Brigham And Women'S Hospital

NIH Research Projects · FY 2026 · 2019-09

Abstract Epstein-Barr virus (EBV) is highly associated with multiple types of lymphomas, which occur at elevated frequencies in people living with HIV. These include Hodgkin, Burkitt, post- transplant, plasmablastic, primary central nervous system and diffuse large B-cell lymphomas, which cause a large burden of disease in the HIV+ population. Despite highly active antiretroviral therapy, HIV+ individuals have elevated risk for EBV+ malignancies, in particular Hodgkin lymphoma. In people living with HIV, nearly all Hodgkin lymphoma and over 40% of immunoblastic lymphomas are EBV+. The EBV oncogene Latent Membrane Protein 1 (LMP1) is highly expressed in many HIV-associated lymphomas, including Hodgkin lymphoma. Yet, much remains to be learned about critical LMP1 roles in lymphomagenesis, in particular with HIV co-infection. Relatedly, much has remained unknown about specific LMP1 roles in germinal center B-cells, a key B-cell state from which most EBV+ lymphomas arise, and how HIV co- infection alters LMP1-dependent lymphomagenesis. Our preliminary data highlights that two LMP1 C-terminal tail domains are non-redundantly important for primary human B-cell transformation at distinct early timepoints post-infection, that each blocks distinct programmed cell death pathways, that they synergistically induces PD-L1 checkpoint signaling, and that germinal center cytokines are important determinants of LMP1 expression level. We have also constructed recombinant EBV with point mutants that abrogate signaling by either or both LMP1 transformation essential (TES) regions and developed a novel model of EBV/HIV co-infection of a novel secondary lymphoid microenvironment. Our aims test the central hypothesis that HIV co-infection dysregulates germinal center B-cell LMP1 expression and signaling, resulting in altered EBV+ B-cell reservoirs, checkpoint signaling and contributing to the observed elevated rates of EBV+ lymphomas. In Aim 1, we will define key LMP1 TES1 and TES2 signaling roles in B-cell oncogenic transformation and their relationship with HIV co-infection. In Aim 2, we will identify how the secondary lymphoid microenvironment and HIV coinfection alter LMP1 expression and oncogenic effects on LMP1 target gene expression. In Aim 3, we will identify how HIV/EBV co-infection alter checkpoint signaling, B-cell development and activation, and responses to checkpoint blockade. Collectively, these studies will newly characterize key aspects of LMP1 signaling in oncogenic B-cell transformation, including with HIV co-infection, and will lay the foundation for novel therapeutic approaches.

NIH Research Projects · FY 2025 · 2019-09

The evidence-based use of prescription medications has led to substantial improvement in healthy aging. Despite this, the use of medications by patients and providers remains suboptimal. Many patients are not prescribed guideline-recommended therapies from which they would benefit; among those for whom appropriate treatment is initiated, almost half do not adhere over the long-term; and others receive potentially- hazardous medications with an unfavorable balance of risks and benefits. The result: preventable adverse health outcomes and health spending for middle-aged and older adults. While many factors influence the suboptimal use of prescription medications, individual, interpersonal and institutional behaviors are central. As a result, existing intervention to address these issues have attempted to remind, reward, motivate, simplify or otherwise change behavior. Unfortunately, these approaches have only been modestly effective and even among those do work, behavior change is rarely sustained over the long- term. The results can be explained by the lack of integrating behavioral principles when designing interventions, a limited focus on evaluating how to deliver them over the long term, and the inherent challenges in delivering precise and personalized behavior change at population scale. Thus, the Brigham and Women’s Hospital Roybal Center for Therapeutic Optimization using Behavioral Science will continue to focus on the thematic area of promoting adherence and maintenance of long-term behavior change. The structure and activities of the proposed Center will be based upon 4 key principles: (1) a multi-disciplinary approach; (2) the testing of principle-driven interventions in real-world settings; (3) the explicit testing of mechanisms of action, and (4) the use of novel analytic methods and technological approaches to gain a deeper understanding of behavioral mechanisms and to personalize interventions. Based on these principles, our Center will have the following Specific Aims:(1) to oversee a translational research program for the testing of principle-driven, potent, practical, scalable and sustainable behavioral interventions to enhance the appropriate prescribing and use of evidence-based medications.; (2) to strategically direct and to provide scientific oversight, fiscal and operational support to ensure the successful completion of behavioral interventions funded by the Center.; and (3) to conduct trials evaluating principle-drive interventions that aim to sustain behavior change for the use of evidence-based medications. The proposed Year 1 studies conducted in partnership with large delivery systems and testing novel approaches to promote the deprescribing of high- risk medications and to support adherence to evidence-based preventive therapies. The expected impact of the Roybal Center for Therapeutic Optimization using Behavioral Science is that it will develop principle-driven interventions that will readily translate to improvements in healthy aging and will also advance our fundamental understanding of how health behaviors can be effectively sustained.

NIH Research Projects · FY 2026 · 2019-09

PROJECT SUMMARY Glioblastoma (GBM), the most common malignant brain tumor and one of the most fatal of cancers, remains impervious to treatment with the current standard of care (SOC) therapies. Even immunotherapies like immune checkpoint inhibitors (ICI) have failed for GBM despite their success with other cancers. One critical reason for this failure is that the brain’s GBM tumor microenvironment (TME) is highly immunosuppressive. To change the GBM microenvironment, over the last period of funding we have been exploring the use of oncolytic viruses (OV), based on herpes simplex virus type 1 (oHSV). Of relevance, we have completed a “first-in-human” clinical trial in subjects with GBM. Recovery of the brain tumors after therapy revealed persistence of the oHSV in some patients, highly significant infiltration of CD8+ and CD4+ T cells with an effector transcriptomic signature, and a significant correlation between subject survival and changes in T cell metrics. Very interestingly, pre-existent and/or seroconverted HSV1 serology was a highly significant independent predictor of subject survival, suggesting the existence of anti-HSV1 T cell memory that could be stimulated by tumor injection with the oHSV to differentiate into effector T cells that would then aid in the anticancer effect. In fact, we have found that patients with pre-existent HSV1 immunity or that seroconverted were the ones who were more likely to clear HSV1 antigen from injected GBMs. Two questions arise from these findings: 1- what is the role of antiviral HSV1 “bystander” T cells in therapy efficacy, and 2- what is the significance of oHSV antigen persistence in injected GBMs? Our overall hypothesis, informed by our clinical trial data, is that oHSV’s antiGBM effectiveness is based on expansion from “bystander” anti-HSV1+ memory T cells into effector T cells, whose activity is marked by infiltration and “clearance’ of replicating oHSV previously injected into the GBM. To test thus hypothesis, we plan to pursue the following aims: Aim 1- Determine if a pre-existent anti-HSV1 memory T cell population differentiating into an effector T cell population infiltrates syngeneic murine GBMs infected with oHSV; Aim 2- Determine if antiviral bystander T cells aid antitumor T cells in tumor rejection upon oHSV administration, and Aim 3- Characterize whether oHSV persistence in tumors stimulates further effector antitumor T cell responses or leads to terminal exhaustion of T cells. The impact from these studies will be to significantly inform whether oncolytic immunotherapy depends on pre-existent immunity to the cognate OV, leaving to avenues for improvements in the next phase of clinical trials for this modality.

NIH Research Projects · FY 2024 · 2019-09

Project Summary/Abstract Liver deformation leads to difficulties in tumor localization during minimally invasive liver surgery (MILS). The goal of this proposal is to develop an efficient surgical navigation tool for MILS by compensating for liver deformation and mapping preoperative data to the patient’s anatomy. Specifically, we will develop a non-rigid simultaneously localization and mapping (SLAM) approach to estimate the deformation of liver surface from stereo laparoscopy videos. We will develop machine-learning methods to detect landmarks and perform non- rigid registration. The algorithms will be implemented on a GPU to achieve real-time. Preliminary data has demonstrated the feasibility. During the R00 phase, we will mainly address the clinical needs and develop novel ways to provide intraoperative guidance. This project will greatly improve the tumor resection accuracy in MILS. The candidate for this award Dr. Haoyin Zhou is a postdoc at Surgical Planning Laboratory (SPL), Brigham and Women’s Hospital (BWH) and Harvard Medical School (HMS). Dr. Zhou has extensive experience and expertise in computer vision, machine learning and their applications in medicine. BWH is an international leader in basic, clinical and translational research on human diseases, and has established multiple research programs to promote the work and professional career development of young investigators. National Center for Image Guided Therapy, and Advanced Multi-modality Image Guided Operating (AMIGO) suite will greatly support this research. Dr. Zhou’s long-term research goal is to develop and apply advanced computer vision and machine learning technologies to improve understanding, diagnosis, treatment, and prevention of diseases for better health care. His long-term career goal is to become an independent investigator working at the frontier of medical image processing and image-guided therapy. To achieve these goals, Dr. Zhou plans to receive more education and training in the following four areas: (1) Critical training in conducting translational research in the hospital environment with surgeons and radiologists, (2) knowledge in the development of technologies for surgical guidance, (3) training in machine learning and its applications in medicine, and (4) training on writing grant applications independently and seeking funding. Dr. Zhou will participate in formal courses selected from Harvard, Harvard Catalyst, MIT CSAIL and Stanford Courses. He will attend weekly seminars at BWH, HMS and MIT. He will also attend one or two academic conferences per year to discuss his work and meet with experts in the field. A strong mentoring team, including one primary mentor, three co-mentors, and two collaborators, has been organized for the K99 phase of this award, which will provide solid support on both research and career development to Dr. Zhou based on their well-established expertise in diverse research fields. Prof. William M. Wells III (primary mentor) is a professor in medical image processing. Prof. Jayender Jagadeesan (co-mentor) is an assistant professor in surgical robotics and surgical navigation. Drs. Ali Tavakkoli and Jiping Wang (co- mentors) are experienced surgeons. All mentors and collaborators are from BWH, HMS.

NIH Research Projects · FY 2025 · 2019-09

Project Summary/Abstract The stability of the mammalian genome depends on a remarkable toolkit of surveillance, repair, signaling, and checkpoint mechanisms. Mutations in the DNA itself, or corruptions in many of these genome integrity mechanisms, can result in disease including cancer. Given the importance of mutation and cell division in tumorigenesis, two central pathways in genome integrity are the DNA damage response, and the cell division cycle. A more complete understanding of these pathways is crucial to our knowledge of normal cellular development in homeostasis, stem cell biology, the etiology of cancers, as well as for technical applications like gene targeting. This project seeks to tackle outstanding problems in these fields in order to elucidate fundamental molecular cell biology mechanisms that can improve therapeutic outcomes in cancer. The F99 phase is focused on double-strand break (DSB) repair and the control of end resection, a critical molecular ‘choice’ of whether to repair a DSB by blunt end-joining or by homologous recombination. I revealed novel mechanistic insights about the protein controlling this choice, 53BP1, findings relevant to the treatment of BRCA1-deficient cancers with PARP1 inhibitors. We found that—instead of blocking end resection as was generally thought—53BP1 recruits polymerase alpha to counteract resection by fill-in synthesis of the resected DSB. In the remainder of the dissertation work, I will explore how BRCA1 and 53BP1 regulate resection and fill-in synthesis in light of this new model. I will also gain the necessary experience and exposure scientifically and professionally to transition to a cancer-focused postdoc in a stellar lab. For the K00 phase, I will shift my focus and approaches to study mechanisms preserving genome integrity in the critical window of mitosis, where diverse chromatin biology pathways converge. I plan to learn and implement high throughput screens, computational analysis of larger, statistically-powerful data sets, as well as in vivo modeling in the mouse, and analysis of sequencing data from human tumor samples. These new approaches, coupled with my already strong background in genetics, microscopy, and biochemistry, will allow me to address the most pressing and challenging issues in genome integrity and cancer biology today. With the aid of this award, I intend to continue my research contribution and gain experience in order to become a leader of my own cancer-focused lab and a leader in the field of genome integrity.

NIH Research Projects · FY 2025 · 2019-09

Project Summary Conventional dendritic cells (cDCs) are central regulators of the adaptive immune response, and have been shown to be required for the induction of T cell-mediated anti-tumor immunity. In particular, a subset of cDCs (cDC1) is responsible for transporting tumor antigens to the lymph node and cross presenting antigen in order to activate cytotoxic T lymphocytes, thereby inducing an anti-tumor response. We have recently observed TIM- 3 (T-cell immunoglobulin and mucin domain containing-3) expression on cDCs in human and murine mammary tumors, and found that TIM-3 blockade improved response to standard-of-care paclitaxel chemotherapy in models of triple-negative and luminal B disease. This occurred through increased chemokine expression by cDCs, without a corresponding in T cell infiltration, leading me to hypothesize that the spatial localization of cDCs and T cells within tumors is a critical determinant of successfully immunotherapy. In the F99 portion of this application I will therefore seek to determine if TIM-3 blockade alters the spatial organization of T cells, and if this is responsible for therapeutic efficacy. In the K00 phase of this proposal I will expand these studies to evaluate whether cDC/T cell clustering is a prerequisite for response to immune checkpoint blockade and other therapeutic modalities.

NIH Research Projects · FY 2026 · 2019-09

Abstract Measuring the extent of lymph node disease burden (LNDB) is crucial for diagnosing and predicting cancer outcomes. Yet, accurately quantifying LNDB remains a challenge in clinical practice, hindering both clinical trials and patient care. This Academic-Industry Partnership proposes to address this unmet need by developing accurate and time-efficient LNDB quantification tools specifically for oncology clinical trials. Our multidisciplinary team includes extensive complementary expertise in tumor metrics, machine learning, translational technology, cancer imaging, and clinical trials informatics. The members of the team include leading academic researchers from Dana-Farber Cancer Institute, Brigham and Women's and Massachusetts General Hospitals with industry leaders from Yunu, Inc., a commercial clinical trials imaging informatics platform vendor used by 18 Cancer Centers, including 12 NCI-designated facilities. Current software and algorithms for quantifying LNDB fall short, demanding excessive manual work that impedes the use of valuable prognostic factors like total metabolic tumor volume (TMTV). To address this unmet need, we leverage unique resources: a vast collection of expertly annotated contrast CT and PET/CT datasets, a proven platform for integrating AI tools into clinical trials workflows, and an experienced team with a successful track record in deploying AI imaging solutions. A key aspect of our work involves continuously improving these quantification tools through ongoing data collection from clinical trials, ensuring their real-world effectiveness. Our project focuses on three main aims: (1) Optimize semi-automated 3D lymph node annotation, segmentation, and analysis, including enhancing technologies for data access, optimized image annotation, scalable training, and efficient deployment and integration to the Yunu system, (2) Create tools for extracting clinically relevant information from both CT and PET images to provide an integrated PET/CT clinical review mode, and (3) Integrate a data analytics platform to extract new insights within Yunu's clinical trial informatics environment. Completing these aims will directly address the critical need for quantitative LNDB assessment in precision cancer treatment. Moreover, it will pave the way for similar segmentation and quantification tools for solid tumors and other diseases. Our team has unique access to many thousands of annotated images and possesses the combined academic and commercial expertise to turn these innovative goals into reality, ultimately providing a unique set of tools for assessing LNDB in patients enrolled in clinical trials.

NIH Research Projects · FY 2026 · 2019-08

Project Summary / Abstract This project aims to improve needle placement accuracy for image-guided prostate interventions, including biopsy and focal treatment. Building upon the success of the previous cycle, the project seeks to enhance the robustness and effectiveness of the technology in complex anatomical structures, thereby aiding clinical translation for prostate cancer care and broader applications. Percutaneous needle placement is a critical procedure in both the diagnosis and treatment of prostate cancer. Although these procedures are often assisted by an external needle-guiding device for accuracy, the unpredictability of needle deflection due to interactions with varying tissue densities frequently necessitates multiple placement attempts. This prolongs the procedure time and can lead to excessive tissue damage. The project’s previous cycle aimed to tackle this problem by developing two technologies: a fiber-Bragg-grating (FBG)-based shape-sensing needle (sensorized needle) for real-time feedback and a data-driven needle steering algorithm (COADAP) for active compensation of needle deflection. Together, these technologies created a closed-loop adaptive needle placement system, enhancing needle placement accuracy. However, the team identified these technologies’ limitations when the needle encountered complex, interconnected multistructural anatomy. In such situations, the needle’s interactions with different structures led to significant deflection, limiting the technology’s application in clinical settings. Therefore, this phase aims to address this challenge by extending the capabilities of the sensorized needle and COADAP algorithm. The research plan comprises three specific aims: (Aim 1) Develop a multi-core FBG sensorized needle for robust distributed shape sensing: We will enhance the design of sensorized needles using multi-core fiber (MCF) sensors for robust and distributed needle shape sensing. We will develop a machine-learning model to predict the needle trajectory using real-time shape information. (Aim 2) Extend the COADAP algorithm for interconnected multistructural anatomy: The objective is to compensate for needle deflection in interconnected multistructural anatomy. This involves the development of an extended COADAP algorithm, called Shape- Control COADAP (SC-COADAP), to account for the full needle shape in model predictive control. (Aim 3) Validate the sensorized needle with COADAP in interconnected multistructural anatomy: We will test the hypothesis that adaptive needle placement with the MCF sensorized needle and SC-COADAP meets the required accuracy. This will be done via ex vivo and in vivo validation, using a multistructural anatomy-mimicking phantom and swine models, respectively.

NIH Research Projects · FY 2026 · 2019-07

Project Summary/Abstract Sepsis is life-threatening organ dysfunction resulting from a dysregulated host response to infection. Two adaptation programs are set off during sepsis, one that mobilizes the immune system to enact resistance mechanisms directed against the pathogen, and one that tolerizes tissues against the harmful consequences of the response to infection. Recent studies support unique metabolic frameworks that mediate disease resistance and tolerance mechanisms. We are interested in the role of metabolites in mediating disease tolerance to sepsis, particularly how metabolites control the toxic mediators unleashed on tissues during sepsis. It has been well established that circulating hydrogen peroxide is elevated in human sepsis and negatively correlated with survival. Critically, antioxidant mechanisms such as cellular glutathione pools are rapidly depleted during sepsis due to excess hydrogen peroxide production. This, in turn, leads to high peroxide concentration inside cells, cell death, and peroxide release into the systemic circulation. We hypothesize that neutralizing extracellular hydrogen peroxide is crucial for establishing disease tolerance to sepsis. This proposal builds on our discovery in the previous funding period that branched-chain ketoacids (BCKAs) – metabolic products of branched-chain amino acid (BCAA) metabolism – function as antioxidants that directly neutralize hydrogen peroxide. Our studies further demonstrated the protective function of BCKAs in mouse sepsis models and indicated that BCKA levels are positively correlated with survival in human sepsis patients. Finally, we found that lactate dehydrogenase (LDHA) compromises BCKA antioxidant activity during sepsis. We will continue to focus on three major goals using a combination of biochemical engineering approaches, global and targeted metabolomics, and computational analysis methods. Goal 1: Stabilizing extracellular BCKAs to enhance sepsis survival. BCKAs are rapidly cleared from the circulation and utilized as cellular fuel, or alternatively depleted by LDHA during sepsis. We seek to engineer BCKAs and other small molecule derivatives in order to prevent cellular uptake and depletion during sepsis and enhance BCKA capacity to promote disease tolerance and survival. In Goal 2, we seek to establish circulating BCKAs and their derivatives as early prognostic biomarkers in sepsis. Only a handful of clinical biomarkers were shown to have prognostic value in sepsis, highlighting the unmet need in identifying reliable early biomarkers. We will take a human-centric reductionist approach to determine the extent to which BCAA-pathway metabolites, including BCKAs and their derivatives, could predict disease outcome across sepsis endotypes. And in Goal 3, we will identify broadly acting metabolites that enhance sepsis survival. We have established global metabolomics and computational prioritization methods in mouse sepsis models. We will leverage these pipelines towards characterizing metabolite landscapes in diverse sepsis patients and identify metabolites with broad protective activity. Together, we hope that our progress may unlock the potential of metabolite-mediated therapeutics for sepsis.

NIH Research Projects · FY 2024 · 2019-05

Parkinson's disease (PD) and Dementia with Lewy bodies (DLB) produce profound motor and cognitive impairment associated with aggregation of α-synuclein (αS). Female sex is commonly reported to delay the age of onset and to produce milder phenotypes, but the reasons are unknown. Accumulation of αS is increasingly implicated in familial and sporadic forms of these synucleinopathies. Our lab has discovered that female sex preserved a part of physiologically folded, aggregate-resistant tetrameric αS in PD-type mice, supporting published evidence for the existence of normal multimeric αS forms in healthy brain. During the first grant period, we have analyzed female sex and elevation of brain estradiol (by the estradiol prodrug DHED) and showed it can normalize the αS tetramer- monomer ratio and decrease early LB-type aggregates. Given this progress, we now wish to extend this novel hypothesis to answer certain key questions about protective estrogen pathways that could be used as disease modifying treatments. Our proposed new experiments will be enabled by our early-onset, progressive mouse models in which the E46K-like tetramer abrogating αS mutation (3K) caused sex dimorphism early in the PD-type neuropathology development. In aim 1, we will determine the age- and sex dependencies of αS pathological aggregation for WT, 1K and 3K in premature and mature mice. The studies will be controlled in mice with depleted estrogen. In aim 2, we will investigate the role of extranuclear and synaptic estrogen receptor on the temporal relationship between changes in synaptic function (electrophysiological studies) and alterations in αS pathologic aggregation (histopathology and biochemical studies) in genetic model mice with membrane-only estrogen receptor alpha. We will further examine the effectiveness of a novel therapy that increases palmitoylation (using a small molecule inhibitor for acyl-protein thioesterase 1) and thereby the level of synaptic estrogen receptors. In aim 3, we will determine, whether the shared αS tetramer-abrogation by PD risk factors (GBA1-L444P, GBA1-E326K) known for pathologic excess of soluble wildtype αS monomer accumulation and that produces more severity by male sex, are also responsive to DHED treatment. We will compare these with our novel familial G51D-and amplified (3D) mice with excess soluble mutant αS. The results of these studies will be far reaching as they will provide the foundation to understanding mechanisms through which estrogen prevents αS dyshomeostasis in the brain of robust PD-type mice in vivo, to improve and create neuroprotective treatments in PD, DLB and Gaucher’s PD.

NIH Research Projects · FY 2025 · 2018-09

ABSTRACT Chronic kidney disease (CKD) affects 1 in 7 adults in the United States. Despite its high prevalence, approximately 90% of those with kidney disease are not aware they have it. In addition, hypertension (HTN) remains a leading cause of end stage renal disease and greatly impacts the risk for adverse cardiovascular outcomes in the CKD population. Primary care physicians (PCPs) are uniquely positioned to effectively manage CKD through early identification and use of evidence-based treatments, but they face time-constraints and competing demands. Clinical decision support (CDS) tools can bridge that gap by utilizing data within the electronic health record (EHR) to provide recommendations. In our prior work, we incorporated behavioral economic principles and human-centered design in a CDS tool to deliver tailored, actionable, and evidence-based recommendations for the management of HTN within a primary care CKD population. We demonstrated that the CDS had a statistically significant effect on lowering systolic blood pressure (SBP), in addition to increasing prescription for evidence-based renin-angiotensin-aldosterone system inhibitor (RAASi) therapy. In this project, we aim to establish the generalizability of these findings by implementing the CDS tool across three health systems. We will also update the CDS to address medication nonadherence and to incorporate new clinical practice recommendations for sodium glucose co-transporter-2 inhibitors (SGLT2i). The specific aims of this project are to 1) adapt and pilot test CKD CDS in multiple health systems, 2) determine the effectiveness of the CDS alerts on lowering SBP and increasing RAASi/SGLT2i prescriptions in a pragmatic randomized trial in 36 primary care clinics across three health systems and 3) use two implementation frameworks, TAM3 and Proctor’s Implementation Outcomes Framework, to assess implementation outcomes and factors influencing implementation in order to inform further dissemination. In summary, this renewal application seeks to establish the scalability of a CDS tool, based on behavioral nudge alerts, across diverse patient populations and various EHR workflows for the management of HTN in adults with CKD within primary care settings.

NIH Research Projects · FY 2026 · 2018-08

The broad objective guiding our research is to conduct analyses that will inform health care providers and policy makers on how to deliver high quality, value-based care for all patients with knee OA. Symptomatic knee OA is a prevalent, disabling and costly disease that affects over 14 million Americans and accounts for $27 billion/year in healthcare expenditure. Lower educational attainment, having no health insurance, and residence in rural, low-resource areas, have been shown to contribute to worse outcomes of knee OA. These challenges are further exacerbated by the gap between ‘what we know’ and ‘what we do’. Strong evidence suggests that exercise is efficacious for pain control, but adequate implementation of exercise programs is hindered by a lack of infrastructure. Telemedicine may become a paradigm-shifting tool in many facets of OA management. Telemedicine is convenient but its adoption depends on patients’ digital literacy and requires careful consideration of how to integrate telemedicine in the continuum of OA care. The armamentarium of intraarticular injections is growing rapidly, but questions about their efficacy, lack of standardization, and high cost raise concern among providers, while aggressive advertising campaigns lead to increased demand for these injections from patients with knee OA. In 2018, the Centers for Medicare & Medicaid Services moved total knee arthroplasty (TKA) off the inpatient-only list, opening opportunities for outpatient/ambulatory TKA delivery. This shift presented potential economic savings for payers but raised questions about patient selection and its impact on patients with knee OA living in rural areas. We propose to enhance the capabilities of the Osteoarthritis Policy (OAPol) Model to examine the value of prioritizing knee OA management strategies based on their potential to optimize health care outcomes. We focus on three major aspects of OA management with sizeable gaps between evidence and current practice: 1) optimizing the value of telemedicine-based OA management and promoting its use among persons with low educational attainment and low digital literacy, living in rural areas; 2) establishing the value of alternative intraarticular injections with various formulations; 3) assessing the value of outpatient/ambulatory TKA and comparing resulting health and economic gains. We propose to use innovative modeling methods to assess the value of telemedicine, orthobiologics, and outpatient TKA and to identify strategies to improve the uptake of these treatments. This study will guide clinicians in optimizing their efforts to promote care that is effective and cost-effective.

NIH Research Projects · FY 2026 · 2018-07

PROJECT SUMMARY There is an increasing focus on understanding the role of microglia in neurodegenerative disorders including late-onset Alzheimer’s disease (LOAD), a disease defined by the accumulation of amyloid beta rich plaques and neurofibrillary tangles containing tau. Microglia are proposed to play a variety of critical roles during disease progression including synaptic engulfment, cytokine release, and phagocytosis of amyloid beta (Aβ). Further, recent GWAS studies have implicated innate immune processes in LOAD, supporting the importance of understanding the neuroimmunological processes underlying the risk and progression of AD. All recent large- scale GWAS have identified SNPs at the INPP5D locus that are significantly associated with AD. INPP5D expression is largely restricted to microglial cells in the human adult brain and we have confirmed previous findings that RNA levels of INPP5D are elevated in AD brain. However, through quantitative western blotting, we show that protein levels of full length, water-soluble INPP5D are reduced in AD brain. To study the functional consequences of reduced INPP5D, we used both pharmacological inhibition and CRISPR-Cas9 genome engineering to lower INPP5D activity in human iPSC-derived microglia. Through unbiased RNA and proteomic profiling and a series of pharmacological manipulations, we demonstrated that reduction of INPP5D activity induces changes in immune signaling and, more specifically, the activation of the inflammasome. These studies have raised important questions that we aim to address in this proposal regarding the constitution of INPP5D in microglia in the Alzheimer’s brain (aim 1), the molecular mechanism(s) linking INPP5D and inflammasome activation (aim 2), and the functional consequences of loss of INPP5D activity and inflammasome activation in microglia on astrocytes and neurons (aim 3). In aim 1, we will utilize quantitative immunostaining, sequential extraction and western blotting, and ELISA to deeply interrogate INPP5D levels and markers of inflammasome activation across a large cohort of human brain samples and iPSC-derived microglia cultures. Aim 2 interrogates candidate pathways that may link INPP5D activity with inflammasome activation that arose from our preliminary analyses. The first of these involves upregulation of PLA2G7, second through dysregulation of scavenger receptors and the third through disruption of lysosome function. Finally, in aim 3 we utilize co-culture models of iPSC-derived neurons, astrocytes and microglia and a conditional INPP5D knock out mouse model to determine the consequences of reduction of INPP5D levels in microglia on neuron and astrocyte biology in the context of AD relevant environments. Together, these studies will provide important new insights into our understanding of the fundamental role of INPP5D in microglia in health and disease, regulation of inflammasome activation in human microglia, and the consequences of sub-lytic inflammasome activation in microglia on neuron and astrocyte biology.

NIH Research Projects · FY 2026 · 2018-04

PROJECT ABSTRACT Diabetes is the leading cause of chronic kidney disease (CKD). When combined, diabetes with CKD exponentially increases risk for cardiovascular disease and death. Preventing or delaying CKD in diabetes would substantially decrease these adverse outcomes, save billions in healthcare expenditures, and improve quality of life for those at high-risk for dialysis-dependent kidney failure. Emerging evidence strongly indicates that primary aldosteronism (PA) pathophysiology is a causative mechanism for the development and progression of CKD in diabetes. PA pathophysiology is characterized by relatively non-suppressible and renin-independent aldosterone production that causes excessive activation of the mineralocorticoid receptor (MR). This maladaptive activation of the MR induces inflammation and fibrosis that contributes to CKD and cardiovascular disease. Our work in R01DK115392 has re-defined primary aldosteronism. We have shown that PA pathophysiology exists across a broad continuum of severity, from mild (or subclinical) to overt (or severe); in this regard, PA is better considered to be a pathophysiologic syndrome. The prevalence of PA pathophysiology is high and almost entirely unrecognized. Our work, and that of others, has demonstrated that PA pathophysiology can be detected in 10-25% of the general population; however, despite this alarming prevalence, the rates of testing for PA, or empiric MR antagonist use, in these high-risk populations is abysmal and rarely exceeds 2%. The scope of this problem is magnified by the fact that randomized clinical trials in patients with diabetes have established the exceptional efficacy of MR antagonists for reducing albuminuria, lowering the risk of CKD progression, incident end-stage kidney disease, and incident cardiovascular outcomes. Despite demonstrating this efficacy, these landmark trials did not investigate the role of PA pathophysiology. Our results from R01DK115392 represent the most likely hypothesis to explain the reno-protective benefits of MR antagonists: there is a prevalent, progressive, and unrecognized, spectrum of PA pathophysiology and MR activation in people with diabetes that increase their risk for CKD. In this renewal, we will extend our work in R01DK115392 by conducting a mechanistic cohort study to deeply characterize PA pathophysiology and MR activation in individuals with diabetes and at-risk for incident or progressive CKD. A thorough understanding of PA pathophysiology as an early mechanistic contributor to CKD in diabetes will provide critical evidence to support broader use of MR antagonists to prevent CKD development and progression in diabetes. Participants with diabetes and CKD3A, or at high-risk for developing CKD, will undergo characterization of PA pathophysiology using profiling of steroids indicative of dysregulated aldosterone synthase activity, measurement of urinary extracellular vesicles containing proteins indicative of pathology MR activation, and large-scale unbiased proteomics to explore biomarkers of fibrosis and aldosterone-MR interactions. Participants will be followed, and measures repeated longitudinally, for 3 years.

NIH Research Projects · FY 2026 · 2018-02

PROJECT SUMMARY Tuft cells are a specialized epithelial cells (EpCs) that initiate airway type 2 inflammation (T2I) through their generation of IL-25 and pro-inflammatory lipid mediators, cysteinyl leukotrienes (CysLTs). We previously reported that airway tuft cells are indirectly activated by common aeroallergens through damage-associated molecular patterns (DAMPs), including the release of ATP and the activation of P2Y2 on tuft cells. Because tuft cells recognize tissue damage, and are detected in settings of airway injury in mouse and humans, we and others have speculated that they may have a role in lung repair, but thus far no such function has been demonstrated and the mechanism(s) by which tuft cells develop in the distal airways are unknown. Our preliminary data demonstrate an important feed forward loop by which tuft cells promote airway remodeling. We find that, in the setting of established inflammation, murine tracheal tuft cells generate CysLTs, activate several airway epithelial progenitor populations that express the leukotriene E4 receptor OXGR1, and drive aberrant airway remodeling. Importantly, we find that elements of the tuft cell and regenerative pathways seen in the murine trachea, are also expressed in allergen-challenged murine lung, and in the sinonasal mucosa of patients with the chronic rhinosinusitis with nasal polyposis (CRSwNP). This grant aims to define tuft cell and CysLT influence on wound repair in these settings, and to define the functional sequelae. To examine this, Aim 1 and 2 will use two murine models of tracheal and lung T2I. Several fate-labelled reporter mice will be tracked and crossed to null strains. Bulk and scRNA-seq will be used to define the altered molecular pathways in regenerating epithelium and several functional assays will be tested. Aim 3 will assess airway repair in patients with CRSwNP using scRNA-seq, spatial multiplexed fluorescent in situ hybridization, and ex vivo analysis. The resulting information will allow us to understand immune epithelial cross talk in the human airway and the role of CysLTs and OXGR1 in driving remodeling.

NIH Research Projects · FY 2026 · 2018-01

Project Summary/Abstract Dr, Mora is a cardiologist cross-trained in epidemiology who has devoted her career to patient-oriented research (POR) in cardiovascular prevention, focusing on the discovery and translational applications of lipid biomarkers of cardiometabolic disease risk, and developing innovative approaches and therapies for preventing cardiometabolic disease. Her POR research has impacted national and international guidelines for clinical practice, In the first K24 cycle, she has mentored more than fifteen preand postdoctoral trainees in POR projects related to lipids, statins, and cardiovascular risk. This has been highlighted in recent years by the achievements of her mentees in presenting their work nationally and internationally, The K24 renewal award will allow her to extend her successful mentoring program. The overall goals of this K24 award are to 1) grow and expand her POR program by providing the next-generation of cardiovascular investigators with opportunities for precision POR in prevention by incorporating technologic advances in high-throughput metabolomics with clinical and health record data as a strategy to improve cardiovascular outcomes; and 2) strengthen and build upon her mentoring program in global cardiovascular health by expanding her POR program to examine cardiometabolic risk factors contributing to premature cardiovascular events. Cardiovascular disease remains the number one cause of death globally, and > 70% of cases can be attributed to cardiometabolic risk factors. Patients with uncontrolled cardiometabolic risk factors are at high risk of suffering from premature and recurrent cardiovascular events. The candidate's ongoing POR projects, exceptional institutional resources, and cost-effective local and international collaborations provide a nurturing environment for the training and career development of junior investigators in POR cardiovascular research. The new research aims proposed in this award will examine a panel of targeted metabolomics with risk of cardiovascular disease from diverse patient populations to better understand how cardiometabolic risk factors could be targeted for precision preventative diagnostic and therapeutic targets. This research program will provide excellent POR opportunities for junior investigators and trainees to be mentored across the full spectrum of clinical, epidemiological, and molecular studies. Results from this mentored POR program will guide future efforts directed at cardiovascular screening, risk stratification, and potentially more targeted precision medicine interventions to improve cardiovascular health. Towards that end, this K24 award will facilitate the progress of Dr, Mora's mentees into the next generation of patient-oriented independent cardiovascular researchers.

NIH Research Projects · FY 2026 · 2017-12

Summary/Abstract This application for renewed support continues its focus on the mechanisms responsible for aspirin sensitivity, a defining feature of aspirin exacerbated respiratory disease (AERD). AERD is a debilitating clinical syndrome characterized by severe sinonasal and bronchial inflammation resulting in chronic rhinosinusitis with nasal polyposis (CRSwNP) and asthma, respectively. Few therapeutic options exist, and none have disease modifying properties. Our proposal focuses on a unique, platelet-driven mechanism through which endogenous cysteinyl leukotrienes (cysLTs), specifically the parent cysLT LTC4, elicits biased signaling through the type 2 cysLT receptor (CysLT2R) on platelets and other cell types to drive immunopathology through IL-33. The central hypotheses are that LTC4 signals at CysLT2R to promote respiratory type 2 inflammation by inducing the expression and release of interleukin 33 (IL-33) by both direct and indirect mechanisms. A corollary hypothesis is that AERD involves a significant pathogenetic contribution from an autocrine LTC4/CysLT2R-mediated platelet activation pathway that provides IL-33 and other mediators that contribute to respiratory tract T2I and drive aspirin sensitivity. We use a complementary approach with molecular tools, a unique set of transgenic mice, and tissues and cells from carefully phenotyped human subjects to test the core hypotheses and validate the biology across species. The studies should reveal new potential strategies for therapeutic development that are based on a novel underlying mechanism,

NIH Research Projects · FY 2025 · 2017-09

PROJECT SUMMARY: Using human brain connectivity to identify the causal neuroanatomical substrate of depression symptoms Depression is the leading cause of disability worldwide. Identifying the brain regions causing depression symptoms can lead to better treatment targets and therapies. Most neuroimaging studies identify brain regions where activity correlates with depression symptoms but cannot determine whether these regions actually cause symptoms. The goal of this project is to causally link depression symptoms to human neuroanatomy. Lesions and brain stimulation can provide causal links to human neuroanatomy. Because symptoms can come from regions connected to the lesion or stimulation site, we study the connectivity of these sites (not just their location) using brain connectivity data from a large cohort of normal subjects (functional connectivity MRI, n=1000). This allows us to map symptoms caused by lesions or stimulation to brain circuits without connectivity data from the patients themselves. With NIMH support, we found that lesions, transcranial magnetic stimulation (TMS) sites, and deep brain stimulation (DBS) sites that cause a change in depression symptoms are all connected to a common brain circuit across 14 independent datasets (Siddiqi et. al 2021 Nature Human Behaviour). Connectivity to this circuit was a better predictor of antidepressant response to TMS or DBS than connectivity to other candidate regions (e.g., subgenual cingulate). However, this circuit requires validation before it can be translated into a target for clinical trials. Here, we will validate our brain circuit for depression using three independent causal sources of information: lesions (Aim 1), DBS (Aim 2), and TMS (Aim 3). For all aims, we will use our published a priori depression circuit to predict overall depression outcomes. We will also perform exploratory data-driven analyses to test whether different circuits are responsible for different symptoms of depression. In Aim 1, we will prospectively test whether our depression circuit can predict depression scores after stroke. In Aim 2, we will test whether our depression circuit can predict change in depression score after DBS across a wide range of DBS patients with different diagnoses. In Aim 3, we will test whether individualized connectivity to our circuit prospectively predicts change in depression symptoms with TMS. Completion of these Aims will validate our depression circuit across different diagnoses and across three independent causal sources of information, providing much stronger validation than could be achieved with one modality alone. If successful, this study will facilitate future trials directly targeting our brain circuit with therapeutic neuromodulation for depression.

NIH Research Projects · FY 2025 · 2017-09

The overarching long-term aims of VERITY are: 1) to develop state-of-the-art methods for clinical research in rheumatology and musculoskeletal diseases that are relevant for the Research Community, 2) to deliver methodologic and bioinformatic assistance to the Research Community, and 3) to train the Research Community in state-of-the-art methods through courses, seminars, and mentoring. During the last cycle, VERITY recruited a large and growing Research Community of rheumatic and MSK disease investigators who participate in courses, mentoring, and utilize the services of the three VERITY Cores. The Overall Section of the application describes: the progress and future directions for VERITY’s burgeoning Research Community; how VERITY has developed and delivered courses to respond to the Research Community’s needs, especially during the COVID pandemic; plans for future courses and mentoring of trainees and junior faculty; and the services offered and organization of the Methodology Core and the Bioinformatics Core. During the previous cycle, VERITY developed a Research Community that has included many junior faculty and trainees, a good number of pediatric rheumatologists, and an increasing group of MSK investigators. These researchers represent the broad range of clinical investigators engaged with NIAMS-focused topics. In addition, the large group of investigators helps provide the Cores with a steady stream of activity and resources. During the prior cycle of the BWH CCCR, VERITY helped produce 160 original articles already cited 1,287 times. These original articles appeared in high impact journals. The VERITY Research Community has been successful with 109 grant submissions during the last 4+ years, tabulating a total of $40,073,225 in annual direct research revenues. The three Cores have been extremely productive and learned much about working effectively with the Research Community. The proposed aims build on the prior successes with: an enhanced Enrichment Program increasing; a Methodology Core that ensures methodologic rigor while incorporating behavioral theory and economics; and a Bioinformatics Core that provides bioinformatic support to better phenotype patient cohorts.

NIH Research Projects · FY 2024 · 2017-08

ABSTRACT In metazoans, gene expression is regulated in a tissue/cell-type-specific manner predominantly via stretches of noncoding sequence referred to as cis regulatory modules (CRMs). CRMs contain 1 or more DNA binding sites for 1 or more sequence-specific, regulatory transcription factors that function to modulate the expression of target gene(s). CRMs that activate gene expression are typically referred to as enhancers, while those that repress gene expression are referred to as silencers. Transcriptional enhancers activate gene expression in a tissue-specific manner in development and also in adult cells in response to cellular or environmental stimuli. Like enhancers, silencers can function in a cell-type-specific manner. Indeed, silencers may contribute a crucial role in the specification of precise gene expression patterns, thus enabling the establishment of sharp expression domains, such as during development. Genomic and computational studies traditionally have focused primarily on predicting and characterizing enhancers. Silencers have been investigated far less and are much less well understood. The overarching goals of this project are to identify and quantify the activities of tissue-specific silencers and their potential bifunctionality as enhancers in alternate cellular contexts, to identify the chromatin signature(s) of silencers, to determine whether silencers exhibit specificity in terms of the promoter and/or enhancer context within which they reduce gene expression, and to elucidate the regulatory roles of silencer-associated repressors, corepressors and DNA sequence motifs. We will also characterize the chromosomal contacts of silencers that are mediated by repressors bound at different classes of silencers. In pursuing these goals, we will develop novel technology for quantitative assays of elements for tissue-specific silencer activity in the context of various enhancer-promoter combinations, and novel technology for identification of proteins found in tissue-specific chromatin assembled at specific cis-regulatory elements in cells where they act as silencers versus in cells where they act as enhancers. We will focus on the developing embryonic mesoderm in Drosophila melanogaster as our model system. We anticipate that the features and chromatin signatures of silencers identified in this project will be evolutionarily conserved across metazoans, including human.

NIH Research Projects · FY 2026 · 2017-08

7. Project Summary The primary objective of this proposal is to characterize the most important genetic and proteomic pathways that contribute to early stages of pulmonary fibrosis (PF_, with the goal of developing biomarkers for, and improving our understanding of, the initial biological processes that result in early PF pathogenesis. Idiopathic pulmonary fibrosis (IPF), the most common and severe form of PF, is increasing in prevalence, and has a mortality rate worse than most malignancies. Given that even early stages of PF may benefit from interventions there is more urgency to improve our understanding of early disease detection and to define the most important pathways that result in early stages of PF progression. In the prior grant cycle, key results helped to improve our understanding of early progressive PF, demonstrated the key genetic and genomic findings that overlap, and that are distinct from, IPF, and identified important genomic findings correlated with early stages of PF. Although these results provide important biologic signals, the predictive power of many of these biomarkers is low, and they leave important questions unanswered. We hypothesize that comprehensive proteomic and genetic assessments of ILA will lead to a better understanding of 1) the factors that best help predict disease risk, 2) the most important pathways implicated in PF development, and 3) which proteins’ secretion is increased in response to higher risk genetic profiles thus implicating their role in early PF pathogenesis. To address these hypotheses, we propose the following specific aims: Aim 1: Can peripheral blood proteins be identified that are associated with, and help to predict, early and later stages of progressive PF? Aim 2: Can polygenic risk scores (PRS) help predict early stage-stage PF and can this genetic data be integrated with proteomic assessments to improve our understanding of early PF pathogenesis? Aim 3: Can differentiated human airway epithelial cells (HAECs) demonstrate the role that high genetic risk (and environmental stimuli) play in the expression of early-stage PF associated proteins? These results will not only improve our understanding of the pathogenesis of both early and late stage PF, but will also identify candidate pathways that could lead to targets for drug development, and will identify biomarkers for future interventional trials designed to target those at the highest risk to develop IPF at a stage before the lung is irrevocably damaged.

NIH Research Projects · FY 2026 · 2017-05

Summary: Despite being one of the most common interventions in hospitalized patients, red blood cell (RBC) transfusion is not without risk. Exposure to allogeneic RBCs can result in RBC alloimmunization, which can make it difficult to find compatible blood for future transfusions and directly increases the risk of transfusion complications. To develop strategies that can actively inhibit alloimmunization, key initiating factors that drive alloantibody formation against RBC alloantigens must be defined. The overall objective of this proposal is to define key initiating factors that contribute to short- and long-term alloantibody production. Our central hypothesis is that complement serves as a key molecular adjuvant that can drive alloimmunization through a CD4 T cell independent (TI) pathway, but that CD4 T cells are required for long-term alloantibody production. Our hypothesis is formulated on the basis of our recent discovery that while initial anti-KEL IgG antibody formation is TI, in the absence of complement component 3 (C3), anti-KEL IgG antibody formation is completely CD4 T cell dependent (TD), suggesting that RBC surface bound C3 may directly drive TI IgG antibody formation. Consistent with this, complement receptors 1 and 2 (CR1/2) on B cells are required for KEL RBC-induced TI IgG antibody production. Our data also demonstrate that patients with sickle cell disease (SCD) experiencing acute chest syndrome (ACS) are not only much more likely to become alloimmunized, but also experience significant complement activation, suggesting that complement activation may enhance RBC alloimmunization following transfusion during ACS. In contrast, for long-lived alloantibody production to be realized, CD4 T cells must be engaged. Using the same KEL model system, our data demonstrate that despite CD4 T cells not being required for initial IgG alloantibody formation, KEL RBCs activate T follicular helper cells (TFH) and follicular (FO) B cells, and that long-lived alloantibody production is TD. In contrast to the requirement for C3 for TI IgG alloantibody formation, while initial alloantibody formation occurs in the absence of toll-like receptors (TLRs), TLR-signaling is required for persistent alloantibody production. Taken together, these data suggest that KEL RBC transfusion can simultaneously engage two distinct immune pathways through a complement-regulated process. To test this, we will weld pre-clinical and clinical studies to test the following specific aims. Aim 1: Define the role of C3 in driving TI MZ B cell-mediated antibody production. Aim 2: Define the role of TLR signaling and 33D1+ DCs in driving TFH and FO B cell formation and long-lived antibody production. We think that successful completion of these aims will provide a unique opportunity to define key factors that initiate distinct types of RBC alloimmunization with the promise of identifying key targets to prevent RBC alloimmunization.

NIH Research Projects · FY 2025 · 2017-04

PROJECT SUMMARY Although cigarette smoking is the major environmental risk factor for COPD, only a minority of smokers develops clinically significant COPD; genetic factors influence this variability. COPD subjects have widely varying contributions of emphysema and airway disease, and the biological determinants of COPD heterogeneity are not well-defined. Protein biomarkers, which are biologically proximate to genetic variants, could play a critical intermediate role in defining COPD genetics and heterogeneity. Our overall hypothesis is that functional genetic variants lead to abnormal proteomic states that will allow identification of protein biomarkers relevant for the development and heterogeneity of COPD. We will use mass spectrometry proteomics to provide comprehensive assessment of available proteins and their proteoforms (including post-translational modifications) in 1054 lung tissue samples from the Lung Tissue Research Consortium (LTRC), including 547 COPD cases and 507 control subjects. Olink proteomics data (generated by TOPMed) will provide orthogonal proteomics data on the same lung tissue biospecimens. Cellular deconvolution approaches using single cell and bulk RNA-Seq data will be used to determine whether proteomic associations relate to changes in lung cellular composition. COPD subtypes will be defined based on both clinical/imaging data and by using network-based stratification of the proteomics data. We will verify potential plasma protein biomarkers of COPD and COPD subtypes by measuring the top 100 lung tissue COPD-specific proteins in plasma samples from the same LTRC COPD cases and control subjects. We will leverage existing LTRC multi-Omics data (including whole genome sequencing, RNA-Seq, and DNA methylation) in conjunction with newly generated mass spectrometry and affinity-based proteomics data to identify rare and common genetic determinants of COPD-related proteins and COPD. Machine learning and network analysis will be used to integrate multi-Omics data to provide insight into COPD pathogenesis and heterogeneity. Network relationships for several top COPD protein biomarkers will be functionally validated using CRISPR-Cas9 approaches in primary lung cells. The identification and characterization of novel COPD protein biomarkers may provide insights into COPD pathogenesis and tools for future clinical trials.

NIH Research Projects · FY 2025 · 2017-03

Project Summary / Abstract The primary purpose of this K24 renewal proposal is to support mentorship by Dr. Lockman of early career investigators in conducting patient-oriented research pertaining to HIV and other infections. This next generation of investigators will need to tackle ongoing infectious disease epidemics (such HIV, tuberculosis, and antimicrobial resistance) and to respond rapidly to future emerging pandemics and pathogens. Effective mentorship of early career investigators to conduct clinical research requires substantial time and effort by experienced mentors, and the need for such mentors exceeds their availability. The initial K24 project period permitted Dr. Lockman to successfully mentor more than 20 early career investigators to lead clinical research projects, all of whom have gone on to successful careers in research and public health practice. This K24 grant also allowed Dr. Lockman to gain additional skills in designing and conducting patient-oriented research with a focus on HIV (particularly in pregnancy). The impact of widely used HIV antiretroviral treatment (ART) regimens during pregnancy on birth outcomes and on long-term maternal and child health, growth and development are not well understood. The research aims of this project, which Dr. Lockman will mentor early career investigators to lead, include studies of the impact of different ART regimens during pregnancy on cardiometabolic factors in women (specifically, pregnancy and postpartum weight gain, and markers of diabetes and metabolic syndrome in pregnancy), and the association between these cardiometabolic factors and pregnancy outcomes and child health and growth. Dr. Lockman’s mentees will primarily use existing data and samples for these aims, including from studies that she leads (multi-country IMPAACT 2010/VESTED randomized trial of 3 ART regimens in pregnancy and an R01-funded study of child developmental/behavioral outcomes after in utero exposure to different maternal ART regimens). Dr. Lockman will also help her mentees access a wealth of other existing data, resources, and co-mentors. The overarching goal of this K24 renewal proposal is to help expand sustained capacity to conduct high-impact patient-oriented research by supporting the mentorship and training of early career investigators.

NIH Research Projects · FY 2025 · 2016-09

Digital Breast Tomosynthesis (DBT) is a breast cancer screening methodology in which radiologists search for cancer in 3D volumes of virtual slices through the breast. DBT performs better than classic, 2D mammography but it takes more time. Our goal is to compare different methods that could reduce the time required while maintaining or improving performance. Beyond the specific goal of improving DBT, we will uncover general principles of attention and perception that can be applied whenever the volume of images threatens to overwhelm the ability of observers to consume those images. We are particularly interested in conditions of “low target prevalence” (low percentage of positive cases). In tasks like breast cancer screening, with many images and very few clinically significant targets, interventions that are effective when tested at high prevalence in the lab may fail in the field when prevalence is much lower. There are three projects: Project 1: Self-Triage by 2D Full-field digital mammography or synthetic images: In screening for breast cancer, there will be some cases that a reader could safely declare ‘normal’ on the basis of the 2D image, alone. Is it reasonable to develop a protocol where some DBT images would be acquired but would not be examined? This “self-triage” would require a very conservative triage criterion in order to avoid triage of any positive cases, but if proven to be safe, self-triage could save significant time and might reduce false negative errors. Project 2: DBT as “hybrid search”: Breast cancer screening involves search for more than one type of target (masses and calcifications, at minimum). Research shows instances where such ‘hybrid’ search for multiple targets leads to elevated errors. We will test the hypothesis that readers are more efficient and/or more accurate if they perform separate searches for each target type. We will measure eye movements to compare search for each target type alone to search for both types together. Experiments with non-experts will investigate basic principles of search in 3D volumes of image data. Project 3: AI Targeted ‘drilling’: Eye tracking has identified two modes of search in 3D stacks of images: “drilling”, where readers move rapidly through depth (Z) while the eyes stay relatively stable in the XY plane, and “scanning”, where readers search widely in XY while moving slowly in Z. We will use eye tracking to evaluate a CAD system developed by iCAD that marks specific locations in the 2D XY image and invites readers to drill in these specific areas. Does that improve CAD performance? Summary: This program of research will produce recommendations for increasing the efficiency of breast cancer screening. Moreover, each study will produce basic science that will be generalizable to other settings and will deepen our understanding of visual search through 3D volumes of image data.