Johns Hopkins University

NIH Research Projects · FY 2025 · 2024-09

The “virtual front door”–websites and digital information–is often the first interaction point that patients have with healthcare systems. However, people who are blind or have low vision face barriers in accessing healthcare information and the appointment-making processes when website information is inaccessible. The American Health Information Management Association (AHIMA) Foundation reported that in 2022, only 5% of hospitals were compliant with Website Content Accessibility Guidelines (WCAG 2.1) and other legal requirements. Principles of universal design could help people who are blind, have low vision, or other disabilities readily establish care. Universal design improves program uptake and effectiveness but is rare in healthcare. We have developed the RAMP (Removing Barriers to the Management of Patient care) score to evaluate the universal design of healthcare system websites and processes for allowing people to establish necessary specialty care. This project will improve the “virtual front door” to specialty care for people who are blind or have low vision. Aim 1, we will refine our RAMP score to more robustly capture the experience of people who have low vision and or are blind in making healthcare appointments. In Aim 2, we will scale RAMP scoring and develop a publicly available data dashboard to allow comparisons of these scores across academic medical centers. And in Aim 3, we will use implementation science approaches to develop a toolbox of tailorable interventions that outline specific actions which academic medical centers can take to improve RAMP scores. By advancing the science of digital medicine, and we will build tools with which academic medical centers can better provide care to people have low vision or are blind, as well as Americans with other disabilities.

NIH Research Projects · FY 2025 · 2024-09

Understanding the unique vulnerability of certain cell populations in the brain to Alzheimer's disease (AD) - a debilitating, chronic disease affecting 6.2M Americans - has proven an elusive goal. Amyloid beta (Aβ) plaques and neurofibrillary tau tangle (NFT) pathology are hallmarks of AD that first become apparent in particularly vulnerable regions of the brain such as the entorhinal cortex (ERC) decades before symptom onset. Understanding how AD pathology affects specific brain regions, including a more complete understanding of the pathologic and molecular changes in selectively vulnerable areas is critical for the development and timing of potential AD treatments. The selective vulnerability of the medial temporal lobe (MTL) is well established, however, a more global picture of how tau pathology affects the mesial temporal lobe, its precise relationship to regional atrophy, and how this pathology is related to molecular changes associated with AD dementia remains unclear. To achieve this goal, we propose to integrate high-field post- mortem imaging, histological and spatial transcriptomic sections from the same individuals in a common coordinate system and learn how gene expression differences in the ERC are associated with early regional susceptibility to AD pathology. The central goal of the proposal is to link the spatial and temporal disease progression of MR markers at mm scale to the molecular substrates of tau pathology and spatial transcriptomics in layer 2 ERC. Uncovering the correlation of neuronal transcriptional changes to NFT pathology and to macroscopic shape change is necessary to understanding the biological link between these different scales and measures of AD pathology. This linkage has so far remained elusive because of the gaps in spatial scale between clinical MRI markers with histological and cellular assessments. We propose to close these gaps by introducing 100 μm high-field postmortem dense MRI reconstructions of the MTL allowing us to combine clinically-derived ERC population disease progression markers with histopathological and molecular profiling in these coordinates. In Aim 1 of this proposal, we will establish a protocol for postmortem high-field MRI and histological analyses of ERC to integrate microscale digital tau-pathology with Mai-Paxinos coordinates and population-based atlas mapping. We draw on ongoing comprehensive and longitudinal studies of aging including BIOCARD and ADRC studies which include cognitive measures, in vivo MRI scans, and postmortem protocols. In Aim 2, we will identify spatial gene expression signatures in layer 2 ERC neurons by anatomic location in Mai-Paxinos coordinates and quantify spatial transcriptional changes associated with regional AD pathology registered to MR measures and clinical outcomes. Integration of regional shape changes by MRI with pathologic and transcriptional information will shed light on the interaction of AD pathology with vulnerable ERC regions and underlying cell type and transcriptional signatures, and will provide the basis for the potential development of new MRI-based biomarkers of AD tau pathology which would be tested in future studies using in vivo clinical MRI.

NIH Research Projects · FY 2026 · 2024-09

Abstract Large-scale epidemiologic studies, including biobanks and genome-wide association studies (GWAS), are now rapidly leading to the identification of novel risk factors for complex diseases. There is increasing opportunity to develop comprehensive models for disease risk incorporating genetic markers, other biomarkers, life-style factors and sociodemographic indicators. There are, however, major challenges as information on all of the potential risk factors are often not available in a single adequately large study. Instead, information may be available from different studies, each of which may include some subsets of the desired variables. Further, because of privacy concerns with individual-level data, only summary-level information, i.e., estimates of model parameters, may be available from some studies. We propose to develop a series of novel statistical methods that will allow data integration across disparate datasets to tackle modern problems faced in genetic and epidemiologic studies. In Aim 1, we will develop a framework for building generalized linear models using detail covariate data from a main study, while incorporating summary-statistics information from an external study. We will develop a series of applications of this framework to GWAS where we will use covariate data from biobanks and perform combined analysis with external summary- statistics data for powerful exploration of gene-environment interactions and mediations. In Aim 2, we will extend the proposed framework of Aim 1 for developing models with high-dimensional covariates with regularized parameter estimates. We will develop novel computational algorithms for practical implementation of the method for large-scale data analysis and develop new theory for inference on model parameters. We will further develop application of the proposed method for fine-mapping and polygenic risk score analysis conditional on covariates. In Aim 3, we will develop applications of the data integration framework to account for different accuracy/depth of disease outcome data across different studies. We will illustrate applications of different methods across the aims using datasets on cancers (breast, melanoma and lung), cardiometabolic traits (type-2 diabetes and coronary artery disease) and a psychiatric disorder (major depression disorder). We will distribute develop and freely distribute user friendly software.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY Inconsistencies between observed effects on biological versus clinical endpoints of recent disease-modifying therapies for Alzheimer's Disease and Related Dementias (ADRD) highlight existing gaps in our understanding of biological processes of ADRD. Better characterization of the interplay between biology and the social environment may help explain these discrepancies. To address this critical gap, the proposed research takes a novel approach to understanding ADRD mechanisms by leveraging cross-national comparisons between the US and India to evaluate biological underpinnings of ADRD, focusing on biomarkers of neurodegeneration, vascular, nutritional, and inflammatory systems, and their interface with social and economic factors. With over 1.4 billion people India is the world's most populous country with a rapidly growing older population and has very different social, economic, and demographic patterns of risk for ADRD compared to the US. Given this novel opportunity for cross-national comparisons of the interface between biological markers of disease and clinical outcomes, we will be able to identify common biological pathways observed in very different social and economic contexts. Our overarching goals are to leverage data collected via Harmonized Cognitive Assessment Protocols (HCAPs) in the US and India to assess the interplay between country, social factors, and ADRD biology using recently collected and rigorously cross-nationally harmonized data on neurodegenerative biomarkers, cognitive outcomes, and other markers of vascular, nutritional, and inflammatory systems. Aim 1 uses neurodegenerative biomarkers to classify people into pathological subtypes, then evaluates associations of other vascular, nutritional, inflammatory, and demographic factors with these subtypes. Aim 2 associates each plasma biomarker with cognitive outcomes, while Aim 3 tests for effect modification by socioeconomic factors. Aim 4 will evaluate the relative contribution of variance in plasma biomarkers alongside other factors in predicting cognitive outcomes. Key innovations include cross-national cohort integration, translational potential to interventions, biomarker research equity, and a research framework centered on the biological and social determinants of ADRD. This proposed research is pivotal in leveraging biology to understand social differences in cognition because cross-national comparisons between the US and India, particularly regarding relationships of biomarkers to cognition and effect modification by social and economic factors, will provide evidence as to the generalizability of findings on ADRD mechanisms in different contexts. Our results will set the stage for high-quality cross-national research to identify intervention targets for ADRD, with the ultimate objective of preventing and/or delaying the onset of ADRD from a global perspective.

NIH Research Projects · FY 2025 · 2024-09

The H-H U54 Program aims to strengthen collaborative research, training, and community-focused initiatives between Howard University (HU) and the Johns Hopkins University (JHU) Sidney Kimmel Comprehensive Cancer Center (SKCCC). Based in the Washington, DC–Maryland–Virginia (DMV) region, the two institutions together serve a large urban population with varied cancer care needs. Howard University and Johns Hopkins University possess complementary strengths that position them to jointly develop innovative programs that improve cancer research, education, and care delivery. H-H U54 will address the regional cancer burden by integrating research excellence, training infrastructure, and community outreach. The program’s overarching goals are to: (1) support collaborative research projects; (2) expand training opportunities at HU; and (3) improve cancer-related education and care in the region. H-H U54 includes four Cores (Administrative, Outreach, Research Education, and Planning & Evaluation); two Full Research Projects; one Pilot Research Project; and one Shared Resource Core (Data Science Shared Resource). Through these components, the Partnership will: (1) build cancer research and training capacity at HU through collaborative projects and shared resources; (2) advance transdisciplinary cancer research at SKCCC with a focus on regional needs; (3) increase the number of investigators and trainees engaged in cancer-focused research; (4) strengthen the research pipeline through ROI@J-HU (Research Opportunity and Innovation at Johns Hopkins and Howard Universities), a structured framework for training and mentorship across undergraduate, graduate, and early-career levels; and (5) implement community outreach and education programs to enhance public understanding of cancer risk, prevention, and care. The Planning and Evaluation Core will oversee continuous improvement of all program elements. Collectively, H-H U54 aims to foster institutional synergy, cultivate the next generation of cancer researchers, and improve cancer outcomes in the DMV region.

NIH Research Projects · FY 2024 · 2024-09

Project Summary: This work is proposed in response to NOT-AR-23-006 as a mechanistic study of innate and adaptive immune responses in systemic lupus erythematosus (SLE). SLE is a systemic rheumatic disease that disproportionately impacts females and racially and ethnically disenfranchised groups. Despite advances in treatment, the molecular mechanisms of SLE pathogenesis remain poorly understood. Cyclic G/AMP (cGAMP) synthetase (cGAS) is a central driver of the cell- intrinsic interferon (IFN) response which has been linked to SLE pathogenesis. When activated by cytosolic double-stranded DNA (dsDNA), cGAS generates cGAMP, a key second messenger for downstream IFN signaling. Resting cGAS is a monomer, and dsDNA-dependent activation entails dimerization and subsequent higher-order oligomer formation, resulting in the generation of phase-separated cGAS. In preliminary studies, we have identified the presence of autoantibodies targeting cGAS in SLE patient sera, which are associated with SLE disease activity. In addition, we have observed that cGAS can bind to and forms condensates on various nucleic acids, but dsDNA is the only ligand that permits the dimerization required for enzymatic activity and formation of hyrdo-gel-like condensates. Building upon these novel observations, we propose to test the hypothesis that biophysical changes triggered by cGAS activation shape the adaptive immune response that leads to the targeting of cGAS as an autoantigen in a subset of SLE patients with active disease. In Aim 1, we will test the theory that dsDNA-dependent gel-like cGAS condensates are preferentially targeted by SLE autoantibodies. To do this, we will develop assays incorporating purified cGAS (monomer vs dimer) complexed with various nucleic acid ligands (dsDNA, dsRNA, ssDNA, ssRNA, DNA-RNA hybrid). In Aim 2, we will determine if phase separation and/or ligand binding alter cGAS uptake and presentation by antigen presenting cells (APCs). To accomplish this, we will utilize monocyte-derived dendritic cells (moDCs) exposed to the same panel of cGAS-ligand complexes used in Aim 1, and will analyze cGAS uptake and subsequent moDC activation using confocal microscopy and flow cytometry. Then, we will examine the effect of nucleic acid binding on cGAS peptide presentation in the context of MHC II using a natural antigen processing assay (NAPA). We anticipate that this work will reveal interplay between innate and adaptive immune components that drives aberrant immune phenomena observed in SLE, providing a conceptual and experimental framework that could be readily applied to the numerous nucleic acid-binding autoantigens featured in SLE.

NIH Research Projects · FY 2025 · 2024-09

HIV pre-exposure prophylaxis (PrEP) uptake has progressed slowly for men who have sex with men (MSM) in the United States, a population disproportionately burdened by HIV. Addressing trauma and related sequelae such as PTSD may help optimize PrEP uptake in this population, as MSM are disproportionately exposed to trauma, particularly interpersonal violence, much of which is motivated by prejudice. Interpersonal violence carries the highest conditional risk of any trauma exposure for developing posttraumatic stress disorder (PTSD), risk which is further amplified in the case of prejudice-motivated violence. There is limited but compelling evidence to suggest that violent trauma exposure and PTSD symptomology may negatively affect PrEP uptake. However, research with large MSM-only samples that examines these pathways longitudinally is lacking, as are trauma-informed PrEP interventions for MSM. This K01 will provide the candidate, Dr. John Mark Wiginton, with the expertise, skills, and opportunities necessary to examine prejudice-motivated interpersonal violence and PrEP uptake pathways among MSM using latent class mediation (Research Aim 1); apply these findings, along with qualitative data from community-engaged research with local MSM and stakeholders, toward development of a novel trauma-informed mHealth + peer support intervention (called BOUNCE) targeting PrEP and coping self-efficacy, peer/social support, and resilience factors (safety, autonomy, trust, trauma awareness) to support PrEP uptake among MSM (Research Aim 2); and conduct usability testing and a proof-of-concept pilot of BOUNCE to assess feasibility, acceptability, and PrEP uptake. Dr. Wiginton will utilize JHU’s training infrastructure to build his professional independence and further cultivate his competence to develop and test trauma-informed HIV prevention interventions tailored to MSM populations to improve HIV disparities and broader sexual health and psychosocial wellness in these populations. Dr. Wiginton seeks training to build his topical and theoretical expertise in trauma exposure, PTSD symptomology, and health behavior impacts (Training Aim 1); gain knowledge and experience conducting community-engaged research (Training Aim 2); develop expertise in designing and delivering interventions (Training Aim 3); build competence in early-phase clinical trial methods and approaches to evaluate behavioral interventions (Training Aim 4); and foster personal and professional development skills (Training Aim 5). With this award, Dr. Wiginton will gain not only exceptional training, but also valuable data, from which to build his research independence with a competitive future R01 to test BOUNCE more rigorously in a Type 1 Hybrid Trial.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY Gun violence in the United States remains a persistent and escalating public health crisis, resulting in over 100 deaths each day. This burden is disproportionately concentrated in communities experiencing socioeconomic hardship, where factors such as poverty, limited educational opportunities, and other social determinants of health (SDoH) converge. These determinants are closely linked to where individuals live, work, and spend time, highlighting the importance of incorporating place-based factors into firearm violence research. This proposed project addresses that need by investigating the spatial and temporal dynamics of gun violence at the neighborhood level in Washington, D.C. from 2014 to the present. My long-term career goal is to become a leading interdisciplinary researcher in firearm injury and mortality prevention, focusing on the spatial, behavioral, and environmental contributors to firearm risk. Through this K18 proposal, I will pursue a career development plan that strengthens my expertise in spatial science with targeted training in gun violence research to complement my growing experience in these areas. My mentoring team offers the breadth of interdisciplinary expertise necessary to support my development and transition to an independent investigator working at the intersection of spatial science and firearm violence research. The proposed study uses publicly available criminology, Census, and SDoH data to (1) develop an analytical approach to detect emerging spatial-temporal clusters of gun violence incidents at the neighborhood and weekly levels in Washington, D.C.; (2) develop a spatial-temporal regression model to examine the impact of SDoH and other place-based factors on gun violence risk; and (3) examine potential spatial-temporal associations between gun violence incidents and alcohol outlet access and hours of operation. Aim 1 hypothesizes that anomalous clusters of gun violence will be identified throughout the study area and time period after adjusting for covariates and baseline conditions. Aim 2 hypothesizes that (a) variation in neighborhood-level SDoH is strongly associated with gun violence risk and (b) neighborhoods adjacent to high-risk areas will exhibit spatial spillover effects. Aim 3 hypothesizes that (a) alcohol outlet access is associated with elevated gun violence risk and (b) outlets with longer and later operating hours will be linked to increased incident rates. The frameworks and findings from this research will enhance our understanding of the spatial and temporal determinants of gun violence and. This work will lay the foundation for future research efforts and larger funded proposals (e.g., R01), and we will collaborate with local partners in Washington, D.C. to support the dissemination and application of key findings related to community safety and surveillance.

NIH Research Projects · FY 2025 · 2024-09

Genetics and genomics have become increasingly important in research and medicine. The understanding of the genetic contribution to disease is quickly expanding from rare disease to common disease, making genetics and genomics relevant to all. We endorse that all levels of the research and clinical workforce should have fundamental knowledge and skills in genetics and genomics and understand its role in public health. These steps are necessary to boost enrollment in research and effectively incorporate genetics and genomics into healthcare. To achieve this goal, we will develop genomics educational modules (GEMs) for the entry-level medical and research workforce. These modules will build on our recent experience developing and delivering an online Genetic Assistant Training Program (GATP) to over 300 successful graduates. Using participant feedback from the GATP and input from a carefully selected Advisory Committee of educators and employers, we will develop GEM content based on the most update to genomics information, best practices, and workforce needs. The content of these modules will be devoted to the following topics: Genetics & Genomics of Cardiovascular Conditions, Cancer, Reproductive Healthcare, Newborn Health, Child Health, Laboratory Genomics, and Responsible Conduct of Research. Educational content will include slide decks, recorded lectures, lab protocols, and assessments. We will incorporate animations in education modules to boost engagement and use the educational principles of adult learning theory and universal design for learning to maximize the educational impact. We will pilot and refine existing and new GEMs targeted to students in entry-level training programs at three local partner sites that offer courses for laboratory associates, medical assistants, and community health workers. These sites include Baltimore’s BioTechnical Institute (BTI), the Community College of Baltimore County (CCBC) Medical Assistant training program, and the Baltimore City Community College (BCCC) Healthcare Workforce Development Program. These sites were selected given that they have established entry-level training programs, their programs include multiple professions that span both laboratory and clinical positions, and train individuals that are likely to be hired by the multitude of local research and medical institutions and companies. Ultimately, we will disseminate the GEMs at no cost on an easily accessible website with the capability to be downloaded and used both nationally and internationally.

NIH Research Projects · FY 2024 · 2024-09

Abstract Johns Hopkins John G. Bartlett Specialty Practice (JGBSP) and Johns Hopkins HIV Women's Health Program (JHHWHP) provides comprehensive HIV care and treatment to women (85% Black/African American) living with HIV/AIDS in Baltimore. The network of Hopkins clinicians practicing in JGBSP and JHHWHP (called the Hopkins HIV Collaborative) identify multiple complex unmet health and social issues daily, such as intimate partner violence (IPV), housing instability and food insecurity that negatively impacts the health of women in their care. The intersection of IPV, poor mental health, housing instability and food insecurity are associated with suboptimal HIV prevention and treatment outcomes, such as antiretroviral therapy failure and unsafe sexual practices. Approaches to IPV and social determinants of health in healthcare organizations are evolving from interventions that targets the woman’s behavior (”she should leave the abuser”) to interventions that partner with community organizations to address IPV as a pervasive health and social problem embedded in structural inequities. Hopkins HIV Collaborative and Hopkins School of Nursing in partnership with community organizations, House of Ruth, Maryland (HRM), Technical Assistance Collaborative (TAC) and Older Women Embracing Life (OWEL) and expert Advisory Board will adapt and implement a trauma and violence informed care (TVIC) intervention to improve HIV-related and mental outcomes by addressing social determinants of health with abused women living with HIV/AIDS (WLWHA). TVIC is an equity-based approach guided by the ecological framework to account for the intersecting impacts of HIV, IPV and structural inequities on a woman’s life. The TVIC intervention includes: (1) universal education to create a safe environment in the healthcare setting for IPV disclosure; (2) counseling and advocacy based on women strengths and priorities; (3) coordination with community partners to address unmet social determinant of health; and 4) integration of technology-facilitated safety planning (myPlan app) for clinic-community providers to support abused WLWHA to develop personalize safety plans that directly link to needed local services. The clinic-community partners will conduct a hybrid type 2 effectiveness-implementation study to determine the effectiveness of the adapted TVIC intervention on HIV-related (e.g. viral load/CD4 and adherence) and mental health (e.g. depression and PTSD) outcomes with IPV(+) WLWHA and IPV (–) WLWHA. The partners will also examine mechanisms (e.g., safety behaviors and resources, housing security, food security) by which the TVIC intervention improves HIV- related and mental health outcomes with abused WLWHA. Our partnership will further examine organizational, program and contextual factors that facilitate the implementation of the TVIC intervention and are critical to sustaining the intervention and clinic-community based partnerships.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Polygenic scores (PGS), constructed by common variants identified through large genome-wide association studies (GWAS), are effective tools in research and clinical applications. However, the interpretation of the functional roles of PGS—that involve hundreds to even thousands of common variants—in uncovering the specific components of a phenotype trait or a disease outcome is challenging. This will further obscure the interpretations of downstream analysis in identifying the causal relationships between risk factors and diseases. The proposed project aims to address a critical need to enhance the PGS applicability in investigating disease etiologies using cohort and family-based studies, integrating diverse sources of information including multi-omics data and environmental exposures. In particular, the work will 1) Develop a machine learning approach and its hypothesis testing framework to integrate trait-associated SNPs, multi-omics data, and summary-level statistics of the trait to model the mediating mechanisms underlying genetic associations. Then construct partitioned SNP sets or partitioned PGS (pPGS), with each partitioned component representing distinct functional regulatory pathways linked to the GWAS trait. 2) Develop likelihood-based methods utilizing multi-trait PGS to estimate the causal effects of multiple correlated exposures on an index disease in family-based studies, correcting for biases from assortative mating and population stratification. 3) Identify heterogeneous causal effects of exposures using partitioned SNP sets and pPGSxE interactions in leading causes of mortality, including cardiovascular diseases and cancers; and identify the causal relationships of multiple maternally-mediated exposures and biomarkers on childhood diseases, including autism spectrum disorders and orofacial clefts, through multi-ethnic case-parent trio studies. Finally, the developed methods and results will be disseminated through user-friendly software tools and a summary statistics database. This work will help researchers better utilize various genetic markers, rich omics data, and environmental variables for a more comprehensive and unbiased understanding of how molecular changes contribute to disease causalities, ultimately enhancing public health through better interventions and treatments. The candidate will receive training from a mentoring team of globally recognized experts in the fields of statistical genetics, machine learning, genomics, epidemiology, and subject-matter expertise in cardiovascular diseases, cancer, and mental health; supported by a vibrant intellectual environment at Johns Hopkins University with seminars, collaborations, career development resources, and advanced coursework. This award will allow the candidate to gain critical skills in research, mentoring, communication, and leadership that will ensure success in her long-term goal of establishing an independent research program, focused on pioneering the development of innovative computational methods to advance human health through large-scale dataset integration.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT In-hospital mortality rates for acute respiratory failure (ARF) have improved, resulting in increasing numbers of ARF survivors. While their survival is indicative of major clinical advances in care, many of these individuals are left with long-term physical, cognitive, and psychological sequelae of their critical illness, leading to reduced quality of life (QoL). Interventions in the post-intensive care unit (ICU) setting have struggled to make headway on improving QoL and there is an urgent need to understand relevant modifiable factors. Evidence suggests that health expectations and bothersome levels of uncertainty about future health are two such factors. The unifying goal of this proposal is to understand key factors associated with bothersome uncertainty and expectation formation in ARF survivors at hospital discharge, as these factors are potential targets for intervention. We will study a cohort of 65 ARF survivors to characterize the prevalence of bothersome uncertainty and test the hypothesis that it is associated with perceived quality of healthcare provider communication (Aim 1). We will also perform at least 25 semi-structured interviews with a purposively selected cohort to further elucidate the experiences which shaped ARF survivors’ level of uncertainty and identify the sources of information that most influenced their expectations (Aim 2). This work will be performed leveraging resources allocated to an existing parent study (1R01HL163660), to ensure feasibility and success within the time period described in this proposal. This work will fill a gap in knowledge about how bothersome uncertainty and health expectations develop at the time of hospital discharge after ARF. The results will be applicable to the development of post-ICU interventions addressing expectations and uncertainty. This study will provide the applicant with essential preliminary data for a future K-level grant and necessary training in clinical and qualitative research skills including conduct of a cohort study, collection of patient-reported outcomes, statistical analysis of quantitative data, and conduct and analysis of qualitative semi-structured interviews. This work will be foundational for the applicant’s long-term goal of becoming an independently funded clinician investigator working to improve the care of patients in the ICU.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract I am a principal data scientist and bioinformatics manager of The Experimental and Computational Genomics Core in the Sidney Kimmel Comprehensive Cancer Center (ECGC) at Johns Hopkins University. This Core offers comprehensive bioinformatics support to members of both the Cancer Center, the Bloomberg~Kimmel Institute for Cancer Immunotherapy (BKI), and the Convergence Institute at Johns Hopkins including both standard informatics and innovative analysis pipeline development. To this work, I bring expertise in multi-omics data analysis methods through my role leading the DNA methylation analysis in several tumor types for The Cancer Genome Atlas (TCGA). In my role as bioinformatics manager of ECGC, I oversee day-to-day bioinformatics services and supports the bioinformatics needs of investigators in areas of data integration, annotation, high-throughput and spatial data analysis. In this capacity, I develop bioinformatics software tools to support many cancer research activities. I collaborate with a number of investigators across different research programs in the cancer center. I highlight the key collaborations in this application as illustrative of my research portfolio. For example, I played a key role in development of the comprehensive analysis of T-cell receptor sequencing data for the FEST (Functional Expansion of Specific T cells) assay. I also perform multi-omic analyses of changes in the tumor microenvironment due to immunotherapy and correlate those changes with clinical outcomes. With the support of this R50 award, I will extend my current pipeline development to state of the art single cell spatial technologies and data integration techniques and train future bioinformatics analysts to benefit various cancer-related studies throughout the cancer center.

NIH Research Projects · FY 2024 · 2024-09

The unfolded protein response (UPR) pathway plays an essential role in health and diseases from cancer to neurodegeneration. Of the three UPR pathway branches, the IRE1-XBP1 pathway is the most highly conserved in comparison with the PERK and ATF6 pathways. It has been shown that selective genetic activation of XBP1 in the IRE1 pathway is effective in multiple neurodegenerative disorders from Alzheimer’s disease (AD) to Parkinson’s disease (PD). Using an XBP1-driven luciferase reporter system, we screened a library of newly designed macrocycles called rapafucins that are modeled after the immunosuppressive and anticancer drug rapamycin and identified an activator of XBP1 named Rapireon. Further characterization of Rapireon revealed that it acts as a molecule glue by recruiting FKBP12 to form a ternary complex with the cytosolic domain of IRE1. Moreover, the FKBP12-Rapireon complex was found to selectively activate the nuclease activity of IRE1 without affecting its kinase activity. In this application, we propose to carry out in-depth characterization of the mode of action of Rapireon using both biochemical and structural biology approaches. In preliminary studies, we already obtained a low-resolution cryo-EM structural model of the FKBP12- Rapireon-IRE1 ternary complex. We will continue to collect more data and refine the the structure to better than 2.5 Å resolution. In parallel, we will build on our existing high- resolution (below 2 Å) FKBP12-Rapireon binary complex x-ray crystal structure and attempt to obtain the crystal structure of the ternary complex. To improve the potency and specificity of the existing Rapireon lead, we will design and synthesize a DNA- encoded library (DEL) of Rapireon analogs and develop a solution-phase proximity ligation/deep sequencing platform to identify new analogs of Rapireon from the DEL. Once a potent lead compound is identified, we will attempt to improve the pharmacokinetic property and bioavailability of Rapireon through structural optimization of Raprieon, giving rise to a Rapireon analog that can serve as a tool compound for exploring its potential in treating neurodegenerative diseases.

NIH Research Projects · FY 2025 · 2024-09

Abstract Despite decades of concerted efforts, the prevalence of obesity and its associated morbidities such as type 2 diabetes (T2D) and cardiovascular diseases (CVD) continue to climb in the US and racial and ethnic minority populations living in low-income households and communities are disproportionally affected. Part of the reason is a well-observed vicious cycle of intergenerational amplification. However, the underlying pathways driving this cycle remain poorly understood. This proposal aims to explore a novel hypothesis regarding the role of clinical and subclinical infection and resulting inflammation in the intergenerational cardiometabolic link. The proposed study is motivated by a strong scientific premise. First, growing evidence generated by us and others demonstrated that maternal cardiometabolic conditions contribute to child cardiometabolic risks. This intergenerational link may originate in utero and amplify the cardiometabolic risk in current and future generations, underscoring the importance of the early life period. Second, there is growing evidence that infection may lead to both a local and systemic inflammatory state. In the context of maternal- fetal dyad, maternal infection was found to be associated with increased levels of pro- and anti-inflammatory cytokine levels in cord blood, independent of vertical pathogen transmission. To date, little is known about metabolic-immune system crosstalk in early life and health implications. The overarching goal of this project is to investigate the association of the early life antibody profile to a broad array of pathogenic and commensal microbes and systemic immunoproteomic profiles in the intergenerational cardiometabolic link. We will also explore micronutrient status as a protective factor. Specifically, we aim to 1) identify early life immune response signatures of long-term cardiometabolic outcomes; 2) examine the role of early life immune responses in the intergenerational cardiometabolic link; and 3) explore the interplay of early life micronutrient status and immune responses on the intergenerational link of cardiometabolic outcomes. We will leverage the rich resources of the Boston Birth Cohort (BBC), with ~3,500 mother-child pairs who were enrolled at birth and followed prospectively. We have shown that the BBC is a high-risk population for adverse cardiometabolic outcomes. A particularly novel aspect of this study is that we will leverage existing antibody repertoire data generated by cutting-edge technology (PhIP-Seq) and immunoproteomic profiles generated by the high- throughput Olink platform at two critical developmental windows: at birth (reflecting the in-utero state) and at age 1-2 years (reflecting early life immune response). Successful completion of this study will help to deepen our understanding of the immunologic pathways underlying the intergenerational cardiometabolic link, reveal novel biomarkers and targets, and lead to a new paradigm for early prediction and prevention to halt or reverse the vicious intergenerational cycle of cardiometabolic disease.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Alcohol Use Disorder is a chronic condition that can result in devastating health, social, and financial outcomes. A key characteristic of problematic alcohol drinking is continued use despite negative consequences. In punished alcohol seeking models, subjects must decide between drinking paired with an aversive punishment or abstaining from further drinking. Preliminary evidence suggests that subjects resistant to punishment show similar baseline drinking behaviors as subjects that are sensitive to punishment. Thus, a potential behavioral impairment in aversion resistant subjects compared to their aversion sensitive counterparts could lie in how resistant subjects update the outcomes, or contingencies, of their actions. Recent evidence from pharmacological inactivation and ex-vivo slice studies points to the role of the orbitofrontal cortex (OFC) in mediating aversion resistance. Interestingly, the OFC has also been widely investigated for its role in updating outcome contingencies. However, how contingency updating processes may contribute to punished alcohol seeking behaviors has yet to be elucidated. In my first aim, I seek to evaluate the effects of punished alcohol seeking on OFC activity using microendoscopic calcium imaging. In my second aim, I will use time-locked optogenetics to assess the effects of OFC activation and inhibition during punished alcohol self-administration. In my third aim, I will evaluate how rats classified as aversion sensitive or aversion resistant perform on reversal learning tasks used to assess outcome updating. The central goal of this work is to investigate if dysregulation in OFC activity as well as impairments in contingency updating contribute to individual differences in punished alcohol seeking. The findings of the proposed research will significantly advance our understanding of the neurobiological and behavioral contributions in drinking despite negative consequences.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY Neuroscience research has historically relied on observing tightly controlled behaviors in siloed laboratory experiments, constraining our understanding of the neural bases of complex behaviors observed in naturalistic settings. With ongoing advances in unobtrusive sensing technology, artificial intelligence, and machine learning (AI/ML), and availability of computing power, the field of neuroscience has been afforded an opportunity to make large-scale discoveries hitherto unimaginable. For this to be realized, however, it is crucial to facilitate secondary analyses that cut across individual datasets, allowing for research that transcends individual project designs. Such a goal cannot be achieved without a data archive that provides a compelling technical solution for storing and curating datasets, and that provides close integration with analytical resources that require minimal technical expertise to be leveraged. Here, we propose the Ecosystem for Multi-modal Brain-behavior Experimentation and Research (EMBER), a data archive specifically tailored to serve the unique needs of the Brain Behavior Quantification and Synchronization (BBQS) research community, which will be at the forefront of advancing neurobehavioral knowledge in coming years. At the heart of EMBER is a scalable, hybrid data archive which will house and manage multimodal and multi-species data collected by diverse research groups. Crucially, our hybrid architecture will not only automatically execute the optimal storage scheme for different modalities of data, leveraging existing BRAIN Informatics resources, but also achieve dual objectives of ensuring the security of behavioral and environmental data — which may include Protected Health Information (PHI) and Personally Identifiable Information (PII) — as well as expediting querying and data access not only within BBQS datasets but also with other BRAIN resources. Different cadres of EMBER users, such as BBQS data generators, analysts, as well as the broader neuroscience community will be able to ingest, curate, and instigate discovery from data using a user-friendly portal that will streamline highly technical data harmonization and synchronization steps. In particular, development, testing, and deployment of analysis tools will be supported by cloud-based sandboxes that are seamlessly integrated with ML/AI resources developed by the BBQS Data Coordination and Artificial Intelligence Center (DCAIC). Integral to EMBER’s success will be acceptance in the community as the gold-standard engine for discovery, providing utility beyond being simply a passive, program-mandated data archive. Throughout its lifecycle, we will nurture bidirectional collaboration with the data generators, analysts, as well as the broader neuroscience research community to introduce and maintain tools for sharing, querying, and analyzing data. We anticipate that EMBER and associated data resources will maximize the BBQS program’s potential to reach its ambitious objectives of transforming our understanding of the link between brain and behavior.

NIH Research Projects · FY 2025 · 2024-09

Modified Project Summary/Abstract Section The OpenNotes rule in the United States enables all patients to have easy access to their medical records. The policy affords many benefits to patients such as increased accessibility, improved transparency, and better communication with medical providers. Additionally, OpenNotes may help address health disparities by increasing transparency in provider documentation and medical decision-making. However, there is ongoing discussion regarding the potential impacts of this policy on the quality of clinical documentation. Certain documentation styles may limit the detail or type of information recorded in notes, and patients may encounter challenges in understanding the terminology and format of clinical notes. While the nationwide rollout of OpenNotes may have implications for the quality of documentation and patient perceptions of care, most studies rely on self-reports through survey mechanisms or a limited number of clinical specialties. We will characterize the effects of OpenNotes on clinical documentation through an empirical computational analysis, comparing changes in clinical language before and after the policy implementation. In support of our analysis, we will develop clinical Natural Language Processing (cNLP) tools to analyze medical language and identify the most likely types of documentation changes. Our focus will be on mental health care due to the sensitive nature of these notes. We will use cNLP tools to identify changes and patterns in language use in EHR notes, comparing language before and after OpenNotes went into effect. We will also evaluate the effect of OpenNotes policies on language in patient records for various patient populations, and examine how policy changes may relate to changes in healthcare disparities. Our analysis will draw on clinical notes from patient care settings within the Johns Hopkins Medical System and two specialties: mental health, selected because of the potential high impact of OpenNotes, and primary care, a comparison setting for which we expect different types of changes.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Neuroscience research has historically relied on observing tightly controlled behaviors in siloed laboratory experiments, constraining our understanding of the neural bases of complex behaviors observed in naturalistic settings. With ongoing advances in unobtrusive sensing technology, artificial intelligence, and machine learning (AI/ML), and availability of computing power, the field of neuroscience has been afforded an opportunity to make large-scale discoveries hitherto unimaginable. For this to be realized, however, it is crucial to facilitate secondary analyses that cut across individual datasets, allowing for research that transcends individual project designs. Such a goal cannot be achieved without a data archive that provides a compelling technical solution for storing and curating datasets, and that provides close integration with analytical resources that require minimal technical expertise to be leveraged. Here, we propose the Ecosystem for Multi-modal Brain-behavior Experimentation and Research (EMBER), a data archive specifically tailored to serve the unique needs of the Brain Behavior Quantification and Synchronization (BBQS) research community, which will be at the forefront of advancing neurobehavioral knowledge in coming years. At the heart of EMBER is a scalable, hybrid data archive which will house and manage multimodal and multi-species data collected by diverse research groups. Crucially, our hybrid architecture will not only automatically execute the optimal storage scheme for different modalities of data, leveraging existing BRAIN Informatics resources, but also achieve dual objectives of ensuring the security of behavioral and environmental data — which may include Protected Health Information (PHI) and Personally Identifiable Information (PII) — as well as expediting querying and data access not only within BBQS datasets but also with other BRAIN resources. Different cadres of EMBER users, such as BBQS data generators, analysts, as well as the broader neuroscience community will be able to ingest, curate, and instigate discovery from data using a user-friendly portal that will streamline highly technical data harmonization and synchronization steps. In particular, development, testing, and deployment of analysis tools will be supported by cloud-based sandboxes that are seamlessly integrated with ML/AI resources developed by the BBQS Data Coordination and Artificial Intelligence Center (DCAIC). Integral to EMBER’s success will be acceptance in the community as the gold-standard engine for discovery, providing utility beyond being simply a passive, program-mandated data archive. Throughout its lifecycle, we will nurture bidirectional collaboration with the data generators, analysts, as well as the broader neuroscience research community to introduce and maintain tools for sharing, querying, and analyzing data. We anticipate that EMBER and associated data resources will maximize the BBQS program’s potential to reach its ambitious objectives of transforming our understanding of the link between brain and behavior.

NIH Research Projects · FY 2025 · 2024-09

Modified Project Summary/Abstract Section Suicide among Black preadolescents has increased rapidly over the last two decades, reaching unprecedented levels. While there have been substantive gains in knowledge related to the etiology of preadolescent suicide ideation and behaviors (SIB), most of this work has included predominantly White samples or have been cross-sectional or short-term longitudinal studies. Less is known about the course of SIB during preadolescence, and malleable individual-specific and social ecological precursors and correlates associated with this course, among low-income, urban Black youth. Such work is vital to informing developmentally and culturally relevant preventive interventions aimed at mitigating this major public health problem. The proposed R01 seeks to characterize the epidemiology and course of SIB among a socioeconomically disadvantaged, urban sample of Black preadolescents, and to identify factors that confer risk or protection for SIB over time in this understudied population. To do this, we will build on data collection that occurred as part of a cluster randomized preventive intervention trial (DA039869) conducted in 48 urban elementary schools with ~5,000 economically disadvantaged K-2 students of which 2,100 are Black and will be between the ages of 10-12 in the fall of 2024. The proposed 4-year longitudinal study seeks to accomplish the following aims: characterize the severity and course of SIB during pre- and early adolescence in a random stratified sub-sample of 1,000 Black youth drawn from the larger sample of 2,100. Urban, economically disadvantaged Black youth represent a disproportionately understudied population in preadolescent SIB research (Aim 1); identify risk and protective individual, proximal and distal environments as well as macro-level factors that may be associated with the emergence and progression of SIB (Aim 2); and determine whether the early elementary school-based universal preventive interventions targeting emotion regulation and social problem-solving result in reduced engagement in SIB across the preadolescent and early adolescent years (Aim 3). In addition, in Years 2 and 3 we will draw 2 random stratified sub-samples from the larger sub-sample of 1,000 to conduct 2 pilot studies encompassing observations of parent-child interactions (e.g., communication, conflict) and qualitative interviews aimed at better understanding Black youth’s experiences and coping with racial discrimination. The consideration of multi-level influences and our multi-modal approach to assessing these influences through the inclusion of quantitative and qualitative assessments will provide a better understanding of the risk and protective factors that have otherwise been unmeasured and/or missed in current research. The investigative team brings together expertise in the etiology, epidemiology, and prevention of SIB among Black preadolescence; child and developmental psychopathology; minority health and health disparities; and mixed methods; thus, we are extremely well-positioned to accomplish the study aims.

NSF Awards · FY 2024 · 2024-09

Strengthening American Infrastructure (SAI) is an NSF Program seeking to stimulate human-centered fundamental and potentially transformative research that strengthens America’s infrastructure. Effective infrastructure provides a strong foundation for socioeconomic vitality and broad quality of life improvement. Strong, reliable, and effective infrastructure spurs private-sector innovation, grows the economy, creates jobs, makes public-sector service provision more efficient, strengthens communities, promotes equal opportunity, protects the natural environment, enhances national security, and fuels American leadership. To achieve these goals requires expertise from across the science and engineering disciplines. SAI focuses on how knowledge of human reasoning and decision-making, governance, and social and cultural processes enables the building and maintenance of effective infrastructure that improves lives and society and builds on advances in technology and engineering. Cities and towns across the United States have witnessed rapid growth of electric bike (e-bike) usage in recent years. Along with this growth has been an increase in e-bike crashes, highlighting the urgent need to improve bicycle infrastructure. This SAI project seeks to improve bicycle infrastructure planning and design across U.S. communities to promote safer and more widespread e-bike use. Until now, transportation planners and engineers typically design bicycle infrastructure with a traditional, non-electric bike in mind. This is problematic because e-bikes are faster, heavier, and larger than traditional bicycles, creating new challenges for planning and designing bicycle infrastructure. This project strengthens American bike infrastructure to prepare for an e-bike future by studying how different types of bicycle facilities affect cyclists' and e-cyclists' perceptions of comfort and safety, as well as their riding behavior. The research helps transportation planners make better infrastructure investment decisions to increase bicycle use, enhance rider safety, and promote transportation equity. Cyclists' perceptions of the bicycle infrastructure they interact with play a major role in shaping their cycling behavior and infrastructure-related choices. However, little is known about whether and how the comfort and safety perceptions of e-bike users and traditional bike riders differ. Grounded in social and behavioral theories, this project advances knowledge of e-bike users' infrastructure needs and preferences by developing a social and cognitive psychological account of cyclists' and e-cyclists' comfort and safety perceptions across cycling environments. A multidisciplinary research team develops and tests a novel socioecological theory of planned behavior model by collecting and analyzing multi-sourced, complementary datasets such as survey, interview, bike trip trajectory, and surface street imagery data. The integration of these datasets, coupled with state-of-the-art generative AI technologies and modeling approaches, advances bicycle infrastructure research on both theoretical and methodological fronts. Numerous stakeholders, including transportation agencies, bikeshare operators, and bicyclist organizations are engaged throughout the project for co-design activities to maximize societal impacts. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract Innovation in chronic disease management is urgently needed to effectively control hypertension (HTN) in Ghana and Nigeria. Both countries are suffering silent epidemics of chronic diseases with rates closely resembling those of high-income countries. Uncontrolled HTN causes cardiovascular disease, stroke, chronic kidney disease, and premature death. However, HTN is poorly controlled in both countries due to patient-, provider, and system-level barriers. A pressing global health challenge is implementing evidence-based and contextually appropriate strategies to improve chronic disease management in Ghana and Nigeria. Multilevel interventions improve HTN control. For instance, team-based care, a health systems-level and organizational intervention, improves the quality of HTN care. Telehealth can be enhanced with home blood pressure monitoring (HBPM) to address patient-, and provider-level barriers. The COVID-19 pandemic has spurred efforts to increase access to timely and appropriate care through re-engineering primary care to be patient- centered and digitally enabled. Sphygmo Home, a remote telemonitoring app that links with validated blood pressure (BP) and glucose monitoring devices, is a promising solution to improve patients’ self-management of chronic disease. In a previous pilot study, we investigated the impact of a multilevel and digitally-enabled home- based intervention compared to enhanced usual care (UC). After 12 months, 80.5% in the intervention arm, compared to 24.2% in the enhanced UC arm, had controlled BP (p <0.001). Given the promising findings, we designed a larger scale trial, consisting of an innovative multilevel intervention linking HBPM with a telemonitoring platform (Sphygmo Home app), team-based care including physicians and nurses, and the use of simplified hypertension treatment protocol at hospitals, to improve HTN control. Using a hybrid type 2 effectiveness-implementation design among 800 adults with uncontrolled HTN clustered in 16 hospitals across 3 regions (Ashanti, Northern, and Bono) in Ghana and in Ondo state, Nigeria, we seek to 1) Assess the effect of the ADHINCRA Program in improving BP control at 12 months using a stepped wedge cluster randomized trial of adults with uncontrolled HTN (systolic BP ≥140 mm Hg) and 2) Use the Pragmatic Robust Implementation and Sustainability Model (PRISM) to evaluate the reach, adoption, and maintenance of the ADHINCRA Program at 12- and 24-months post-randomization and explore contextual factors that are associated with the adoption and maintenance of the program in each site using the Service Availability and Readiness Assessment (SARA) tool. Through early and continued stakeholder engagement with health system leaders, providers, and patients, we seek to close the wide “know-do-gap” and reduce global chronic disease disparities. We also propose a comprehensive dissemination strategy to reach critical audiences and achieve buy-in, policy, and practice change.

NIH Research Projects · FY 2024 · 2024-09

Abstract Oral HPV is the cause of increasing incidence of HPV-related oropharynx cancer (HPV-OPC) in the United States and globally, and is expected to continue into the next century despite an effective vaccine. The risk of HPV-OPC and HPV-related anogenital malignancies is significantly increased among people living with HIV (PLWH). Oral and plasma HPV and E6 antibodies are associated with increased future risk of HPV-OPC and present an opportunity for screening for HPV-OPC. We have developed the longest running and largest cohort of healthy people living with and without HIV, with biomarkers of HPV-OPC. This study will combine our existing unique enriched cohort of individuals with HPV16 biomarkers with new participants identified in a screening scenario to develop a larger cohort of individuals at-risk for HPV16-OPC (called the MOUTH2 study). We will screen for oral and blood biomarkers with the aim to 1) study progression to HPV-OPC and how it differs in those with and without HIV; 2) characterize impact of HIV on oral HPV16 persistence, and 3) evaluate performance characteristics of stand-alone vs sequential biomarker screening. This prospective observational cohort will provide the ability to examine questions necessary to understand the long- term natural history of oral HPV in people living with and without HPV and to inform future study design to elucidate the benefits and harms of screening.

NIH Research Projects · FY 2025 · 2024-09

SUMMARY Project Title: Long-term Effects of a household Air Pollution intervention: Follow-up of a randomized controlled trial Globally, nearly 3 billion people are exposed to household air pollution (HAP) from the use of solid fuels (biomass or coal) for cooking and heating. In 2019, HAP accounted for an estimated 2.3 million premature deaths and 3.6% of global disability-adjusted life years lost. As a strategy to mitigate HAP and improve health outcomes, we recently completed an 18-month intervention of liquefied petroleum gas (LPG) stoves and fuel (HAPIN trial; UM1HL134590, MPIs: Checkley, Clasen, Peel), however current evidence suggests that the health benefits of HAP reduction may not become apparent until several years later. Leveraging the participant cohort and comprehensive data collected in the HAPIN trial, we seek to determine the long- term effects of an 18-month LPG stove, continuous fuel and behavioral messaging intervention on health outcomes among children in Puno, Peru (n=709). We will measure clinical outcomes, kitchen concentrations and personal exposures to PM2.5 once yearly and monitor biomass cooking stoves continuously using temperature loggers throughout the study period. We will examine whether health outcomes of intervention participants (lung function, cardiovascular risk profile, and neurodevelopmental outcomes) differ to those from control households through age eight and conduct exposure-response analyses based on the PM2.5 exposure and stove use data during the intervention and subsequent follow-up period. Additionally, we will evaluate if intervention households continue to use LPG for a higher percentage of cooking time than controls and to experience lower PM2.5 exposures. This study will provide valuable insight on the longer-term effects of HAP mitigation during a critical period of child development and generate evidence which can inform government policies for clean fuel intervention programs. Moreover, it will contribute unique data on pediatric lung function measures and childhood cardiovascular disease risk, which is currently limited in low- and middle-income countries.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY The opioid epidemic in the United States is a public health crisis stemming from prescription opioid use, accessibility to potent synthetic opioids, and alarmingly frequent unintentional fatal overdoses. Chronic pain significantly contributes to this crisis, affecting over 100 million citizens in the United States, surpassing the incidences of diabetes, heart disease, and cancer. Moreover, prolonged use of prescription opioids for pain management markedly escalates the likelihood of heroin initiation and the development of opioid use disorder (OUD), with approximately 10% of patients with chronic pain eventually developing OUD. It is imperative to address these risks by investigating factors contributing to the reduction of prescription opioid use, potentially leading to a decline in adverse health outcomes, instances of OUD, and unintentional fatal overdose cases. Non-opioid treatments, including cannabis and cannabinoid-derived products, are increasingly considered for chronic pain management, with over 24 million United States citizens using cannabis for its analgesic properties. Although clinical trials indicate a significant analgesic effect of cannabinoids compared to placebo, there remains a scarcity of research on effectiveness and potential negative consequences. Moreover, the expanding legalization of medical and recreational cannabis in the United States presents novel opportunities to explore the relationship between opioids and cannabis use in patients with chronic pain. However, notable constraints limit early evidence from studies on opioid and cannabis use in patients with chronic pain, including recall bias, which affects cross-sectional data analyses. Consequently, the existing literature inadequately addresses the factors related to chronic pain that influence opioid and cannabis use in these patients. Intensive longitudinal studies with ecological momentary assessment may address these limitations and offer valuable insights into the mechanisms facilitating opioid and cannabis use for chronic pain. In the current proposal, I have designed a mixed-methods study to expedite the development of interventions targeting the negative consequences of opioid and cannabis use among patients with chronic pain. This project entails advanced secondary quantitative analyses of real-time smartphone-based ecological momentary assessment data from my primary sponsor’s NIDA R21 (R21 DA048175; PI: Thrul). Then, I will conduct an original semi-structured interview-based qualitative study using purposive maximum variation sampling of local expert substance use clinicians working with patients with chronic pain who use cannabis and opioids for their analgesic properties. This project establishes a foundation for intervention development for patients with chronic pain at risk of consequences from cannabis or opioid use; it also aligns with NIDA's primary objective of determining the impact of substance use and addiction on individuals, families, peers, and society, addressing a shared goal and pivotal priority funding topic – the ongoing opioid epidemic.