Univ Of North Carolina Chapel Hill

NIH Research Projects · FY 2026 · 2026-02

Six adeno-associated virus (AAV) vector based biodrugs have been approved by the FDA to treat genetic disorders. The great therapeutic success of AAV gene transfer has been tempered by the often-associated liver toxicity and, with liver-directed therapies, the concomitant fall in the transgene expression. There are marked interpatient differences in susceptibility to AAV liver toxicity and transgene expression, and we have demonstrated similar inter-donor variability in cultured human hepatocytes and in various strains of mice, strongly implicating the role of genetic background. We are proposing to study AAV liver interactions in Collaborative Cross (CC) mice, a relatively new genetic reference population engineered to maximize genetic diversity. We have successfully used CC mice to identify candidate genes which may underlie susceptibility to liver toxicity from several drugs. We have also observed marked differences between CC lines in the extent and kinetics of transgene expression after AAV liver targeting as well as liver toxicity, and this susceptibility was reproduced in hepatocyte spheroids. Our central hypothesis is that CC inter-strain susceptibility to AAV hepatotoxicity and transgene expression will be mirrored in cultured hepatocyte spheroids prepared from the strains and that combining in vivo and hepatocyte spheroid data will provide new insights that will improve the safety and efficacy of AAV gene therapy. To this end, we will pursue 3 specific aims: Aim 1. Elucidate the role of genetic factors underlying susceptibility of AAV liver toxicity and variation in transduction efficiency. After systemic administration of AAV vectors to the fully inbred CC populations (63 lines), we will identify the associations between host genetic background and protein/metabolite biomarkers and susceptibility to liver toxicity and to the long-term, stable transgene expression. Aim 2. Identify non-genetic factors influencing susceptibility to AAV liver toxicity and transduction efficiency. The effect of different parameters (AAV serotypes/variants, dose, transgene, dsAAV vs ssAAV, steroids, empty AAV virions) on AAV liver toxicity and transduction efficiency will be studied in CC strains identified in Specific Aim 1 as susceptible to liver toxicity and/or reduced transgene expression. Aim 3. Explore a novel model culture system to study AAV liver toxicity and transduction. We have demonstrated that primary hepatocytes cultured as spheroids in 386 well plates maintain a mature hepatocyte phenotype and are transduced by AAV. We propose to expand these studies to determine correlations with results from our live CC studies, and to further pursue the underlying mechanisms. Our proposed studies should provide mechanistic insight that may result in the design of safer AAV vectors, as well as identify promising biomarkers to guide safer dosing of existing AAV vectors. Moreover, our studies may support future susceptibility testing of iPSC-derived hepatocytes obtained from patients who are candidates for AAV gene therapy.

NIH Research Projects · FY 2026 · 2026-02

PROJECT SUMMARY Enteroendocrine cells (EECs) are rare sensory cells scattered throughout the gastrointestinal epithelium that interface between environmental stimuli like nutrients and microbes and the body's response, secreting over 20 distinct hormones that act locally and systemically. Our lab uses EEC-deficient mice and human intestinal organoids to uncover the intestinal functions regulated by EECs and uses these models as a blank slate to test the roles of individual EEC-derived products on intestinal physiology. EECs are often dysregulated in metabolic and gastrointestinal diseases, such as inflammatory bowel disease (IBD), although their roles in disease pathogenesis remain unknown. Many of these diseases are associated with impaired function of the intestinal epithelial barrier, allowing undigested food, microbes, metabolites, and toxins to cross the epithelium, triggering local and systemic inflammation. Tight junctions are essential for barrier integrity and are composed of several proteins which are supported by sphingolipids called ceramides, best characterized in the skin. In the intestine, barrier proteins are often reduced in IBD, along with several species of ceramides. Similarly, loss of ceramides within the intestinal epithelium exacerbates chemically-induced colitis and supplementation of ceramides improves colitis in mouse models. We discovered that several species of ceramides are reduced or absent in EEC-deficient mouse small intestine. Moreover, EEC-deficient human intestinal organoids display increased barrier permeability and upregulate an inflammatory gene signature. In preliminary experiments, we found that EEC-deficient mice also display impaired barrier function with increased permeability and markers of inflammation. When challenged with oral ingestion of dextran sulfate sodium (DSS), which classically induces colitis, EEC-deficient mice displayed significantly greater weight loss compared to controls. These data led us to hypothesize that EECs promote a strong barrier by regulating ceramide abundance and may be effective therapeutics for inflammation-mediated barrier dysfunction. Our first aim is to determine the role of EECs in the structure-function relationship between tight junctions and ceramides using in vitro human intestinal organoid cultures. Our second aim is to define the role of EECs in DSS-induced disease progression and recovery, and to test the role of the EEC hormone PYY in protecting the gut against DSS-induced damage. Our third aim is to perform targeted analysis of sphingolipid metabolic pathways of human intestinal organoids and murine intestine to define the mechanism by which EECs participate in ceramide biosynthesis in homeostasis and in disease. We expect that restoration of exogenous PYY to EEC-deficient models will improve barrier function and mitigate the severity of DSS-induced disease by increasing the abundance of ceramides within the epithelium. These experiments will define a new role for EECs in maintaining gastrointestinal homeostasis, uncover a novel mechanism regulating barrier integrity in health and disease, and provide a basis for future therapies aimed at repairing a leaky gut.

NIH Research Projects · FY 2026 · 2026-02

ABSTRACT Relapsing malaria species, such as Plasmodium vivax (Pv), remain major challenges to malaria elimination due to their propensity to form hypnozoites that cause chronic latent infection in the liver and give rise to frequent relapses. Pv relapses cause significant morbidity and mortality worldwide. Despite advances, genotyping to distinguish relapses from re-infections remains fraught, limiting the evaluation of anti-relapse interventions like primaquine and tafenoquine. This study applies novel genomic and bioinformatic tools to clinical trial data in Southeast Asia and introduces innovative approaches to parse Pv relapse outcomes. Our approach leverages molecular inversion probes (MIPs) to deeply sequence Pv infections, capturing the diversity across the vivax genome and complexity within infected individuals. We will use Tapestry, a new bioinformatics tool, to enable haplotype reconstruction and identity-by-descent (IBD) analysis within and across multiclonal infections. Finally, Bayesian statistical models will refine relapse predictions by integrating genetic complexity, IBD relatedness, and clinical factors. Aim 1 investigates primaquine failures observed in a Thai Pv relapse trial (NCT04228315). Suspected relapses occurred in four individuals despite chloroquine and primaquine treatment; host CYP2D6 polymorphisms were ruled out. We hypothesize that high initial hypnozoite burden drove these relapses. We will generate evidence for this via genomic analyses that enhance detection of circulating parasite variants and assess infection complexity as a proxy for liver-stage hypnozoite burden. Aim 2 evaluates malaria elimination interventions in a Cambodian military cohort. Aim 2A tests whether rebound infections after cessation of monthly prophylaxis (MMP with dihydroartemisinin - piperaquine and weekly primaquine) represent relapses due to high hypnozoite burden, as reflected by genetic complexity. Aim 2B classifies Pv recurrences in soldiers wearing permethrin-treated uniforms to estimate vector-prevention efficacy. Results will differentiate relapse from reinfection and recalibrate protective efficacy estimates. In summary, this proposal seeks to address a fundamental gap in our ability to use genotyping to evaluate anti-relapse and other interventions that are needed to decrease the global burden of Plasmodium vivax. Expected outcomes include refined relapse classification, improved understanding of hypnozoite dynamics, and insights into anti-vivax interventions across diverse settings. Future directions include scaling our approach to larger cohort studies across diverse settings to improve classification of relapse outcomes.

NIH Research Projects · FY 2026 · 2026-02

Herpes simplex virus (HSV) is highly contagious and can be transmitted via physical contact. HSV can be diagnosed by detecting the presence of the virus in lesions or the antibodies in the blood. Yet, viral shedding can happen from asymptomatic infections, highlighting the need for early and accurate detection of HSV to prevent transmission. The most common ways to detect HSV are nucleic acid testing of an active infection via qPCR or serological testing of antibody levels in patient serum. However, qPCR is only accurate if a person is symptomatic and in asymptomatic people both the FDA and the CDC recommend against serological testing due to issues with sensitivity. Additionally, current testing for CNS complications arising from HSV infections requires highly invasive cerebral spinal fluid (CSF) sampling to diagnose. Thus, rapid, accessible, sensitive, and accurate point- of-care tests are in dire need. In 2021, we published a watershed paper describing how we can leverage cell surface glycans that the SARS- CoV-2 virus uses to bind and infect cells, to capture it onto rapid test strips for sensitive detection of the virus (Kim et al, ACS Central Science). Inspired and motivated by our success with SARS-CoV-2 sensing, we propose a novel lateral flow strip assay (LFSA) device for rapid and reliable point-of-care antigen-based detection capable of differentiating between HSV-1 and HSV-2 infections and sensing of CNS complications through serum. As cell surface proteoglycans such as heparan sulfate play an important role in the binding and cell entry of HSV, we will leverage it as a universal binder and use type specific cell receptors to distinguish between HSV strains (Specific Aim 1). Higher selectivity will be achieved by exploring sensitivity to sulfonation of heparan sulfate and other glycocalyx proteins. Sensor performance will be evaluated in complex fluids such as human genital fluids or saliva, and in genital washings of HSV-infected mice. To enhance our ability to identify and subtype HSV, we will engineer tailored cell membranes to optimize their interactions with viral envelope proteins, and strip and print these cell-derived membranes on paper test strips in Specific Aim 2. In Specific Aim 3, we will develop a blood test for the rapid quantitative screening of glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL), upregulated biomarkers upon CNS damage. We will incorporate electrochemical signals for quantitative assessment. This Bluetooth device will enable early and fast triage of patients for further screening. Together, these devices will enable us rapid and cost-effective screening of high-risk populations, accurate subtyping, and a swift connection of patients with treatment.

NIH Research Projects · FY 2026 · 2026-02

ABSTRACT Like all viruses, Human Cytomegalovirus (HCMV) does not encode a ribosome, instead requiring host ribosomes and translation machinery to translate viral mRNAs. While many viruses inhibit host translation to blunt host antiviral responses and ensure viral mRNAs access to ribosomes, HCMV is somewhat unique in that infection actually increases overall levels of protein synthesis in infected cells. The general increase in protein synthesis has been interpreted as a global increase in the translation of all mRNAs, both viral and cellular, as infection activates key cellular translation factors and complexes. However recent studies have challenged this dogma by revealing a more complex relationship between infection and mRNA translation. Our preliminary data show that rather than causing a non-specific increase in translation efficiency, infection leads to surprisingly diverse outcomes for different mRNAs; the translation efficiency of some cellular mRNAs is increased, while others are unaffected or show temporal changes in translation efficiency during different stages of infection, suggesting different factors regulate distinct groups of RNAs during different stages of infection. Consistent with this idea, while infection activates key translation initiation complexes like the eIF4F complex, which bridges the interaction between mRNAs and ribosomes, eIF4F is only required for the translation of cellular mRNAs encoding host factors that HCMV needs to replicate, with multiple studies showing that eIF4F activity and integrity are largely dispensable for the translation of HCMV mRNAs. We hypothesize that infection activates alternative host, and potentially viral, factors to temporally regulate the translation of viral mRNAs. Using a variety of proteomics approaches we identified changes in the composition of the translation machinery caused by infection and found novel roles for several alternative host and viral proteins in HCMV mRNA translation and replication. These include the cellular DHX29 RNA helicase and the YBX1 RNA binding protein, which both regulate the translation of specific subsets of cellular RNAs under different conditions. In this proposal we determine the molecular mechanisms these factors use to regulate viral protein synthesis by defining how they recognize viral and cellular RNAs, recruit translation initiation complexes, and ultimately control mRNA translation. In the process we uncover new aspects of cell biology and the host:pathogen interface critical for remodeling cell signaling and survival in infection and other disease states.

NIH Research Projects · FY 2026 · 2026-02

PROJECT ABSTRACT Importance: Healthcare settings are struggling to provide enough nurses to meet patients’ needs. About 40% of nurses reported high rates of burnout and leaving their positions prematurely. Burnout is driven by high job demands and limited organizational resources. Virtual nursing (VN), an organizational strategy borne of necessity to deliver patient care during the pandemic, was also viewed as an approach to potentially mitigate nurse burnout. To date, 43% of US hospitals have already implemented some form of VN, where remote nurses engage in team-based care using telehealth. Hypothetically, VN is expected to reduce the job demands for bedside nurses. However, little is known about the relationship between the use of VN and nurse job demands and resources. To address this knowledge gap, we will use a multi-site, natural experiment across nine diverse hospitals. Objective: Generate real-world, data-driven evidence on the job demands and resources, drivers of burnout, for bedside nurses who do and do not use VN. Specific aims: (1) Determine the association between the use of virtual nursing and workplace job demands among bedside nurses using EHR and survey data. (2) Determine the association between the use of virtual nursing and individual job demands among bedside nurses using eye-tracking technology and wearable devices. (3) Determine the job resources required to support VN and identify organizational solutions to mitigate nurse burnout using Design Thinking workshops. Methods: Guided by the Job Demands-Resources (JD-R) framework and using a mixed-methods sequential design, we will examine the relationship between VN use and the job demands and resources that drive nurse burnout. First, we will use novel quantitative data (EHR and physiologic) to gain data-driven, real-world insights on job demands (e.g., time pressure, mental demand). Second, we will apply design thinking to understand the job resources needed to support VN and design organizational solutions that address systemic aspects of burnout. Expected outcomes: On successful completion of our research, we expect contributions to include to (1) understand the association between using VN and workplace job demands, (2) understand the association of using VN and nurse job demands for bedside nurses using physiologic data, and (3) determine the required organizational resources to better support bedside nurses using virtual nursing.

NIH Research Projects · FY 2025 · 2026-01

Project Summary The function and regulation of both coding and non-coding RNAs depend on their structures. A subset of RNAs contain pockets capable of binding ligands, and targeting RNA with small molecules can potentially modulate gene expression and cell state. To date, identifying and progressing these ligands within cells has posed a formidable challenge. I have developed a technology for transcript-specific detection of ligand binding in cells that is scalable for high throughput screens. This method simplifies the complex RNA ligand measurement into a manageable and efficient PCR-based strategy, which I used to discover a first-site fragment ligand that binds the 5’-UTR of MYC, a conventionally difficult-to-ligand target. In Aim 1, I propose to use my in-cell screening platform to discover molecules that exhibit enhanced binding to MYC mRNA when bound by the first-site ligand. Potential hits will be chemically linked to create ligands with substantially higher affinity than either ligand alone. My current first-site binder reduces c-MYC protein levels without affecting mRNA levels, suggesting translational regulation. In Aim 2, I will use functional studies to address a critical gap in our understanding of how small- molecule ligands can target RNA, to produce meaningful biological effects, focusing on how RNA structure affects ribosome recruitment to the mRNA. This project is designed to provide a comprehensive understanding of ligand-RNA interactions in cells, informing the development of RNA-targeted tool compounds and, ultimately, therapeutics. The overarching vision of this research and training program integrates RNA screening technologies, bioinformatics and cheminformatics, mechanistic studies, and mentoring opportunities. Through this program, I will gain a strong foundation for a career as an independent researcher and leader in RNA chemical biology and therapeutics.

NIH Research Projects · FY 2025 · 2025-12

ABSTRACT Temporomandibular Disorders (TMDs) represent a significant burden on musculoskeletal health, accounting for an estimated $4 billion in healthcare costs annually. Pediatric Temporomandibular Degenerative Joint Disease (TM DJD) is especially concerning, with risks including growth abnormalities, severe joint damage, and potential blindness. Addressing the critical gaps in our understanding of pediatric TM DJD's progression, severity, and management is imperative. Our research proposes innovative, evidence-based strategies to improve early diagnosis and personalized care, utilizing cutting- edge multimodal imaging, artificial intelligence (AI), and machine learning. Our strategy unfolds across two synergistic aims, each poised to significantly advance TMJ DJD diagnosis, prognosis, and patient-specific treatment. Aim 1 employs advanced analytics, combining multimodal Cone-Beam CT (CBCT) and Magnetic Resonance Imaging (MRI) registration, with articular disc quantitative markers. This aim introduces a novel application of symptom phenotyping via mobile app tracking and biological marker assessments, integrating AI algorithms to predict early disc and condylar changes in children—a critical step toward preemptive treatment strategies. Expanding on Aim 1's foundation, Aim 2 leverages longitudinal datasets of pediatric and adult TM DJD patients to develop a groundbreaking diagnostic and prognostic toolkit. This includes pioneering privileged information learning techniques to merge advanced quantitative CBCT and MRI imaging features with clinical data, filling crucial gaps in real-world data sources. A key innovation is the application of EMERSE, the Electronic Medical Record Search Engine, for comprehensive clinical notes data abstraction, compared to large language models’ accuracy and reliability for information retrieval. Our comprehensive approach evaluates the performance of feature selection, machine learning, and statistical models, refining our preliminary Ensemble via Hierarchical Predictions through Nested model. We commit to rigorously testing our models' usability, feasibility, and acceptability in clinical environments through a tri-phase assessment strategy, focusing on practical implementation, expert clinician calibration, and integration into community dentistry for broader application. Aligned with the NIH Heal Initiative, the NIDCR Temporomandibular Disorder Collaborative for IMproving PAtient-Centered Translational Research, our proposed work also fulfills objectives within the NIH Strategic Plan for Data Science. Our interdisciplinary team combines clinical experts at the University of Michigan and the University of the Pacific with the computational expertise of partners in bioinformatics, natural language processing, statistical modeling, machine learning, and software engineering from the Michigan Department of Learning Health Systems, the University of North Carolina, and Isomics Inc. Leveraging a decade of collective experience and an established, robust infrastructure for quantifying multimodal data, our research network is uniquely positioned to ensure the sustainability, accessibility, and utility of our research outcomes for the TMD research and clinical communities. This collaboration is set to enhance clinical decision- making and identify targeted treatment decisions for specific risk groups in pediatric TM DJD care.

NIH Research Projects · FY 2026 · 2025-12

The University of North Carolina (UNC) Global HIV Prevention and Treatment Clinical Trials Unit (CTU) has a well-established record of high quality, innovative clinical research, strong network and scientific leadership. The CTU engages with critically important populations infected with and at high risk of HIV in southeastern US, southern Africa and southeast Asia. Our CTU is led by three experienced principal investigators (Joseph Eron MD, Mina Hosseinipour MD and David Wohl MD) and will support all four NIH Clinical Trials Networks (CTN); Adult Therapeutic Strategies, HIV Prevention, Vaccine Prevention and Pediatric, Adolescent and Maternal Therapeutic Strategies. Our four experienced Clinical Research Sites (CRS) include Chapel Hill CRS (Adult Strategies, Prevention and Vaccine CTN) led by Dr. Wohl, Greensboro CRS (Adult Strategies, Prevention and Vaccine CTN) led by Cornelius Van Dam MD, Malawi CRS (all four CTN) led by Lameck Chinula MD and Vietnam CRS (Adult Strategies, Prevention and Vaccine CTN) led by Vivian Go PhD. Participants with HIV include those newly diagnosed (including with acute infection), PWH stably suppressed on therapy, PWH with adherence challenges to care or medication, and PWH with drugresistant HIV. We will enroll PWH at risk for comorbidities and PWH or without HIV including those with co-epidemic pathogens such as tuberculosis (TB) and Hepatitis B virus (HBV) which affect USA populations but the higher disease prevalence in Malawi and Vietnam allows research efficiency. We have skilled, experienced clinical and translational investigators working hand-in-hand with junior investigators in US and international settings, who will engage and execute the network scientific agenda. A globally representative set of senior scientists and public health leaders on our Scientific and Strategic Advisory Group advise the CTU leadership team. The CTU administration has a highly organized structure that is responsive to our research teams and CRSs. Each CRS engages the communities representing the affected populations in an interactive, openminded way. State-of-art communication and experienced, outstanding and well-organized laboratory, pharmacy, regulatory, quality and data management support the CTU, CRSs. Using this robust framework the UNC Global CTU is positioned optimally to continue our scientific, and network leadership and clinical trials support to all four NIH HIV networks, contributing to the elimination of HIV and significant co-infections in the USA and globally.

NIH Research Projects · FY 2026 · 2025-12

Project Summary The AIDS Clinical Trials Group (ACTG) has been at the forefront of clinical research to advance HIV therapeutics and improve the health of people living with HIV/AIDS for 30 years. Rigorous scientific research conducted by the ACTG has laid the cornerstones for current HIV treatment guidelines. In this application for the competitive renewal of the ACTG we propose a transformative research agenda that draws on an international consortium of leading clinical and laboratory HIV investigators in collaboration with a world-class Statistics and Data Management Center to design and conduct innovative interventional clinical trials that will significantly reduce the global burden of disease due to HIV, TB and hepatitis B. The Leadership and Operations Center (LOC) provides scientific leadership and fiscal and organizational management of the ACTG. The ACTG Executive Committee (AEC) will serve as the overarching governing body of the network. The AEC is guided by an Executive Management Committee that includes the Network Chairs, Chief Quality Officer and the Chairs of the Laboratory and Statistical and Data Management Centers. Transformative Science Groups will oversee the development and execution of the ACTG research agenda, which will be coordinated and prioritized by the Scientific Agenda Steering Committee (SASC). Protocol development, implementation, training and network evaluation will be facilitated by the Network Clinical Core at Social & Scientific Systems, Inc. The LOC financial management group (Admin Core) at the University of California, Los Angeles will oversee resource management and protocol fund distribution at the direction of the AEC. The LOC will assure the engagement of Community in all aspects of the ACTG, and will coordinate communication between all three components of the network. Specific aims of this proposal include: 1) Identify interventions to reduce HIV reservoirs and control HIV replication in the absence of ART; 2) Test novel and durable interventions targeting HIV infection; 3) Improve the treatment and prevention of drug sensitive and drug resistant tuberculosis; 4) Prevent or improve the treatment of HIV-related non-infectious co-morbidities and evaluate strategies to cure hepatitis B virus infection in people with and without HIV.

NIH Research Projects · FY 2025 · 2025-09

Abstract Problematic alcohol use (PAU), a complex phenotype that combines alcohol use disorder (AUD) and alcohol- related problems identified by a survey (AUDIT-P), is a major public health issue that arises from intricate interactions between genetic and environmental mechanisms. Genome-wide association studies (GWAS) have identified genomic regions associated with PAU, but it is difficult to determine which genomic variants functionally contribute to the development of PAU, largely because many of these variants are located in the noncoding genome. Recent advances in high-throughput sequencing technologies now permit the functional characterization of thousands of noncoding, disease-associated variants simultaneously with massively parallel reporter assays (MPRA). However, MPRA studies have traditionally been conducted in vitro which limits our ability to identify tissue- and sex-specific variant effects. Because the regulatory genome is sensitive to factors like cell state, tissue type, and environmental perturbation, it is crucial to study the regulatory function of noncoding variants within the intact physiological context. The goal of this project is to identify which PAU risk variants alter transcriptional regulatory capacity in the intact brain and liver under natural physiological conditions and to determine whether this modulation will differ in response to ethanol exposure. To determine the regulatory activity of variants in a tissue- and sex-specific manner, I will perform in vivo MPRA via intracerebroventricular and systemic tail vein injections (Aim 1). I will then perturb the animals with acute or chronic ethanol administration via intraperitoneal injection which may induce variant regulatory activity that is not present in the homeostatic state (Aim 2). The results of this work will pinpoint the putatively causal PAU-associated variants in a tissue- and sex-specific manner as well as which variants exhibit functional regulatory activity only in the environmentally perturbed state. Successful completion of this project will positively contribute to the neurogenetics field by determining which variants should be pursued for further study within their natural genomic context, thus elucidating the underlying molecular mechanisms of genetic predisposition for PAU.

NIH Research Projects · FY 2025 · 2025-09

ABSTRACT Neuroplasticity is a key feature of cortical systems allowing for flexible shaping of pyramidal cell activity necessary for learning, adaptation, and recovery from injury. A shared feature of neuroplasticity across cortical and subcortical regions is the involvement of inhibitory interneurons in refining pyramidal cell activity. In the motor cortex, pyramidal cells tile their activity to skilled behaviors, likely being shaped by local inhibitory interneurons. However, how pyramidal cell sequencing emerges in the motor cortex to produce and adapt skilled behaviors remains unknown. Delineating the mechanisms and circuitry involved in shaping pyramidal cell sequencing is crucial to understanding the fundamental rules of motor plasticity, and to inform future therapeutic interventions to enhance neuroplasticity. While previous studies have investigated the role of interneuron subtypes in motor plasticity; the predominant interneuron in layer 1 of cortex, neuron-derived neurotrophic factor (NDNF) neurons, has yet to be researched. NDNF neurons have been characterized across cortical regions including auditory, visual, somatosensory, and prefrontal cortex. While their functional role across these cortical regions continues to be explored, there is evidence these neurons regulate pyramidal cell inputs, attenuating top-down inputs and gain-controlling bottom-up inputs. Skilled behavior learning and execution involves the dynamic combination of top-down inputs originating from the basal ganglia and bottom-up inputs deriving from the cerebellum to shape pyramidal cell activity. Our overall hypothesis in this proposal is that motor learning and execution rely on NDNF neurons to refine pyramidal cell activity through regulation of top-down and bottom-up inputs. To test this, I will first determine the anatomical localization of NDNF neuron somata, dendrites, and axons. Then, I will establish the dynamics of NDNF neurons in M1 during motor execution and learning using two-photon calcium imaging. Lastly, I will casually test the role of NDNF neurons on shaping pyramidal cell activity by optogenetically activating and suppressing NDNF neurons while performing large-scale neural recording of pyramidal cells. In all, this work will establish the role of motor cortex NDNF neurons in neuroplasticity.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT People involved in the criminal legal system (CLS) face a disproportionately high burden of substance and opioid use disorders (SUD/OUD), which upon release from jail or prison is compounded by lack of access to care and results in extremely elevated post-release drug overdose mortality. Few interventions have been able to reduce overdose risk among CLS-involved people. A number of ongoing studies are testing strategies for linking CLS-involved people to medications for OUD (MOUD) in the community. However, lack of insurance for many CLS-involved people makes these care linkages unsustainable after study completion. Medicaid expansion provides an avenue to address healthcare needs for many CLS-involved people. Recent studies show that pre-release Medicaid enrollment increases post-release MOUD and reduces overdoses for CLS-involved people. However, benefits appear to accrue to white individuals and not to black individuals – a concerning inequity because overdose deaths are rapidly increasing among racially minoritized people in the US. Research to date, which has been ecological, has not been able to identify the mechanisms by which Medicaid enrollment may improve MOUD and overdose outcomes and why these benefits may differ across racialized groups. Large, longitudinal, individual level data can map the pathways through which Medicaid expansion benefits some groups but not others. While overdose prevention work among CLS-involved people deservedly focuses on MOUD access, the role of mental health treatment is also critical. Two-thirds of people with OUD have co-occurring mental health needs, a burden that is likely even higher among CLS-involved individuals. Hence, MOUD without mental health care may fall short in MOUD engagement and overdose prevention for CLS-involved individuals. In this application, we propose to conduct a quasi-experimental study, by leveraging the 2023 Medicaid expansion in North Carolina (NC), to examine racialized inequities in enrollment in Medicaid among CLS- involved individuals, as well as post-release MOUD and mental health care access. We will further examine the impact of enrollment in Medicaid and MOUD and mental health care access on fatal and non-fatal drug and opioid overdoses. We will use 13 years of Big Data (2013-2025) on all formerly incarcerated people in NC linked with Medicaid and death records, which our team already has access to through two ongoing studies focused on suicide and polydrug overdose prevention. Our study is aligned with RFA-CE-25-149’s Funding Option A. This study will be the first to examine the individual-level impact of Medicaid enrollment, MOUD access, and mental health services on drug and opioid overdoses among CLS-involved people. This study will further identify mechanistic factors that contribute to racialized inequities among CLS-involved people to help enhance and sustain linkage to care for all CLS-involved people, but especially racially minoritized individuals, thereby enhancing the impact of Medicaid expansion for all people.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT Cancer remains a leading cause of morbidity and mortality in the United States, with an estimated 2 million new cases and over 620,000 deaths projected in 2025. While significant progress has been made in prevention, early detection, and treatment, widespread implementation of evidence-based interventions (EBIs) remains a challenge. The Centers for Disease Control and Prevention’s (CDC) National Comprehensive Cancer Control Program (NCCCP) supports 66 sites nationwide in developing and implementing comprehensive cancer control plans. To enhance the reach and impact of effective EBIs, NCCCP sites require increased capacity to scale and sustain these initiatives. Building on findings from the 2023–2024 Scaling What Works (SWW) Pilot, we propose the SWW-IMPACTS (Improving and Accelerating Cancer Prevention, Treatment, and Survivorship) initiative, a tailored capacity-building program designed to strengthen NCCCP sites’ ability to implement and sustain four CDC-identified pilot projects. Using the Leeman et al. Framework for Capacity Building, we will apply multi-modal capacity-building strategies—including training, tools, technical assistance, assessment, and feedback—delivered through a community of practice, virtual learning sessions, and an in-person symposium. Our overarching goal is to strengthen NCCCP sites’ capacity to implement, adapt, and sustain effective cancer prevention and control EBIs while identifying the most effective strategies for building capacity at scale. Our specific aims are to: 1. Assess NCCCP sites’ capacity-building needs to refine SWW-IMPACTS protocols and align strategies with site staff’s preferences; 2. Develop a community of practice that fosters EBI selection, adaptation, implementation, evaluation, and sustainment through structured training and technical assistance; and 3. Evaluate the effectiveness of capacity-building strategies to determine how different formats and mechanisms influence practitioner capacity and EBI planning behaviors. By systematically examining changes in practitioner capacity and EBI planning behaviors, SWW-IMPACTS will generate insights to inform future capacity-building efforts. The long-term impact of this work will be a stronger, more sustainable infrastructure for implementing and scaling EBIs, ensuring that NCCCP sites can continually improve cancer prevention, treatment, and survivorship outcomes nationwide.

NIH Research Projects · FY 2025 · 2025-09

Abstract Genetic studies have been highly successful in identifying causal factors associated with autism spectrum disorders (ASD). However, current genetic associations do not completely explain liability for this complex disorder. Several environmental exposures, like air pollution, pesticide or heavy metal exposures, are associated with ASD through epidemiological studies. However, unlike genetic studies, these environmental epidemiological associations have inherent problems including that environmental factors are difficult to quantify, and confounding variables are prevalent. In addition, while epidemiological datasets can highlight risk factors for autism, developing new treatments requires an understanding of the cellular and molecular consequences of genetics and environmental exposures on brain cells. While both genetic and environmental risk factors for ASD have been identified, how genetic background accentuates or blunts response to environmental risk factors, termed gene x environment interactions (GxE), has not been well studied. Our group has pioneered the “GxE in a dish” approach to identify genetic variants modulating response to environmental toxicants using human neural cells including brain organoids where exposures can be tightly controlled. To identify how the combination of genetic variation and environmental exposures lead to risk for ASD, to identify cellular and molecular mechanisms mediating these effects, and to suggest treatment targets to reverse these, we will conduct “GxE in a dish” studies using cortical organoids to understand the cellular and molecular consequences of autism-associated environmental toxicants modulated by genetic variation. We will conduct acute and chronic exposures on cortical organoids derived from 115 unique participants to environmentally relevant concentrations of 7 toxicants and vehicle in cortical organoids, modeling exposures during pregnancy, and we will perform single cell RNA-seq (scRNA-seq) for each organoid. We will identify common genetic variants associated with differences in gene regulation in response to environmental exposures within each identified cell type. Then, we will determine the impact of exposure-sensitive genetic variants on ASD diagnosis, intellectual ability, and brain development. These analyses will highlight whether exposure-sensitive alleles accentuate ASD risk allele effects within specific cell types of the developing brain. Overall, our proposal will identify genetic variants exerting cell-type specific modulations on environmental exposures through a novel “GxE in a dish” design. Successful completion of these aims may uncover unexplained risk for ASD that cannot be accounted for by genetics or exposures in isolation.

NIH Research Projects · FY 2025 · 2025-09

ABSTRACT There are more autistic adults in the service system than ever before, and this number is estimated to increase by as much as 300% by 2030. Outcomes for autistic adults are often characterized by low rates of employment and community participation, and high rates of anxiety, depression, and suicidality. Our community partners, including autistic adults and caregivers, have identified the need for research across the adult lifespan that identifies intervention and service targets to promote a high quality of life characterized by good mental health and community participation. We believe that generating a better understanding of autistic adults, including those in mid- and later life, is a pressing public health problem where rapid advancements are needed. To date, however, the field of adult autism research has primarily relied on small, non-representative samples limited to young adulthood. This has hindered our ability to understand outcomes and identify service targets across the adult lifespan and the full autism spectrum (i.e., inclusive of those with and without intellectual disability and a variety of levels of support needs). In response to ROA-OTA-25-006, we leverage an unprecedented collaboration between senior researchers across 4 NIH Autism Center of Excellence (ACE) sites focused on autistic adults. We employ a data driven approach to characterize service needs and targets in cross-sectional and longitudinal samples of autistic adults representative of the full adult lifespan and the full autism spectrum. We will deploy two complementary datasets that are optimally poised to make rapid advancements in service access, NIMH Data Archive (NDA) and Simons Powering Autism Research (SPARK). The NDA data collected across ACE projects provides one of the largest samples of well-characterized autistic adults (n=1,400). The SPARK dataset represents one of the largest longitudinal samples (n=400) of autistic adults. This proposal has three tasks: (I) Dataset Aggregation from the NDA to harmonize the parallel assessment protocol developed by the study team and utilized across 4 ACE sites to identify modifiable adult outcomes. (II) Data Generation to 1) generate geocodes to examine the influence of environmental and neighborhood factors (e.g., socioeconomic factors, provider density, environmental exposures) on service use and needs and trajectories of change in adult outcomes and 2) collect a third time point of data in a longitudinal cohort of 400 autistic adults from SPARK to examine trajectories of change in these modifiable outcomes across adulthood. This additional data collection will complement our aggregated NDA data by advancing our ability to answer questions about drivers of service needs measured over time across the entirety of the dynamic adult years. (III) Data Analyses using both machine learning and (longitudinal) latent transition analyses. We will use machine learning to identify subgroups in the NDA dataset based on their differing profiles of service use and needs and predict subgroup membership based on service targets and sociodemographic indicators. This will allow us to examine specific hypotheses focused on identifying the greatest service needs in this population, the relation between service needs and service targets to improve adult outcomes (mental health, community participation, quality of life). We will use latent transition analysis in the SPARK dataset to identify drivers of service use and needs based on trajectories of change across time. This will allow us to identify longitudinal trajectories of adult outcomes and their relation to service needs. Our work will be conducted in partnership with a 20-member Community Advisory Board (CAB) that includes autistic adults, family members/caregivers, researchers, clinicians and service providers for autistic adults, and state services representatives. The CAB will identify community-driven priorities for analysis. It will also provide interpretation of findings that will inform innovative, implementation-ready approaches to enhance meaningful outcomes for autistic adults. The intensive exchange of knowledge between the CAB and the data science team will produce a team of autistic community research partners experienced in collaboration with potential for major contributions to public service well beyond this grant. This OTA directly addresses the Autism Data Science Initiative goals by using multiple data sources to characterize service utilization patterns and pinpoint potential service targets that will lead to effective and scalable interventions across the lifespan. This work will advance our understanding of adulthood and aging in autistic people and accelerate community-informed, efficient, and effective policy and program priorities that address service access to improve quality of life, increase community participation, and reduce co-occurring mental health challenges.

NIH Research Projects · FY 2025 · 2025-09

Abstract The infant brain undergoes heterogeneous, nonlinear development across multiple phases, with cognitive progression exhibiting diverse subdomain patterns. Traditional regression and artificial intelligence (AI)-based models linking brain development to cognitive outcomes often overlook the dynamic nature of brain maturation and cognitive progression. Other challenges arise from limited sample sizes and unmeasured early lifestyle and environmental exposures. In our prior work, we developed a computationally efficient, easily interpretable centile-based explainable-AI toolbox, which has been proven effective in the early diagnosis and prognosis of knee osteoarthritis. In this work, we integrate this centile-based AI with the recently developed cross-cohort meta-matching techniques to predict infant cognitive growth. We will leverage four infant brain multimodal magnetic resonance imaging (MRI) databases to derive individual centile score maps from structural and resting-state functional MRIs, separating influences into anatomical and functional domains. Additionally, we will incorporate latent neural signatures (LNS) associated with “unseen” non-infant, non-imaging phenotypes—such as adolescent fluid intelligence, social behavior, or PM2.5 pollution exposure—mapped from two large-scale children and adolescent datasets. By identifying key biomarkers, we aim not only to elucidate the specific anatomical and functional brain regions influencing distinct infant cognitive subdomains but also to determine whether LNS metrics mapped from childhood/adolescence can serve as proxies for underlying cognitive, behavioral, or environmental exposures impacting infant cognitive development. This meta-matching approach is a novel application with significant potential to uncover previously hidden implications, linking insights from children and adolescent data to infant brain measures. Two specific aims guide our project. Aim 1: construct a computationally efficient, easily interpretable centile score-based explainable- AI toolbox and assess the improvement in infant cognitive prediction with centile score-based imaging biomarkers. Specifically, we fit developmental trajectories and obtain individual centile score maps for all brain imaging measures, evaluating them using various machine learning approaches to improve predictions of infant cognitive development. Aim 2: Assess whether integrating unseen non–brain-imaging phenotypes via meta-matching—including adverse childhood experiences, latent lifestyle and environmental exposures and psychiatric disorders---can further enhance cognitive outcome predictions. With the transparency of explainable-AI, this project will not only provide a holistic understanding of infant cognitive development in relation to brain structure and function but also establish a novel framework to link brain regions activated by childhood and adolescent cognitive, behavioral and environmental factors, as well as psychiatric disorders, to infant cognitive outcomes. Our expert team, with diverse specializations in neuroimaging, infant brain development, advanced statistical modeling and machine learning, is committed to sharing findings and methodologies with the broader scientific community. This dissemination will enhance replicability, foster innovation, and expand the applicability of insights in early brain and cognitive development. Furthermore, the psychiatric disorders incorporated in meta-matching in Aim 2 hold clinical significance, potentially aiding in early intervention strategies for neurodevelopmental conditions.

NIH Research Projects · FY 2025 · 2025-09

ABSTRACT Malaria represents a major global public health challenge, killing 619,000 people each year, predominantly children in Africa. The recent emergence of artemisinin partial resistance (ArtR) in Africa has the potential to lead to a global public health crisis and may result in the failure of test-and-treat strategies that serve as a cornerstone of malaria control. If it follows the historical example of Southeast Asia, where ArtR parasites are now widespread, millions of additional malaria cases could occur each year. A major challenge for disease ecology is understanding and predicting how resistance to interventions emerges and spreads. For malaria, transmission models in popular use today are simulation based, allowing for rich representations of transmission cycles and also capturing the true random nature of infection. This creates significant problems for model-based inference. Traditional inference methods like Bayesian Markov chain Monte Carlo (MCMC) cannot be used in most cases, and more advanced methods are limited in scope or power. Deep learning offers a new and general-purpose solution to this problem. Deep neural networks (DNNs) trained on large amounts of simulation output can learn the complex relationships between parameter inputs and outputs. The trained “surrogate” model can then be used to produce outputs that closely resemble the original simulation model in a fraction of the run-time, or they can be used within traditional Bayesian MCMC to estimate parameters. This approach, referred to as “deep learning surrogates” (DLS), is gaining traction in many areas of research but has not yet penetrated infectious disease modeling. Most applications of DLS have focused on speeding up prediction. While this is an important use-case, in infectious disease modeling we are equally interested in learning from observed data. Here, mathematical models can provide estimates of crucial parameters like the basic reproductive number of a pathogen, or more detailed outputs like the complete surface of disease prevalence over a geographical region. Thus, DLS has enormous potential by linking complex simulation models to traditional parameter estimation methods. The goal of the proposal is to apply DLS methods to the urgent problem of antimalarial resistance in Sub-Saharan Africa. Specifically we will: 1) develop a temporal DLS model to predict the impact of drug policy interventions in Kinshasa Province, DRC and 2) develop spatial DLS models to predict the spread of artemisinin resistance in the Great Lake region of Africa and Ethiopia. In both cases, we will leverage some of the most comprehensive epidemiological and genetic datasets available.

NIH Research Projects · FY 2025 · 2025-09

Project Summary/Abstract Here, we propose a training program with two years of training to prepare the candidate for a successful transition to independence, in the field of developing machine learning integration algorithms to predict undercharacterized genomic and proteomic data. The training plan is designed to guide the candidate's scientific and professional development, under the men-torship of Dr. Noble and guidance from five advisory committee members (Drs. Christine Disteche, Jay Shendure, Brian Beliveau, Mike MacCoss, and Sheng Wang) at the University of Washington. The committee will help the candidate extend their knowledge of proteomics, spatial imaging, and machine learning development. The proposed research focuses on developing semi-supervised machine learning integration tools that can predict the various types of single-cell profiles (e.g., chromatin accessibility, spatial locations, proteomics) from known measurements (e.g., gene expression). In Aim 1, we propose to computationally fill in the gap of single-cell time series snapshots to infer continuous cellular profile changes, by building a conditional variational autoencoder model with continuous time representations. The model will enable us to infer temporal maps of single cells in conditions with sparser time points captured (e.g., a mouse mutational strain collected in another experiment, human embryonic development, chromatin accessibility measurements). In Aim 2, we will develop a semi-supervised joint machine learning model stitching together the conditional variational autoencoder model and graph neural network to predict the physical locations of cells with dissociated gene expression and chromatin accessibility measurements. In Aim 3, we will combine the semi-supervised framework with deep tensor factorization and use genomics and bulk assays to infer single-cell proteomics profiles and identify genome-scale protein markers in single cells with only gene expression profiles. The research plan will generate computational tools to project single cells to their spatiotemporal contexts and understand the protein mediators. The tools will be generally applicable to studies of complex biological systems (e.g., embryonic development) and diseases (e.g., cancer). With the rapid development in single-cell time-series, spatial imaging, and proteomics, we expect our methods to have increasing power for biological knowledge detection.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY Nearly half of new HIV infections in the United States (US) arise from persons with HIV (PWH) who are known to be living with HIV but who are out of care. Novel interventions to reach and rapidly suppress PWH who are out of care are urgently needed, particularly in the rural Southeastern US where limited HIV care access and persistently high HIV incidence results in poor HIV-related health outcomes. Long-acting injectable antiretroviral therapy (LAI) is a tremendous advance in HIV therapy, replacing daily pills with every-other-month injections. FDA labeling for LAI currently supports use for PWH who are virally suppressed, but efficacy of LAI suppressing viral replication among viremic PWH has now been shown. Despite the potential advantages of this less-frequent dosing option, few LAI studies have engaged PWH who are out of care. Field-based LAI, where injections are given in the community rather than in a clinic, may extend LAI access to difficult-to-reach populations of PWH. In this study, investigators will evaluate field-based LAI in North Carolina (NC) for PWH who are out of care. The study explores the determinants, acceptability, feasibility, and impact on HIV viral suppression of field-based LAI, which includes field-based delivery (implementation strategy) of LAI (evidence-based intervention). The study’s Aims map to the five steps within a modified Implementation Mapping framework, engaging key agents in the patient, clinic, community, and policymaking sectors via a combination of formative work (Aim 1a), workshop- based procedural co-production (Aim 1b), and pilot testing (Aim 2). Specifically, in Aim 1a, investigators will recruit ~40 key informants for in-depth interviews and focus group discussions. Guided by the Consolidated Framework for Implementation Research, this aim examines barriers or facilitators of field-based LAI, including internal and external influences relevant to future implementation trials. Aim 1b utilizes preferences and determinants elicited in Aim 1a in sequential workshops with key informants to co-produce and refine field-based LAI procedures and protocols for Aim 2 (Phase I) and future implementation trials (Phase II). Finally, in Aim 2, using established methods for identifying and tracing PWH who are out of care at an academic HIV clinic in NC, investigators will enroll 40 PWH who are out of care into a longitudinal pilot study of field-based LAI, following participants for 7-months, which corresponds to the first five injections. PWH who are contacted and eligible but decline LAI will be offered enrollment for a one-time survey, capturing reasons for declining. Primary outcomes are acceptability and feasibility of field-based LAI, assessed through administrative records, exit interviews, and surveys at 0, 3, and 7 months. Secondary outcomes are 7-month viral suppression, re-engagement with in-clinic care, care retention, and drug resistance. Ending the HIV epidemic is not possible without engaging PWH who are out of care and not suppressed, particularly in rural regions of the US where the epidemic continues to expand. The proposed study engages crucial key informants and tests a strategy to rapidly suppress viremia via field-based LAI among a high-priority population of PWH, informing future implementation science trials.

NIH Research Projects · FY 2025 · 2025-09

ABSTRACT Genome-wide association studies (GWAS) have successfully detected thousands of association signals for type 2 diabetes (T2D) and related metabolic traits, a key step toward identifying genes and causal pathways that modify individual-level heterogeneity in disease risk. Most genetic associations are driven by noncoding variants, motivating discovery of regulatory mechanisms and potential effector genes, especially in pancreatic islets, adipose, skeletal muscle, and liver. However, variant effects on regulatory elements, genes, and gene functions are often ambiguous and not comparable across studies due to inconsistently defined association signals and non-standardized study designs and analysis strategies. To capitalize on investments in genetic research for T2D, the community needs harmonized cross-tissue data to prioritize variants and genes for in-depth mechanistic studies, risk prediction, and identification of drug targets. To guide detailed mechanistic studies, harmonized cross-cell type data on plausible gene functions are needed, but are challenging for any one lab to perform at scale. Substantial evidence shows that mitochondrial dysfunction plays a key role in multiple tissues involved in T2D pathogenesis through defects in pancreatic beta-cell dysfunction, insulin resistance, adipose tissue beiging, obesity, and complications. Mitochondria play a key role in cellular energy metabolism through the production of ATP from oxidative phosphorylation, generation of reactive oxygen species, and apoptosis, and T2D GWAS signals are enriched for mitochondrial genes. Demonstration of mitochondrial defects for genes not previously shown to influence energy metabolism would motivate future studies of specific mechanisms. Here, we will provide resources to meet these needs. We will detect regulatory variants and elements at T2D GWAS signals in disease-relevant cells/tissues by developing a uniform pipeline to discover genetic variants associated with chromatin accessibility (caQTL) and colocalizing caQTL and T2D signals. We will identify candidate effector genes for T2D GWAS signals by systematically integrating molecular quantitative trait loci and chromatin looping data to predict which genes are altered by noncoding risk variants, and we will integrate these results, by signal, with predictive models and data about tissues of action at cell-type resolution. To assess gene function, we will perform harmonized genome-wide assays to identify effects on mitochondrial function for genes at T2D GWAS signals and at pathway hubs in beta cells, adipocytes, myocytes and hepatocytes. Together, these analyses and data about T2D GWAS signals will provide valuable resources to the community, including the most likely regulatory variants and elements, tissues of action, and effector genes, as well as evidence of gene effects on mitochondrial function. We will collate these comprehensive resources by signal and assimilate them into data portals for the community.

NIH Research Projects · FY 2025 · 2025-09

PROJECT SUMMARY/ABSTRACT Women constitute an estimated 20% of new HIV diagnoses in the United States, with the highest burden of cases among women in the Southeast. Low pre-exposure prophylaxis (PrEP) utilization among women presents a challenge to addressing the burden of HIV in the Southeast and ending the US HIV epidemic. Only an estimated 2% of the 170,000 women who could benefit from PrEP are using it. Low PrEP use among women in the US may be attributable to lack of awareness and beliefs that PrEP is not appropriate for women. Fewer than 15% of women with HIV risk indications are aware of PrEP. Many women who are aware of PrEP believe that it can only be used by men, or believe that PrEP is not appropriate for them due to low perceived HIV risk. Building on an existing website prototype and prior PrEP messaging research, we propose a web-based awareness raising and demand creation approach consisting of a website with tailored PrEP information and decision support disseminated through social media to women throughout the Southeast. In Aim 1 we will develop a replicable social media targeting approach optimized to engage women with indications of PrEP need. This will generate ad campaigns refined through focus group discussions followed by a social media targeting study to identify social media platforms and targeting terms for engaging women with PrEP need. In Aim 2 we will build the PrEP decision support website based on existing prototype content. To update website content, we will conduct a preference elicitation study to expand the site to address long-acting PrEP methods followed by user testing to refine the website with input from women throughout the Southeast. In Aim 3 we will conduct a pilot trial of the PrEP decision support website with 100 women recruited through social media to evaluate intervention feasibility, acceptability, and appropriateness and to explore intervention effects on PrEP interest and uptake. Women will be randomized to receive either the decision support website or a standard education website and linked to a PrEP finder site to facilitate connections to PrEP providers. We will conduct in-depth interviews with women receiving the PrEP decision support website to understand their experience of the intervention. If the intervention proves feasible and shows promise to promote PrEP interest and uptake, this study will lay the foundation for a larger randomized controlled trial to evaluate the intervention effect on PrEP uptake among women in the Southeast with indications of PrEP need. Ultimately, the PrEP decision support website and social media dissemination strategy may provide a wide-reaching approach to promote need- proportionate PrEP uptake among women.

NIH Research Projects · FY 2025 · 2025-09

Program Director/Principal Investigator (Last, First, Middle): Cheatham, Carol Abstract and Public Health narrative of the Phase Summary of the Phase I/II: Abstract of the Phase Summary of the Phase I/II Prevention of and intervention in fetal alcohol spectrum disorders (FASD) requires a detailed knowledge of proximal and distal maternal and paternal risk factors that are associated with specific child traits common to FASD. In the completed R61 Phase, we created and piloted novel protocols for: 1) interviewing mothers (with biomarker validation) to determine maternal alcohol consumption on a weekly/monthly basis across pregnancy to assess their specific contributions to child traits and severity of FASD outcomes; 2) determining maternal experience with stress, trauma, and mental health status during pregnancy and their contribution to the severity of effect on FASD diagnostic traits in their offspring; 3) interviewing biological fathers of the index pregnancy regarding paternal traits that may contribute to the risk for FASD from exposure to teratogens such as alcohol, other drugs, environmental toxins, and social environment during pre-conception; and 4) establishing a comprehensive, summary FASD risk score from the above innovations when combined with other empirically-established risk factors. The R33 Phase will now initiate an exploration of a multivariate, comprehensive approach to FASD risk via two applications for better understanding FASD etiology. In the prospective study, 200 women and as many of their partners as we can consent (estimated to be a minimum of 100) will be recruited from prenatal clinics, and their offspring will be assessed at six weeks and nine months post-partum and diagnosed as to their status on the continuum of FASD by pediatric dysmorphologists and a multidisciplinary team. The second application of the new methods will gather the new data retrospectively and link the data to two existing cohorts of maternal/child dyads whom we have followed over time to assess their FASD status and the severity of their physical, neurodevelopmental, and behavioral traits. Both studies will add new insight to our long-term quest to understand more completely the respective contributions of a broad range of host, agent, and environmental factors to the etiology of FASD. This R33 Phase will provide substantial validation of the utility of collecting weekly alcohol use data, mental health status assessments, paternal information, and FASD risk score innovations via expert clinical assessment of the offspring of each pregnancy. In developing this more comprehensive approach to FASD risk, both study phases draw on our existing clinical epidemiology infrastructure, the experience of our multidisciplinary team, and the participants in existing longitudinal cohorts. RELEVANCE (See instructions):

NIH Research Projects · FY 2025 · 2025-09

Project Summary Our goal is to identify gene-environment interactions (GxE) with acute and chronic exposure to the ambient air pollutant ozone (O3) that contribute to common, chronic respiratory diseases like asthma and COPD. However, detecting GxE with O3 exposure in human epidemiologic studies is extremely challenging for a number of reasons, including statistical power and precision of exposure assessment. To overcome these challenges, we have exploited genetically diverse, multi-parental mouse populations, namely the Diversity Outbred (DO) and Collaborative Cross (CC, inbred), as GxE discovery platforms because in these models we can maximize information about both genetic variation and O3 exposure. Previously, we utilized the CC to identify a large-effect GxE quantitative trait loci (QTL) with acute O3 on chromosome (Chr) 15 that affected airway injury and inflammation. At this locus, two candidate genes emerged, Angpt1 and Rspo2. We also found that a common variant at the orthologous locus in humans (rs10086579, located between ANGPT1 and RSPO2) affected response to acute O3 in humans, demonstrating proof of concept for our approach. This variant also exhibited GxE with chronic air pollution in COPD, indicating it likely affects response to both acute and chronic exposure. Here, we propose to first identify the causal gene on Chr 15 in mice (Angpt1 vs. Rspo2), then identify new GxE QTL for both acute and chronic O3 responses. In all cases, we will translate our findings from mouse to human through targeted analysis of GxE with common variants in human orthologs of the genes we identify in mice using existing genotype and O3 exposure data from 3 human studies. The human studies include (1) an acute O3 challenge dataset (n=191) in which inflammation was quantified, (2) the Multi-Ethnic Study of Atherosclerosis Air Pollution Study (MESA-Air, n~6000) in which associations between chronic O3 exposure and COPD (emphysema and lung function) have been quantified, and (3) the Children’s Health Study (CHS, n~1800) in which associations between chronic O3 and childhood-onset asthma have been quantified. In Aim 1, we will evaluate Angpt1 and Rspo2 using knockdown/knockout and rescue experiments in mice. In parallel, we will conduct an expanded human genetic analysis of acute and chronic O3 response with rs10086579 and nearby variants using the 3 human datasets. In Aim 2, we will identify new GxE for acute O3 response in mice by performing a QTL mapping study involving two CC strains that are phenotypically divergent but not due to variation at the Chr 15 QTL. Gene expression QTL (eQTL) mapping in alveolar macrophages (AM) and mediation analysis will be used to identify candidate genes. We will then test for GxE in the human studies. In Aim 3, we will identify GxE for chronic O3 response using DO mice, employing a longitudinal study design in which lung function is measured prior to and after O3 exposure. After mapping QTL at high resolution and identifying candidate genes, we will test for GxE in the CHS and MESA-Air. In total, our work will reveal novel genes associated with that affect O3-induced asthma and COPD onset and/or progression.

NIH Research Projects · FY 2025 · 2025-09

Since its founding in 1990, the NHGRI Ethical, Legal, and Social Implications (ELSI) Research Program has supported empirical, analytical, and conceptual research to anticipate and address the ELSI of genetics and genomics. This broad focus has fostered a substantial and multidisciplinary community encompassing a wide range of experiences and expertise. We propose to support three biennial conferences of the ELSI research community (referred to as the “ELSI Congress”). With dedicated conferences, the ELSI research community can meet to share research findings, develop collaborations, particularly among trainees and early career scholars, and foster participation from a broad array of scientific perspectives, intellectual traditions, and lived experiences. While each of the three ELSI Congresses will have their own set of unique aims, as determined by the Organizing Committees, the following specific aims reflect our approach to overall conference planning. Aim1: Expand ELSI’s reach to scholars across new generations, communities, and disciplines. The core goal of the ELSI Congress is to bring together ELSI researchers from the broadest array of scientific perspectives, intellectual traditions, and lived experiences through various outreach and communication efforts. We propose to invite participation from less resourced institutions and to contact NIH grant recipients focusing on strengthening genetic variation research. Aim 2: Utilize innovative methods to identify emerging trends in genomics, and important ELSI themes for upcoming Congresses. To ensure that the key topics addressed at each Congress reflect the latest developments in both ELSI and genomics, we would employ a modified version of horizon scanning methodology. Horizon scanning is a multi-step process recommended in NIH’s Novel and Exceptional Technology and Research Advisory Committee (NExTRAC) framework to identify and prioritize emerging biotechnologies and applications that have the potential to impact society (NExTRAC, 2020). We would use this strategy to examine the recent state of the ELSI and genomics fields and help predict new developments. Results from the horizon scanning would be analyzed by our team and used along with card sort methodology to assist the Organizing Committee in prioritizing and selecting topics and themes for the Congress. These activities would be repeated prior to each Congress. Aim 3: Develop robust strategies for reviewing each Congress and a plan for how we implement what we learn. To assess how effectively we've maximized participation in ELSI Congresses, we would gather basic information about participants during the registration process and assess any changes over time. Through post-Congress evaluation surveys and follow-up Zoom sessions, we would also use feedback gathered from the Congress participants, ELSI Program Staff, and the Organizing Committee to inform future meeting format decisions, topic and theme selections, and venue selections. We would also ask about perspectives and research findings that attendees believe might have been missing from Congress proceedings, as well as asking for specific recommendations for planning future Congresses.