Brigham And Women'S Hospital

NIH Research Projects · FY 2025 · 2024-11

PROJECT SUMMARY This application requests funds to support the 2024 Biomarkers of Aging Conference, which will be held from November 1–2, 2024 at the Joseph B. Martin Conference Center at Harvard Medical School in Boston, Massachusetts. This conference has been organized by the Biomarkers of Aging Consortium following the success of our inaugural event in 2023. We again aim to bring together many stakeholders who work on all aspects of aging biomarkers. Although tremendous strides have been made in the development of aging biomarkers, none have been systematically validated. Moreover, there is little consensus within the field on how such biomarkers may best be developed, validated, and deployed. This represents a major hindrance in the translation of these tools from preclinical studies to clinical trials to test the ability of geroprotectors to extend healthy lifespan. The annual Biomarkers of Aging Conference is a key initiative organized by the consortium in parallel to ongoing scholarly work and other projects. We envision this conference as the premier yearly venue for scientists working on aging biomarkers to meet and discuss the most pressing issues in the field, a need evidenced by the overwhelming response to our inaugural 2023 symposium. We strongly feel that a coordinated and ongoing effort will be necessary to realize the promise of the burgeoning aging biomarkers field in improving the lives of aged individuals across the world. To support this goal, we have organized this year's conference with the goals of: (1) disseminating the latest research related to aging biomarkers to a broad audience through scientific presentations; (2) considering critical outstanding issues that are impeding the field from moving forward and identifying concrete steps to meet these challenges; (3) providing a unique forum for networking between academic scientists, clinicians, regulatory experts, and representatives from industry; and (4) supporting the career development of junior scientists, particularly those from backgrounds underrepresented in science, through active participation opportunities and cultivation of an environment that encourages interactions with senior experts in the field. We believe we have organized a strong program which will directly support the consortium's broader goal of enabling the establishment of reliable biomarkers of aging for clinical use. We feel that this conference will be useful to the community and will continue to serve as an important annual event for all those working to bring biomarkers of aging to the clinic to improve human lives.

NIH Research Projects · FY 2024 · 2024-09

Abstract The most effective treatment to tackle the ongoing opioid crisis in the US is buprenorphine, one of several medications for opioid use disorder (OUD). Buprenorphine reduces overdose mortality by up to 70%, increases treatment retention, and suppresses illicit opioid use, making it one of the most important interventions in reversing the overdose epidemic. However, more than 30% will discontinue buprenorphine by 12 weeks due in part to the emergence of craving for opioids, leading to relapse and heightened risk of an overdose. Unfortunately, there are currently no evidence-based adjuncts to buprenorphine to reduce cue-reactivity and the risk of early treatment discontinuation. Therefore, research to identify interventions that can be used as adjuncts to buprenorphine is urgently needed. Glucagon-like peptide-1 (GLP-1) agonists, FDA-approved medications for the treatment of diabetes and obesity, potentiate insulin release, inhibit glucagon release, delay gastric emptying, and reduce food intake. The activation of GLP-1 receptors, which are highly expressed in the brain, reduce the hedonic value of food and appear to have similar effects on reward valuation for substances of misuse, raising the possibility that these medications could be repurposed for the treatment of OUD. Preliminary clinical studies suggest GLP-1 agonists may impact substance use in humans, but these studies were based on older formulations such as exenatide and liraglutide. The newer formulations such as semaglutide have greater homology to native GLP-1 and are associated with fewer gastrointestinal adverse events. Data are therefore lacking to validate the use of newer, more efficacious formulations in terms of safety profiles and initial impact on cue-reactivity and OUD-related outcomes. Our central hypothesis is that semaglutide will demonstrate attenuation of cue-reactivity providing preliminary evidence of its utility as an adjunct to buprenorphine to prevent relapse. This proposal will be the first placebo-controlled randomized trial of the weekly formulation of semaglutide as an adjunctive treatment to buprenorphine in individuals with OUD by evaluating cue-induced craving. We will also study the safety and tolerability of semaglutide over the course of the 12-week trial. This innovative R21 has public health impact because it will contribute to the identification of an effective pharmacotherapy adjunct to buprenorphine for OUD and is highly responsive to the NIDA programmatic goals of identifying novel treatment strategies for individuals with OUD. The NIDA Director has specifically cited the need to conduct OUD research with medications with targets other than opioid receptors, and to repurpose existing medications including GLP-1 agonists. If successful, results from this study will lay the groundwork for the design of an adequately powered efficacy trial to determine whether semaglutide treatment can improve OUD-related outcomes for those receiving buprenorphine.

NIH Research Projects · FY 2025 · 2024-09

Time for accurate and timely diagnosis is critical yet increasingly constrained. It is important for ensuring patients have adequate time to share their histories, and for clinicians to collect and reflect on patient data, and communicate and document their diagnostic assessments. Both patients and clinicians report feeling insufficient time and rushed in their diagnostic encounters, with clinicians increasingly reporting time pressures, after-hours work, and lack of control over time needed to care for patients and write their notes. High quality diagnosis for individual clinicians and health systems requires not only adequate time but also the ability to have feedback from patients to continuously learn about diagnostic outcomes and experiences. A team of clinicians and health services researchers who have engaged in more than two decades of work studying diagnostic safety will work with systems engineers to deepen our understanding of relationships between diagnosis quality (processes, outcomes, communication with patients) and time and stress. We will also study a natural experiment, comparing diagnostic encounters at two sites, one that allocates 20 minutes (Hennepin HealthCare) vs. another allocating 30 minutes (Brigham and Women’s) for primary care encounters. The project will leverage new EMR technologies that can: a) screen patients for symptoms to identify diagnostic encounters and collect downstream feedback from patients, b) capture detailed timestamp information recording each keystroke before, during, and after these diagnostic encounters, and c) record and transcribe clinical encounters and using generative AI technology to automatically produce clinicians’ notes. Studying diverse clinics at these two sites, the project has the following three specific aims: 1. Identify 400 patients with diagnostic visits and solicit their feedback on diagnostic processes and outcomes. 2. Collect and analyze data examining relationships between EMR-measured time, clinician stress, and diagnostic outcomes. This includes using large-scale EMR timestamp data from 40,000 visits, deploying a new Assessing the Assessment tool, the SaferDx tool, and validated MiniZ clinician stress measures. 3. Collect transcripts generated from 100 AI-documentation-recorded diagnostic encounters and conduct qualitative analysis of diagnostic communication conversations during the visit, as well as evaluate the features and quality of the AI-generated notes produced by two commercial vendors. Detailed information from each encounter will permit evaluation of key time relationships (e.g. how far behind in schedule clinician is for that encounter, after-hours time), rich evaluation of key elements in the clinical assessment (e.g. diagnostic uncertainty and differential diagnosis, psychosocial issues, don’t miss diagnoses), and correlation with clinician stress (e.g. burnout, perceived time pressures, cognitive load). Triangulating these data sources and analyses, the project will advance our understanding of time required to evaluate common symptoms, along with the quality of these diagnostic assessments and of AI-generated notes.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY Alzheimer's disease (AD) is a prevalent neurodegenerative disorder that leads to cognitive decline and dementia. The disease imposes emotional and financial burdens on patients and their families, with over 5.8 million adults in the US alone affected by AD. The number of cases is expected to double by 2050, with estimated costs exceeding $1 trillion. Early diagnosis is crucial for effective management and prevention of AD, but current diagnostic methods like neuroimaging and cerebrospinal fluid analysis have limitations in terms of cost, availability, and invasiveness. Blood-based biomarkers offer a promising alternative for accessible and repeated measurements. Recent advancements in blood-based biomarkers, including amyloid-beta (Aβ), phosphorylated tau (pTau), and Neurofilament Light chain (NfL), show potential in diagnosing and tracking AD. Plasma Aβ levels can detect abnormalities before the onset of dementia symptoms, while elevated concentrations of specific pTau isoforms are strongly associated with clinically diagnosed AD. NfL serves as a broad indicator of neurodegeneration. These biomarkers align with findings from CSF and PET methodologies, presenting opportunities for transforming AD diagnosis, prognosis, and treatment monitoring. Despite the FDA approval of immunoassays for amyloid plaques and pTau, there is a significant lack of commercially available point-of-care (POC) blood tests for AD. Existing blood-based AD tests are lab-specific, bulky, expensive, and require specialized equipment. The EU/US Clinical Trials on Alzheimer's Disease (CTAD) Task Force emphasizes the urgent need for user-friendly, accurate, and accessible tests, particularly in primary care settings. Implementing POC testing alongside cognitive assessment could reduce specialist visits, shorten wait times, and generate significant cost savings for healthcare systems. To address these challenges, we propose to develop a smartphone-based POC diagnostic system. The system utilizes microfluidics, nanotechnology, optical sensing, and deep learning to detect AD-related biomarkers (Aβ42, Aβ40, pTau181, pTau217, pTau231, and ΝfL) in blood-plasma within 30 minutes. The goal is to create an affordable (<$5 material costs), disposable, and mass-producible microfluidic cartridge that enables rapid and sensitive (LoD<10pg/mL) detection using platinum nanoparticles to generate visible optical signal (bubbles). This innovation has the potential to fill the gap in AD management by providing an accessible and cost-effective tool for comprehensive blood-based biomarker testing, improving screening, monitoring, and treatment efficacy for individuals affected by AD.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY This project relies on new biological insights into how SORL 1-retromer functions as an endosomal recycling unit to understand the structure and function of pathogenic variants in the SORL 1 gene that cause, or contribute to the risk of, Alzheimer's disease. Alzheimer's disease (AD) is the only major cause of death for which no preventive or significant disease-modifying treatment exists, and will cost the U.S. a trillion dollars annually by 2050. Only 4 truly causal genes have been identified: APP, PSEN1, PSEN2, and SORL 1. Of these, certain alleles of SORL 1 cause late onset AD that phenocopies the common sporadic disease. SORL 1 encodes a 2214-residue type I transmembrane protein that has 24 distinct domains. Its function in neurons is to help traffic membrane proteins such as the glutamate receptor subunit GLUA 1, APP, and other cargo to their correct destinations after endocytosis. To do this it forms a specific complex with cargo and with the retromer, a multiprotein assembly that is the master regulator of trafficking out of early endosomes. Pathogenic mutations cause endosomal traffic jams, ultimately leading to neurodegeneration. Since pathogenic SORL 1 mutations are involved in ~3% of all AD cases, it is very important to determine if a given mutation is pathogenic, and if the afflicted patient will be a candidate for therapy aimed at normalizing protein trafficking out of the endosome. Our overall approach is for human genetics to first identify likely pathogenic variants so that we can then more deeply probe their biology--- integrating structural, biophysical, biochemical, and cellular biology. This is innovative in expanding our mechanistic understanding into how SORL 1-retromer drives and modulates Alzheimer's disease. We will determine the effects of putative pathological SORL 1 variants on the structure, stability and cargo binding of SORL 1 protein. Both biochemical (dimerization, binding to the retromer multi protein complex, and binding of cargo) and biophysical (overall and local protein folding, protein stability, dynamical properties of the protein structure) will be measured. In the case of mutations in the VPS10/10CC portion of SORL 1, the crystal structures of selected mutant proteins will be determined to provide atomic-level details of the effect of the mutation on the local and global conformations of these two domains. In the case of mutations elsewhere in this large protein, we will use a model we have built (employing the deep learning algorithm AlphaFold2) of the ectodomain to aid in structure determination by cryoEM/ET, enabling us to predict the likely effects of mutations on the conformation - and biochemical functions - of SORL 1. This information will be incorporated, along with cell biology in neurons, plus histopathology, human genetics and mouse model data from other labs, to provide a comprehensive picture of the relationship between a given mutation's effects on SORL 1 structure and function and its pathogenicity in human disease.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY/ABSTRACT Approximately 141 million medical imaging examinations are performed in the United States annually. Over 12% of these examinations result in a radiologist recommendation for additional imaging (RAI). However, RAI rates vary among peer subspecialists, radiologists often disagree with RAI generated by other radiologists, and RAI language is often ambiguous and not readily actionable. Such variation in decision patterns is present in other professions and other areas of medicine, hypothesized to be a by-product of our personal biases and unique approaches to judgement, and a major source of professional errors. Referring provider failure to pursue clinically necessary RAI or radiologist failure to make clinically necessary RAI (medical imaging underutilization) can lead to diagnostic error. Referring provider pursuit of clinically unnecessary RAI (medical imaging overutilization) diminishes diagnostic excellence by creating waste and can lead to diagnostic delays. Furthermore, sociodemographic disparities appear to exist in RAI creation and completion. Our goal is to reduce variation and sociodemographic disparities in RAI creation, referring provider agreement, and patient adherence. Our innovation is the use of a validated natural language processing algorithm to enable a large- scale, theory-informed, versatile audit and feedback process for clinical adherence to evidence-based and equity-informed best practices across a multi-site health system. We will focus on head and neck radiology, which has the largest inter-radiologist RAI rate variation we have observed. Aim 1: Identify sociodemographic disparities in head and neck imaging RAI. We will measure the extent to which RAI rates (potential radiologist bias), referring provider agreement rates (potential referring provider bias), and RAI examination completion rates (patient factors including patient preferences) differ by patient socioeconomic status, sex, race, ethnicity, insurance, and income. Aim 2: Describe RAI-related epidemiology and diagnostic error for three conditions: thyroid cancer, lung cancer, and canal dehiscence syndrome. We will establish the 5-year healthcare system incidence of these diseases; measure the association of radiologist RAI rate with detection rate, sensitivity, and specificity; and measure radiology-related diagnostic error (false negatives, misdiagnoses, and delays to diagnoses). Aim 3: Develop and locally disseminate best practices for the studied conditions. We will generate local clinical consensus best practices using published evidence as well as gathered evidence from Aims 1 and 2, with a Delphi approach that includes a multi-disciplinary team of experts and also patients. Aim 4: Reduce RAI variation through a peer learning audit and feedback intervention. We will measure change in RAI rates, RAI rate variation, and referring provider agreement. We will also assess change of disparities in RAI creation, agreement, and adherence, and measure change in RAI actionability. If effective, this study will serve as a model for the development and audited implementation of best practices that reduce variation, diagnostic error, and disparities in medical imaging care.

NIH Research Projects · FY 2025 · 2024-09

Poor sleep health (e.g., insufficient sleep duration, fragmented sleep, untreated sleep disorders) is associated with increased risk of Alzheimer’s Disease (AD). Poor sleep health also increases soluble Amyloid βeta and tau concentrations in cerebrospinal fluid suggesting a potential mechanism for sleep disturbance to promote AD pathogenesis. All of these could increase the risk for AD, meaning that poor sleep health and untreated sleep disorders are potential catalysts for AD risk, and that improving sleep may be a modifiable target for AD prevention among older adults. Sleep difficulties remain unaddressed among many older adults, especially those in low resource settings, such as among residents of low-income housing facilities. Our team (the Sleep Matters Initiative) has an established, effective Sleep Health and Wellness (SHAW) program, comprised of sleep and sleep disorders education. We propose to expand the SHAW program to include mindfulness, the Eastern practice of focused concertation in the present moment, which has been shown to improve sleep, reduce stress, and strengthen cognitive function in older adults. Guided by User Centered Design, we will conduct iterative stages of feedback from older adults and prototyping, that will ensure the sleep and mindfulness messages and materials are accessible, usable, and feasible for cognitively unimpaired older adults (age 55 years and above) in low-income housing in Boston. Given that networks of trusted other seniors are essential sources of information and influence, we propose a novel social network approach, that will identify opinion leaders in low-income housing facilities and engage these individuals as Sleep Health Champions (SHCs) to aid in diffusing the adapted SHAW materials and resources through interpersonal communication and small group sessions. Our objective in this R34 is to culturally adapt the SHAW and mindfulness modules to the needs of cognitively unimpaired older adults in low-income housing facilities, then conduct a feasibility and acceptability pilot study of the proposed social network approach to deliver the adapted SHAW program to cognitively unimpaired older adults in low-income housing in Boston with the aim of improving sleep, quality of life (QoL), and cognitive function. We will conduct the proposed planning activities and feasibility study in close collaboration with our longtime partner, the City of Boston Age Strong Commission. The culturally adapted SHAW and mindfulness program will be evaluated in a planned cluster randomized controlled trial in cognitively unimpaired seniors in low-income housing in Boston on sleep health behaviors, QoL, and cognitive function in a planned R01 that will be submitted in Year 3 of this award. It is hypothesized that exposure to the adapted, SHC-deployed SHAW and mindfulness intervention in the planned R01 will be associated with improved sleep, QoL, and markers of cognitive decline.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Sequence-specific DNA binding by transcription factors (TFs) regulates RNA synthesis at target genes. This is a highly dynamic and context-dependent process, allowing cells to accurately regulate gene expression in response to diverse signals. While prior work has identified DNA binding preferences for numerous TFs, our understanding of the fundamental principles governing TF-DNA binding specificity and affinity remains incomplete. This is primarily due to limitations of current high-throughput methods, which fail to reliably detect low- to medium-affinity TF-DNA interactions that are more common and important for genomic binding in vivo. To address this gap, I have developed PADIT-seq, an innovative high-throughput reporter assay that enables functional testing and quantification of TF binding affinity across thousands of DNA sequences in a single experiment. The overall goal of this proposal is to utilize and further develop PADIT-seq to uncover fundamental TF-DNA binding principles, which will significantly advance our mechanistic understanding of the regulatory genome. Aim 1 will determine the role of medium-low affinity auxiliary binding sites and DNA shape features in determining TF genomic occupancy. I hypothesize that preferential recognition of sequential low-medium affinity sites flanking a core motif cooperatively increases residence time beyond what is predicted by core motifs alone. Aim 2 will apply PADIT-seq to identify the TFs whose binding is affected by pancreatic disease associated noncoding variants. It will also further develop PADIT-seq to make the assay even higher-throughput, enabling testing of higher numbers of TFs more easily. Finally, Aim 3 will elucidate intrinsic orientation biases of DNA binding domains in positioning partner proteins on DNA. Successful execution of these aims will provide major insights into the grammar and mechanisms underlying TF regulatory specificity. This work will also reveal how alterations in gene regulation driven by noncoding variants contribute to complex human diseases. My PhD research focused on identifying disease-associated genetic variants that are functionally relevant through genomic approaches. However, determining the precise TFs whose DNA binding is disrupted by these variants remained challenging. To overcome this barrier, my postdoctoral research has centered on pioneering a high-throughput PADIT-seq technology to sensitively profile how noncoding genetic variants alter TF-DNA interactions. While developing PADIT-seq has been a crucial advance, I need further training to complement this breakthrough with additional skills necessary to fully connect genotypes to cellular phenotypes. This will enable me to provide a complete picture elucidating how noncoding variants dysregulate transcriptional programs to promote disease. The K99/R00 award will provide invaluable training to equip me with the scientific and professional expertise needed to elucidate how noncoding variants dysregulate gene networks to promote human disease as an independent principal investigator.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY Renal cell carcinoma (RCC) accounts for 4.1% of new cancer cases in the United States (US) – 1 out of every 25 diagnoses – and the number of individuals living with the disease has consistently increased over the past five decades. When patients are diagnosed with RCC, they often ask: “What can I do to improve my chance of survival?” A cancer diagnosis is a “teachable moment,” a time when an individual may be open to behavior change. But what behaviors should be endorsed? As yet, sufficient data are unavailable to give evidence-based, disease-specific lifestyle recommendations. Few studies have considered modifiable behaviors that might improve survival. Such studies are imperative given that 14,000 individuals die from RCC in the US each year. As such, we seek to comprehensively study the associations of dietary patterns and physical activity with RCC survival using data from three large, prospective cohorts: the Health Professionals Follow-up Study, Nurses’ Health Study, and Nurses’ Health Study 2. These cohorts are unique in their collection of repeated food frequency questionnaires (FFQs), physical activity assessments, and extensive covariable data, both before and after diagnosis. They also include more than 1000 confirmed cases of RCC, among whom roughly 300 have died from disease. In Aim 1, we will use FFQs to compute pre- and post- diagnostic adherence to the alternative healthy eating index (AHEI) and Dietary Approaches to Stop Hypertension (DASH), type 2 diabetes prevention, inflammatory, and insulinemic diets. We will then evaluate RCC-specific and overall mortality among RCC patients in relation to adherence to each pattern post-diagnosis and change in adherence to each pattern from pre- to post-diagnosis. Due to its impact on hypertension, we hypothesize that adherence to the DASH diet will be most strongly protective against RCC-specific mortality, even relative to an otherwise healthy diet (AHEI). In Aim 2, we will evaluate RCC-specific and overall survival among RCC patients in relation to post-diagnostic physical activity (including by volume, type, and intensity), post-diagnostic sedentary behavior, and pre- to post-diagnosis change in physical (in)activity levels. We hypothesize that increasing physical activity will be associated with a reduced risk of RCC-specific mortality and that increasing sedentary behavior will be associated with a greater risk of RCC-specific mortality. Results will offer first ever insights into dietary choices that improve RCC survival, and results regarding physical (in)activity will be borne from analyses including over five times the number of outcomes as had the prior pertinent study. Our research will thus yield a foundation for developing evidence-based lifestyle recommendations for RCC survivors. Only equipped with data from rigorous and well powered research can we offer RCC patients some self-determined control over their outcomes.

NIH Research Projects · FY 2024 · 2024-09

SUMMARY Trained immunity describes the relatively new observation that exposure to inflammation alters the innate immune cells, monocytes and neutrophils, to alter their behavior such that they respond to a second stimuli with more efficiency. This process is akin to the immunologic memory of the adaptive immune system. Initially observed in response to pathogens and vaccination, it is now increasingly clear that sterile, chronic inflammation leads to systemic reprogramming of macrophages. While developed to improve efficiency of pathogen clearance, this mechanism comes at the cost of promoting cardiovascular disease. Rheumatoid arthritis (RA), a common, chronic autoimmune disease, carries the burden of premature mortality to cardiovascular disease. No studies have directly tested whether inflammatory RA induces trained immune responses in innate cells of the arthritic joint or in the aortic wall. This proposal hypothesizes that trained immunity occurs in response to RA in the macrophages of the joint and in the bone marrow. Additionally, we propose that this training of the innate immune system causes the macrophages of the aorta to become pro-atherogenic, and thus promote development of atherosclerosis. The overarching hypothesis of this proposal is that trained immunity is a novel cause behind the increased incidence of cardiovascular disease in RA patients, and proposes to test this hypothesis using murine models. The PI is a K01 awardee in her 4th year of funding and will use these pilot studies to pursue her long term research goal to pursue mechanisms linking RA and cardiovascular disease. Indeed, these studies will provide the pilot data necessary to pursue independent R01 funding exploring the links between inflammatory arthritis, trained immunity, and cardiovascular disease.

NIH Research Projects · FY 2025 · 2024-09

Despite current therapies and prevention measures, individuals with type 1 diabetes (T1D) experience a disproportionately higher risk of cardiovascular events due to a more severe and accelerated atherosclerotic burden present in vessels, a longer duration of diabetes exposure, and often asymptomatic early disease that can lead to sudden cardiac death as the first manifestation of disease compared to patients with type 2 diabetes (T2D) or those without diabetes. Moreover, established lesions in the presence of T1D are more resistant to therapeutic strategies (diet or pharmacologic lipid-lowering) that normally facilitate plaque regression. Therefore, there is an urgent need for novel therapies to reduce the development of T1D- associated atherosclerosis that can lead to cardiovascular sequelae. Current paradigms suggest that chronic inflammation coupled with sustained endothelial inflammatory responses, altered macrophage chemotactic and efferocytotic functions, and accumulation of senescent cells may be critical links to the accelerated lesion progression and impaired regression with T1D. Therefore, targeting these processes in the vessel wall may provide a novel therapeutic approach to limit atherosclerotic progression and facilitate regression. However, significant gaps remain in the molecular underpinnings that regulate T1D-associated atherosclerotic pathobiology with limited studies derived from human coronary arteries. A large portion of the non-coding genome is actively transcribed and constitute microRNAs (miRNAs) or long non-coding RNAs (lncRNAs). Studies from our laboratory have uncovered novel cell-specific roles for a range of miRNAs and lncRNAs in regulating key endothelial cell-leukocyte inflammatory networks in atherosclerosis, such as NF-kB signaling. Considerable gaps exist though in our understanding of how human ncRNAs contribute to accelerated atherosclerosis and differences in T1D and T2D. We hypothesize the existence of evolutionarily conserved driver ncRNAs and their targets in the arteries of subjects with T1D and T2D and seek to uncover their expression, function, mechanism, and interactomes in the Cardiovascular Repository-T1D (CaRe-T1D) using unique approaches across humans, pigs, and mice. To better understand these ncRNAs we propose to: 1) identify and prioritize ncRNA expression from human subjects with T1D- or T2D-associated atherosclerotic lesions; 2) explore the functional significance and mechanistic targets of ncRNAs on cellular inflammation, senescence, and metabolic pathways; and 3) determine the therapeutic impact of altered ncRNA expression in the progression and regression of experimental T1D- or T2D-associated atherosclerosis models. The outstanding qualifications of our multi-disciplinary team in the ncRNA field, vascular biology, bioinformatics and transcriptomics, molecular imaging, and translational aspects of diabetes-associated atherosclerosis uniquely position us to establish an unprecedented molecular view of ncRNAs in the development of T1D-associated atherosclerosis that can inform new paradigms of RNA-based therapeutics for this devasting disease.

NIH Research Projects · FY 2024 · 2024-09

Enhancing Policy Impact for Reproductive Health Equity (EnPIRHE) Project Summary/Abstract- 30 lines The World Health Organization affirms that sexual and reproductive health (SRH) services are integral to the wellbeing and flourishing of individuals and communities. However, societal dynamics of power and oppression pattern access to these services, presenting disproportionate barriers to younger people, individuals who identify as Black, Indigenous, and people of color (BIPOC individuals), those with disabilities and chronic disease, individuals who are transgender or gender-nonconforming (TGNC individuals), and people of lower socioeconomic status. One exacerbating factor for these health inequities is the social stigmatization of sexuality, which compels individuals to keep their utilization of SRH services private for fear of negative repercussions, particularly for people who hold minoritized identities. In the United States, one major threat to patient privacy is the paper trail associated with utilization of health insurance. Health insurance billing and claims processing for commercial insurance plans frequently involve sending an “explanation of benefits” (EOB) to the primary subscriber of the health insurance plan whenever services are provided to any covered family member. When a person is covered by a parent’s or spouse’s insurance, EOBs are often sent to the primary subscriber, thereby breaching the person’s confidential health information. Concerns about confidentiality related to insurance billing can also compound existing barriers to care faced by multiply marginalized persons. Thus, leading health care organizations have called for policy change to correct this gap in patient confidentiality, and state governments are increasingly interested in policy solutions to protect individuals’ privacy when using insurance for sensitive services. Massachusetts is one of only seven states that has enacted legislation (the PATCH law) to protect confidential use of health insurance coverage, and one of only five that extends such protections to commercially insured people of all ages, providing a rare opportunity to understand individuals’ utilization of, knowledge of, and attitudes toward such policy protections. How this novel policy intervention has affected individuals’ attitudes towards and ability to utilize insurance for sensitive health services has not been studied. We propose to fill this critical gap in the literature through a mixed-methods study that will directly query SRH service users on their knowledge of, attitudes towards, and intention to use the protections of the PATCH law. This novel inquiry will be grounded in an intersectional framework, will engage a diverse statewide patient population, and will use a mixed methods approach including survey data and qualitative interviews to understand barriers to insurance utilization, with the goal of improving future health policy interventions.

NIH Research Projects · FY 2025 · 2024-09

Chronic obstructive pulmonary disease (COPD) is a leading cause of morbidity and mortality worldwide. While numerous scientific advances have been made to improve the care of patients with COPD, current therapeutic options remain limited. The growing availability of electronic health data and new computational tools have brought an unprecedented opportunity to accelerate the discovery of new therapeutic options for COPD via the analysis of existing health care data. We hypothesize that observational health data can be utilized to identify drug repurposing opportunities for COPD in a valid and expeditious way. The overarching goal of this proposal is to develop a population-based analytics and data infrastructure that will allow robust and valid evaluation of non-COPD drugs and COPD outcomes in patients with COPD, leveraging existing claims data sources and state-of-the-art methods for causal inference. The claims data will cover U.S. commercially insured individuals and Medicare beneficiaries. Electronic health records (EHR) and longitudinal data from COPDGene, a cohort of almost 5,000 smokers with longitudinal collection of extensive clinical and patient-reported data over 10-year period, will be linked to claims and used to develop, validate, or further refine key definitions for claims-based analyses, including endpoints, COPD severity markers, and COPD subtypes. The infrastructure will be developed using statins and diabetes medications, and further refined via emulation of selected randomized controlled trials (RCTs) that evaluated non-COPD medications for the prevention of COPD exacerbations in patients with COPD over the past decade. We will also evaluate the comparative effectiveness of new immunomodulating agents, such as dupilumab. While many previous observational studies of repurposed medications have been found to have substantial bias, we will build on the lessons learned in pharmacoepidemiology over the past decade and use causal inference methods that have demonstrated high validity in previous investigations and RCT emulation projects. Finally, as part of the project we will conduct thorough assessment of treatment effect heterogeneity across patient subgroups, including, but not limited to subgroups based on age, sex, race/ethnicity, comorbidities, and comedications, as well as COPD subtypes developed as part of this proposal. The proposed work will generate highly needed evidence on the impact of selected non-COPD medications on COPD outcomes. More importantly, it will form the foundation for future monitoring and evaluation of repurposing opportunities in COPD, expediting the path to discovery of new therapeutic targets for this debilitating disease.

NIH Research Projects · FY 2025 · 2024-09

Wounds have a sizable impact on public health: 1 out of 50 Americans has a chronic wound at any given time and the cost of wound care exceeds $100 billion per year. Similarly, hypertrophic scars with excessive scar tissue greatly impair quality of life for millions of patients. However, therapeutic solutions for wound healing (WH) remain quite limited. Sex has received growing interest as a factor in wound healing, and some studies show higher rates of non-healing wounds in men. It has long been known that in male rodents testosterone (T) impairs wound healing via androgen receptor effects. Sex hormone (SH)-induced changes in wound repair have been studied as a possible clinical risk factor, but their impact is uncertain due to factors like illness that alter hormone levels. We developed clinically relevant new experimental models and showed that T limits wound healing. Further, we have proven that patients on T have impaired wound healing. A critical knowledge gap that remains unaddressed is the set of molecular mechanisms and pathways T acts through to change the wound healing response. We have identified new immunomodulatory effects of T that may mediate these effects. Conversely, estradiol (E2) may accelerate wound repair rates. Essential aspects of how E2 improves wound healing remain similarly unknown. We will address these gaps in understanding hormone modulation of WH with a program spanning three project directions, including overcoming the failure of current in vitro (petri dish) models to recreate in vivo wound cell behavior changes induced by sex hormones (Project 1: In Vitro System) reducing the need for animal experiments, and defining how testosterone modulates the evolution of the immune response during wound healing to impair closure and this induces a fibrotic or regenerative repair response (Project 2: Mechanisms of T Immunomodulation). Finally, we will expand our work to deeply profile the effects of estradiol on immune cell subtypes and the wound cytokine milieu (Project 3: Estradiol Wound Healing Mechanisms). This project will deploy innovative tools to probe SH-WH mechanisms, expanding scientific knowledge of how T and estradiol interact with sex chromosomes and the immune system to regulate wound healing biology. This may enable identification of new therapeutic targets that can alter only those dysfunctional wound healing pathways with high specificity (ie, without any hormone effects). This study seeks to transform current concepts of how hormones modulate wound repair and develop potential new treatment approaches for millions of patients with chronic wounds.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY / ABSTRACT Very preterm survivors continue to experience high rates of neurodevelopmental impairment (up to ~60%) after discharge from the neonatal intensive care unit (NICU). These impairments lead to significant burden for individuals, communities, and society, as translate to high rates of special education in school, social and mental health difficulties, and reduced employment potential in adulthood. As primary prevention of preterm birth is presently infeasible, it is imperative to prioritize early interventions to mitigate adverse long-term effects of very preterm birth on child and family outcomes. One critical window for intervention is the third trimester of gestation, during which the preterm brain volume quadruples in size and is highly sensitive to positive and negative environmental experiences. This is a time very preterm infants spend in the NICU, frequently exposed to atypical sensory experiences (loud alarms, noise, pain) and a paucity of human interaction. Enriching experiences in the NICU during this key period can lead to exponential downstream effects on infant neurodevelopment. Music- based interventions (MBI) have been recently studied as enriching interventions for hospitalized infants. However, evidence from existing studies lacks rigor due to small sample sizes, study design limitations (mostly observational), and outcomes focused on short-term associations without mechanistic investigation and long- term follow-up. To fill this gap, we propose a rigorous, two-center randomized controlled trial (RCT), employing a novel MBI tailored based on preliminary data and inclusive of evidence-based musical elements with layered parent voice to facilitate engagement. The MBI will be delivered on average 5 days/week between 32-40 weeks gestation (or discharge), followed by comprehensive evaluation of relevant clinical, neuroimaging, and neurodevelopmental outcomes during the NICU stay and up to 2 years of age. Outcomes will include assessment of acute (physiologic and behavioral) and cumulative stress (amygdala volume on term-equivalent brain magnetic resonance imaging [MRI] and telomere length) in the NICU, intranetwork connectivity in key networks (language and salience) on term MRI along with investigation of other relevant regions of interest and internetwork connectivity, and comprehensive neurodevelopmental assessment of language, cognition, behavior, social emotional, and family functioning at 2 years' corrected age. Our overarching goal is to improve long-term neuro-developmental outcomes of very preterm infants through leveraging music medicine as an evidence-based innovation in the NICU. This work has the potential to benefit over 63,000 very preterm infants born each year in the U.S. and many more worldwide.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY – Skipping the hospital: Acute hospital care at home for people living with dementia In 2020, Alzheimer’s Disease and Related Dementias (ADRD) affected 5.8 million Americans and represented the fastest growing segment of our population.1 It was the sixth leading cause of death in the US; 1 in 3 older adults died of ADRD; and cost of care was $305 billion. A constant for people living with dementia (PLWD) is hospitalization: PLWD are hospitalized at twice the rate as older adults without ADRD.2,3 Well- documented is the harm of hospitalization: 1 in 3 will lose functional status; 1 in 5 will become delirious.4,5 The harm of hospitalization is magnified in PLWD: they have 5 times the odds of an adverse event.6,7 Acute hospital care at home (AHCaH) was specifically developed as a substitutive delivery model to help avoid these common harms for older adults while receiving the care that they need at home. The current model provides hospital-level care in the home after presenting to the emergency department (ED) with an acute illness such as infection or heart failure. AHCaH includes twice daily in-home nurse visits, daily physician visits, physical and occupational therapy, intravenous medications, biometric monitoring, in-home diagnostics, home health aide care, and 24/7 response. Serious illness conversations (SICs) at home for applicable patients are essential for setting goals of care and ideal given the home environment. Prior studies including several randomized controlled trials demonstrated significant improvements in 30-day readmission, safety, and cost.8–15 The impact on family caregivers and clinicians caring for PLWD is understudied. The mechanism of action for home hospital is patients are more physically active, sleep better, have more days at home in a familiar environment with improved locus of control and experience, and have less hospital-acquired disability.”16 Home hospital care is now approved at over 296 hospitals in 37 states. There exists a critical need to better serve PLWD and their family caregivers when they become acutely ill. Despite its focus on older adults, few home hospital efforts specifically target PLWD and may decline such patients due to insufficient family caregiver support in the home, perceived risk of caring for PLWD in the home, and lack of clear goals of care. We propose a 3-part PLWD-specific year-long pre-enrolled AHCaH pathway: 1) in-home SIC and caregiver resourcing; 2) video and in-home acute illness evaluation on demand including mobile integrated health paramedic and home health aide; and 3) as needed and as appropriate AHCaH with additional ADRD resources including home health aide care and delirium prevention measures. Our overarching aim is to implement and evaluate (NIH Stage III) an AHCaH pathway specifically for PLWD that will serve as a national model. We will evaluate in a randomized controlled trial the effect of a pre- enrollment AHCaH pathway on quality of life over 12 months for persons with moderate to severe dementia (Aim 1). We will evaluate the experiences of family caregivers using a mixed-methods approach (quantitative and qualitative) in both pre-enrolled home hospital and usual care (Aim 2).

NIH Research Projects · FY 2025 · 2024-09

Project Summary: Osteopetrosis is a heritable skeletal disorder characterized by abnormal systemic increase in bone mass density, bone marrow failure, bone fractures, osteomyelitis, and impaired vision and hearing, among other clinical features leading to physical disability and death of patients. Osteopetrosis can be caused by mutations in the Clcn7 gene that result in defects in the function of osteoclasts (OCs), tissue resident cells of the bone derived from hematopoietic progenitors and specialized in bone resorption. Bone marrow transplantation (BMT), which replaces defective OCs and restores bone resorption is the only available treatment for osteopetrosis despite knowing its etiology for decades. However, not all patients are eligible for BMT, depend on HLA-match donors, and patients who receive BMT frequently suffer from severe complications including toxicity of conditioning treatment, graft versus host disease (GVHD), among others, which results in high transplant-related mortality. Alternative therapies for osteopetrosis have been reported that include genetic therapy using retroviral infection for delivery, unfortunately clinical trials showed elevated incidence of vector- induced hematological malignancies in these patients. Others have reported a therapeutic approach, currently in clinical trials, that utilizes lentiviral infection in cells to provide with functional genes followed by transplantation, however, this therapy requires conditioning treatment including irradiation or chemotherapy to achieve engraftment of genetically modified cells. In this grant, we proposed a novel alternative therapeutic strategy that combines CRISPR/Cas9-based genome editing tools to correct osteopetrosis-causing Clcn7 mutations ex vivo in hematopoietic progenitors, followed by autologous infusion of mutation-corrected cells into osteopetrotic mice to restore normal bone remodeling. This novel approach overcomes the undesired long term and fatal consequences of BTM, since it does not require HLA-match donors and conditioning treatment including irradiation or chemotherapy for cell engraftment. The goal of this grant is to develop and establish standard protocols for the assessment, design, testing and validation of CRISPR/Cas9 genome editing technologies that would offer individual patients with a mutation-specific and cell-specific approach to treat osteopetrosis.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT Approximately 1 in 3 reproductive aged women and girls suffer from migraine, the most disabling disease of this demographic worldwide. Affective disorders are 2-3 times more common among migraineurs, and migraineurs with psychiatric comorbidity report more functional impairment and worse quality of life than migraineurs without psychiatric conditions. Despite the high prevalence of this comorbidity and evidence of shared pathophysiology, the association between migraine and affective disorders remains largely unexplored. Fluctuations in female sex hormone levels play a significant role in migraine and affective disorder presentations and are particularly volatile across the menstrual cycle and during reproductive life transitions (puberty, postpartum, menopause); however, the longitudinal relationship between migraines and affective disorders across the life course has not been studied. Up to two-thirds of female migraineurs experience menstrual migraine and half of women with affective disorders report premenstrual exacerbation of anxiety and depression. However, migraine has not been studied as a risk factor for premenstrual syndrome/premenstrual dysphoric disorder or as a marker of increased hormonal sensitivity among women with anxiety or depression. The objective of this research is to collect and analyze detailed longitudinal data on migraine and mental health symptoms to establish migraineurs as a unique phenotype of individuals with affective disorders due to their vulnerability to hormonal fluctuations. In Aim 1, Dr. Crowe will determine the longitudinal association between migraine and affective disorders across the lifespan with an emphasis on hormonal transitions using data from the Nurses’ Health Study cohorts. In Aims 2 and 3, she will focus her work on hormonal fluctuations across the menstrual cycle. She will design and implement a sub-study in the Nurses’ Health Study 3 and Growing Up Today Study cohorts using smartphone data and ecological momentary analysis to estimate the relationship between migraine (menstrual and overall) and premenstrual syndrome/premenstrual dysphoric disorders (Aim 2). Dr. Crowe will also collect data on affective disorder symptom variability across the menstrual cycle among migraineurs, compared to non-migraineurs (Aim 3). To carry out this research, Dr. Crowe will receive training and mentorship from a team with expertise in epidemiological measurement of affective disorders, smartphone digital phenotyping, and modeling of high-dimensional longitudinal data. She will also draw on the myriad professional resources available at Brigham and Women’s Hospital, Harvard Medical School, and Harvard T.H. Chan School of Public Health. Altogether, the proposed research and training will improve affective disorder risk assessment and screening, inform treatment for those with comorbid affective disorders and migraine and prepare Dr. Crowe with the skills and preliminary data to become an independent researcher at the intersection of mental health and reproductive epidemiology.

NIH Research Projects · FY 2026 · 2024-09

Project Summary/Abstract Minimal change disease and primary focal and segmental glomerulosclerosis are morphologic expressions of a diffuse podocytopathy of to date unknown cause, and all present with acute onset Nephrotic Syndrome. Although the majority of patients achieve clinical remission, relapse and treatment failure is common, and when progressing to end stage kidney disease, the disease frequently and vigorously recurs in the allograft. We recently published a groundbreaking study that identified circulating autoantibodies against the extracellular domain of nephrin in a subset of adults and children with non-genetic Minimal Change Disease and in a single patient with recurrent disease in the allograft, which correlate with disease activity. Our findings underpin the paradigm-shifting hypothesis that at least a subset of these diseases are mediated by an organ- specific, antibody-mediated autoimmune disease of B cell origin which causes an acquired diffuse podocytopathy by means of direct action of the autoantibodies on the podocyte, an essential component of the kidney filter. The current proposal now aims at proving this concept by 1) establishing pathogenic autoimmunity in anti-nephrin mediated podocytopathy by means of analyzing immunophenotypes and immunological signatures, and by 2) identifying direct downstream pathomechanistic effects by nephrin autoantibodies that cause changes in podocyte structure and function. Altogether, results from these studies will serve as critical basis for the development of novel, personalized and targeted treatment strategies for our patients with minimal change disease, primary focal and segmental glomerulosclerosis as well as those patients with recurrent disease in the transplant.

NIH Research Projects · FY 2024 · 2024-09

Project Summary In mammals, 5-methylcytosine is the most common form of DNA methylation, and the level of methylation of some specific CpG sites shows a strong correlation with age. These correlations can be used to build machine learning-based models that can accurately predict the age of biological samples. Because these models can quantify age with very high accuracy, researchers have termed them epigenetic aging clocks (e.g., Horvath’s pan-tissue epigenetic clock and Hannum’s blood-based epigenetic clock). However, the reliability of existing epigenetic clocks is limited, as they are built based on pure correlations, and it is unclear whether age- associated methylation changes are causal to aging-related phenotypes. A new generation of epigenetic clocks built on causal information will be more reliable and can enable the possibility of large-scale screening of anti-aging interventions. For the F99 phase of this proposal, I performed epigenome-wide Mendelian Randomization to identify CpGs potentially causal to aging-related traits. This causal information was then incorporated into epigenetic clock models to build causality-informed aging clocks, which are shown to separate age-related damage from adaptation, namely DamAge and AdaptAge. I also built ClockBase, a database that contains over 300,000 experimental samples from GEO with the epigenetic age pre-calculated. I plan to further standardize the sample information using large language models and apply the causality-informed biomarkers to screen for anti-aging interventions. In the K00 phase, I will use the protein language model and protein design tool to expand the universe of anti- aging interventions. Specifically, I will study the protein structural features across mammalian species with various lifespans to understand which features are associated with longevity. Then, I can incorporate this information into protein design and optimize existing proteins to support a longer lifespan. This proposal will advance our understanding of the molecular mechanisms underlying aging by incorporating causality into epigenetic clock models. By distinguishing between age-related damage and adaptation, we can develop more precise and informative aging biomarkers, which will have significant implications for aging research and potential clinical applications. The K00 phase of the project will pioneer the application of protein language models and protein design tools in aging research. Ultimately, it could pave the way for a completely new branch of aging research – treating aging through the gradual redesign of the proteome.

NIH Research Projects · FY 2024 · 2024-09

The All of Us Research Program is a landmark longitudinal cohort study that aims to enroll 1 million or more participants reflecting all people of the United States and create a unique biomedical data resource that can advance precision medicine and improve health. Since 2016, the All of Us New England Consortium (AoUNE) has contributed to the success of the national program by engaging, enrolling and retaining individuals in Eastern Massachusetts through a collaboration of Mass General Brigham (MGB), New England’s largest regional health system, and Boston Medical Center (BMC), the largest safety net hospital in the Northeast. In the process, we have designed and implemented robust procedures for participant retention strategies that leverage multimodal engage to retain strategies in all populations. We have achieved high retention of our participant partners (PPs), including both passive (87%) and active (>40%) retention rates. Importantly, we have contributed to consortium-wide activities that have led to successful scientific contributions to retention. The AoUNE PIs are active participants in All of Us engagement activities as Engagement lead within the national program, and locally with our Community Advisory Panel (CAP). We are well poised to support the Division of Engagement and Outreach to achieve the NIH All of Us Area of Interest 1 to focus on: • Aim 1: Supporting existing participants and retention efforts. • Aim 2: Sustaining engagement efforts and disseminating research findings to participants as a part of return of value. We propose a process that will develop evidence-based solutions/models for scalable program wide-efforts to support the shift from enrollment to an engage to retain model for the All of Us Research Program.

NIH Research Projects · FY 2025 · 2024-09

ABSTRACT Women with severe aortic stenosis (AS), a condition characterized by the narrowing of the aortic valve opening, often experience delayed diagnosis, undertreatment, and higher mortality rates compared to men, indicating both delayed care-seeking and a lack of appropriate diagnostics and monitoring for female patients. Yet, the influence of anatomical and functional differences in the female population on AS presentation, management, and outcomes remains poorly understood. Furthermore, despite the prevalence of symptoms, women with severe AS receive less aortic valve replacement (AVR) treatment and have higher excess mortality rates over a five-year period compared to men. Our proposed project integrates innovative medical image processing and computational modeling methods, such as statistical shape analysis (SSA), convolutional neural networks (CNN), and inverse finite element analysis (FEA), to gain sex-specific insights into cardiac remodeling and dysfunction, with a specific focus on severe AS in women. By focusing on cardiac remodeling, a consequence of prolonged aortic valve disease, our goal is to enhance AS treatment for women by considering sex-specific differences in ventricular responses to AVR-induced afterload. To achieve this, we will develop a personalized, mathematical approach that leverages sex-differentiating anatomical and functional characteristics of the left ventricle (LV), ultimately aiming to improve survival outcomes. Additionally, we will compare the predictive value of these sex- differentiating measures to traditional indices, enhancing our understanding of their effectiveness in guiding clinical management. We hypothesize that advanced anatomical metrics (e.g., shape scores) and material characteristics (e.g., cardiac stiffness) are superior predictors of post-intervention cardiac events and dysfunction compared to traditionally collected clinical measures. Our research consists of two main aims. Aim 1 involves developing a fully automated, neural network pipeline to segment clinical images, creating an advanced SSA model to extract hidden geometrical features, and establishing a correlation between shape scores and post- intervention clinical events. This analysis will assess the predictive power of sex-specific measures compared to the male population, cases where sex is not considered in the model training, and universal clinical indices. Aim 2 focuses on developing a computational tool to estimate patient-specific stiffness of the inhomogeneous LV tissue, with an examination of its potential value in predicting diastolic dysfunction and AVR outcomes. Our research serves as a steppingstone to guide clinicians in preprocedural patient selection, optimize surgical timing, and improve survival outcomes. By developing a sex-specific risk stratification tool and a mechanistic framework for effective prognosis, we aim to provide valuable means to enhance treatment and mitigate devastating events associated with severe AS, particularly for female patients.

NIH Research Projects · FY 2024 · 2024-09

ABSTRACT Venous thromboembolism (VTE), consisting of pulmonary embolism and deep vein thrombosis, is a common and consequential public health problem affecting up to 600,000 adults in the United States annually. VTE requires timely detection and treatment, but the VTE diagnosis workflow in ambulatory care is fraught with challenges, including delays, inaccuracies, and misdirection, influenced by multiple factors including nonspecific symptoms and a lack of systematic measurement and quality improvement tools. VTE is associated with health disparities (highest in black and African American populations) and missed or delayed VTE diagnosis can have serious consequences for patient and healthcare cost outcomes, resulting in increased risk of morbidity, mortality, and prolonged hospital stays. These issues may be further compounded by variation in the types of ambulatory care practices (primary care versus urgent care) and the geographical locations and socio-economic status where patients seek care. Our team developed an electronic clinical quality measure (eCQM) that uses structured and unstructured EHR data to measure Diagnostic Delay of Venous Thromboembolism (DOVE) in primary care settings that was recently endorsed by the Partnership for Quality Measurement. Using this eCQM, the rate of delayed VTE diagnosis in urban, metro, and rural primary care practices across three large healthcare systems using different EHR systems was found to be consistently over 70%, suggesting that this is an important type of diagnostic error (DE) with likely negative impacts on patient outcomes. Building on our preliminary work, we propose to leverage EHR data and stakeholder expertise to gain an understanding of VTE DE risk factors, disparities and outcomes. We will develop artificial intelligence (AI) and statistical learning tools to identify, factorize, and address vulnerabilities in a range of VTE DE workflows including delayed and missed VTE diagnosis in both ambulatory and urgent care settings. This study brings together a strong interdisciplinary team of experts in primary care, VTE diagnosis, informatics, data science (natural language processing and machine learning). The advanced data-driven eCQM will be refined using high-dimensional EHR data (structured and unstructured) to quantfy timely, delayed and missed VTE diagnoses. To increase generalizability of the results, we will use multiple data sources from 220 primary care/urgent care practices and clinics associated with 13 hospitals from urban, metro and rural clinics in the Northeastern and Southern United States (2 different EHR vendors). If successful, this approach will substantially improve our understanding of DEs and related risk factors, VTE DE related costs and build a foundation for improving VTE diagnostic accuracy and precision and diminish disparities in healthcare outcomes.

NIH Research Projects · FY 2026 · 2024-09

Project Summary Migraine, a chronic intermittent headache disorder, ranks in the top five causes for years lived with disability. Approximately 15% of the US population experiences migraine, with women afflicted approximately twice as often as men. Although pharmacologic medications are often used as first-line treatments for migraine, these treatments may have difficult side effects and may increase the risk for migraine chronification. As a result, individuals with migraine often turn to other treatment modalities, including the use of natural products and dietary supplements, for long-term migraine management. Preliminary evidence from the COcoa Supplement and Multivitamin Outcomes Study (COSMOS) suggests a cocoa extract supplement may have beneficial effects on migraine. COSMOS was a randomized, double-blind, placebo-controlled trial testing a cocoa extract supplement containing 500 mg cocoa flavanols/d (including 80 mg (-)-epicatechin, plus 15 mg caffeine and 50 mg theobromine) for the prevention of cancer and cardiovascular disease in 21,442 older adults. Every six months, participants were asked about the occurrence of adverse events, including migraine. Individuals randomized to the cocoa extract supplement were significantly less likely to report migraine (hazard ratio (HR)=0.85; 95% confidence interval (CI): 0.78, 0.93) than those assigned to placebo. However, several important gaps in knowledge remain. First, COSMOS enrolled only older adults but the prevalence and disability burden of migraine is highest at younger ages (i.e. 15-49 years) and it is unknown if cocoa extract is effective in a younger population. Second, COSMOS did not collect detailed information on changes in migraine frequency, as recommended by current guidelines for trials of migraine treatments. Finally, an animal study suggested a potential dose-response relationship between cocoa consumption and migraine pathophysiology, highlighting the importance of considering higher amounts of cocoa extract and bioactive content in future human studies. Our long-term goal is to conduct a fully powered trial evaluating the effectiveness of a cocoa extract supplement on reducing the frequency of migraine attacks. As a first step, we propose to conduct a three-arm pilot study. We will recruit and randomize (1:1:1 allocation ratio) 114 adults with episodic migraine to receive one of the following treatments for 12 weeks: 1) 1000 mg of cocoa extract (including 160 mg/d (-)-epicatechin, 100 mg theobromine, and 30 mg caffeine); 2) 500 mg of cocoa extract (including 80 mg/d (-)-epicatechin, 50 mg theobromine, and 15 mg caffeine); or 3) placebo. Our proposed pilot study will allow us to address the following aims: 1) to assess the feasibility of recruitment, retention, and adherence; 2) to determine the acceptability of higher doses of cocoa extract supplement to this patient population; 3) to optimize data collection and data management and establish the infrastructure needed for a large-scale trial.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT Immune checkpoint inhibitors (ICIs) have drastically improved cancer survival over the past decade, but this survival comes at the cost of a new class of immune-related adverse events (irAEs) characterized by inflammatory and auto-immune pathologies that occur and persist long after ICI discontinuation. These irAEs can have major impacts on long-term quality-of-life, but our ability to appropriately address them is limited by an insufficient understanding of irAE rates and severity profiles. Automated methods to identify and monitor irAEs could improve clinical care, biomedical research, and pharmacovigilance, however, irAEs are often only documented in clinical text and cannot currently be automatically extracted from the EHR at scale. The overarching objective of this proposal is to create applied informatics technologies for cancer surveillance research and survivorship care in patients treated with ICIs. Our central innovation is the development and clinical validation of natural language processing methods, particularly neural language models, that can handle the complexities of the EHR for irAE extraction using unstructured and structured data streams. In Specific Aim 1, we conduct a clinical trial of informatics-assisted irAE detection from the EHR, measuring feasibility and effectiveness in improving registration onto Alliance A151804, an NCI cooperative group irAE biorepository. This will be the first trial of informatics-based adverse event detection for cancer care and a major step toward clinical translation. In Specific Aim 2, we develop new methods to extract irAEs according to their severity grade for detailed and standardized computational phenotyping, and perform external validations. In Specific Aim 3, we optimize generalist large language models for irAE information extraction without task- specific fine-tuning, including innovative methods to tailor models’ diagnostic reasoning to each patient. This work is highly significant for developing, applying, and validating informatics methods that take full advantage of the EHR to support the long-term goal of improving quality-of-life and survival in patients treated with ICIs. This clinical translational work will be carried out by an expert team of cancer clinicians, clinical trialists, informaticians, and computer scientists.