventional anticoagulation.