University Of Pennsylvania

NIH Research Projects · FY 2026 · 2023-04

Project Summary Ending the HIV epidemic will require novel strategies to expand the HIV prevention continuum among men who have sex with men (MSM), who are disproportionately affected by HIV. The COVID-19 pandemic has underscored the need for remote care approaches such as HIV self-testing (HIVST) to sustain access to HIV services. However, the benefits of self-testing are limited if they do not spur behavioral change or linkage to care, yet only 1 in 10 MSM who self-test obtain preventive care afterwards, and the majority of MSM with indications for PrEP have never used it. Interventions to support linkage from HIVST, the first key step in the HIV “status neutral” continuum, are needed. To maximize the impact of HIVST, linkage to care is a critical practice gap that needs to be addressed, a gap that can potentially be bridged by a peer intervention to support linkage and PrEP uptake. To expand the HIV prevention continuum among MSM, this research will leverage HIVST and evaluate a peer-led intervention to support engagement in care and PrEP uptake through peer linkage after self-testing. The overall goal of this career development award is to provide Dr. Cedric Bien- Gund with the necessary research skills to become an independent clinician-investigator in the development, evaluation, and implementation of behavioral interventions to prevent HIV infections. To achieve this goal, we have assembled a mentoring team and proposed a rigorous training plan to develop his skills in 1) mixed methods for behavioral interventions, 2) intervention design and mapping for implementation, and 3) advanced clinical trial design, including implementation science designs. These training objectives complement a research plan to develop and pilot a behavioral intervention to increase linkage to PrEP among MSM through integration of HIVST distribution and peer-led linkage to PrEP. The specific aims are: 1) identify barriers and facilitators to PrEP linkage after HIV self-testing among MSM, 2) develop a peer-led linkage intervention for HIVST, and 3) test the acceptability, feasibility, and preliminary efficacy of the intervention on PrEP linkage and uptake among MSM by conducting a pilot randomized controlled trial. This project will leverage an ongoing collaboration with the Philadelphia Department of Public Health to expand HIVST and PrEP uptake. The proposed research addresses the first steps in the HIV prevention continuum and will support Dr. Bien-Gund's goal of becoming an independent investigator with expertise in behavioral interventions to end the HIV epidemic. This research will provide preliminary data for an R01 application to test the intervention in a hybrid type I effectiveness-implementation trial, with the goal of optimizing the impact of HIVST by closing the linkage gap after testing.

NIH Research Projects · FY 2026 · 2023-04

PROJECT SUMMARY/ABSTRACT Iodine deficiency has increased dramatically in the U.S. in recent decades leading to over 40% deficiency in reproductive age women. Moreover, infertility and pregnancy loss are increasingly common with far reaching physical, social, and emotional consequences. Targeted low-cost interventions are needed to address these adverse reproductive outcomes. Iodine is a potential therapeutic for these outcomes as it is biologically important for critical hormones involved in reproduction, placentation, and growth and development of offspring. Severe deficiency is well known for its effect on hypothyroidism and irreversible brain damage in offspring of deficient pregnant women. However, little is understood on the effects of deficiency on women's fertility, fecundity, pregnancy loss, and other pregnancy complications. Research into the implications of deficiency has proven quite challenging as it does not always present clinically and is incredibly variable day- to-day. It is commonly recommended that 10 urine samples are needed to accurately classify iodine status of an individual. Yet many studies fail to follow this recommendation and rely on a single spot urine which can lead to grossly attenuated findings, hampering progress in iodine research. An accurate evidence base is critically needed to inform policy and individual decisions on iodine fortification, supplementation, and dietary intake, all which of which offer a potential low-cost solution to promote the health and wellbeing of women and their offspring. We propose a novel application of biospecimen pooling to classify individual's iodine status and overcome prior measurement challenges. We pooling have developed an innovative hybrid design that uses both and random sampling to measure iodine in preconception and throughout pregnancy.The overarching goal of this study is to investigate the role of iodine on reproductive and perinatal outcomes including rarely studied outcomes of fecundability, fertility, very early pregnancy loss. This work will utilize the EAGeR study (n=1228), an existing well-defined, preconception cohort of women at high risk for pregnancy loss with daily urine collection preconception, and if they achieved pregnancy, during the first four weeks of pregnancy with additional spot urine samples throughout, and collection of the placenta at delivery. Using novel biospecimen pooling methods we will classify iodine status in preconception, early-, mid-, and late- pregnancy. Using a trial emulation approach, we will investigate the effects of iodine deficiency, across critical periods of susceptibility on reproductive and perinatal outcomes. We will also measure iodine in placenta samples; little is known about how maternal iodine in gestation relates to placental iodine and how this interrelationship relates to pregnancy outcomes. The successful completion of these aims with the novel characterization of iodine status from preconception through gestation using biospecimen pooling and in the placenta will enable investigations into iodine's role in reproductive and perinatal health. If implicated, iodine is a low-cost intervention, that could be used to target women at risk for adverse outcomes.

NIH Research Projects · FY 2026 · 2023-04

PROJECT SUMMARY Inhibition of the DNA replication checkpoint regulator ATR is a new and promising cancer treatment. ATR inhibitors (ATRi) function as cancer treatments by causing double-stranded breaks (DSBs) at sites of problematic DNA replication. Indeed, we have recently demonstrated that structure-forming repetitive DNA sequences strongly influence on ATRi-driven breakage. However, our recent preliminary studies indicate that abnormal DNA structure formation is not the sole determinant of vulnerability at these sites. We have now shown that ATRi- driven breakage at inverted retroelement repeats is strongly stimulated by treatments that promote their transcription. Moreover, because the transcription of retroelements is silenced at most genomic locations, their derepression substantially increases breakage caused by ATRi. We hypothesize that cancer-associated alterations and silencing inhibitors that foster the transcription of inverted retroelements will increase sensitivity to ATRi treatment. Importantly, advanced prostate cancer, most notably castration-resistant prostate cancer (CRPC), exhibits many features expected to cause increased transcription of inverted retroelements. These alterations include the hypomethylation of retroelements, the loss of RB1 and p53-mediated repeat silencing, and the abnormal processing of RNA-DNA hybrids due to RNASEH2 deficiency. Herein, we propose to determine how each of these prostate cancer-associated changes affect the localization and number of DNA breaks induced by ATRi. Furthermore, we will explore the molecular mechanism by which inverted retroelement transcription increases ATRi-driven breakage at select sites and determine if further inhibition of retroelement silencing by clinically approved drugs synergizes with ATRi to suppress the growth of tumors in mouse models of CRPC. Finally, we will determine if this combination treatment is more effective in the context of prostate cancer-associated mutation of ATM, BRCA2 and RB1. Collectively, these studies will characterize new mechanisms by which cancer cells are sensitized to ATRi as well as identify novel combination treatments for CRPC.

NIH Research Projects · FY 2026 · 2023-04

Persistence of the latent HIV reservoir in people living with HIV (PLWH) remains the critical barrier to an HIV cure. Numerous reservoir reduction and control studies have met with only limited success due to our profound lack of understanding of the cellular mechanisms that allow the HIV reservoir to persist during antiretroviral therapy (ART). The goals of this proposal and RFA AI-22-025 are to define the characteristics of the HIV reservoir enabling cell death resistance and to determine whether these mechanisms impact reservoir reduction strategies in PLWH. Previous studies have examined the viral reservoir from the aspect of the integrated provirus, including viral diversity, intactness, and integration site, but have not been able to directly define potential cell death resistance mechanisms that perpetuate the viral reservoir. Similarly, challenges in identifying and characterizing resting infected cells ex vivo, including rarity, heterogeneity, and absence of a defining phenotypic marker, have limited our ability to determine how the HIV reservoir is maintained under ART. To address these issues, we developed a novel single cell strategy to identify HIV+ cells via integrated proviral DNA with simultaneous epigenetic and cell surface profiling (Assayfor Transposase Accessible Chromatinsequencing with cell surface profiling and viral alignments,V-ASAPseq). Using this strategy, we have directly profiled the HIV reservoir in ART treated PLWH at the single cell level, finding extensive reservoir heterogeneity within and between individuals, but the potential for shared regulatory characteristics directly relating to cell death resistance. Here, we will apply V-ASAPseq and V-TEAseq (transcriptome, epigenome, and surface profiling) to define cell death resistance mechanisms of the HIV reservoir. Our central hypothesis is that reservoir persistence over time under ART and after immunotherapeutic challenge is associated with targetable cellular features, some of which are shared and others distinct between subpopulations of HIV+ CD4+ T cells. In Aim 1 we will determine reservoir-associated changes in cell death resistance signatures over time, between anatomical compartments and after reactivation. In Aim 2, we will determine the epigenetic and transcriptional features of HIV+ cells that drive cell death susceptibility in vitro and persistence in vivo after reservoir-targeting immunotherapies from human clinical trials. Together these studies will define targetable features of reservoir persistence and cell death both at rest, during ART, and in the context of reservoir-targeting immunotherapies with the ultimate goal of reducing the HIV reservoir.

NIH Research Projects · FY 2026 · 2023-04

Project Description/Abstract Fracture healing is a significant health issue for patients with diabetes despite the availability of insulin. Strategies to improve fracture healing are underdeveloped due to concerns of costs, effectiveness and side-effects. Preliminary data demonstrate that lineage specific deletion of the transcription factor FOXO1 in chondrocytes or osteoblasts completely rescues diabetes impaired fracture healing measured histologically, by microCT or mechanical testing. We also determined that lineage specific loss of cilia, restricted to chondrocytes or osteoblasts, interferes with fracture healing and mimics diabetic fracture healing. Based on these exciting data we have conceived an application focusing on the role of FOXO1 and primary cilia in chondrocytes and osteoblasts as important contributing factors to deficient fracture healing in diabetics. Thus, the proposed studies will test the hypothesis that diabetes results in upregulation of FOXO1 and concomitant downregulation and loss of cilia, which in turn causes a loss of cell specific signaling needed to activate chondrocytes/osteoblasts and consequentially leading to deficient fracture healing. To address the therapeutic benefits of this hypothesis we have developed a nanofiber hydrogel with controlled release of an insulin-like growth factor-1 mimetic, called NFH-IGF. There are two Specific Aims. Aim 1 will determine if FOXO1 suppresses ciliogenesis and downstream signaling pathways needed to activate healing responses in chondrocytes and osteoblasts in diabetic fracture healing. Specific mechanisms will be tested using the newly developed CyTOF technology and mice with targeted deletions of IFT80 to inhibit ciliogenesis, deletion of FOXO1 or double deletion of FOXO1+IFT80. Aim 2 will further develop a novel device with controlled release of a mimetic with IGF-1 activity, nanofiber hydrogel- IGF (NFH-IGF). The goal is to determine whether NFH-IGF treatment improves T1DM and T2DM diabetic fracture healing. Mechanistic studies will determine whether NFH-IGF downregulates FOXO1 and upregulates cilia in chondrocytes and osteoblasts to enhance intracellular signaling pathways that stimulate these cells. We anticipate that proposed studies will not only result in new knowledge about the role of cilia in diabetic fracture healing but also result in the development in a novel therapeutic aid for the treatment of T1DM and T2DM using nanofiber hydrogel-IGF formulations.

NIH Research Projects · FY 2026 · 2023-04

SUMMARY Cold-induced thermogenesis (CIT) allows endotherms, including mammals, to maintain body temperature at ~37oC despite sometimes much colder ambient temperature. Pharmaceutical activation of CIT is being investigated by many groups as a potential therapeutic approach to obesity. Despite decades of investigations of CIT, however, how different fuels are burned during CIT, by which tissues, and to what extent, remains ill- defined. We propose here to carry out a comprehensive quantification of systemic metabolic fluxes during cold exposure in mice. These studies are enabled by the development by us and others of: (1) steady-state infusions with non-perturbative amounts of heavy isotope-labeled fuels in live, awake, and ambulatory mice, allowing precise quantification of whole-body fuel turnover and of relative contribution of each fuel to tissue oxidation rates; and (2) acute kinetic studies to allow quantitative estimates of rates of tricarboxylic acid cycle turnover, and thus of VO2, in individual tissues. Based on extensive preliminary data, we hypothesize that CIT is largely fueled from fat stores, but that it is nevertheless critically dependent on anaplerotic carbohydrate sources, provided by the liver, to sustain fatty acid oxidation. We will have 3 aims: Aim 1: Comprehensive quantification of whole-body fuel turnover during CIT in mice. Aim 2: Comprehensive quantification of fuel use in individual tissues during CIT in mice. Aim 3: Test the role of carbohydrate flux in BAT during CIT.

NIH Research Projects · FY 2026 · 2023-04

ABSTRACT Vertebrae originate from somites during embryonic development. Somites are segmented from the presomitic mesoderm (PSM) and the process is known as somitogenesis. Somitogenesis is controlled by key Notch signals in the PSM that oscillate with a periodicity matching that of somite formation. Hypoxia occurs naturally in developing embryos before the circulatory system is established. However, exacerbation of hypoxia as it may take place during gestation disrupts the oscillatory Notch signals in the PSM and leads to abnormal somitogenesis and altered spine development. Spondylocostal Dysostosis (SCDO) is characterized by severe vertebral malformations and is caused by homozygous loss-of-function mutations of components of the Notch signaling pathway. Mice carrying similar homozygous mutations phenocopy the human disease. Heterozygous Notch LOF mutations cause the more modest, although more frequent, human defect of congenital scoliosis (CS), which is also phenocopied in heterozygous mouse mutants. These mice phenotypes are worsened by gestational hypoxia. The mediators of the hypoxic response are the transcription factors Hypoxia-Inducible Factor-1alpha (HIF1) and HIF2. The role of HIF1 and HIF2 in somitogenesis has not been addressed. To fill this gap of knowledge, we conditionally inactivated HIF1 in the PSM using TCre transgenic mice (HIF1 mutants). Loss of HIF1 in the PSM causes abnormal somitogenesis and spine malformations reminiscent of SCDO/CS and gestational hypoxia. Conversely, preliminary data showed that HIF2 is not necessary for spine development, but the concomitant loss of HIF1 and HIF2 ameliorates the spine abnormalities observed in HIF1 mutants. Hypoxia increases stability and transcriptional activity of the HIFs; therefore, we were intrigued by the observation that gestational hypoxia and loss of HIF1 in the PSM alter somitogenesis in a similar manner. Notably, both loss of HIF1 and gestational hypoxia led to an increase in intracellular hypoxia in the PSM. Furthermore, preliminary findings revealed that the impairing of mitochondrial respiration, which was used as a tool to reduce intracellular hypoxia, partially corrected the spine defects observed in HIF1 mutants. Considering our preliminary data, ourworking hypothesis is thatboth loss of HIF1 in the PSM and gestational hypoxia increase intracellular hypoxia, which in turn dysregulates the Notch signaling pathway and alters somitogenesis. We also hypothesize that loss of HIF1 in the PSM stabilizes HIF2 by increasing intracellular hypoxia, and the augmented HIF2 transcriptional activity mediates some of the effects due to loss of HIF1. Our hypotheses will be tested in two Aims. Accomplishment of the proposed experiments will establish, for the first time to our knowledge, the role of HIFs and mitochondria respiration in somitogenesis. It will position HIF1 upstream of the Notch signaling pathway in PSM. It will shed new light into our current understanding of the in vivo cross-talks between HIF1 and HIF2. Lastly, it will provide novel insights into the pathogenetic mechanisms leading to congenital scoliosis because of gestational hypoxia.

NIH Research Projects · FY 2025 · 2023-04

PROJECT SUMMARY/ABSTRACT Aging is an inexorable, multifactorial process in which organisms lose fitness and ability to maintain homeostasis. With advances in modern medicine and standards of living across the globe, life expectancy, and thus aging, is set to expand rapidly. Cognitive decline due to Alzheimer’s disease and other age-associated dementias is one of the most debilitating aspects of aging, robbing millions of people of everyday function and independence. Healthier aging and independence are potentially worth trillions of dollars in addition to unquantifiable social and emotional benefits. As we get older, our cells are not the only thing in our body that age. The microbiome is the collection of trillions of microorganisms that inhabit our gastrointestinal tract. Like organ systems, the microbiome also changes with age, losing diversity and gaining deleterious species. It is widely accepted that the microbiome plays an important role in metabolism, digestion, and obesity, but recently it has also been linked to disease processes in the brain, such as autism and depression. The vagus nerve connects the central and enteric nervous systems to mediate gut-to-brain signaling, and its ablation has been shown to induce cognitive deficits in rats. Additionally, it has also been shown that performing fecal microbiome transplants (FMT) from old mice into young germ-free mice induces cognitive deficits. In initial experiments, I have shown that passive transfer of the microbiome by cohousing young and old mice induces cognitive deficits in young mice. This effect is not seen in cohoused germ-free or antibiotics-treated mice and is reproduced upon FMT into young germ-free mice from old stool donors. Ablating or inhibiting afferent vagal neurons also induces a cognitive deficit, while vagal stimulation with low dose capsaicin or hormonal activation reverses deficits associated with the aged microbiome. Thus, I propose that the aged microbiome impairs cognition through inhibition of gut-to-brain signaling. To explore this, I will first use bacterial sequencing to identify bacterial species in the aged microbiome that are sufficient to induce cognitive deficits (Aim 1). Next, I will determine which components of gut-to-brain signaling are required for learning and memory (Aim 2). Finally, I will characterize the effects of the aged microbiome with brain-wide mapping of neuronal activation during memory encoding (Aim 3). These studies will provide insight into understudied mechanisms of aging and potentially identify new targets to combat age-associated cognitive decline. I have collected a significant amount of preliminary data and possess the tools and skills required to pursue these aims. The institutional support and resources of the University of Pennsylvania, along with the expertise and mentorship of my sponsors, Dr. Virginia Lee, internationally renowned for her research in neurodegeneration, and Dr. Christoph Thaiss, a microbiome expert, maximize my chances at success. The training I will receive during this proposal will position me to be a future leader in aging and neurodegeneration as a physician-scientist.

NIH Research Projects · FY 2025 · 2023-04

ABSTRACT Astrocytes are critical components of synapses, providing essential metabolic support, regulating synapse formation, and modulating synaptic firing. The mechanisms by which astrocytes support synaptic function are largely unknown. In response to neuronal activity, astrocytes produce local calcium spikes that promote the release of neuroactive transmitters, such as ATP. ATP release from astrocytes is essential for sustaining neuronal firing, synapse maturation, and plasticity. Prior work in monoculture astrocytes revealed that lysosomes undergo robust exocytosis and release ATP in response to glutamatergic stimulation. How this process of lysosome exocytosis occurs within astrocytes that are synaptically connected with neurons remains unknown. Even less is known regarding the cytoskeletal organization that impacts the trafficking and transport of lysosomes in astrocyte branches. However, perturbances in the cytoskeletal organization of astrocytes impairs calcium responses and reduces ATP release, leading to impairments in neurodevelopment and early onset neurodegeneration. These data suggest that the regulation of lysosome trafficking is essential in maintaining astrocyte-neuron interactions. My preliminary data suggests that neuronal firing restricts the mobility of lysosomes in astrocytes and may promote lysosome exocytosis in astrocytes in a non- cell autonomous manner. Specifically, I find that in developing astrocytes, lysosomes display short-range bidirectional motility that is dampened by synaptic activity. However, in mature astrocyte branches, lysosomes are largely immobile, and their motility is insensitive to synaptic activity. Pharmacological perturbations to the cytoskeleton revealed that this anchoring of lysosomes in astrocytes is likely due to a switch from microtubules to actin filaments. Based on these data, I hypothesize that as astrocytes mature, lysosomes accumulate in perisynaptic compartments due to a switch from microtubule to actin cytoskeletal tracks. This localization may position lysosomes to undergo activity-dependent secretion, releasing contents that support the maturation of synaptic compartments. To test this hypothesis, I will (Aim 1) define mechanisms of lysosome positioning in astrocytic branches and (Aim 2) determine the impact of synaptic activity on lysosome exocytosis in astrocytes. I will use a robust system to coculture neurons and astrocytes to investigate the dynamics of this process with high spatiotemporal resolution using cutting edge methodology in live cell imaging. Combined, these aims will define lysosomes in astrocytes as signaling organelles that play crucial roles in synaptic maturation. Knowledge gained from this study will elucidate new molecular pathways for how astrocytes are key components of the tripartite synapse and enlighten our understanding of how astrocyte dysfunction may contribute to synaptic deficiencies in neurodevelopmental and neurodegenerative disorders.

Fonds de recherche du Québec – Santé · FY 2023-2024 · 2023-04

Volet: Formation postdoctorale - Citoyens canadiens et résidents permanents; Domaine: Maladies infectieuses et immunitaires; Objet: Infections parasitaires; Objet: Réactions immunitaires; Application: Santé; Application: Fondements biomédicaux de la santé humaine; Mots-clés: CRYPTOSPORIDIUM, PARASITE IMMUNOLOGY, INNATE IMMUNITY, MOUSE MODELS, INTERFERON GAMMA, INTESTINAL EPITHELIAL CELLS

Fonds de recherche du Québec – Santé · FY 2023-2024 · 2023-04

Volet: Formation postdoctorale - Citoyens canadiens et résidents permanents; Domaine: Maladies infectieuses et immunitaires; Objet: Infections virales; Objet: Réactions immunitaires; Application: Santé; Application: Fondements biomédicaux de la santé humaine; Mots-clés: MOUSE MODELS, TYPE 2 IMMUNE RESPONSES, LUNG REPAIR, ASTHMA , INFLUENZA VIRUS, TUFT CELLS

NIH Research Projects · FY 2026 · 2023-04

Abstract ________________________________________________________________________________________ The current FDA-approved responsive neurostimulation (RNS) device offers a promising alternative to surgery for more than 600,000 Americans with intractable epilepsy who are not candidates for resective surgery. Unfortunately, there are no validated biomarkers to predict seizure outcomes before these devices are placed, and approximately 1/3 of patients do not benefit from RNS long-term. There is a critical need to develop biomarkers based upon clinical and electrophysiological data to determine the most effective therapy for patients with medication-resistant seizures, and to bring quantitative rigor to clinical decision making. The long-term goal of this proposal is to discover and validate a predictive biomarker signature for RNS response that can be used in epilepsy surgery decision making and broadly adopted. To achieve this goal, our overall objective is to develop this prognostic biomarker signature using machine learning applied to a carefully selected set of features and models calculated from intracranial EEG (IEEG) obtained during presurgical evaluation that incorporates qualitative clinical features. We will collaborate across centers and with industry partners via a novel federated approach, whereby each clinical site will post data in a common format to their own, private, cloud-based data store, which will be accessible to analysis pipelines run centrally from our cloud-based platform. Our central hypothesis is that biomarker signatures derived from multimodal data collected during evaluation prior to device implant can be used to predict patient response to RNS therapy. Our preliminary data, analyzing 10 RNS patients each from UCSF, NYU and UPenn, demonstrates our ability to perform the proposed research. In the R61 Phase, we will test this hypothesis retrospectively in 125 patients who underwent IEEG prior to RNS device placement at the UPenn, UCSF and NYU epilepsy centers. Our specific aims for this phase are: 1) To build a federated processing pipeline for biomarker discovery using presurgical evaluation neuroimaging, IEEG and clinical metadata, 2) To identify a predictive biomarker signature from this data. Our federated analysis framework will enable us to: (a) accelerate biomarker discovery across multiple sites and industry partners, (b) satisfy patient and industry limitations on sharing proprietary data, (c) provide a practical framework for rapid adoption across clinical centers worldwide. In the R33 phase, the biomarker signature will be validated in 100 additional patients followed longitudinally at 9 clinical sites. The proposed research is innovative because it represents a substantive departure from the status quo by rigorously analyzing multimodal patient data to predict response to RNS and guide decisions on device implantation. The proposed research is significant because it has the potential to dramatically improve the success rate of RNS for epilepsy through better patient selection. This study also puts into place a novel, versatile, federated data mining infrastructure for multi-center and industry collaboration in translational neuroscience.

NIH Research Projects · FY 2025 · 2023-04

Abstract ________________________________________________________________________________________ The current FDA-approved responsive neurostimulation (RNS) device offers a promising alternative to surgery for more than 600,000 Americans with intractable epilepsy who are not candidates for resective surgery. Unfortunately, there are no validated biomarkers to predict seizure outcomes before these devices are placed, and approximately 1/3 of patients do not benefit from RNS long-term. There is a critical need to develop biomarkers based upon clinical and electrophysiological data to determine the most effective therapy for patients with medication-resistant seizures, and to bring quantitative rigor to clinical decision making. The long-term goal of this proposal is to discover and validate a predictive biomarker signature for RNS response that can be used in epilepsy surgery decision making and broadly adopted. To achieve this goal, our overall objective is to develop this prognostic biomarker signature using machine learning applied to a carefully selected set of features and models calculated from intracranial EEG (IEEG) obtained during presurgical evaluation that incorporates qualitative clinical features. We will collaborate across centers and with industry partners via a novel federated approach, whereby each clinical site will post data in a common format to their own, private, cloud-based data store, which will be accessible to analysis pipelines run centrally from our cloud-based platform. Our central hypothesis is that biomarker signatures derived from multimodal data collected during evaluation prior to device implant can be used to predict patient response to RNS therapy. Our preliminary data, analyzing 10 RNS patients each from UCSF, NYU and UPenn, demonstrates our ability to perform the proposed research. In the R61 Phase, we will test this hypothesis retrospectively in 125 patients who underwent IEEG prior to RNS device placement at the UPenn, UCSF and NYU epilepsy centers. Our specific aims for this phase are: 1) To build a federated processing pipeline for biomarker discovery using presurgical evaluation neuroimaging, IEEG and clinical metadata, 2) To identify a predictive biomarker signature from this data. Our federated analysis framework will enable us to: (a) accelerate biomarker discovery across multiple sites and industry partners, (b) satisfy patient and industry limitations on sharing proprietary data, (c) provide a practical framework for rapid adoption across clinical centers worldwide. In the R33 phase, the biomarker signature will be validated in 100 additional patients followed longitudinally at 9 clinical sites. The proposed research is innovative because it represents a substantive departure from the status quo by rigorously analyzing multimodal patient data to predict response to RNS and guide decisions on device implantation. The proposed research is significant because it has the potential to dramatically improve the success rate of RNS for epilepsy through better patient selection. This study also puts into place a novel, versatile, federated data mining infrastructure for multi-center and industry collaboration in translational neuroscience.

NIH Research Projects · FY 2025 · 2023-03

Acute respiratory distress syndrome (ARDS) is a severe, rapidly progressing lung condition characterized by hypoxic respiratory failure that requires intensive supportive care during hospitalization, with nearly 40% of patients requiring invasive mechanical ventilation. This life-threatening syndrome can be precipitated by infectious processes or trauma with the largest risk among patients with sepsis, pneumonia, and shock. ARDS affects over 200,000 adults in the U.S. annually, and accounts for 10% of intensive care unit (ICU) admissions. The average hospital mortality rate among patients with ARDS has been estimated between 41-58%, with rates ranging from 17-73% across hospitals. Despite advances in our understanding of its pathophysiology, mortality has remained steady in recent years with few studies seeking to understand the variation in hospital outcomes. Our study focuses on differences in nursing resources, an important hospital characteristic that has not been adequately addressed in the ARDS literature. With no known cure, the treatment of ARDS is largely supportive, with respiratory management being a key focus as well as maintaining adequate fluid balance. These responsibilities, in addition to the extensive care coordination that ARDS patients require, largely belong to registered nurses. Our primary objective is to examine how variations in nursing resources are associated with differences in ARDS outcomes, including mortality and readmissions. We employ tapered multivariate matching, a novel approach which allows us to carefully control for differences in clinical risk of patients to clearly identify the basis of ARDS outcome differences. A second objective is to identify the nursing and hospital characteristics of “high performing” hospitals where variations in ARDS outcomes between patients were minimized. After identifying high and low performing hospitals, we will explore the open-ended responses of thousands of nurses who shared their perspectives of supports and barriers to care delivery in hospital settings. By examining patient, community, nurse and system-level factors, we seek to uncover whether there are combinations of nursing resources, organizational supports and care processes that are most effective in reducing ARDS outcome differences. If our study hypotheses are supported and we can identify characteristics of high performers, it will strengthen the evidence regarding the link between nursing resources and high-quality outcomes for seriously ill patients. Our proposal is well-aligned with multiple goals of NINR, including creating structures that ensure high quality outcomes, using lessons learned about nursing factors that influence unwanted variation. Collectively, the results of this study will provide the foundation for the next phase of our research, which includes the development of innovative models of care delivery that integrate evidence-based nursing resources that are associated with high quality outcomes for hospitalized patients with serious illness.

NIH Research Projects · FY 2025 · 2023-03

PROJECT SUMMARY Alzheimer’s disease (AD) is a leading cause of death in developed countries. Over 50 genetic loci have been associated with late-onset AD risk, yet we still do not fully understand the disease pathogenesis and have failed to find successful solutions for prevention or treatment of dementia or cognitive decline. AD is influenced by genetic and environmental (social, built, and physical) factors. Understanding the interplay between these genetic and non-genetic factors is crucial to address the underlying biology of the disease. Many studies have focused on identifying either genetic causes or modifiable risk factors associated with AD, and most gene- environment studies of AD have been restricted to single-gene x single-environmental factor studies (primarily focusing on the gene APOE). Few studies have addressed how upstream factors like socioeconomic status and ambient air pollution interact with risk across many genetic locations (polygenic) to influence gene expression and proteomic changes that lead to AD and related dementias. The specific aims of this study are to 1. (F99 phase) determine social, built, and physical environmental variables associated with dementia risk and/or cognitive decline, independent of and modified by polygenic risk and 2. (K00 phase) identify transcriptomic and proteomic signatures that mediate the effect of environmental exposure on dementia/cognitive decline. During my dissertation phase, I will train in polygenic risk score computation, predictive analysis, mixed-effect modeling, and machine learning to characterize the effects of genetic and environmental determinants on AD and related dementias. I will employ polygenic risk score methods that have been designed to improve predictive accuracy in multi-ethnic populations. As a post-doctoral fellow, I will expand my training to multi-omic data integration and analysis to move our understanding of risk factors for AD and related dementias beyond studies of association to an understanding of causal pathways and the biological mediators of environmental exposures. This research will leverage the Multi-Ethnic Study of Atherosclerosis parent and ancillary studies (MESA Neighborhood and Aging, MESA MIND, and MESA Air), a longitudinal cohort unprecedented in its scope of social determinants of health along with dementia adjudication and multi-omic data. This fellowship application aligns with the NIA Strategic Directions for Research Goal D-1 “to determine how genetic, molecular, cellular, and social/environmental factors interact for brain health and neurodegeneration.” As a result of this work, we will have identified upstream (policy-level) and downstream (biological mechanisms) points of intervention and prevention. In addition, the research and career development provided by this award will help me launch my career as an independent investigator of AD prediction and prevention.

NIH Research Projects · FY 2026 · 2023-03

Project Summary Acting adaptively requires quickly picking up on structure in our environment (e.g., the layout of a city you are visiting for the first time) and storing the acquired knowledge for effective future use (efficient navigation on subsequent visits). Dominant theories of the hippocampus have focused on its ability to encode individual snapshots of experience, but we and others have found evidence that it is also crucial for finding structure across experiences (understanding the relationship between different views of the same distant building). The mechanisms of this essential form of learning have not been established. We have developed a neural network model of the hippocampus instantiating the theory that one of its subfields can quickly encode structure using distributed representations, a powerful form of representation in which populations of neurons become responsive to multiple related features of the environment. The first aim of this project is to test predictions of this model using high resolution functional magnetic resonance imaging (fMRI) in paradigms requiring integration of information across experiences. The results will clarify fundamental mechanisms of how we learn novel structure, adjudicating between existing models of this process, and informing further model development. There are also competing theories as to the eventual fate of new hippocampal representations. One view posits that during sleep, the hippocampus replays recent information to build longer-term distributed representations in neocortex. Another view claims that memories are directly and independently formed and consolidated within the hippocampus and neocortex. The second aim of this project is to test between these theories. We will assess changes in hippocampal and cortical representations over time by re-scanning participants and tracking changes in memory at a one-week delay. Any observed changes in the brain and behavior across time, however, may be due to generic effects of time or to active processing during sleep. The third aim is thus to assess the specific causal contributions of sleep to the consolidation of structured information. We will use real-time sleep electroencephalography (EEG) to detect the peaks of slow oscillations, when endogenous replay is known to occur, and play sound cues to bias memory reactivation. We will also expand our neural network model to examine how offline hippocampal replay of recent regularities can shape distributed representations in neocortex, providing a mechanistic account of offline consolidation of structured information. We expect that this work will clarify the anatomical substrates and, critically, the nature of the representations that support encoding and consolidation of novel structure in the environment. Having a robust, neurally grounded model of these processes will help connect research in this area across laboratories and provide a framework for evaluating what goes wrong in mental health disorders like depression and schizophrenia that involve profound disturbances in learning and sleep.

NIH Research Projects · FY 2026 · 2023-03

Project summary For fitness `serial phenotypes mechanistic single conditions. synapse Using relative project cytolysis, stimulation arginosuccinate transcriptional CAR despite provide mechanisms show tumor cells aspartate serial an distinctive understand single affected immunotherapy cellular immunotherapies, clinical outcomes depend on he proliferative potency and metabolic of the therapeutic product. For their most successful indications, CAR T cells are effective killers,' each T cell recognizing and eliminating many target cells. Certain metabolic ( e.g. glycolytic capacity) are associated with T cell cytotoxic potential. However, the underpinnings for these relationships are under-defined and have been studied using a ex-vivo expansion process followed by a standard cytotoxicity assay in nutrient-rich Two critical events define the efficiency of T cell serial killing: migration and immune formation/cytolysis. Importantly, each event is influenced by the local metabolic milieu. a specialized CAR T cell conditioning regimen, the goal of this research to is determine the energy cost of migration versus cytolysis using innovative eSIGHT RTCA technology. Our will reveal how the spare respiratory capacity (SRC), supports CAR T cell migration and/or founded on the hypothesis that cells that can replenish their SRC in repetitive antigen models, are more efficient serial killers. We also use multi-omic approaches to identify synthase 1 (ASS1), a gene distinguishable at the metabolic (Seahorse), (RNAseq), epigenetic l evel (ATAC seq), and functional (tumor clearance in vivo) in T cells. Supporting the premise of our work, we show that ASS1 supports high SRC levels frequent antigen encounter in repetitive stimulation models in vitro. In parallel work, we data t hat reductive glutamine metabolism is enhanced in 28  CARTs, suggesting for why 28  CARTs outperform BB  CARTs in some hypoxic tumor models. We also that expressing i soforms of the GOT family of amino transaminases enhance CAR T cell anti- function. Given the prior link connecting reductive glutamine metabolism and GOT1 in Jurkat we hypothesize a fundamental link, involving reductive glutamine metabolism, GOT1-mediated replenishment, and fumarate production via ASS1, to support mitochondrial function and killing in CAR T cells. Finally, we will test the hypothesis that fructose can be repurposed as important fuel for CD123 CAR T cell cytotoxic function in acute myeloid leukemia (AML). AML is in that fructose levels can increase from 20  M up to 8mM in the bone marrow. To better the i mmune-suppressive microenvironment in AML, we will expand on our existing cell RNA sequencing data to i dentify the source of ructose-producing cells in the AML bone marrow. Our findings will have translational relevance in improving cellular for advanced cancers. t f

NIH Research Projects · FY 2026 · 2023-03

Project Summary For HIV cure approaches to be widely implemented, they will need to be safe, affordable and highly effective. The development strategies that allow therapeutic agents to be infused into people living with HIV (PLWH) rather than being manufactured ex vivo may represent an important step to reaching this goal. In this application, the investigators merged their expertise in mRNA lipid nanoparticles (mRNA-LNPs) and HIV CAR technology to propose to develop injectable agents that will target and remove the latent reservoir. A key advantage of this approach is that we can target tissues and cells such as the reproductive track or T follicular cells where CTLs are either excluded or have diminished activity. In Aim 1, we will optimize the composition of these mRNA-LNPs performing in vitro studies. Once lead compounds are identified, we will test these in humanized mouse for in vivo activity. Finally, using a state of the art non-human primate model we will test the ability of mRNA-LNP complexes to reduce the viral reservoir.

NIH Research Projects · FY 2026 · 2023-03

PROJECT SUMMARY/ABSTRACT Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a novel coronavirus identified at the end of 2019, has led to the current global pandemic. The SARS-CoV-2 virus belongs to the subgenus sarbecovirus of the genus betacoronavirus, the genus from which two SARS-CoV-2 closely related viruses (SARS-CoV-1 and MERS-CoV) have crossed the species barrier to humans in the past 17 years. These coronaviruses have crossed into humans through zoonotic transmissions from animal reservoirs highlighting a potential threat for future spillovers. Therefore, development of intervention strategies that can mitigate outbreaks of future coronaviruses is critical. To prepare for future coronavirus (CoV) pandemics, it is desirable to generate vaccines capable of eliciting neutralizing antibody (nAb) responses against diverse CoVs. Currently there are two major challenges to develop prophylactic vaccine-based strategies against coronaviruses; 1) identification of CoV spike broadly neutralizing antibody (bnAb) sites for vaccine targeting; and 2) the development of vaccine strategies that can reproducibly induce durable and protective bnAb responses against a broad range of coronaviruses. In this R01 grant application, we will squarely address these knowledge gaps by employing a bnAb epitope based rational vaccine design approach to develop immunogens and immunization strategies that can induce coronavirus protective bnAb responses by vaccination. The project consists of 3 aims: Aim #1 will design novel spike S2 stem bnAb site targeting vaccine immunogens using a rational reverse vaccine engineering approach. Using CoV spike S2 stem helix bnAbs and their UCAs we will design, CoV S2 stem peptide-based nanoparticles, rationally engineered S2 bnAb germline-targeting S-protein trimer immunogens and their multimerized nanoparticle versions that can efficiently in vivo activate B cell precursors targeting the S2 stem region conserved across β-CoV spikes. Aim #2 will iteratively evaluate and optimize prime boost immunization strategies in appropriate pre-clinical animal models to develop vaccine protocols that can reproducibly induce durable and protective bnAb responses against diverse β-CoVs. We will assess the in vivo protective efficacy of the vaccine- induced bnAb responses in appropriate virus challenge models. Aim #3 will generate spike S2 stem helix bnAb based “super antibodies” against β-coronaviruses by utilizing rational antibody engineering approaches. The overall goal of this R01 grant proposal is to rationally design novel vaccine immunogen candidates, develop robust vaccination strategies that can induce durable protective bnAb responses against a broad range of β- coronaviruses and develop “super antibody” molecules promising for broad coronaviruses intervention strategies to mitigate SARS-CoV-2 variants of concern and emerging coronaviruses as part of pandemic preparedness.

NIH Research Projects · FY 2025 · 2023-03

In genome-wide association studies (GWAS), the lack of data sources for non-European populations results in polygenic risk prediction models that have low transferability across populations. This problem exists in many epidemiologic studies and impacts public health much more broadly. Furthermore, the rapid identification of novel risk factors for complex diseases brings increasing opportunities to develop comprehensive risk prediction models to combine information on genetic and other types of risk factors. The scientific goal of this proposal is to provide enhanced disease risk prediction tools for the general population integrating genetic and other data sources across disparate studies. The specific aims include: (Aim 1) develop enhanced genetic risk prediction models combining GWAS summary statistics with external genomic information, and extend the method to jointly analyze multiple related diseases; (Aim 2) develop a flexible statistical framework that can integrate population-specific, summary-level risk parameter estimates for genetic markers and a variety of other risk factors to further improve multi-population disease risk prediction; and (Aim 3) develop and validate the risk prediction models for leading causes of mortality and other complex traits/diseases, distribute user-friendly software and tools, and investigate their clinical utilization through applications in precision medicine. Dr. Jin’s long-term goal is to establish an interdisciplinary research program that combines statistical genetics, functional genomics and epidemiology, and develop novel statistical and computational methodologies for integrating multi-source health-related data to improve healthcare. This award will facilitate the necessary training required for Jin’s successful transition to independence, including support from the mentoring and advisory committee, advanced coursework, and active participation in collaborations, workshops, and scientific conferences. Jin will gain expertise that complements her current skill set through working closely with a highly multidisciplinary mentoring team with a combined expertise in statistical genetics, genomics, epidemiology, and precision medicine. Johns Hopkins University provides young researchers with an active and engaging intellectual environment, with tremendous opportunities for interdisciplinary collaborations and career development services such as teaching institute, grant writing workshops and interview skills practice. The research supported by this grant will generate enhanced, user-friendly disease risk prediction tools for the general population, as well as data integration methodologies that can be widely implemented by the community to accelerate future research in disease risk prediction and prevention. Upon completing this award, Jin will gain a critical set of skills in research, mentoring, communication and management that will ensure her success in establishing an independent research program and pursuing broader career goals.

NIH Research Projects · FY 2026 · 2023-03

PROJECT SUMMARY Structural plasticity of neuronal connections is crucial for the wiring and rewiring of neuronal circuits in response to experience during development and in adulthood. Defects in plasticity of neuronal connectivity underlie, exacerbate, or contribute to the pathogenesis of many neurodevelopmental, neuropsychiatric, and neurological disorders, including age-related decline. However, our understanding of the molecular control of structural plasticity across the lifespan and in different neuronal contexts is far from complete, in part due to the lack of an experimentally tractable system to study this complex process at this resolution. The well-defined nervous system of the nematode Caenorhabditis elegans is an ideal system to identify the genes and molecular mechanisms involved with direct comparison of multiple life stages. We propose to exploit a robust model of structural plasticity we discovered in C. elegans to identify and compare the genetic and molecular regulation of experience-dependent structural plasticity across development, adulthood, and aging at single neuron resolution. In Aim #1, we will use the power of C. elegans genetics to screen 20 conserved cell adhesion, scaffolding, and signaling molecules for roles in experience-dependent structural plasticity during both development and in early adulthood. Aim #2 will comprehensively characterize the impact of aging on a neuron, circuit, and behavior in both sexes, and directly measure any changes in the capacity for structural plasticity across adulthood and aging by inducing and inhibiting structural plasticity with opto- and chemo-genetic tools. We will identify the mechanisms that maintain or degrade the capacity for structural plasticity with age, providing novel characterization and understanding of structural plasticity across the lifespan. In Aim #3, we will leverage the model of experience-dependent structural plasticity in C. elegans to gain mechanistic insights into the role of multiple conserved and disease-associated cell adhesion molecules in the regulation of structural plasticity. Using a combination of transgenic rescue experiments and insertion of tags/tools into the endogenous CAM genes, we will define the cellular, molecular, and temporal mechanisms by which CAMs contribute to plasticity. The proposed experiments will directly contribute to our understanding of the mechanisms and conserved genes that regulate experience-dependent structural plasticity. thereby informing its role in brain health, disease, and aging, while potentially identifying novel molecular targets for therapeutic intervention.

NIH Research Projects · FY 2025 · 2023-03

PROJECT SUMMARY Soft tissue sarcomas (STSs) are diverse mesenchymal tumors that occur within connective tissues such as muscle, fat, and cartilage. STS is a highly heterogeneous malignancy with over 70 genetic and histological subtypes. In addition, high rates of recurrence and lack of effective treatment for patients emphasize the need to identify novel therapeutic vulnerabilities common to multiple STS subtypes. Metabolically, STS tumors consistently exhibit high rates of glucose uptake and robust hypoxia gene signatures in patients. Therefore, we focused on fructose-1,6-bisphosphatase (FBP), a rate-limiting enzyme in gluconeogenesis, to combat the typical glycolytic dependence of STS. In previous studies, we showed that FBP2, the muscle-specific isoform of FBP, is severely downregulated in several prevalent STS subtypes. Surprisingly, FBP2 re-expression in STS in vivo opposes sarcoma progression through two spatially distinct mechanisms in the cytoplasm and the nucleus. FBP2 restoration decreases cytosolic glycolytic flux while nuclear FBP2 directly binds to c-Myc, a transcriptional regulator of growth and metabolism. This interaction attenuates c-Myc-dependent expression of TFAM, a key regulator of mitochondrial biogenesis, thereby inhibiting oxidative phosphorylation. These mechanisms, at least in part, contribute to the ability of re-expressed FBP2 to suppress tumor growth in murine STS models. However, my preliminary data suggest that nuclear FBP2 may also directly regulate other c-Myc cell cycle target genes CDK4 and AURKA to contribute to STS suppression. Moreover, how FBP2 regulates c-Myc and the sites of FBP2/c-Myc binding are not known. Recent studies suggest that FBP2 oligomerization and conformation may also play an important role in FBP2's nuclear-to-cytosolic shuttling, and reveal new binding sites for other proteins in the nucleus like c-Myc. Therefore, I hypothesize that the exposed N-terminal regions of tetrameric FBP2 complexes bind directly to c-Myc, contributing to STS suppression by inhibiting both TFAM and cell cycle regulators. In Aim 1, I will map the sites of interaction between FBP2 and c-Myc and determine whether the tetrameric state of FBP2 is necessary for binding. In Aim 2, I will explore the functional outcomes of the FBP2/c-Myc interaction in sarcoma, including the regulation of cell cycle genes AURKA and CDK4. Together, this proposal will provide more insight into the recently discovered nuclear functions of FBP2 to create novel therapies for a diverse set of genetically heterogeneous sarcomas.

NIH Research Projects · FY 2026 · 2023-03

Project Summary. The 5-year K01 Mentored Research Scientist proposal will employ brain, neurocognitive, and computational tools (e.g., deep learning) to understand the impact of opioid-use disorder (OUD) and common co-occurring issues on executive function and clinical outcomes. There have been record numbers of fatal and non-fatal overdoses (ODs) associated with opioids (and other drugs) in the past 12-months. Improving classification and predictive capabilities to enhance treatment and prevent relapse is of the upmost importance. Deficits in neurocognition often are associated with poor treatment outcomes (e.g., more drug use, medication non-adherence), yet co-occurring issues associated with OUD (e.g., depression, anxiety, physical/sexual abuse, neglect) make it difficult to parse which contributing factors lead to worse executive function (EF) and poorer treatment outcomes. Novel brain, neurocognitive, and computational tools are needed to help determine these differences, in order to lay the foundation for better treatments. This need has shaped both the training plan and the associated research project in a 5-year K01 Mentored Research Scientist proposal, building on Dr. Regier's prior preclinical and clinical addiction neuroscience experience (focused mostly on cocaine-use disorders, cue- reactivity, subcortical networks, prior adversity, and univariate imaging (fMRI) techniques). Mentor Dr. Childress will guide career development, and will coordinate training and individualized mentoring from a group of top-tier experts centered around 4 areas: Training Aim 1) opioid use disorder (OUD), its treatments, and comorbidities (Dr. Kampman, mentor), Training Aim 2) neurocognition (Dr. Gur, mentor), the impact of mental health, and its relationship to clinical outcomes, Training Aim 3) functional near-infrared spectroscopy (fNIRS), a mobile, non- invasive cortical brain imaging technology (Dr. Ayaz, Mentor), and Training Aim 4) advanced computational techniques (deep learning; Drs. Ayaz and Curtin) in outcome prediction. The training aims will be enabled by the Research Project Aims. Research Aim 1 (Conventional Approach): Examine differences between OUD vs HC on EF scores and PFC activity during EF tasks (Aim 1a); Using step-wise regression, examine relationship of brain (PFC) data and/or co-occurring variables with EF (Aim 1b) and clinical outcomes (Aim 1c). Research Aim 2 (Deep Learning): Examine whether multi-task, spatiotemporal brain data can distinguish OUD from HCs (Aim 2a). Within the OUD population, examine whether multi-task, spatiotemporal brain data can classify better or worse EF (Aim 2b) and/or drug-use outcome groups (Aim 2c). Exploratory: Add co-occurring variables into the deep learning pipeline to determine whether they improve classification of either EF and/or drug-use outcomes. The proposed K01 will facilitate Dr. Regier's transition to an independent research career focused on brain- behavioral vulnerabilities in relapse and recovery. It will also provide much-needed knowledge about neurocognition and its neural correlates and co-occurring contributors to relapse risk in those struggling toward recovery.

NIH Research Projects · FY 2026 · 2023-03

SUMMARY – mVACS PROGRAM Clostridioides difficile is the most reported nosocomial pathogen in the United States and a major public health threat worldwide. Challenges in treating infections with conventional antibiotics and increasing rates of recurrent infection underscore the need for new interventions. To date, no vaccine has proven to be effective at clearing C. difficile from infected individuals. The mVACS program—"mRNA Vaccines for C. difficile Suppression”—is tightly focused on the goal of designing and implementing improved vaccines to mitigate or eliminate C. difficile infection (CDI). For this we will employ modified mRNA vaccine technology, which has been pioneered so successfully by team member Dr. Drew Weissman and his collaborators at BioNTech to immunize against SARS- CoV-2. Already Drs. Weissman, Alameh, and Zackular have established a collaboration with BioNTech to develop an mRNA targeting C. difficile toxins and other antigens and shown their lead formulation to be highly protective in mice challenged with a lethal dose of C. difficile. However, C. difficile is not fully cleared from the mice, and there is mild transient pathogenesis, so there is more to be done. The team is moving forward with this anti-toxin vaccine, but improvements in design are necessary for optimal efficacy. The mVACS team is a highly skilled and synergistic group dedicated to developing modified mRNAs to oppose C. difficile infection and pathogenesis. The program consists of three projects and three cores. Project 1 (Vaccine Development) (Project Leads: Alameh and Weissman) will test new mRNAs against multiple C. difficile targets, as well as mixtures of mRNAs and novel nanoparticle/lipid formulations. Project 2 (Antigen Discovery) (Project Lead: Zackular) will take advantage of advanced analysis of C. difficile microbiology and ecology of infection to produce a series of novel vaccine targets. Project 3 (Immunology) (Project Lead: Abt) will quantify mucosal adaptive immune responses against C. difficile in humans and mouse systems, identifying gaps and correlates of efficacy. Projects 2 (Antigen Discovery) and Project 3 (Immunology) will flow new data to Project 1 (Vaccine Development) to optimize vaccine design. The Projects will be complemented by three Cores: Core A (Administrative Core) (Core Leads: Bushman and Weissman), Core B (Genomics Core) (Core Leads: Bittinger, Bushman, and Moustafa) and Core C (Clinical Core) (Core Leads: Kelly and Conrad). Together with our industry partner BioNTech, we are highly optimistic that we can advance effective new vaccine designs to suppress C. difficile.

NIH Research Projects · FY 2026 · 2023-03

Project Summary / Abstract A total of 18.2 million people in the U.S. currently live with type 2 diabetes and non-alcoholic fatty liver disease (NAFLD). Susceptibility to cardiometabolic diseases is highly variable, and currently no FDA-approved drugs exist to treat NAFLD. Recent work suggests that cardiometabolic diseases share several genetic factors, and our long-term goal is to reveal the complex interplay between genomic and non-genomic risk factors in the development of disease to improve risk prediction and identify drug targets for repurposing to treat NAFLD. In our first aim we will apply causal single and multiple causal mediation analysis in the UK Biobank to identify intermediate or moderating endophenotypes that can serve as potential intervention targets for type 2 diabetes and NAFLD. We provide a framework for precision phenotyping and quantify how much individual-level genetic burden for disease can be reduced if one would intervene on intermediary endophenotypes. It may ultimately enable clinicians to detect early departures from patient-specific baseline risk that, while themselves are still asymptomatic, are predictive of the subsequent onset of disease symptoms. Our second aim is to identify and validate drug targets for potential repurposing in NAFLD using genomic and real-world data. We will identify candidate drug targets using two approaches: 1) instrumental variable analysis using genetic instruments of the `druggable' genome (e.g., Mendelian Randomization analysis) and 2) a computational gene expression signature-based approach based on the knowledge of drug activity and disease pathophysiology. Predictive validity of drug efficacy for candidate drug targets will be assessed using real-world data of 9.1 million Veterans in the Veterans Health Administration healthcare system, 3.6 million patients in the Penn Medicine clinical data warehouse, and 3.5 million patients in the Vanderbilt Synthetic Derivative. Long-term therapeutic efficacy will be evaluated using emulated target trials in NAFLD patients with cirrhosis, hepatic decompensation, liver transplant, and liver cancer as the primary treatment endpoint during five years of follow-up. Short-term drug efficacy will be evaluated in healthy patients using self-controlled case series analysis with change in alanine transferase as the primary outcome. It is anticipated that our genomics- informed and pharmaco-epidemiological approach to drug repurposing will accelerate drug-discovery efforts and lead to the use of existing agents to treat NAFLD with shortened drug development times.