Stanford University

NIH Research Projects · FY 2026 · 2023-12

Dilated cardiomyopathy (DCM)-associated heart failure is a leading cause of mortality worldwide. About a third of DCM is due to gene variants in a broad range of cardiac muscle proteins. Although this information has improved patient management, it has not yet led to new therapeutics that target the underlying mechanisms of disease. A major roadblock is that the consequences of the DCM-causing mutations are not understood in sufficient detail to identify points of therapeutic intervention. During the first funding cycle of this project, we used large-scale screening of synthetic microRNAs as an entry point to discover genes that, when inhibited, restored contractility of induced pluripotent stem cells (hiPSC-CMs) carrying DCM-causing mutations. We identified two synthetic microRNAs that normalized contractility of DCM cardiomyocytes comparable to CRISPR-correction of the underlying mutation. Neither microRNA affected isogenic, control hiPSC-CMs, indicating that they act on disease-related processes. We biochemically identified their targets, identifying 203 genes, of which individual siRNA-mediated inhibition of 117 restored contractility of TNNT2 mutant DCM mutant hiPSC-CMs from different patient donors. While some of the candidate genes have been tested as therapeutic targets in heart failure, the vast majority represent new therapeutic target space for inherited DCM. This is multi-PI renewal application is to determine the mechanisms of action of these genes and to establish evidence of disease modifying activity using human genetics and a mouse DCM model. The multi-PI and co-I team unites expertise in iPSC and animal models, systems biology, and human genetics that will have a synergistic impact on our long-term goal of defining therapeutic mechanisms for DCM that would not be possible through separate proposals. Given the diverse genetics and clinical presentations of inherited DCM, our overarching hypothesis is that subsets of the candidate genes, and the physiological processes they affect, will revert contractile dysfunction in a DCM mutation-specific manner. Thus, Aim 1 is to define mechanisms that restore contractile function in DCM caused by different gene variants, and associate beneficial molecular genetic and metabolic pathways with particular DCM-causing mutations, Aim 2 is to investigate whether genetic variants linked to each of the miR- target genes associate with human cardiovascular diseases or quantitative traits using existing GWAS studies, and Aim 3 is to test whether targets of a microRNA that selectively ameliorates contractility in TNNT2-mutant hiPSC-CMs converge on ER stress using a mouse knock-in model engineered with the same Tnnt2 mutation as in the patient hiPSCs.

NIH Research Projects · FY 2025 · 2023-12

PROJECT SUMMARY/ABSTRACT Complex behaviors of the brain, such as cognition, perception, motivation, and mental illness, still remain difficult to explain. To truly understand these processes, it is necessary to understand the basic mechanisms that underly them. Synaptic transmission, the release of neurotransmitters from the presynaptic neuron upon membrane fusion, relies on SNAREs (soluble N-ethylmaleimide sensitive factor attachment protein receptors). SNAREs on the neurotransmitter containing vesicles form a stable, trans SNARE complex with SNAREs on the presynaptic membrane. Once signaled, these SNAREs twist together to provide the energy necessary for membrane fusion. This cis SNARE complex, now a highly stable four helix bundle on one membrane, must be disassembled and recycled to allow further rounds of fusion. Without a pool of fusogenic SNAREs, synaptic transmission would cease. cis SNARE disassembly is accomplished by NSF (N- ethylmaleimide sensitive factor) and adaptor proteins called SNAPs (soluble NSF attachment proteins). Together, the three components form a 20S complex, in which NSF, upon ATP hydrolysis, disassembles SNARE complex and maintains a pool of fusogenic SNAREs. Yet the key dynamical processes and principles of this explosive disassembly step remain unknown. The overall goal of this project is to elucidate the fundamental mechanisms of synaptic transmission by understanding SNARE disassembly. To uncover the principles of SNARE disassembly, both NSF and its yeast ortholog Sec18 will be examined. Studying the dynamics of NSF in its neuronal context has proven difficult due to the complexity of the presynaptic system and the inability to investigate more than a handful of mutants at a time. Studying Sec18 and the yeast 20S (Y20S), in coordination with the neuronal 20S, will enable the use of a wide variety of molecular and biochemical tools that will allow for the dissection of NSF/Sec18 action. The high degree of orthology between the Y20S and 20S also means that observations and principles gained by studying the Y20S will directly transferrable to the neuronal 20S. The hypothesis is that disassembly of SNAREs by the Y20S is mediated by a conserved allosteric network that spans multiple promoters within the Y20S complex (and therefore the 20S complex as well), which play a key role in the modulation of neurotransmission. To test this hypothesis, CryoEM studies of Sec18 and the Y20S have already been completed. This has allowed for the determination of residues that correlate to differences in conformation, assisted by unsupervised machine learning methods. I propose saturation mutagenesis of every single residue in Sec18 in an in vivo assay tying Sec18 activity to survival that will reveal the fitness of each residue in its ability to mediate SNARE disassembly. Second, electrophysiology experiments on mutant NSF in key residues in this allosteric network will directly tie these biophysical mechanisms directly to synaptic transmission.

NIH Research Projects · FY 2026 · 2023-12

Project Summary Radiation therapy (RT) is an important component of cancer treatments, yet its usage has been hampered due to cardiovascular side effects. Although RT-induced heart disease (RIHD) disproportionally affects cancer patients, the mechanisms underlying RIHD susceptibility remains elusive. In this multi-PI R01 grant, our team will elucidate the mechanisms underlying RIHD susceptibility by utilizing human induced pluripotent stem cell (iPSC) technology and comprehensive multi-omics profiling of heart tissues after irradiation. We will identify genetic polymorphisms associated with RIHD by mapping expression quantitative trait loci (eQTL) in endothelial cells derived from 250 genetically diverse donors (200 cancer patients and 50 healthy control) after irradiation using single cell RNA-sequencing (Aim 1). We will construct multi-cellular iPSC-derived engineered heart tissues (EHTs) and use complementary genetic mouse model of RIHD for in-depth functional and molecular profiling after irradiation. We will also use cutting-edge multi-omics techniques (transcriptome-epigenome-proteome) to elucidate the molecular signatures underlying RIHD (Aim 2). Finally, we will screen 5,000 FDA approved drugs for mitigating RIHD using novel iPSC reporter constructs for high throughput analysis (Aim 3). In summary, understanding genetic risk factors of adverse tissue response to irradiation and identifying potential radioprotective therapeutics will improve the therapeutic index of RT and minimize RIHD.

NIH Research Projects · FY 2026 · 2023-12

Project Summary/Abstract The proposed research will improve the understanding of structure-property-function relationships in formulations of charge-altering releasable transporter (CART) gene delivery vectors. These materials demonstrate remarkable efficiency for mRNA transfection with low cytotoxicity due to charge-neutralizing degradative chemistry and have shown remarkable selectivity towards different organs in vivo depending on the chemical structure of the CART. A predictive understanding of how chemical variation affects nanostructure and biological activity will be established. If successful, a set of design rules for CARTs will guide the optimization of mRNA/CART complexes for improved cellular transfection and catered cellular/organ selectivity enabling the development of site-specific CART / RNA therapeutics. The fellow will be the first to perform detailed structural and dynamic studies using advanced cryogenic transmission electron microscopy (cryoEM) and in situ X-ray scattering, illuminating the morphological properties of mRNA/CART nanoparticles. Additionally, this proposal will establish if nanostructure variation arises from changes in formulation technique and CART chemical structures (cation, lipid) and relate these nano-structural variation to differences in biological function. The fellow will develop microfluidic mixing protocols (t-mixer) and screen mRNA/CARTs with differing sizes/morphologies in vitro with cell cultures to establish correlations between functional outcome and nanostructure. In addition to cryoEM and scattering, supplementary measurements of zeta potential, size, phase, thermal transitions, supramolecular interactions, etc. will be carried out to determine the effect physico-chemical properties has on nanostructure in different CART formulations. In separate future research not covered by this proposal, the most distinct mRNA/CARTs will be further studied with in vivo experimentation in mouse models with our collaborators. The fellow will also receive formal and informal training in the responsible conduct of research, teaching, career development skills applicable to their future career goals of becoming a research professor and participate in outreach and mentoring. These studies will take place in a highly interdisciplinary training environment at Stanford University in the lab of Prof. Robert Waymouth, in close collaboration with Dr. Christopher Tassone at SSRL (SLAC national laboratory).

NIH Research Projects · FY 2026 · 2023-12

Project Summary The mammalian central nervous system contains unique projections from the cerebral cortex thought to underpin complex motor and cognitive skills. These projections include the corticospinal tract. involved in motor function, and the corpus callosum, involved in executive function. The cerebral cortical neurons that give rise to the corticospinal tract and corpus callosum are, respectively, corticospinal motor neurons and callosal projection neurons. These neurons develop from the same progenitor pool at the same time in development, but they acquire strikingly different projections to serve strikingly different behaviors. The mechanisms whereby corticospinal and callosal projection neurons develop represents a fundamental open question in basic neuroscience: how do the unique projections underlying complex mammalian behaviors arise? While it is known that transcription factors play a critical role in the fate of corticospinal, callosal, and other cortical projection neurons, the contribution of other gene regulatory mechanisms is poorly understood. We posit that a genomic cluster of selectively expressed microRNAs are epigenetically co-regulated in corticospinal motor neurons (Aim 1 ), where they in turn co-regulate axon guidance pathways (Aim 2) to favor corticospinal over callosal projection neuron fate (Aim 3). We will employ deep sequencing and in vivo functional perturbation studies to test our hypothesis. This microRNA-mediated specification of fate represents a novel mechanism of cortical projection neuron development, with implications not only for fundamental mechanisms of cortical development, but also for understanding the evolution of the complex connectivity of the mammalian central nervous system.

NSF Awards · FY 2023 · 2023-12

Technologies for expressing ideas in visual form have been critically important throughout human history. From ancient cave paintings to modern digital graphics, such technologies lie at the heart of some of our most significant inventions, including art, writing, and mathematics. Despite the importance of such technologies, little is known about how the human mind is capable of using them in such varied ways. Perhaps the most basic and versatile of these technologies is drawing, which can be used to convey information about the visual world at many levels of abstraction, ranging from realistic illustrations to simplified diagrams. This project will harness large datasets and advanced data analysis techniques to develop a rigorous understanding of the mental processes involved when people use drawings to communicate visual concepts in different ways. Results from this project will advance our understanding of why people prefer to use certain kinds of images in some contexts and not others, with implications for how to design effective visualizations for a variety of applications, including STEM education and research. This project’s focus on the problem of how abstract ideas can be communicated in clear and accessible ways extends to its education plan. This plan encompasses two initiatives to develop inclusive learning experiences that promote computational literacy among K-12 and undergraduate students that have historically faced systemic obstacles to this training. Aim 1 of this project seeks to resolve a classic debate concerning whether drawings derive their meaning by resembling objects in the world (i.e., are image-like) or by being composed of discrete symbolic expressions (i.e., are language-like). The proposed experiments will evaluate the hypothesis that drawings are neither purely image-like nor purely language-like, but can vary strongly depending on what the illustrator can see, what they know, and what information they wish to communicate. To test this hypothesis, the proposed analyses will employ crowdsourcing and computer-vision techniques to measure the degree to which different drawings preserve perceptual information and/or are organized into discrete symbolic units. For example, some drawings may contain rich visual details that resist summarization in words, while other drawings may be entirely composed of simpler marks that can be readily described using words. Aim 2 will investigate the process by which people come up with new ways to visually communicate with each other over time. The proposed experiments will evaluate the hypothesis that drawings that initially resemble a concrete object tend to become increasingly abstract and symbol-like when people repeatedly communicate about it, reflecting shared goals and knowledge between communicators. The proposed analyses will measure consistency and variability in the resulting drawings, providing quantitative insight into the factors that affect the development of new symbolic systems for communication. Aim 3 seeks to better align the scientific training undergraduate psychology students receive to the reality of modern scientific practice in psychology. Specifically, it will integrate teaching of open-science best practices, exploratory data visualization, and model-based data analysis into the introductory statistics curriculum in Psychology at University of California San Diego, as well as collaborative final research projects to help students synthesize what they have learned and hone their communication skills. Aim 4 strives to broaden access to general education about artificial intelligence (AI) in historically underserved communities by partnering with local K-12 schools to develop learning experiences that illustrate the relevance of AI to students’ everyday lives, as well as how AI intersects with other disciplines, including the arts, psychology, medicine, and law. 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 · 2023-12

PROJECT SUMMARY Optimizing treatments in mental health requires an easy to obtain, continuous, and objective measure of internal mood. Unfortunately, current standard-of-care clinical scales are sparsely sampled, subject to recency bias, underutilized, and are not validated for acute mood monitoring. The recent shift to remote care also requires novel methods to measure internal mood. Recent advances in computer vision have allowed the accurate quantification of observable speech patterns and facial representations. The continuous and objective nature of these audio-facial behavioral outputs also enable the study of their neural correlates. Here, we hypothesize that video-derived audio-facial behaviors have discrete neural representations in the limbic network and can provide a critical set of reliable longitudinal estimates of mood at low cost across home and clinic settings. To test our hypothesis, we will enroll ten surgical epilepsy patients with comorbid major depression already undergoing surgical implantation for clinical reasons. We will obtain simultaneous video-derived audio-facial features, invasive brain recordings, and frequent assessments of mood. In Aim 1, we will combine continuous video recordings with frequent mood assessments to build a longitudinal mood prediction model using video- derived audio-facial features. In Aim 2, we will identify neural correlates of audio-facial dynamics using synchronized intracranial EEG under spontaneous and task settings. In Aim 3, we will use high frequency direct electrical stimulation to determine the causal influence of limbic activity on audio-facial features and internal mood. The result of this study is a mood-decoding model based on audio-facial behavioral features that are causally linked to limbic activity and mood. This model will allow for objective, passive, longitudinal, remotely-enabled, and low-resource measurements of internal mood. Multiple use cases exist to significantly advance psychiatric care, ranging from acute mood tracking to optimize rapidly-acting interventions such as psychedelics and neurostimulation, to longitudinal telehealth-enabled monitoring for suicide risk monitoring, treatment dose optimization, and relapse prediction. Across inpatient, outpatient, and at-home settings, this model can deliver important real-time mood and electrophysiological insights to both patients and providers. Relevance to NIMH RDOC Matrix: Negative Valence Systems: Construct: Loss; Circuit: vmPFC, Parietal cortex, default mode network; Physiology: LFP; Behavior: Rumination and Sadness.

NIH Research Projects · FY 2026 · 2023-12

Antihypertensive and statin therapy represent imminently scalable interventions for preventing Alzheimer’s disease and related dementias (ADRD). Evidence from randomized trials for the effect of these medications on preventing ADRD provided mixed results and has often been limited by short follow-up times, low statistical power, and a lack of representativeness for the broader population and routine care. Using large-scale electronic health record (EHR) data from three integrated health systems in the US as well as nation-wide data from the UK and Denmark, this project will employ an innovative and well-validated method for causal effect estimation to fill this evidence gap. Specifically, we will exploit thresholds in blood pressure, LDL, and cardiovascular disease risk in clinical guidelines. Patients close to these thresholds are similar to each other except that crossing a given threshold results in a sudden jump in the probability of receiving the medication. Importantly, the validity of this approach can be fully verified in the data, including by comparing patients’ characteristics just above versus just below each threshold. Our datasets have follow-up times between 17 and 35 years, include detailed pharmacy records, and have minimal loss to follow-up due to complete linkage of all US datasets to Medicare claims data and the single-provider nature of the UK and Danish health system. Generated as part of an NIH New Innovator Award to the PI, our extensive preliminary analyses demonstrate that this innovative approach in EHR data is both feasible and valid and that all key variables are reliably recorded in our EHR datasets. Our approach in EHR data has also successfully replicated findings from clinical trials on the effect of antihypertensive and statin therapy on cardiovascular disease events, giving us a high degree of confidence that we can extend our approach to ADRD. Bringing together a team with deep expertise in ADRD, causal inference, and EHR data, we will establish the causal effect of antihypertensive (Aim 1) and statin (Aim 2) therapy on the incidence of ADRD. Aim 3 will determine whether antihypertensive and statin prescriptions have adverse behavioral effects, which is critical knowledge for interpreting findings (regardless of their direction) in Aims 1 and 2. All analyses will ascertain the causal effects both of receiving a prescription and of long-term adherence to these medications, use novel machine-learning approaches to determine how effects vary across detailed patient subgroups, and be compared to more common analytical approaches that make stronger assumptions than our threshold-based method. Although validation studies have generally found the reliability of ADRD diagnoses in our EHR datasets to be high, we will also conduct extensive probabilistic bias analyses for potential under- and overdiagnosis of ADRD. This project will inform clinical and public health guidelines as well as directions for the development of new ADRD preventive interventions. In demonstrating the value of our approach, this project could also encourage efforts in EHR data that exploit threshold-based decision making in other areas of medicine.

NIH Research Projects · FY 2025 · 2023-09

Enter the text here that is the new abstract information for your application. This section must be no longer than 30 lines of text. Opioid addiction is now the fastest growing drug problem in the United States. Chronic opioid use induces opioid dependence, which is characterized by extremely unpleasant physiological and psychological symptoms after drug use is terminated. Opioid users learn to associate opioid intake with relief from negative physical and affective states. These learned associations are major obstacles for successful addiction treatment, since even after a prolonged period of abstinence, re-exposure to such cues often triggers drug craving and relapse to drug seeking. Therefore, the neuronal circuits underlying opioid withdrawal might be a potent target for preventing relapse. Indeed, we recently revealed an essential role of the paraventricular nucleus of thalamus (PVT) to the nucleus accumbens (NAc) pathway in mediating opioid withdrawal symptoms. Repeated opioid exposure causes long-term potentiation in the PVT→NAc pathway, furthermore silencing of this pathway disrupts opioid-associated memory and causes enduring protection against relapse to opioid use. However, PVT and NAc are both functional heterogenous structures with complex anatomical connections with their up- and down- stream brain regions. Beside opioid addiction, the PVT→NAc pathway also regulates motivated behaviors, such as feeding and sleep. Different functions are likely mediated by distinct subgroup of neurons in this pathway. We thus have formed a team with strong expertise in epigenomics sequencing, spatial imaging technologies, and neurobiology of drug addiction. We propose to (1) combine single cell transcriptomic and epigenomic imaging to establish a spatial resolved single cell atlas in the PVT and NAc; (2) identify opioid-responsive cell types and opioid-induced changes in their chromatin accessibility and gene expression during different stages of opioid addiction in the PVT; (3) use cell type specific gene manipulation to determine the contribution of opioid-induced gene expression changes to behavioral adaptations caused by repetitive opioid exposure and withdrawal. Together, our results will help identify novel molecular targets for treating opioid addiction.

NIH Research Projects · FY 2024 · 2023-09

PROJECT SUMMARY The CDC estimates that adverse drug reactions (ADRs) cause 1.3 million emergency department visits annually in the U.S., and that hundreds of thousands of these patients require hospitalization. ADRs are often caused by drugs binding proteins in the body that were not intended targets. Predicting this off-target binding is difficult. There are methods that use 3D molecular structure to predict if a small molecule can bind a given protein, but the majority of the human proteome does not have an experimentally-solved structure. Recent breakthroughs in protein structure prediction have enabled high confidence prediction of nearly any protein's structure from sequence alone, meaning that we can leverage structure information for the entire human proteome in a way that was impossible two years ago. Additionally, recent advances in structural informatics algorithms have improved our ability to identify locations on a protein surface with high binding propensity; despite this, current ADR prediction algorithms are unable to both leverage binding information of functionally uncharacterized proteins and make interpretable predictions that can guide drug design. I propose to create methods to predict drug binding pockets and ADRs in an interpretable manner at the proteome scale. I will accomplish this by 1) building a graph representation of known and predicted drug-pocket pairs; 2) using this graph to estimate ADRs associated with pockets and drugs; and 3) extending the pocket and ADR prediction methods to predict and explain ADRs caused by proteome-wide off-target binding. Application of the proposed method to the entire human proteome will allow the prediction of a drug's potential ADRs before it is used in humans, improving drug development and reducing the number of ADRs experienced. I will conduct this project in the lab of Dr. Russ Altman at Stanford University, where I am working toward my long-term career goal of becoming an independent researcher developing computational methods that accelerate drug development and aid understanding of drug response at the molecular level. My training environment sets me up well to achieve this goal as Dr. Altman has an excellent track record of mentoring graduate students and Stanford University provides a plethora of educational resources and a highly collaborative research environment. The Altman group has developed algorithms for characterizing protein microenvironments and has a history in both computational structural biology and drug response research, providing me with easy access to experts in domains highly relevant to my proposed work. Beyond the proposed research, my training plan includes attending seminars and conferences, collaborating with other research groups, taking additional coursework, teaching, and oral and written communication of my work.

NIH Research Projects · FY 2025 · 2023-09

Long COVID affects millions of people in the U.S. and has disproportionately impacted vulnerable populations including low-income persons and communities of color who often face barriers to healthcare access. As trusted, accessible providers, federally-qualified healthcare centers (FQHCs) are well-positioned to help mitigate inequities by providing access to Long COVID care in their medically underserved communities. We propose that a care model, Long COVID Care Resources and Education to Advance Community Health (REACH) where a centrally-coordinated, multidisciplinary Long COVID hub program that supports and partners with networks of safety-net FQHCs in the community will help expand and improve the care of vulnerable patient populations suffering from Long COVID. The Stanford Long COVID hub program is a team-based multidisciplinary clinical and research program rooted in a primary care-specialty care partnership and, together with key community partners including Community Health Center Network and San Mateo Medical Center and others, our goal is to extend the reach of this program and expand access for vulnerable patients with Long COVID through the following specific aims: AIM 1: Improve community awareness and education on Long COVID for patients and clinicians. AIM 2: Support primary care providers in partner safety-net FQHCs by creating a collaborative learning community with peer-to-peer asynchronous and real-time consultation. AIM 3: Improve Long COVID care referral coordination and access at the Stanford hub clinic. Our approach is to build upon the evidence-based and well-established Chronic Care Model (CCM) with innovative components that are adaptive and responsive to the rapidly changing landscape of Long COVID care. We will implement the tiered educational outreach and peer-to-peer primary care support strategies across partnering FQHCs with synergistic expertise from our colleagues at the Evaluation Sciences Unit, Office of Community Engagement, and Center for Continuing Medical Education. We will utilize a stepped wedge design and evaluate the model with a formative and summative mixed-methods approach guided by the Reach, Effectiveness, Adoption, Implementation, and Maintenance (RE-AIM) framework to assess overall project reach and impact and adapt strategies throughout the REACH project duration. As part of the cooperative, we will collaborate with AHRQ and other recipients in the Learning Community to share, incorporate, and disseminate learnings in a collective effort to support the primary care community in Long COVID education and management. Overall the goals are to expand access to comprehensive, coordinated, and person-centered care for vulnerable patients with Long COVID.

NIH Research Projects · FY 2025 · 2023-09

Abstract Genome-wide screens in mammalian cells have emerged as a powerful tool for determining the relationship of individual genes to a chosen biological phenotype. However, biological systems often rely on the concerted action of multiple genes at once to elicit phenotypes. Nowhere is this more evident than in cellular differentiation, where cell state transitions often involve the modulation of 5-7 master regulatory factors. Consistent with this observation, successful efforts to reprogram cells, from Yamanaka on, have generally found that simultaneous expression of 3-5 transcription factors are needed to elicit cell state or type changes (similar to an “AND-gate- like” genetic circuit), and others have improved the efficiency or accuracy of these transitions by further perturbing other factors such as epigenetic remodelers. Given these observations, we posit that the ability to carry out highly combinatorial forward genetic screens for cell state phenotypes would produce a “sea change” in our ability to engineer cells with highly specific properties, transforming the quality of cells available for research and cell therapy applications. To this end, we propose an iterative platform that leverages a large multiplicity of perturbation (MOP) per cell, intelligent structuring of engineered perturbation libraries, and machine learning approaches to both identify combinations of perturbations most likely to elicit specific cellular phenotypes, and to engineer maximally informative new perturbation libraries. We have piloted this platform on a simple “toy model” wherein the simultaneous expression of 6 different proteins (across a total universe of 30 different potential factors) are required to elicit a phenotype. By overloading cells with ~14 perturbations per cell, structuring a library of ~80 perturbation combinations, then identifying further observations that would provide maximal information about the causative perturbation combination, we were able to confidently uncover this six- input “AND-gate” underlying state logic. While this initial ability to “solve” highly polygenic phenotypes is exciting, challenges to extending our platform to primary human cells include identification and minimization of dominant negative perturbations, identification of optimal MOP for each biological question, perfection of methods for high MOP of primary cells, exploration and optimization of the direction and mechanism of gene expression perturbation, and the engineering or selection of state changes sufficiently durable for therapeutic utility. We plan to initially apply this platform to the trans-differentiation of naive T cells into regulatory T cells and the generation of inexhaustible T-cells for cell therapies, with an eye toward establishing collaborations to deploy this platform to develop diverse cell types with regenerative or therapeutic value. In short, we posit that complex, therapeutically relevant phenotypes demand a polygenic design language that reflects the combinatorial vocabulary and grammar of human biology. We anticipate that our cell engineering platform will provide the first native implementation of this language.

NIH Research Projects · FY 2024 · 2023-09

PROJECT ABSTRACT Pandemic preparedness requires strengthening surveillance for emerging viruses, but also a plan for public health response when the next pathogen rapidly infects humans on a global scale. In order to ensure that the disproportionate disability and death experienced among disadvantaged populations in the US does not repeat in a future pandemic, public health agencies will need to validate resource allocation and surveillance tools within a health disparities framework. The RADx-UP Consortium enables such as an evaluation, since this NIH-funded Consortium of over 130 projects, with over 370,000 nationwide participants, focused on improving test access, and eliciting COVID19 stress and vaccine perception among underserved persons. Using RADx- UP data as the ground truth, we will test whether three area level vulnerability indices—the Social Vulnerability Index, the Minority Health Social Vulnerability Index, and the Community Vulnerability Index—identify persons experiencing food or housing insecurity, or gaps in healthcare access during the pandemic (Aim 1). We will leverage methods from clinical trial literature to assess RADx-UP data generalizability. We will link to American Community Survey, and generate county-standardized estimates of pandemic stress and vaccine concerns for the more than 900 US counties with participants in the RADx-UP consortium. We will then assess the association of these standardized estimates with the three area level vulnerability indices. A second aim of the proposed work will be to assess the predictive performance of the promising tool of wastewater surveillance among underserved populations. We will link RADx-UP data with the publicly available National Wastewater Surveillance System data, and compare wastewater infection prevalence metrics with the test positivity rate among RADx-UP performed tests, and county-level hospitalizations and deaths. We will evaluate changes in predictive performance over time (e.g., before versus after vaccine availability), and with integration of area- level vulnerability indices and other census demographic variables. With the ultimate aim of reducing health disparities in the future pandemic, our team of epidemiologists, statisticians, nephrology and infectious disease clinicians, and health policy experts will evaluate existing and emerging pandemic preparedness tools. In doing so, we hope to promote a public health infrastructure responsive to groups most vulnerable to the health and social turbulence inherent to a pandemic.

NIH Research Projects · FY 2025 · 2023-09

Project Summary This proposal aims to develop computational tools that analyze the structural variability of the macromolecules imaged by Cryogenic electron microscopy (CryoEM) and Cryogenic electron tomography (CryoET). As the function of most macromolecules involves dynamic interactions among their own components or with other molecules, the structural flexibility of those macromolecules is often key to accomplishing their functions. CryoEM/CryoET makes snapshots of macromolecules embedded in vitrified ice, which provides direct information of individual protein particles in different compositional and conformational states. Using advanced computational methods, we will be able to resolve the structural heterogeneity of proteins and gain a deeper understanding of their structure-function relationship. The algorithm developed in this proposal will be using the Gaussian mixture model for protein structure representation and deep neural network for embedding snapshot images of proteins onto a latent space depicting their conformational states. In this proposal, we address the issue of protein structural variability from three aspects. First, we will build a pipeline for simultaneous orientation and conformation refinement for single particle analysis, which will make it possible to solve systems with large-scale structural variability. Second, we will integrate constraints from molecular models into our pipeline, so that prior knowledge from biochemistry can be used to guide the protein heterogeneity analysis. Finally, we will focus on CryoET and expand the method to look into the dynamic of macromolecular systems inside cells. In sum, the proposed work will produce software tools for a comprehensive analysis of protein structural variability, which will provide new insights into the functioning mechanism of macromolecules.

NIH Research Projects · FY 2025 · 2023-09

ABSTRACT – OVERALL Gastric cancer is a leading cause of cancer morbidity and mortality worldwide. The bacterium Helicobacter pylori (Hp) is the single greatest risk factor for gastric cancer, its infection triggering an inflammatory cascade within the gastric microenvironment. Many people infected with Hp develop a precancerous lesion called gastric intestinal metaplasia (GIM), and while some are minimally affected by the condition, others go on to develop invasive gastric cancer. There remain many unanswered questions about how Hp interacts with the gastric microenvironment and promotes gastric cancer, and why GIM poses variable risk to patients. The focus of this Program Project Grant (PPG) is characterizing the molecular and genomic features of gastric epithelial cells in high-risk versus low-risk gastric precancerous lesions, with Hp as a stratifying risk factor. The PPG involves three distinct yet synergistic projects: (1) Molecular and Cellular Determinant of High-Risk Gastric Precancerous Lesions. (2) Ex Vivo Modeling of Gastric Precancerous Lesions. (3) Molecular Risk Stratification of Gastric Precancerous Lesions. The leaders of the PPG’s multidisciplinary research teams have backgrounds in the relevant clinical specialties of infectious disease, gastroenterology and gastrointestinal oncology. The PPG leverages broad and deep research expertise in single-cell sequencing, Hp biology, epidemiology and clinical research for gastric cancer prevention. There are several robust and synergistic clinical cohorts and biospecimen repositories that make up the foundation of the PPG. These include two cohorts of gastric precancerous lesions, the Gastric Precancerous Conditions Study (GAPS, Stanford University) and the NCI-supported Gastric Cancer Precursor Lesions Study (GPCL, Pontificia Universidad Católica de Chile), the Gastric Cancer Registry (GCR, Stanford University), and the NCI-supported Hp Genome Project (HpGP, Vanderbilt University). The translational and clinical projects in the PPG offer a novel strategy of high-impact precision interception and cancer prevention to reduce gastric cancer risk. The interdisciplinary approach in this PPG is essential for improving clinical prevention strategies and risk attenuation of gastric cancer.

NIH Research Projects · FY 2024 · 2023-09

Project Abstract Neuropsychiatric symptoms (NPS) are commonly observed in individuals with mild cognitive impairment or Alzheimer’s disease (AD) dementia. These symptoms affect up to 97% of patients during the course of AD and may cause accelerated declines in cognitive functions and conversion to dementia. Though numerous efforts have been devoted to investigating the etiology of NPS, the neurobiological basis underlying NPS in AD dementia remains unclear. There is an urgent need to advance the mechanistic understanding of these symptoms, which is crucial for early detection and timely intervention to prevent AD progression. Increasing evidence has indicated that differential NPS overlap substantially and are relevant to dysfunctions in distinctive brain networks. Assessing NPS dimensionally and their associated circuit-level dysfunctions would therefore provide significant benefits to deepen our understanding of neural circuits involved in the expression of NPS. In response to the guidelines of the PAR-20-159, the overall objective of the project is to assess neural circuits and identify neurophysiological subtypes (i.e., subtypes) underlying dimensions of NPS in dementia. We hypothesize that distinct patterns of neural circuits will reflect latent dimensions of NPS domains that span from preclinical to severe AD dementia, and interact to define neurophysiological subtypes that are predictive of clinical symptoms and the rate of AD progression. In Aim 1, we will identify interpretable neural circuits and the linked latent dimensions of NPS domains using a sparse multivariate correlation analysis. In Aim 2, we will identify neurophysiological subtypes using statistical clustering with guidance from the NPS dimension-associated circuitry characteristics. We will further evaluate and interpret the neurobiological meanings and clinical relevance underlying these dimensions and subtypes. The proposed approaches will be developed and evaluated by assessing resting-state functional MRI from two independent cohorts (OASIS-3 and ADNI) with more than 1,800 subjects in total. Successful outcomes of the project will lead to an improved understanding of the neurobiological mechanism underlying NPS and its clinical relevance, form a promising new avenue to potentially guide the intervention of NPS and better the management of AD progression, and hence pave the way towards precision medicine of AD dementia.

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY The primary cilium is a cell surface organelle that plays critical roles in human health. Multiple G protein-coupled receptors (GPCRs) are trafficked to the primary cilium where they carry extracellular signals across the membrane to initiate intracellular signaling events. Genetic studies have linked GPCR signaling at primary cilia to human metabolic disease. For example, ciliary GPCRs regulate diverse metabolic processes such as the perception of satiety, the secretion of insulin, and the formation of adipocytes. With 42% of U.S. adults classified as obese, understanding how the primary cilium functions as a GPCR signaling center is critical to addressing this major human health concern. In this proposal I will test how the primary cilium membrane composition controls GPCR signaling. Lipids have profound effects on GPCR signaling through (1) direct binding and (2) indirect modulation by changing membrane bilayer properties. Through these interactions, GPCRs play fundamental roles in cellular lipid signaling and organismal lipid homeostasis. A key barrier to understanding how GPCRs regulate human metabolism is the lack of tools to study lipids in cells. I have developed a unique skillset and a set of tools to visualize, quantify and manipulate lipids at primary cilia to address these challenges. This proposal tests three fundamental questions related to cilia lipid signaling. First, despite its importance in regulating metabolism, it is unknown whether the primary cilia membrane is altered by dietary lipids. External stimuli robustly change the plasma membrane (PM) composition to drive cell signaling events required for cellular homeostasis. To test this at cilia, I will treat cells with fatty acids or cholesterol to mimic the human diet and ask whether the membrane composition is altered. Cilia lipids will be further examined in mice fed different chow diets and in mice with metabolic disease (Aim 1). Second, despite having a membrane that is structurally continuous with the PM, the primary cilium maintains a distinct membrane composition that is critical for GPCR signaling through unknown mechanisms. I will test whether lipids exchange between the PM and cilia membrane, and then determine how lipids are delivered to cilia by disrupting membrane trafficking pathways (Aim 2). Finally, I will determine what lipids are required for FFAR4 activity at cilia. FFAR4 is a GPCR that intimately relies on the integrity of the cilia membrane environment for signaling. By cross comparing this screen with a screen I previously performed to find regulators of the ciliary GPCR SMO, I will identify generalizable pathways controlling ciliary lipid homeostasis. Importantly, this screen will also determine the specific lipid requirements of FFAR4, which is a promising target for treating metabolic disease due to its role in insulin secretion and adipogenesis. Through this research I will develop robust methodologies that can be utilized to study cilia in diverse contexts, and I will advance our understanding of cilia biology, membrane biology, and GPCR signaling. The long-term vision of this project is to identify new strategies for correcting lipid or GPCR signaling defects found in human metabolic disease.

NIH Research Projects · FY 2025 · 2023-09

Project Summary T cells play a central role in the immune response, detecting antigenic peptides cradled within MHC molecules (pMHCs) displayed on the surface of diseased cells via specific interactions with cell-surface T cell receptors (TCRs). This recognition triggers downstream T cell activation and cytotoxic killing. In vivo, T cells are exquisitely sensitive and specific, able to be activated by a single antigenic peptide displayed by a diseased cell. Immunotherapies attempt to harness this sensitivity and specificity to eliminate cancerous cells by either transfusing patients with T cells engineered to display TCRs specific for tumor-associated antigens (neoantigens) or injecting peptide ‘vaccines’ to stimulate expansion of neoantigen-specific T cell clones. Predicting which neoantigen/TCR combinations will activate a potent T cell response in a patient remains a formidable challenge. There are a vast number of potential pMHC/TCR complexes: MHC molecules are encoded by 23,000 HLA alleles, each MHC displays a ~9 amino acid peptide (209 possibilities), and each patient can express >1020 possible TCRs. While many techniques leverage next-generation sequencing to screen millions of pMHC/TCR combinations for high-affinity binders, these screens can test only a small fraction of possible combinations. Moreover, the strength of pMHC/TCR binding does not predict activation: many high-affinity peptides do not activate T cells, and many potent agonists bind with only moderate affinities. T cells generate pN to nN forces on pMHC/TCR complexes as they crawl over antigen-presenting cells, and emerging evidence has established that these biomechanical forces are essential for sensitive and specific TCR-pMHC recognition: pMHC/TCR complexes that drive potent activation form ‘catch’ bonds that strengthen under force, while those that do not form ‘slip’ bonds more likely to break. Thus, developing improved immunotherapies requires new technologies capable of testing large numbers of candidate pMHC/TCR interactions for their ability to form catch bonds and activate T cells under physiological forces. My lab is uniquely qualified to address this critical need. In prior work, we developed a microfluidic platform that enables recombinant cell-free expression, purification, and quantitative in vitro characterization of >1,500 proteins in hours and at low cost. Here, we will apply this powerful technology to systematically investigate which pMHC/TCR combinations form ‘catch’ bonds that predict activation (Platform 1) and which neoantigens are efficiently displayed by 1000s of different MHC sequences encoded by variable HLA alleles (Platform 2). To further test candidate pMHC/TCR combinations in their cellular context, we will apply a novel droplet-based technology we invented to co-encapsulate 10s of millions of T cell/APC pairs and sort them based on activation (Platform 3).

NIH Research Projects · FY 2025 · 2023-09

Project Summary/Abstract Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide. HMG-CoA reductase (HMGCR) inhibitors, statins, show high potential in the prevention and treatment of cancer including HCC. We will investigate the mechanism by which statins fight against HCC and discovering the biomarkers to predict the therapeutic effects. Through our previously published work, we have used our conditional transgenic mouse models of HCC to identify a novel pathway that statins suppress MYC signaling to execute the anti-cancer properties. Also, we identified that MYC rewires metabolic pathways to promote fatty acid synthesis in addition to glucose and glutamine pathways. Inhibition of fatty acid synthesis by TOFA elicits dramatic regression of MYC driven tumors and the efficacy correlates to MYC level. Statin (e.g., Atorvastatin) blocks MYC phosphorylation in our MYC-driven HCC model and inhibit tumor initiation and progression (see our Preliminary Results). We hypothesize that the MYC pathway is suppressed by statins and this is a mechanism by which statins can prevent and treat HCC, both through direct anti-oncogene effects as well as by restoring immune surveillance. We will determine the mechanisms by which statins protect against HCC, we propose to 1) evaluate the anti-cancer efficacy of statins at different progression stages of MYC driven HCC (before MYC induction, early stage of tumorigenesis, late stage of HCC) and the condition of association with NASH; 2) identify specific metabolism pathways regulated by statin in MYC-HCC; 3) define the changes of immune system and specific effectors/cytokines influenced by statin; 4) discover the biomarkers that can predict the therapeutic effect of statin in prevention of HCC. Our team includes expertise in Medical Oncology, the MYC oncogene and Tumor Immunology (Felsher), Gastroenterology and HCC (Dhanasekaran) and Hepatology and liver disease (Verna and Brown). Dr. Verna and Dr. Brown are members of the Liver Cirrhosis Network (LCN) clinical program (RAF- CA-23-023) and are currently investigating the effect of lipid lowing medications (Statins) in patients with compensated NASH, ALD, cholestatic and cryptogenic cirrhosis. The LCN study provides us with a unique opportunity to identify mechanisms through use of our preclinical transgenic mouse model of HCC that can be evaluated using human clinical samples to available to us through the LCN. Our work will help identify lead to the identification of the mechanisms by which statins can block HCC as well as identify biomarkers that can predict when these agents are most likely to be useful in preventing HCC.

NIH Research Projects · FY 2025 · 2023-09

ABSTRACT/SUMMARY – Overall Distant metastasis is the primary cause of cancer-related death. To colonize distant tissues, cancer cells must migrate while evading elimination by the immune system. Evidence suggests that key steps in the induction process of immune tolerance occur early in the metastatic cascade, located at the regional lymph nodes proximal to the primary tumor site. However, the nature of the interactions between malignant, immune and stromal cells remains poorly understood, including those that involve metastatic cells within the lymph nodes. Even though lymph nodes are in fact commonly assessed in cancer patients to determine disease stage and treatment plan, they are understudied in the context of metastatic progression. To fill this scientific knowledge gap, we propose a Research Center to unravel the role of lymph nodes in metastatic progression. We have established that lymph node metastasis constitutes an essential, first step in the metastatic cascade of cancer progression. We have found that such metastases act locally upon the adaptive immune system within the lymph nodes to begin to induce systemic tolerance of the tumor. We will further explore this new paradigm of metastases in two malignancies, head and neck cancer and lung adenocarcinoma, by focusing on the kinetics and spatiotemporal changes at the primary tumor, lymph node and distant sites, associated with the onset and progression of metastasis. We have assembled a multidisciplinary team whose coordinated efforts will involve the application of genomic and single-cell in-situ imaging technologies on preclinical and human samples to explore the evidence and mechanisms of the induction of immunosuppression in the lymph nodes. We propose two Research Projects that focus our scientific theme on lymph node metastasis by analyzing kinetics in a mouse model (Project 1) and spatial temporal changes in samples of lymph nodes and their concurrent primary tumor (Project 2), inter-connected through integrative computational analyses. Both projects will utilize a shared resource core dedicated to the acquisition of patient samples and associated clinical annotation and data management (Biospecimen Core and Data Core). These efforts will yield highly multiplexed, multi-scale datasets which will be analyzed by novel bio-computational methods to reconstruct intracellular and intercellular molecular interaction networks in order to identify, then functionally validate, critical mediators of metastasis. Our ultimate objective is to advance our understanding of the systemic consequences of lymph node metastases and identify new biomarkers and therapeutic approaches. Our Research Center is also dedicated to promoting our early investigators as the next generation thought leaders applying principles of systems biology to the study of metastasis. Our Outreach Core activity will ensure that our Research Center’s scientific and methodological advances in applying the principles of cancer systems biology toward the study of tumor-immune-stromal interactions are fully disseminated in the cancer research and broader communities.

NIH Research Projects · FY 2025 · 2023-09

Abstract: Auditory and vestibular sensory cells use the hair bundle, a stair-cased array of actin filled stereocilia, to translate mechanical motion into an electrical signal. Mechanically-gated (MET) ion channels located at the tips of shorter stereocilia are activated by force created by the pulling of a tip link that extends between stereocilia. As sensory hair bundles are a major site for both genetic disorders like Ushers syndrome and are also susceptible to damage from noise and aging, understanding how these bundles operate is critical to designing therapies for prevention and restoration of function. Mammalian cochlear hair bundles have unusual morphologies and interstereocilia connectivity that is not as tight as other inner ear end organs. There is considerable debate as to the mechanisms underlying processes impacting MET currents and hair bundle mechanics, like fast and slow adaptation, gating compliance and voltage driven responses. There is further controversy over whether we truly have causal links between MET current responses and mechanical, molecular mechanisms. Before being able to use the power of genetic manipulation of newly identified MET molecules, we need a clear understanding of hair bundle biophysical properties and how they impact MET receptor currents. We hypothesize that the lack of connectivity in bundle motion is to optimize the hair bundle's response to natural stimulation and that synchronization of stereocilia comes from the tectorial membrane (OHCs) or the fluid stimulation (IHCs). We further hypothesize that we will identify mechanical correlates for fast and slow adaptation as well as gating compliance; however, we do expect there to be less slow adaptation as compared to other hair cell types but also that the mechanism of slow adaptation will not align with classical theories. And finally. we hypothesize that MET channel properties work with hair bundle mechanics to create tuning of the receptor current. We will investigate each of these hypotheses in the following specific aims. SA1 will generate a comprehensive data set of MET channel and hair bundle properties at multiple frequency positions from rats and mice P10-12 of age. By taking advantage of three modes of stimulations, wide probe, fluid jet and the newly developed narrow probe, we can separate between MET channel and hair bundle properties. SA2 will directly address hair bundle mechanics and known hair bundle properties using the newly developed high-speed imaging with either narrow probe or fluid jet technology. Experiments will target MET channel gating compliance, fast and slow adaptation and voltage dependent mechanical hair bundle responses. SA3 will generate frequency response curves under physiological conditions using the wide probe and fluid jet to define the filtering properties of the channel and the hair bundle. Completion of these aims will provide an unprecedented level of quantitative information as to how the hair bundle moves and how this motion shapes the MET receptor current generated. They will be the standard by which molecular manipulations can be assessed.

NIH Research Projects · FY 2024 · 2023-09

Project Summary In the US, Alzheimer’s disease (AD) is the sixth leading cause of death, affects 11% of the population over age 65, and costs $355 billion each year. One of the first impairments in AD is spatial memory, which involves the hippocampal area CA1. CA1 encodes new information, driven by inputs from medial entorhinal cortex (MEC), and retrieves and consolidates old information, driven by inputs from hippocampal area CA3. Hippocampal inhibitory neurons, which are lost early in AD, can reduce the influence of, or gate, these inputs. However, we do not understand how loss or dysfunction of inhibitory neurons in AD affects inputs to CA1 and how this subsequently disrupts spatial representations and thus memory. This proposal will explore the dynamics of inputs to CA1, as gated by inhibitory neurons, and its effects on spatial memory, as an avenue for AD treatment. My central hypothesis is that loss of CA1 somatostatin-expressing inhibitory neurons ungates MEC inputs to CA1 during retrieval and consolidation, destabilizing spatial maps and impairing memory in AD. I will examine this hypothesis using a chronic recoverable implant design I have developed which enables simultaneous recording from dozens of neurons in CA1, CA3, and MEC. I will record neural activity while wild type and AD model mice encode, consolidate, and retrieve memories in a spatial alternation task and spatial contexts. During these three memory phases, I will measure: CA3 and MEC input drive to CA1 and its dynamics over learning (Aim 1), the relationship between CA1, CA3, and MEC spatial maps (Aim 2), and the firing patterns of CA1 somatostatin- expressing and parvalbumin-expressing inhibitory neurons (Aim 3.1). I will then stimulate each inhibitory neuron type in aged AD model mice during each of the three memory phases to rescue the deficits identified in Aims 1, 2, and 3.1 (Aim 3.2). This research will advance our understanding of how the hippocampus dynamically encodes, retrieves, and consolidates information, how it goes awry in AD, and how it can be treated, advancing Goal 1B of the National Plan to Address AD. My expertise in spatial memory, in vivo electrophysiology, and AD makes me uniquely qualified to pursue this novel line of research at the intersection of basic and translational neuroscience. These aims will be supported by an exceptional mentoring team of Drs. Lisa Giocomo, Tony Wyss-Coray, and Scott Linderman, advisory team of Drs. John Huguenard, Ivan Soltesz, and Gareth Howell, and training environment of Stanford University. This research will provide me with crucial training in neural data statistics, mechanisms of neurodegeneration, evidenced-based inclusive mentorship, and lab management. This project and the training it provides will open new lines of inquiry about the role of hippocampal inhibitory neurons in healthy, aged, and AD conditions and facilitate my transition to an independent faculty position.

NIH Research Projects · FY 2024 · 2023-09

ABSTRACT How to ensure adherence to computerized cognitive training in unsupervised circumstances (e.g., at-home, self- administered) in older adults at risk for Alzheimer’s disease (AD) or AD related dementia (AD/ADRD) is understudied. The objective of the R61/R33 is to refine and test a novel facial expression-based personalization engine (FPE) for monitoring and modulating real-time effective engagement, with an ultimate goal of enhancing long-term adherence in unsupervised cognitive training in older adults at risk for AD/ADRD. Here, Effective engagement is defined as the extent to which someone is actively engaged and performing with significant attention and enjoyment while training, addressing a balance between adherence and cognitive gains/plasticity from the training. Based on previous work, including ours, we hypothesize that (1) mental fatigue revealed in facial expressions will reflect a trainee’s degree of effective engagement, which can be modified by modulating task novelty; (2) our proposed FPE will ensure the effective engagement in cognitive training by monitoring trainee facial expressions and modulating training in response, promoting the trainee’s long-term adherence to the training and cognitive plasticity. In R61 (Y1-Y2), we will generate the FPE for monitoring and modulating real- time engagement in cognitive trainings in older adults at risk for AD/ADRD by refining our established application programming interface using a Stage I design. In R33 (Y3-Y5), we will conduct a Stage II intervention efficacy study comparing effective engagement and adherence in unsupervised cognitive training between training programs with vs. without FPE in older adults at risk for AD/ADRD. We will address milestones proposed in both stages to (a) ensure the readiness of the proposed FPE for R33 (R61 milestone) and (b) evaluate and further revision of FPE for future implementation test (R33 milestone). Impact: the proposed FPE may assist in monitoring and improving effective engagement and adherence in older adults with unsupervised cognitive training. In the current application, we will test FPE in a cognitive training program called speed of processing training. However, such FPE may be embedded to any computerized cognitive training in future studies to help address adherence related issues.

NIH Research Projects · FY 2025 · 2023-09

Summary Macrophages are among the earliest immune cells present during fetal development. Different populations of macrophages have distinct functions, with early yolk sac derived macrophages having an immune tolerant function and later liver derived macrophages having a more robust inflammatory profile. In the mouse lung, the inflammatory profile of liver derived macrophages increases late in development and peaks around the time of birth. This pro-inflammatory phenotype of fetal macrophages conflicts with previous notions that the fetal immune system resides solely in a tolerant state. Inflammatory macrophages may function to protect the developing fetus and newborn from pathogens encountered right at birth, but might also contribute to inflammatory disease pathogenesis, particularly in infants born preterm. We hypothesize that newly formed macrophages arising from the fetal liver are programmed for inflammation via the IKKb/NF-kB pathway. However, once macrophages travel to various organs in the developing fetus, they may adopt tissue-specific features. This proposal will use state of the art, complementary approaches to measure developmental changes in the immune signature of fetal macrophages within developing mouse tissues. Experiments using knockout mice will test if canonical IKKb/NF-kB signaling is required for the pro-inflammatory phenotype. While the myelopoietic cytokine GM-CSF is known to promote alveolar macrophage differentiation in the lung after birth, our preliminary data suggest it may also regulate the inflammatory phenotype in fetal lung macrophages. Studies using Csf2 (the gene encoding GM-CSF) knockout mice will test the requirement of GM-CSF on the developing lung immune system and specifically macrophages. The project will bring together experts in developmental immunology and computational modeling and employ novel, cutting edge approaches to complex systems immunology. The results generated by this proposal will fill a significant gap in our understanding of the fetal immune system and the unique functional properties of macrophages protecting newborns.

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY Aging is the main risk factor for a variety of brain diseases, such as stroke and neurodegenerative diseases. Additionally, recovery from stroke and other types of brain injury declines with age. There is an unmet need for the development of more effective therapies centered on aging to counter the decline in repair capacity and the onset of neurodegenerative diseases. The adult brain contains neurogenic stem cell niches that have the potential to generate new progeny that migrate to distal sites, which could play a critical role for repair in age- related disease and injury. During aging, neural stem cells show a progressive loss in their ability to proliferate and give rise to new neurons (neurogenesis), and this is accompanied with a decline in repair ability. However, the mechanisms underlying this deficit are not well understood. My preliminary findings suggest that aging leads to changes in cell migration and adhesion abilities in neural stem cells, with activated neural stem cells and their progeny becoming less migratory with age. Based on these findings, my specific hypothesis is that with age, activated neural stem cells undergo reversible changes in cell migration and adhesion that lead to decreased neurogenesis. My proposal aims to elucidate the mechanisms underlying the age-related decline in migration in activated neural stem cells and uncover therapeutic strategies to mitigate this. Aim 1 will identify specific genes and regulatory factors that underlie the migratory defect in old activated neural stem cells and perturb them to boost the migration of old cells. Aim 2 will evaluate the therapeutic potential of blocking a signaling pathway that is important for regulation of cell migration and adhesion for repair upon stroke injury and explore the mechanisms by which it does so. Together, these independent aims will contribute to the field by giving a mechanistic understanding of how age causes a decline in neural stem cell function through dysregulation in cell migration and adhesion as well as provide a potential therapeutic avenue for improving neurogenesis and recovery from stroke in old brains. Through this work, I will be trained in the field of aging and neural stem cells as well as gain diverse expertise in cutting-edge experimental approaches. My scientific training coupled with mentoring by physician-scientists will help me in building a career as a physician-scientist interested in brain aging and treating patients with neurological diseases.