Stanford University

NSF Awards · FY 2024 · 2024-10

The goal of this project is to develop innovative computational methods that integrate classical and quantum algorithmic tools within the fields of statistics and operations research. The project focuses on applications involving models such as stochastic differential equations, and areas such as machine learning, and data analytics, which arise in various applied engineering and scientific disciplines. Leveraging the diverse expertise of the research team in classical and quantum algorithms, statistics, and operations research, the project will develop quantum-enhanced algorithms for decision-making under uncertainty in both single-stage and multi-stage settings, as well as quantum-accelerated multilevel Monte Carlo methods. These methods will enable, by means of substantially faster algorithms, significant advances in the design of efficient Bayesian inference and machine learning procedures. They will also benefit practitioners across various scientific domains in the physical and social sciences. The project's educational and outreach efforts include curriculum development, diversity initiatives, workshops, and partnerships with local schools. These efforts will broaden the participation of the computing community both in terms of the use of novel quantum methods but also in their application to a wide range of applications. The research plan builds on recent advancements in both quantum and classical algorithms, including contributions from the team members. By developing new quantum Monte Carlo estimators and leveraging advances in parallel randomized multilevel Monte Carlo methods, the team will systematically explore quadratic speed-ups through variable time quantum algorithms and quantum-inside-quantum Monte Carlo strategies. Specific objectives include developing quantum Monte Carlo strategies for solving Markov decision problems with a guaranteed query complexity comparable to evaluating a policy (not necessarily optimal). Another objective is the analysis of stochastic optimization problems with a zero-order oracle, achieving quadratic speed-ups compared to classical approaches. The researchers will further explore quantum accelerated algorithms for computing expectations under a wide range of equilibrium/Boltzmann distributions. Moreover, the investigators will establish upper and lower bounds that confirm the optimality of the quantum accelerated algorithms. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

The drug discovery process has a high failure rate which leads to a significant number of diseases that remain untreatable. Often, drug therapies are limited by our incomplete understanding of the biological pathway causing the disease. While some key pathways have been identified, and drug therapies have been designed to modulate them, we expect that there are large numbers of uncharacterized pathways that must be discovered for effective drug development. Biologists commonly conduct time-intensive experiments focused on well- studied proteins and thus miss novel connections between proteins and associated phenotypes. Existing computational methods often rely too much on known protein functional relationships. This reliance limits the potential for discovery of novel protein interactions and pathways that modulate understudied phenotypes. The increase in high throughput databases of protein data collected at scale allows us to overcome these biases. High-throughput datasets provide information about sequence, interaction, structure, and expression—all of which can provide useful information about proteins and their likely functional interactions. There are not adequate algorithms to combine these high-throughput data sources in a biological coherent manner, in order to predict protein interactions and pathways of biological response. Current pathway prediction algorithms use known examples to generate a fitness function that is used to predict the likelihood of a novel pathway; this approach may miss pathways that cannot be traversed with the heuristics used to define the fitness function. This project addresses these issues by (1) creating a representation method for pathways that incorporates the heterogenous data sources, specifically using attention to identify the most discriminant features, and (2) implementing reinforcement learning algorithms that balance exploration and optimization to learn trajectories in the protein network that correspond to pathway function. We will then (3) use the learned representation to identify the phenotype associated with the novel proposed pathway and identify the impact of variations of this pathway on disease. Application of this framework on the human proteome will enable better understanding of the pathways responsible for psychopathologies, thus improving the specificity of potential drug targets and the efficiency of drug development. This project will take place in the Helix Lab, advised by Dr. Russ Altman, at Stanford University, and the training plan is designed with the goal of becoming an independent researcher, developing computational methods for molecular proteomics. Dr. Altman has an excellent record of mentorship and Stanford University provides a diverse range of resources and collaborators. The Helix Lab has a strong history in both computational protein characterization and drug response research, providing access to domain experts. Beyond research, the training plan includes attending seminars and conferences, collaborations, coursework, and teaching.

NIH Research Projects · FY 2025 · 2024-09

PROJECT ABSTRACT The candidate, Neha S Joshi, MD MS, is a physician scientist and neonatal hospitalist who seeks to identify clinical benchmarks and quality markers for late preterm infants during the birth hospitalization. Dr. Joshi is seeking a K23 award to become an expert independent investigator in the identification of high value care practices for newborn care. Late preterm infants comprise of 280,000 infants born in the United States annually. Approximately 40% of these infants require NICU care, though considerable variability exists amongst institutions for their clinical management and admission location. This variability likely comes at both a financial cost, in addition to the patient-level cost of separation of the mother-infant dyad and its associated risks including breastfeeding and bonding. In order to minimize variability and optimize care for late preterm infants, Dr. Joshi is proposing the following Aims: Aim 1: Evaluate current clinical morbidities and medical intervention rates in management of late preterm infants during the birth hospitalization. Aim 2: Test the association of institutional structural variables with late preterm care outcomes all California births. Aim 3: Develop process measures/clinical benchmarks, structural measures, and outcome measures for late preterm infants. Dr. Joshi will leverage the strengths of two large research networks – the California Perinatal Quality Care Collaborative and the Better Outcomes through Research for Newborns Network – to help achieve these aims. Dr. Joshi is mentored by exceptional leaders in research networks for well newborn and NICU care, health services research, perinatal outcomes research, implementation science, and the clinical care of late preterm infants. Their directed mentorship, a robust training plan, and proposed research aims will complement her prior training in Pediatric Hospital Medicine and Clinical Research and Epidemiology. Career development activities include a training plan focused on leveraging large academic datasets for research, development of quality care indicators, advanced principles in implementation science, and scientific/grant writing and scholarship dissemination. Dr. Joshi will benefit from the world-class research and clinical environment, and renowned expertise at Stanford University. At the conclusion of this award, Dr. Joshi will be optimally positioned to establish and lead implementation efforts and quality measurement for late preterm infants and well newborn care.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Dilated Cardiomyopathy (DCM) is the leading cause of heart failure. Characterized by left ventricular dilation and impaired contractility, DCM results in pump failure and arrhythmogenesis leading directly to heart failure and sudden cardiac death. There are more than 50 genes implicated in DCM development that each produce a common DCM pathology. Induced pluripotent stem cell derived cardiomyocytes (iPSC-CMs) carrying DCM mutations display phenotypic aspects of genetic DCM, providing a powerful in vitro tool to study the cellular and molecular mechanisms of the disease. Our previous work utilized a specific patient-derived DCM mutation in iPSC-CMs and found that these cells, with a known phenotype of protein aggregation, exhibited increased Endoplasmic Reticulum (ER) stress which resulted in an activation of the Unfolded Protein Response (UPR), a compensatory and adaptive reaction to cell stress and aberrant protein folding. Further activating the UPR pharmacologically reduced ER stress in these cells and rescued cardiomyocyte contractility, indicating a direct link between the ER stress identified in this cell line and the impaired cardiac function seen in DCM. Our preliminary findings identified that Activating Transcription Factor 4 (ATF4), a stress response transcription factor, is a key mediator of the UPR upregulation that relieves the cardiomyocyte of ER stress. Endogenous ATF4 expression is upregulated during UPR activation, however its efficacy as a transcription factor remains inhibited in DCM. We have found that pharmacological bolstering of the UPR response increases ATF4 transcription factor activity and rescues cardiac contractility. The proposed research plan will investigate the UPR across several DCM gene mutations to identify how impaired proteostasis results in cardiac dysfunction, uncovering a novel phenotype in DCM which we believe will be broadly applicable to other cardiac diseases. Further, we will investigate the mechanism of ATF4 rescue of ER stress induced contractility deficits in iPSC- CMs and in mouse models of genetic DCM to reveal an new mechanism and therapeutic target for DCM.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Our overarching goal is to determine whether a newly discovered form of macromolecular organization – protein phase-separation – contributes to the age dependency of human diseases. Recently, it has been appreciated that many proteins related to age-dependent disease have the capacity to self-associate, condensing to form separate ‘phase-separated’ compartments called biomolecular condensates. In vitro, some of these protein condensates can mature over time into toxic aggregates. However, the generality of this property is unclear, as is the degree to which it may be altered for mutant proteins associated with different ages of disease onset and progression. Our proposal leverages comprehensive libraries of human disease alleles along with biochemistry, cell biology, and physiological modeling to investigate and define the contribution of protein phase separation, and aggregation, to the age dependency of human disease processes. Many human diseases involve defects in protein folding that can be amplified with age-dependent declines in protein quality control. Moreover, many disease alleles arise within intrinsically disordered regions of proteins, which often control phase separation behaviors. Yet whether disease alleles commonly create imbalances in protein phase separation and aggregation processes is unclear. Taking advantage of comprehensive libraries of mutant proteins associated with diverse human diseases, we recently investigated the phase-separation processes of more than two hundred disease-associated proteins. These data revealed a strong enrichment for phase separation properties among proteins with later ages of disease onset. In targeted follow-up experiments we also validated that disease variants in those proteins had strong effects on their phase separation and aggregation behaviors. To define the relationships between protein phase separation and the age dependency of human disease we will conduct the following experiments: 1. Define phase separation properties of proteins driving diverse human diseases; 2. Characterize aggregation and prion-like ‘seeding’ associated with human disease alleles; 3. Identify protein- autonomous and age-related systemic drivers of altered phase separation in disease. We will also investigate whether protein phase separation provides a mechanism to understand and potentially block the impact of dominant disease alleles in the context of aging. Together, our proposal will define biophysical and systemic features driving phase separation and aggregation, a critical aspect of many age-related disease pathologies.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract: There is a compelling need to develop treatments for mental deficiencies from fetal exposure to alcohol. The impairments are often lifelong and while early intervention services may help reduce some of the effects of alcohol exposure, there are no cures or adequate specific medical treatments for Fetal Alcohol Spectrum Disorders (FASD) presently available. Results from studies in humans and animal models suggest that a disruption in neuronal plasticity is the underlying mechanism responsible for the cognitive impairments caused by fetal alcohol exposure. Vinpocetine, a phosphodiesterase inhibitor, has been shown in multiple animal studies, including multiple models of FASD, to improve neuronal plasticity. Therefore, we hypothesize that vinpocetine may ameliorate the deficits observed in this condition. However, we recently found that the doses of vinpocetine that are commonly used in humans produce blood levels that are much lower than effective levels in animal models. Thus, higher doses in humans are needed to produce levels that match effective levels in animals. Further, dose-response curves are not available from the prior animal studies. Therefore, in the R61, specific aim 1 is designed to characterize the dose/plasma concentrations response curve for vinpocetine effects in several FASD animal models. Although vinpocetine is well tolerated in humans at doses that are typically used, the tolerability of the higher doses is not known. Specific aim 2 in the R61 will determine the maximum tolerated oral dose of vinpocetine in healthy adult volunteers and develop pilot data on pharmacokinetic time curve for vinpocetine effects. The data gathered in the proposed series of animal studies and the Phase I healthy human dose escalation study in the R61 portion will guide specific aim 3, which will establish a multicenter research team, develop tools for data management and research oversight, develop the experimental research design, refine a protocol including dosages for the subsequent Phase I and Phase II studies in the R33, and prepare an operations and procedures manual for the FASD human studies. In the R33, we propose Phase I and Phase II studies to assess safety and potential cognitive efficacy of doses of vinpocetine (guided by the findings of the R61 studies) in treating adolescents and adults with FASD. Therefore, specific aim 4 will assess the safety of doses of vinpocetine in adolescents, while specific aim 5 will assess the efficacy and safety of vinpocetine to enhance cognition in adolescents and adults with FASD in a Phase II study. The Phase II study will provide data to determine optimal dose, effect sizes, and best neuropsychological assessment to be used as the main outcome for a future Phase III trial.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY/ABSTRACT Disuse, denervation, and several diseases result in skeletal muscle atrophy and weakness – a major contributor to disease-related disability and death. The mechanisms underlying these processes are incompletely understood, and therapeutics are only emerging. MicroRNAs are known to regulate many important cellular processes. We discovered that in muscle developing weakness due to disuse (human) and denervation (mouse), there is a marked reduction in microRNA320. Further, bioinformatic analysis demonstrates that FoxOs – a group of transcription factors important in muscle degradation -- are potential targets of miR320. Indeed, when we disrupted miR320 in cultured muscle cells, the FoxO pathway and protein ubiquitination were upregulated. There is also evidence from others that miR320 may have roles in skeletal muscle metabolism. Given these findings, we created a muscle-specific knockout mouse (miR320mKO) to explore the role of this miRNA in controlling skeletal muscle growth and maintenance in a long- term, in vivo model. We have found that these mice develop severe muscle wasting over their first 4 months of life. This project will fully characterize the miR320mKO mice at the phenotypic level, investigate the mechanisms by which this phenotype occurs, and carry out a pilot effort at miR320 treatment in a model of mouse muscle atrophy. It promises to open up new avenues in treatment of skeletal muscle disease. Specifically, we will: 1. Characterize the phenotype of miR320mKO mice -examine muscle size and microscopy, fiber size and type, muscle contractile force in KO vs. controls; examine growth of proliferation and myotube formation of miR320mKO primary muscle cell cultures 2. Investigate the mechanisms underlying the phenotype of miR320mKO mice -dissect operant molecular signaling pathways and events using RNA sequencing; identify potential targets of miR320 by miR-eCLIP and RNA sequencing, and confirm those targets with 3’UTR luciferase reporters in C2C12 cells 3. Carry out a pilot treatment of skeletal muscle wasting with miR320 in mice -study denervated limb muscle following delivery of miR320 via electroporation vs. controls

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Alzheimer's disease and related dementias (AD/ADRD) rank prominently among age-associated neurodegenerative disorders, with Parkinson’s disease trailing as the second most common. Contemporary studies on AD and Mild Cognitive Impairment (MCI) have unveiled cognitive decline indicators mirrored in nuances within gait and hand movements. These indications often emerge long before AD or MCI diagnoses are confirmed. Consistently, research has correlated slowed gait with cognitive deterioration, elevated brain amyloid levels, and an augmented AD risk. However, the interplay between systems influencing both cognition and movement has largely been explored in separate studies. The depth of understanding around the cognitive efforts required for gait initiation or motor planning remains scant. Though dementia screening traditionally hinges on comprehensive neuropsychological evaluations and neuroimaging biomarker studies, gait and movement assessment offers a more direct approach. Crucially, motor features remain unaffected by language, educational background, or cognitive capabilities, positioning them as unbiased and consistent evaluative instruments. For example, the Short Physical Performance Battery (SPPB) tests can be easily conducted at home and monitored, even using smartphone applications. In this project, we chart a course to harness cutting-edge AI and computer vision (CV) tools to aid in distinguishing diverse dementia and MCI subtypes, such as AD-related MCI versus MCI with PD pathologies. Our approach integrates multi-modal brain imaging with gait and movement data from videos, aiming to extract nuanced markers for phenotyping (pre)clinical AD. These markers can then serve as precise digital trackers for both the progression and distinction of age-related degenerative disorders. Ultimately, we aspire to enhance the understanding of the intricate links between gait, movement, and cognition in aging and AD/ADRD scenarios.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY Pulmonary neuroendocrine cells (PNECs) are sensory epithelial cells that signal to the brain through sensory neurons and locally through neuropeptides and neurotransmitters. We used scRNA-seq to comprehensively profile and analyze mouse and human PNECs, which revealed over 40 PNEC neuropeptides and hormones in diverse combinations. Here, we propose to map the innervation and molecular subtypes of human pulmonary neuroendocrine cells and identify the functional subsets in human lung, beginning with an investigation of functionally distinct neuroendocrine stem cells. Using precision cut lung slice cultures to establish an injury model inducing proliferation, we will identify the location of proliferative PNECs and measure their complete transcriptomic profiles by scRNA-seq. In parallel, we will use multiplex single molecule in situ hybridization methods to localize the human PNEC neuropeptides, identify their combinations in situ, and their cognate receptors in human lung. Collectively, these studies will comprehensively characterize the cellular and molecular features of human PNECs, their stem cells and niches. PNEC expansions and ectopic pulmonary neuroendocrine cells are the distinguishing pathologic features underlying a common form of pediatric diffuse lung disease, neuroendocrine cell hyperplasia of infancy (NEHI), which is characterized by diffuse obstructive ventilatory defect. In adults, a pre-neoplastic condition called diffuse idiopathic pulmonary neuroendocrine cell hyperplasia (DIPNECH) is also associated with airway obstruction and prominent respiratory symptoms thought to be due to bioactive peptides from neuroendocrine cells. We will identify the neuropeptide and receptor expression in pathological cell niches during NE stem cell transformation in DIPNECH. This work establishes a molecular foundation for the diverse clinical presentations associated with pulmonary neuroendocrine lesions and identifies panels of neuropeptides and hormones localized to precise anatomic locations that will provide the basis for developing novel diagnostic and therapeutic approaches.

NIH Research Projects · FY 2025 · 2024-09

Enter the text here that is the new abstract information for your application. This section must be no longer than 30 lines of text. Drugs are approved by regulators because they are relatively safe and effective. However, there are typically unanswered basic science questions about the detailed mechanisms of action, the impacts of genetic and epigenetic variation, and the full range of phenotypic responses. This missing knowledge often leads to reduced efficacy and increased adverse events. My overall scientific goal is to generate more complete understanding of the mechanisms of drug response and their sources of variation, in order to enable more precise drug therapies. The last two decades has seen an explosion of data relevant to drug response. We have abundant data about human genetic variation and gene expression (and other omic) profiles that illuminate key cellular pathways in disease. Advances in protein 3D structure prediction provide useful models for most proteins, which enable proteome-wide screening for off-target drug interactions. Biobanks, electronic medical records (EMR), FDA adverse event databases and medical claims data provide clinical information and environmental exposures. My lab has a track record creating methods for analysis of all these critical data types. We focus on computational/statistical approaches that integrate data at all scales. In 2000, we created the Pharmacogenetics Knowledgebase (PharmGKB) which curates information about how human genetic variation influences variation in drug response. PharmGKB has high quality information for 100s of drugs and genes, but pharmacogenetics typically explains far less than ~50% of variation in drug response. I hypothesize that a large fraction of the remaining variation can be explained by unknown off-targets, undiscovered pathways of drug response, genetic and epigenetic differences in expression, and differences in disease physiology. Thus, my proposed work focuses on computational methods that use publicly available data to answer five driving questions: (1) What are the full set of clinical responses to drugs, alone and in combination? (2) What are the molecular targets (particularly off-targets) that are modulated by a drug? (3) What are the pathways that modulate drug response? (4) How does genetic variation in targets/pathways lead to variation in drug response? (5) How do epigenetics create variability in drug response? We will evaluate our methods with independent, held-out gold standard data sets (to establish quantitative statistical performance), and collaborate with experimental colleagues to validate key novel hypotheses. We will focus on genes and pathways that are critical in drug response.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY A decade ago, with the advent of next-generation sequencing of the human pathogen Mycoplasma genitalium, Karr et al. reported the first whole-cell model that synthesizes diverse mathematical approaches to predict a broad spectrum of biological processes. Given the recent advancements in single-cell and spatial genomics, along with the amassed cell atlas of embryogenesis, the creation of in silico models for entire mammalian embryogenesis—a long-sought goal in computational biology—seems attainable. Nevertheless, two pivotal gaps remain: (1) To capture the intricate and multi-faceted nature of embryogenesis, a cost-effective technology is requisite—one capable of profiling entire embryos at a single-cell level with high temporal resolution in 3D space. (2) To build the in silico model from the massive, high-dimensional datasets, we require powerful machine learning techniques adept at directly learning complex data-driven models and at making non-trivial predictions. In this proposal, I aim to construct the first-ever foundational in silico model of whole-embryo mouse embryogenesis. To begin, I will utilize Ultima's innovative and cost-efficient “mostly natural sequencing-by- synthesis” chemistry, combined with its ultra-high field of view wafer disc platform, to establish a large-scale 3D multi-omics cell atlas of mouse embryogenesis from E6.5 to E16.5. This will involve one-day intervals and incorporate a total of 50 million cells. The versatility of Ultima’s UG100 platform allows us to couple it with RNA metabolic labeling, CRISPR-Cas9 based lineage tracing, and multi-omics, thereby producing a comprehensive, high-definition, 3D cell atlas of mouse embryogenesis. Subsequently, I plan to devise sophisticated temporal modeling techniques for learning multi-scale, multi-modal RNA velocity vector fields. Focusing on the spatial aspect, I will devise a RNA signal-based segmentation technique for single-cell resolved spatial transcriptomics. Computer vision methods, such as the Gaussian process, will be utilized to align serial 2D slices to reconstruct the 3D embryos. To marry both temporal and spatial data dimensions, we will augment our RNA velocity vector field model to encompass data-driven PDE (partial differential equations) models. Preliminary findings suggest our model can accurately simulate the entire C. elegans embryogenesis starting from a single zygote, accounting for protein expression, cell migration, and cell fate dynamics. In parallel, to harness existing vast datasets, we'll integrate our PDE-like model with the Generative Pre-trained Transformer (as used in ChatGPT). This integration will equip our foundational model to seamlessly manage spatial, temporal, and multi-omics data. Prioritizing interpretability and predictability, we will leverage differential geometry analysis as done in my previous Dynamo framework. By merging cutting-edge technology with computational innovation, this project seeks to bridge critical gaps in our understanding of embryogenesis, enabling a first-ever in silico model of mouse embryogenesis that has the potential to revolutionize the study of developmental biology, disease mechanisms, and therapeutic interventions.

NIH Research Projects · FY 2024 · 2024-09

Chronic MSK pain is marked by a complex biologic response accompanied by physiological perturbance in cognition, sleep, and energy levels (fatigue), and is associated with impairments in physical and emotional function. Moreover, the chronic pain experience is not stable over time with intra- and inter-daily fluctuations and the presence of pain flares contributing to unpredictability, uncertainty, and ultimately greater impairment. Current gold standard self-report assessment is burdensome and falls short of providing comprehensive, reliable measures of the pain experience, typically reflecting single point-of-care assessment with inherent recall bias. A potential solution lies in the ubiquitous consumer adoption of wearable devices that provide a window into human health. Through artificial intelligence (AI) and machine learning (ML) several ground-breaking digital biosignatures of human health have been developed. This proposal overcomes the limitations of self-report by combining the precise physiological, sleep, and physical activity measures via wearable devices with AI/ML to develop and validate a monitoring digital biosignature of the individual pain experience in youth with MSK pain. We are well positioned to execute UG3/UH3 aims with: (1) a highly skilled team with scientific expertise in digital technology, AI/ML, digital endpoint development, and clinical trials, clinical expertise in chronic pain in youth, and lived experience expertise from patients, caregivers, and pain advocacy groups; (2) a centralized and standardized digital data collection, processing, and storage system, the scalable and secure My Personal Health Dashboard (MyPHD), and (3) preliminary data to support our digital biosignature development capability. For UG3 phase we will enroll 500 youth (ages 14-24) with chronic MSK pain, capturing continuous physiological (heart, respiratory), sleep, and physical (activity level, mobility, gait) activity metrics via wearables with repeated intra-daily gold standard self-report of pain experience (pain interference, pain intensity, fatigue, mood, stress, pain flares). We will Incorporate user feedback on wearable use and quality of life relevance of data captured, develop a digital biosignature of the pain experience, and prepare for the UH3 phase through outreach and collaboration with (a) individuals with lived experience, (b) individuals who experience health disparities, and (c) FDA to ensure relevance, acceptability, and recruitment of underrepresented youth coupled with scalability of the algorithm for clinical use. For UH3 phase we will enroll 400 diverse youth with chronic MSK pain capturing wearable and self-report of pain experience metrics for clinical validation of the pain experience digital biosignature and accuracy of an opportunity for enhanced wellness alert system. The successful development and validation of digital endpoints are crucial for the evolution of pain management. These endpoints can advance therapeutic development by providing robust, objective measures to monitor treatment response. Our studies, supported by this RFA, will be fundamental in seeking regulatory approval for the commercialization of the associated software or for disseminating open-source analysis packages for future clinical trials.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY AND ABSTRACT Many patients with Alzheimer’s Disease and Related Dementias (ADRD) undergo surgery. Indeed, patients with ADRD patients account for 25% of patients undergoing hip fracture surgery and 10% of patients undergoing high risk surgery. However, the extent to which these patients are at higher risk for adverse postoperative outcomes remains unknown, with existing studies finding conflicting results. Moreover, while many aspects of the management of these patients, such as the use of certain anesthetic agents and gases, have been hypothesized to improve or worsen postoperative outcomes, the evidence base in support of these hypotheses is weak. Our long-term goal is to advance the health of surgical patients with ADRD by developing individualized models of risk assessment as well as evidence-based guidelines aimed at reducing this risk. Towards this end, the overall objective of this study is to (a) identify the extent to which surgical patients with ADRD are at increased risk for adverse postoperative outcomes and (b) estimate the association between various perioperative interventions (e.g., use of anesthetic gases, choice of discharge location) and the incidence of adverse postoperative outcomes. Specifically, this study will test the central hypothesis that surgical patients with ADRD are at increased risk for adverse postoperative outcomes but that appropriate perioperative interventions can reduce this risk. To assess this hypothesis, this study will use a novel linkage between two datasets: healthcare claims data and the Multicenter Perioperative Outcomes Group (MPOG), a large, multicenter registry of surgical cases using data extracted from electronic medical records. This linkage will produce a unique dataset that unites the best aspects of both datasets: the ability to measure perioperative care and the ability to follow patients over time to assess outcomes. We will accomplish the project goals through three specific aims. First, using healthcare claims data, we will evaluate the extent to which patients with ADRD are at increased risk for worse postoperative outcomes and identify the factors that mediate this risk. Second, using the linked healthcare claims data-MPOG dataset, we will evaluate the association between perioperative interventions (e.g., use of anesthetic gases, choice of discharge location) and the incidence of adverse short-term outcomes. Finally, using the linked healthcare claims data-MPOG dataset, we will evaluate the association between perioperative interventions and the incidence of adverse medium and long-term surgical outcomes. The completion of this project will result in a comprehensive understanding of the risks facing surgical patients with ADRD as well as the interventions that can reduce this risk. In addition, it will also help identify targets for further study through randomized trials, and influence clinical guidelines and policies aimed at improving population health outcomes among surgical patients with ADRD. Ultimately, the project is in line with the agency’s priorities as its successful completion will improve shared decision-making between clinicians and patients with ADRD and improve healthcare outcomes for surgical patients with ADRD.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Aging is associated with outgrowths of mutated blood stem cells, termed clonal hematopoiesis of indeterminate potential (CHIP). The most frequent lesions in CHIP include mutations in epigenetic factors (DNMT3A, TET2, ASXL1) and loss of Y chromosome. CHIP associates with increased risk of blood cancers, like acute myeloid leukemia, but also chronic inflammatory diseases of aging such as atherosclerotic cardiovascular disease. The latter is thought to occur due to altered function of myeloid cells, such as macrophages, derived from the mutant stem cells. As Alzheimer’s disease (AD) is another disease of aging where myeloid cells, called microglia, are thought to play major role, it is reasonable to ask if CHIP associates with risk of AD. Surprisingly, epidemiological surveys revealed that those with CHIP had reduced risk of AD and AD-related neuropathologic changes in multiple well-characterized cohorts. Remarkably, ~30-90% of microglia in brain samples from people with CHIP were derived from the mutant clone, indicating replacement of wild-type microglia and the possibility of a direct effect on brain physiology by these mutant cells. While these studies robustly demonstrate that CHIP has a protective association with AD, the underlying mechanisms are unknown. The objective of the current research proposal is to understand why those with CHIP are resilient to AD. Our central hypothesis is that CHIP mutations, in at least some cases, lead to alterations of microglial gene expression programs and functional activity in a manner that promotes resilience to AD pathophysiology. Our approach is to execute three complementary aims to test the central hypothesis: 1) to identify driver gene-specific effects and interaction of CHIP with germline variation on risk of AD in large human cohorts, 2) to assess quantitative changes in mutant microglial fraction and microglial density in CHIP using archival samples from two brain banks, and 3) to assess changes in microglial cell state and gene expression associated with CHIP by performing highly-multiplexed imaging and single-cell genomic assays on human brain samples. The contribution is significant because it will uncover novel genetic and molecular properties that are altered in CHIP to prevent AD pathology. Our proposal is innovative because we will a) use data from >500,000 people, including >20,000 with AD to study the epidemiological association between CHIP and AD, b) perform the first survey of highly-multiplexed imaging of brain to understand the effect of CHIP on microglia density, regional variation, and activity in situ, and c) assemble the largest single-cell genomic dataset of brain samples from CHIP carriers to date to understand alterations in microglial cell state due to CHIP. The expected outcome of this research is to delineate the genetic and cellular mechanisms that occur in CHIP and CHIP-associated microglia to lead protection against AD. The long-term impact of this research will be to stimulate the development of novel therapies for AD that seek to mimic the biological effects of CHIP.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Heart failure, a prominent global health issue, continues to steadily rise in incidence yet has no cure. This condition is distinguished by the heart’s reduced ability to pump blood, largely driven by cardiac bioenergetic abnormalities. As cardiomyocytes rely on mitochondria for 95% of their energy supply, mitochondrial dysfunction characteristically underlies these energetic defects. NAD+ sits at the core of mitochondrial energetics, driving the progression of the tricarboxylic acid cycle in aerobic respiration. Cardiomyocyte failure is linked to NAD+ depletion in the mitochondrial matrix, impairing energy synthesis and sensitizing cells to death. Restoration of mitochondrial function through NAD+ repletion is a powerful therapeutic strategy that has shown early promise in reversing heart failure phenotypes. However, despite the pivotal role of NAD+ in mitochondrial function, a limited understanding exists of the mechanisms governing NAD+ entry into and regulation within the mitochondrial matrix. Notably, recent landmark studies have demonstrated that the mitochondrial matrix cannot independently synthesize NAD+ and have identified the essential transporter responsible for matrix NAD+ import. Yet, little is known about the molecular mechanism of this critical transport process. This project proposes to address this gap in knowledge by exploring the molecular basis of mitochondrial NAD+ import, which will elucidate how mitochondria maintain adequate NAD+ levels and how this process may become dysregulated in disease. Multidisciplinary approaches will be used to investigate fundamental unknowns about the transport mechanism, including the biochemical basis of substrate selectivity and coupling, the key protein features governing transport activity, and the architectural determinants of substrate binding and translocation. Together, this work will shed light on fundamental mechanisms of mitochondrial metabolic regulation and may provide a molecular blueprint for countering mitochondrial dysfunction in the long-term treatment of heart failure.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY/ABSTRACT Fibrosing cardiac diseases cause 25% of deaths in the United States. Fibrosis is a key pathological hallmark of nearly all cardiac diseases, including hypertensive heart disease, atrial fibrillation, and ischemic heart disease, which is caused by myocardial infarction (MI). Across these fibrosing cardiac diseases, cardiac fibroblasts are activated to deposit excessive extracellular matrix that causes organ dysfunction, including diastolic dysfunction, arrythmias, and heart failure with reduced ejection fraction. Despite the clinical burden of cardiac fibrosis, especially after MI, the molecular mechanisms driving cardiac fibroblasts to produce excessive scar tissue are unknown. Uncovering the pathophysiological mechanisms for cardiac fibrosis formation has the potential to reveal novel drug targets to reduce cardiac fibrosis and improve cardiac function. The Research Training Plan will investigate the molecular mechanisms for cardiac fibrosis formation after MI. Specifically, this project will test the hypothesis that thinning of the ventricle wall after MI increases wall stress to activate mechanotransduction pathways in cardiac fibroblasts to produce scar tissue. To investigate this hypothesis, this project will combine innovative computational and experimental approaches, such as advanced imaging, computational modeling, spatial transcriptomics, and animal models. Specific Aim 1 will spatially correlate tissue fibrosis and wall stress after MI in mice by using 2D histology, 3D whole-organ imaging, and finite element analysis. Specific Aim 2 will determine the spatial heterogeneity of cardiac fibroblast subpopulations after MI using publicly available mouse spatial transcriptomics datasets. Specific Aim 3 will functionally test if mechano- transduction pathways activate cardiac fibroblasts by using an in vitro fibroblast-seeded hydrogel stretch assay and an in vivo mouse model of MI. In summary, the proposed studies will investigate a possible pathophysiological mechanism for cardiac fibrosis formation after MI and may provide novel therapeutic targets to treat patients after MI. Importantly, through this project, the applicant, John Lu, will gain diverse expertise in cutting-edge experimental techniques, computational approaches, and scientific reasoning under the mentorship of global fibrosis expert, Dr. Michael Longaker, and leading cardiovascular biologist, Dr. Kristy Red-Horse. Through his training activities, John will also develop the professional and clinical skills to direct an independent laboratory as a future physician-scientist investigator. Furthermore, Stanford University offers an outstanding environment for innovative and collaborative research, with the necessary infrastructure and core facilities to ensure this project’s success. In summary, the strong mentoring environment and fellowship training plan will prepare John to be an independent physician-scientist investigator working at the frontiers of cardiovascular research.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract: In sub-Saharan Africa, low quality care at health facilities contributes to over 1 million child deaths each year. Provider knowledge is a major contributor, but conventional provider educational methods have proven limited due to fixed, universal content; limited geographical reach; and no refresher learning over time. Our long-term goal is to develop a highly effective education strategy to increase provider proficiency with evidence-based interventions that can be scaled-up worldwide. To this end, we have piloted a novel adaptive eLearning (elec- tronic media and devices that adjust to the learner’s needs) intervention called PACE. The overall objectives of this application are to 1) determine the effect of incorporating Tailored Skills Practice and rapid content devel- opment process into PACE and 2) finalize an implementation strategy for PACE, including measures of pro- vider performance and patient outcomes at all facility types in Mwanza, Tanzania. The central hypothesis is that adaptive eLearning blended with in-person skills training that is continuously contextualized to facility needs will increase the quality of care. Our pilot studies of PACE have shown significant improvement in pro- vider knowledge rates, providing the rationale that adaptive eLearning represents a potential solution to over- come known limitations of current educational methods to greatly increase the impact of education on provider proficiency. The specific aims of our two phased approach will: 1) determine if the addition of Tailored Skills Training increases refresher knowledge assignment completion >60% (R21); 2) determine whether rapid con- tent development process using Tanzanian based personnel can disseminate content within 90 days (R21); 3) Validate whether PACE implementation is feasible across all facility types (R33); and 4) Establish and validate a system to derive provider specific pediatric admission quality of care (PAQC) scores for future PACE effec- tiveness study. In our R21, we will recruit clinical champions to conduct Tailored Skills Practice at health cen- ters, recruit a local content engineer (CE) and initiate quarterly meetings with multi-level leadership to continu- ously contextualize PACE to facility needs. For the R33, we will expand PACE to all facility types and explore generating provider specific PAQC scores using both electronic health record data extraction and prospective clinical auditing. Our innovative mixed methods approach will provide a significant framework for the optimal integration of eLearning into tailored skills trainings and clinical auditing for providers in LMICs. Development of an effective pediatric acute care provider education strategy and system to derive provider level perfor- mance and patient outcome metrics will build a foundation for a large-scale implementation study in Tanzania. If successful, this work will improve child global health significantly and broadly advance our knowledge and understanding of provider education and quality of care worldwide.

NIH Research Projects · FY 2024 · 2024-09

Project Summary Aging is a major risk factor for the development of chronic pain with 50% of adults over the age of 65 suffering from at least one chronic pain condition. Unfortunately, there is a major knowledge gap regarding the interaction between age and pain. There is an urgent need for basic research using aged animal models to validate targets relevant to chronic pain treatment in this specific population. As humans and animals age, senescent cells accumulate in tissues throughout the body, and if not effectively cleared by the immune system, can disrupt homeostasis. Certain senescent cells secrete factors that induce inflammation, known collectively as the senescence-associated secretory phenotype (SASP), and include cytokines, chemokines, and proteases. Interestingly, several of these SASP factors are known pain-inducing cytokines released in the dorsal root ganglion (DRG) where primary sensory neuron cell bodies reside and drive hyperexcitability. Senescent cells therefore warrant investigation within the pain circuit in aged mice, and even in young mice after peripheral nerve injury. Our central hypothesis is that age-and injury-induced senescent neurons promote DRG hyperexcitability through production of SASP factors, causing persistent pain following peripheral injury. This hypothesis is founded on our robust preliminary evidence confirming: 1) Induction of senescent neurons within the DRG after peripheral nerve injury, 2) Increased senescent cell burden in the DRG of aged compared to young mice with and without injury as indicated by increased expression of senescent markers, p21 and p16, and 3) Localization of the SASP factor and pain mediator, IL6, to senescent neurons. Additionally, we have preliminary data demonstrating that treatment with a senolytic (anti-senescence) drug improves spared nerve injury (SNI)-induced mechanical allodynia while maintaining overall sensory function in young adult and aged mice. Therefore, a potential mechanism underlying enhanced pain susceptibility following injury in aged mice may be the combination of age-related and injury-induced senescent cells. The overall goal of this proposal is to rigorously validate senescent cells as a target for future therapeutic development. We will pursue validation by genetically, functionally, and phenotypically characterizing deleterious SASP-producing senescent DRG neurons using cross-disciplinary approaches across multiple laboratories. Our approach will leverage three clinically-relevant mouse models (SNI, paw incision and orthopaedic trauma) as well as human post-mortem DRG tissue to strengthen the evidence that our target is likely to be robust in translation. This research will be the first of its kind to investigate and validate cellular senescence in pre-clinical mouse models and has the potential to open a new therapeutic avenue, using senolytic agents, to alleviate pain.

NIH Research Projects · FY 2024 · 2024-09

Our nation is experiencing historic rates of drug overdose deaths that has left behind millions of bereaved families. People who are bereaved by overdose experience a “special grief” that includes guilt, shame, and blame for their loved one’s death that often compounds suffering and help-seeking. People bereaved by drug overdose experience more negative health consequences than those grieving non-drug related deaths (i.e., prolonged grief disorder, substance use disorders, posttraumatic stress disorder, depression, and suicidal ideation). Overdose bereavement is common, especially among people who use drugs who may experience increases in risky substance use while grieving. Overdose deaths have a ripple effect and may increase risk for overdose morbidity and mortality among the bereaved. Peer grief support interventions hold promise for those who are grieving and may be especially important for this population because of the increased stigma, isolation, and risks this population faces. In a novel practice-research partnership, we partner with Peer Community Support Partners (PSCP) who has developed the RIVER peer grief support model for drug overdose bereavement, a promising practice that has been implemented successfully in the community, but has not yet been rigorously tested. This study seeks to not only understand whether a peer support intervention aids those grieving an overdose, but it also proactively engages and connects grievers to resources through medical examiner offices (MEOs) who contact family as part of their standard practice with death investigations. In Aim 1 (R61), through collaboration with PSCP, three MEOs, and our three advisory boards, we will adapt the RIVER training materials to our local communities, refine intervention fidelity measures, and develop intervention and MEO recruitment workflows. In Aim 2 (R61), we will conduct a pilot test with overdose bereaved participants to evaluate if we can engage participants through MEOs, measure RIVER fidelity, and evaluate if RIVER is acceptable to participants. In Aim 3 (R33), we will conduct an RCT to evaluate the effectiveness of RIVER to enhanced usual care. Participants will be recruited from MEOs and will complete baseline, 3, 6, and 12-month surveys. Post-RCT qualitative interviews will supplement data collection and will allow us to understand the characteristics that drive intervention effectiveness. We will also explore how RIVER facilitators’ well-being is affected by intervention delivery using a mixed quantitative and qualitative approach. The proposed research represents a significant step towards understanding and supporting a community that has been too long overlooked. By marrying community and research expertise, this partnership aims to build the science of overdose bereavement and provide increased support for those affected by this tragic issue. This study is part of the NIH’s Helping to End Addiction Long-term (HEAL) initiative to speed scientific solutions to the national opioid public health crisis. The NIH HEAL Initiative bolsters research across NIH to improve treatment for opioid misuse and addiction.

NIH Research Projects · FY 2024 · 2024-09

ABSTRACT Background: Converging lines of evidence suggest that neuromodulation of the neural circuits underlying methamphetamine use disorder (MUD) and subsequent relapse may be an innovative next step in improving treatment outcomes. Emerging research supports the salience network (SN) as a promising target to accomplish these goals. Deep transcranial magnetic stimulation (dTMS) is one type of neuromodulation technique that allows for deeper stimulation of cortical neurons, thus reaching core nodes of the SN like the insula. Objective: The aim of this 2-phase proposal is to assess: 1) whether the H4 coil protocol is effective at engaging the AIns core node of the SN, 2) does this coil and protocol engage the neural target better than a sham condition, and 3) does stimulation of this core node have downstream effects on behavior (i.e., relapse risk). Methods/Design: In the UG3 phase, we will enroll 30 treatment-seeking participants with MUD into a mechanistic trial to determine whether this treatment site and protocol effectively modifies the desired neural target and reduced relapse rates. Participants will receive 30 sessions of 10Hz dTMS to the insula and PFC using the H4 coil. Participants will receive 3 dTMS treatments per day for 10 days totaling 30 treatment sessions. Participants will complete neuroimaging assessments at baseline, after 50% of treatment sessions, post-treatment and 1 month after treatment. In order to advance to the UH3 phase, we will require that dTMS increases activation (of at least a medium effect size) to the respective neural target AND result in reduced relapse rates relative to treatment as usual. If the UG3 milestone criteria are met, in the UH3 phase we will enroll an additional 60 adults with MUD into a 2-arm randomized, double-blind, sham-controlled mechanistic trial to confirm target engagement relative to sham, assess the impact of the protocol on methamphetamine use behaviors, and determine moderators of treatment response. Specific Aims: For the UG3 (Study 1), we aim to demonstrate feasibility, tolerability and target engagement (neural and behavioral improvements). If milestone criteria are met, in the UH3 phase (Study 2), we aim to 1. Confirm target engagement in a 2-arm randomized, double blind, sham-controlled trial. 2. Examine the relationship between target engagement to a more refined measure of use behaviors (i.e., % days abstinent). 3. Determine predictors of treatment outcomes. Impact: The proposed research will elucidate mechanisms of brain and behavior change, accelerate the development of new, device-based, treatment options and will be the basis for developing a large-scale, dose-varying, clinical trial to test new treatment strategies for MUD.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY AND ABSTRACT: The etiology of inflammatory bowel disease (IBD), defined as Crohn's disease (CD) or ulcerative colitis (UC), remains elusive. Although genetic susceptibility plays a vital role in IBD, with over 250 GWAS risk loci, the mechanisms underlying their genetic impact on IBD are still poorly understood. Our surprising discovery reveals that 78 of the IBD susceptibility loci are positioned adjacent to long double-stranded RNAs (dsRNAs), collectively accounting for about 20% of genetic heritability. This insight is founded on a comprehensive understanding of dsRNA editing and sensing mechanisms, supported by human genetic analyses. To prevent undesired immune responses triggered by abundant cellular long dsRNAs, the ADAR1 protein performs adenosine-to-inosine (A- to-I) RNA editing on cellular dsRNAs, marking them as "self" and preventing dsRNA-induced interferon (IFN) responses. Notably, we observed that mice lacking ADAR1 RNA editing cannot survive, but exhibit full lifespan upon eliminating the dsRNA sensor MDA5. Our recent work indicates that insufficient dsRNA editing is associ- ated with presumed dsRNA-mediated inflammation in various autoimmune and inflammatory diseases, including IBD. We discovered that genetic regulatory variants of RNA editing, referred to as edQTLs, are highly enriched in the GWAS susceptibility loci of common immune-related diseases, including IBD. Further, GWAS-defined risk variants are linked to reduced levels of adjacent long dsRNAs, increasing their susceptibility to MDA5 activation. In summary, these findings highlight a crucial role of dsRNA editing and sensing in IBD etiology. Our research objective is to develop effective approaches to systematically evaluate the genetic effects of IBD risk variants on dsRNA editing, allowing construction and validation of a predictive polygenic model of dsRNA-mediated disease risk, known as "dsRNA burden", in both colon enteroids and in vivo animal models. First, we will leverage genetic data from IBD and edQTLs to prioritize dsRNA loci for IBD susceptibility. Subse- quently, we will systematically assess how risk and protective alleles of IBD GWAS variants affect cis-linked dsRNA editing, achieving direct functional validation of causality. Second, we will develop and validate a predic- tive model to assess an individual's dsRNA burden, encapsulating dsRNA-associated IBD in patient-derived enteroid lines. This model will aid in stratifying IBD patients, particularly those with impaired dsRNA editing and heightened dsRNA sensing, contributing to MDA5-dependent chronic inflammation. Finally, we will recapitulate a dsRNA burden system in an in vivo animal model to replicate inflammation and pathology in a native environ- ment. In summary, this work bridges a significant knowledge gap in understanding the etiology of IBD and pro- vide essential mechanistic insights and therapeutic potential for individuals with genetically dysregulated dsRNA editing, leading to chronic IFN responses in IBD.

NIH Research Projects · FY 2025 · 2024-09

Hazardous alcohol consumption remains a significant public health issue among U.S. young adults aged 18 to 25. While interventions exist for college students, non-collegiate young adults, who constitute 38% of this demographic, are less well supported. Text messaging, with its extensive reach and asynchronous communication, emerges as a promising intervention medium. While existing text-based interventions have shown efficacy, there's potential for enhancement by addressing influential environmental factors. Our solution, ASPIRE (Accountability Support through Peer-Inspired Relationships and Engagement), guided by the Social Cognitive Theory, integrates environmental factors alongside traditional cognitive and behavioral elements. A pilot trial with non-collegiate participants from 31 US states revealed promising results: a significant reduction in binge drinking days and related consequences after three months of exposure to ASPIRE. Our next step involves a comparative study of ASPIRE against a Cognitive Behavioral Intervention (CBI). In a proposed assessor-blind, randomized trial, participants will be allocated to either CBI or ASPIRE for three months. Bi-weekly text assessments will measure drinking patterns and peer interactions. While both groups will receive regular feedback, the ASPIRE group will gain additional support targeting positive peer influences and strategies to modify their physical environment. Outcomes, measured using online surveys at multiple intervals, will gauge alcohol consumption and its associated negative consequences. Additionally, GPS data will be collected periodically to analyze patterns, such as time spent at drinking locations. Three primary objectives guide this research: 1. Assessing ASPIRE's effectiveness in reducing hazardous alcohol consumption compared to CBI. 2.Deciphering the mechanisms underpinning behavior change, focusing on the role of peer influence and physical environment. 3. Identifying which subgroups benefit most from ASPIRE to enable more tailored interventions in the future. This research aligns with NIH's priorities, especially NIAAA's strategic plans, emphasizing a broader scope of research and evaluating innovative behavioral interventions for non-collegiate young adults.

NIH Research Projects · FY 2025 · 2024-09

Exposure to adverse childhood experiences (ACEs), such as abuse or neglect, is a powerful risk factor for the development of alcohol use disorder (AUD) in adulthood. Girls are more likely to experience multiple forms of childhood adversity, and as adults, the number of women engaging in alcohol binge drinking has rapidly increased in recent years, significantly narrowing the historical gap with men in rates of alcohol drinking and AUD diagnoses. Despite the abundant epidemiological evidence pointing to complex interactions between childhood adversity, sex, and alcohol use in adulthood, the neural mechanisms underlying sex differences in the effects of early life stress (ELS) on AUD susceptibility remain mostly unknown. Sensitivity to the motor effects of alcohol, which is known to be modulated by other forms of stress exposure, is a potentially highly relevant phenotype influencing AUD susceptibility. Mechanistically, the bed nucleus of the stria terminalis (BNST), a sexually dimorphic and neuropeptide-rich region in the extended amygdala, is a promising mediator of ELS-enhanced alcohol sensitivity. Specifically, activation of corticotropin- releasing factor (CRF) neurons in the BNST is associated with increased stress and other AUD-associated behaviors, including anxiety and alcohol binge drinking, suggesting they may also play a role in alcohol sensitivity. However, it remains unknown exactly how release of the CRF neuropeptide from BNST neurons relates to BNST neuronal activity and synaptic connectivity. Given the complexity of these distinct mechanisms regulating neuronal activation, neuronal connectivity patterns, and neuromodulator release, I will dissect the relative involvement of BNST-CRF neuronal activity, BNST-CRF structural connectivity, and BNST-CRF neuropeptide signaling in mediating ELS-enhanced alcohol sensitivity. With the goal of defining the mechanisms by which ELS-enhanced alcohol sensitivity contributes to AUD susceptibility, my aims will use a combination of behavioral, chemogenetic, viral tracing, and fiber photometry approaches. In the proposed studies, I will use an established, ethologically relevant model of ELS in mice to test the central hypothesis that ELS-enhanced alcohol sensitivity is mediated through increased BNST-CRF neuronal activity, circuit connectivity, and/or neuropeptide release in a sex-specific manner.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract Hair-greying is an early and visible sign of aging with important psychosocial, commercial, and biologic implications. The underlying mechanisms of hair-greying are not well-understood, but the anti-apoptotic BCL2 gene is thought to play a key role in this process. Recent and unpublished studies from our group reveal that the “glacier” bear, a rare color variant of the American black bear found in Southeast Alaska, is a natural model of hair greying that is likely caused by a BCL2 mutation. Glacier bears exhibit variable degrees of hair-greying that occasionally spares the facial region and distal limbs, and is histologically similar to human hair-greying. Genomic studies and genetic association analysis have identified a single region on what corresponds to human chromosome 18 that contains 3 genes, including BCL2. There are no protein-coding alterations in any of the 3 genes but there are 562 non-coding variants within the candidate region, many of which lie in cis-regulatory elements (CREs). In laboratory mice, loss-of-function for Bcl2 has pleiotropic consequences including small size, disruption of kidney and lymphoid development, and postnatal lethality. These abnormalities have not been described in glacier bears, leading us to hypothesize that the cause of hair-greying is disruption of a melanocyte-specific regulatory element. To better understand the pathophysiology of hair-greying and regulation of BCL2, we will: (1) Carry out additional genetic and histologic studies of glacier bear DNA and skin; and (2) Apply a massively parallel reporter assay in three human cell lines to identify CREs for BCL2 and to identify causative variants for the glacier bear mutation.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Progress against pediatric solid tumors has stalled. Current standard therapies largely employ dose intensive cytotoxic agents developed in the 1970s and 1980s that incur severe lifelong toxicity and are unable to cure most patients with high-risk, metastatic, recurrent or refractory disease. Medulloblastoma (MB), the most common malignant brain tumor of childhood epitomizes this reality, since standard therapies are exceedingly toxic and outcomes for patients with metastatic, recurrent or refractory disease remain poor. There is an urgent need for novel, effective targeted therapies for MB. Cerebroglycan (GPC-2) is overexpressed on the cell surface of MB and is not expressed on normal postnatal tissues rendering it a compelling target for treatment with chimeric antigen receptor (CAR) based therapies. CAR based therapies have shown impressive activity in B-cell and plasma cell malignancies, and early signals of activity have been observed with GD2-CAR T cells in children with diffuse midline glioma and neuroblastoma respectively, providing evidence that CAR T cells can mediate significant activity in pediatric brain tumors and solid tumors. In stringent preclinical models, we demonstrated that an iteratively optimized GPC2-CAR mediated significant antitumor activity in MB and NB, but also observed late disease recurrence associated with GPC2 downmodulation. Leveraging deep expertise in enhancing the potency of CAR T cells in the Mackall lab, we demonstrated that overexpression of cJUN in GPC2-CAR T cells led to improved long-term disease control against MB and NB without evidence for toxicity. These data align directly with studies from our lab and others demonstrating that cJUN overexpression lowers the antigen density required for CAR T cell activation, diminishes T cell exhaustion and enhances T cell persistence. Aims 1 and 2 of this Project will define the optimal approach to overexpress cJUN in GPC2-CAR T cells at clinical scale testing state-of-the-art approaches to co-transduction, viral free gene integration and cell selection to identify the most efficient and reproductible platform for consistently delivering an optimized clinical GPC2.cJUN-CAR product. In Aim 3 we will apply the optimal process to manufacture clinical grade GPC2.cJUN-CAR T cells in Arm B of a Phase I trial designed to assess the feasibility, safety and efficacy of GPC2.cJUN-CAR T cell therapy against MB. This trial will compare outcomes between patients treated with GPC2-CAR T cells that did not overexpress cJUN who will have previously been enrolled on Arm A. This work will be among the first to test a potency enhanced CAR T cell therapy for pediatric cancer, will provide valuable information about the promise of GPC2 as a target for MB and will provide preliminary evidence regarding whether cJUN OE can enhance CAR T cell potency without incurring significant toxicity in humans.