Stanford University

NIH Research Projects · FY 2025 · 2023-05

REGULATION OF SKIN HOMEOSTASIS BY RNA-BINDING PROTEINS PROJECT SUMMARY/ABSTRACT One in four Americans are affected by skin disease, intensely motivating an understanding on the mechanisms underlying epidermal homeostasis. RNA-binding proteins (RBPs) and the main arginine methyltransferase PRMT1 are required for the control of keratinocyte proliferation and differentiation. We have identified two nucleolar RNA helicases and multiple PRMT1 targets that are required for normal skin homeostasis. We have also identified PRMT1 itself is an RBP. A long-term goal of my research is to understand homeostatic mechanisms in skin; the goal of this K01 application is to characterize the roles of RBPs in epidermal homeostasis, specifically the two helicases, PRMT1 and PRMT1 target RBPs. In Aim I, we will test our model for PRMT1’s maintenance of the progenitor state in keratinocytes. Our preliminary data indicates that five stable RBP interactors of PRMT1 – which are also targets of its methyltransferase activity – are also required to maintain homeostasis. In Aim IA, we test the consequence of arginine methylation on these RBPs. In Aim IB, we test the effect of these RBPs and their methylation on gene expression in keratinocytes. In Aim II, we test our model for how RNA helicases promote keratinocyte differentiation. Our data suggests two helicases are sequence-specific, pre-mRNA-binding proteins that promote differentiation by departing the nucleolus to regulate splicing and potentially transcription. Our results also suggest that these helicases can form homo- and heterodimers, with the heterodimer being the strongest interaction. In Aim IIA, we will test their role in transcriptional control of keratinocyte differentiation and whether their apparent control of splicing is direct. In Aim IIB, we will evaluate their dimerization state and its relation to their role in homeostasis, splicing and transcription. My background is in RBP biochemistry, bioinformatics, methods development, and CLIP-seq. Over the course of the training period and within the environment of Stanford’s Department of Dermatology, I plan to acquire expertise in (1) epithelial biology, (2) proteomics, (3) machine learning, and (4) statistics. My research interest in skin biology requires this broad skill set, and this research plan will prepare me for an independent career as an academic scientist working on the mechanisms of gene regulation in epithelial tissue.

NIH Research Projects · FY 2026 · 2023-05

Project Summary The cellular makeup of tumors can radically influence response to treatment, and survival outcomes. Biomarkers derived from tumor biopsies have had modest success in their clinical utility for prognosis or guiding treatment decisions, being confounded by factors such as cellular composition of tissues Moreover, different biomarkers may be needed in female vs male patients. In prior work we showed how meta-analysis of large clinically annotated public cancer datasets with clinical annotations can robustly identify specific genes and processes associated with survival for patients in both pan-cancer and cancer-specific ways. Here we still systematically investigate cancer-specific prognostic cell types through integration of single cell RNA-seq (scRNAseq) with bulk RNA-seq and methylation data. We will validate selected findings in tissue microarrays. First, we will identify cancer-specific cell transcriptional states and ecosystems associated with survival and treatment response, extending prior work that identified 10 different “ecotypes” of co-occurring cell states across carcinomas. Second, we will extend our framework to isolate cancer-specific cell-type-specific methylation profiles and their correlation with imputed gene expression across populations using paired bulk RNA-seq and methylation from TCGA. Third, we will validate survival associations of cancer- specific cell states by staining human tissue microarrays. We will focus on high grade serous ovarian cancer (HGSOC), which has dire prognosis, and non small-cell lung cancer (NSCLC) for which we have extensive information on immunotherapy response. We will use CODEX imaging on large tissue sections to assess the spatial organization of outcome-related cell states in NSCLC and HGSOC. Overall, we will comprehensively map cancer-specific cell states and ecotypes across malignancies, identifying potential biomarkers and possible new therapeutic targets.

NIH Research Projects · FY 2026 · 2023-05

Abstract: Sensory hair cells are required for balance function. Vestibular hair cell degeneration causes balance dysfunction manifested as dizziness and vertigo. In mice, a limited degree of spontaneous regeneration occurs in the utricle, a vestibular organ detecting linear acceleration. Moreover, addition of the transcription factor Atoh1 robust enhances regeneration of hair cells in the mouse utricle, but regenerated hair cells mature only partially relative to native hair cells. In preliminary experiments, we have characterized a novel AAV-ATOH1 construct leading to regeneration of more mature hair cells in the mouse utricle. With the long-term goal of regenerating human hair cells to restore balance function, two major obstacles remain: 1) we have an incomplete understanding of the molecular signatures of human hair cells, supporting cells and hair cell precursors, 2) adult human inner ear tissues are not readily available to test promising therapeutics discovered in animal models. To overcome these obstacles, we have designed a surgical method to procure live utricles from deceased organ donors who typically have normal auditory and vestibular function. We have begun assembling their medical records, single-cell transcriptomes, and histologic sections of utricles. In parallel, we have procured utricles from vestibular schwannoma patients undergoing surgical resection. Here, we propose to increase the recruitment of organ donors and vestibular schwannoma patients and delineate and validate the transcriptomes of hair cells, supporting cells, and hair cell precursors in adult human utricles in these two cohorts (Aim 1). Furthermore, we will determine whether our novel AAV-ATOH1 enhances hair regeneration and maturation in cultured human utricles (Aim 2). Another goal of this award is to further my career as an investigator and mentor in patient- oriented research. To build on my previous experience in bench research and mentoring, this award is designed to protect my time and help me gain knowledge and skills to 1) study human hair cell regeneration and 2) mentor others pursuing patient-oriented research. In summary, we will apply state-of-the art technologies (single-cell RNA-sequencing, gene therapy, bioinformatic strategies) to study vestibular hair cell regeneration in live human utricles. We have assembled a team of collaborators and experienced mentors in patient-oriented research. At the end of this 5-year proposal, we will have 1) delineated transcriptomes of human hair cells, supporting cells, and hair cell precursors, 2) revealed whether novel AAV-ATOH1 enhances regeneration and maturation of human vestibular hair cells, and 3) enhanced my ability to perform and mentor others in patient-oriented research in sensory disorders.

NIH Research Projects · FY 2026 · 2023-05

Abstract More than 50% of youth will experience at least one form of significant adversity in early life. Such adversities pose significant risk not only for the development of psychopathology over the life course, but also for attempted suicide, a leading cause of death in people ages 10-24 years. We have recruited and assessed 220 9- to 13-year-old boys and girls across four timepoints, each two years apart, to examine the effects of exposure to ELS on trajectories of stress reactivity and reward sensitivity, and, in turn, their impact on the onset of psychopathology and suicidal behaviors across adolescence. In this cohort we have conducted repeated measurements of symptoms and diagnoses of psychopathology, neural, endocrine, cognitive, immunological, and behavioral assessments of stress reactivity and reward sensitivity, and early exposure to adversity, including the type, severity, and timing of stressful events. We have published a series of papers from this project elucidating the effects of ELS on psychobiological functioning, trajectories of brain development, and biological aging, and the consequences of these alterations for clinical functioning. In this MERIT renewal application, we propose to build on and extend our work in three important ways. First, we will conduct an additional assessment of our participants at age 20 in order to examine the effects of ELS on trajectories of neurodevelopment and clinical outcomes from childhood to young adulthood, as well as the persistence of COVID-19 pandemic-related difficulties in mental health, stress, and brain metrics. We will also extend our examination of how environmental pollutants and conditions affect relations among these variables. Second, we will extend and replicate our findings in a younger, non-Western sample by analyzing data from the Growing Up in Singapore Towards Healthy Outcomes (GUSTO) project, an ongoing prospective study in which many of the same, or comparable, measures that we administered in our project have also been collected regularly from approximately 1,500 parents and children since the prenatal period. Extending and replicating our findings with the GUSTO dataset, which includes younger, non-Western children from Southeast Asian families in Singapore, will complement findings from other large cohorts, like ABCD and NCANDA, that have assessed only Western participants. Finally, will leverage our own and GUSTO data to examine the effects of the COVID-19 pandemic shutdown on children’s and adolescents’ psychobiological functioning. In both datasets we have a unique opportunity to compare comprehensive psychobiological data collected from the same youth before and after the pandemic shutdowns in order not only to examine how the pandemic has altered young people’s psychobiological functioning and development, but importantly, to also identify risk and resilience factors across cultural contexts. Further, the new proposed adult assessment in our ELS project will allow us to examine the persistence of COVID-related difficulties by re-assessing participants whom we studied soon after pandemic quarantine restrictions ended.

NIH Research Projects · FY 2025 · 2023-05

Store-operated Ca2+ entry (SOCE) generates Ca2+ signals that are critical for many physiological processes, from immune cell activation and differentiation to muscle activity, secretion, and motility. Store-operated Ca2+ channels (SOCs) are activated by receptors that deplete Ca2+ from the ER; the loss of Ca2+ is sensed by STIM1, which then accumulates at ER-plasma membrane (ER-PM) junctions where it binds, traps, and activates calcium-selective Orai channels diffusing in the PM. Gain-of-function and loss-of-function mutations in this pathway have both been connected to serious human diseases, underscoring the critical importance of precise regulation. The long-term goal of our laboratory is to understand the molecular basis of SOC properties and regulation as well as their cellular roles. While the overall organization of the SOCE pathway is now known and many of the underlying proteins have been identified, major gaps still exist in our understanding of how they act to regulate SOCE location and amplitude. Over the next five years we aim to investigate three fundamental processes that regulate calcium influx through SOCs. (1) The dynamics of ER-PM junctions. These junctions where the ER closely approaches the PM are the only sites in the cell where STIM can bind and activate Orai, such that their size, abundance and location determine both the amplitude and location of Ca2+ entry. While a host of tethering proteins at junctional sites is known, their specific roles in junction initiation vs. turnover is unclear. By monitoring the appearance and removal of ER-PM junctions in living cells with fluorescent markers we will distinguish the different contributions of known tethering proteins to the initiation, lifetime and turnover rate of new junctions, as well as their ability to conduct SOCE. (2) The mechanism of STIM1 activation and its interaction with Orai1. The cytosolic domain of STIM1 undergoes a massive conformational change after ER Ca2+ depletion in order to unmask and extend the CRAC activation domain (CAD) to activate Orai in the plasma membrane. By studying STIM1 with single-molecule fluorescence and crosslinking techniques we aim to identify steps in the activation process and intermediate states that may help mitigate the energetic cost of unfolding and refolding STIM1. Similar approaches will be applied to determine basic features of the STIM-Orai interaction - the stoichiometry of the STIM-Orai complex, the conformation of CAD in the bound state, and the binding interface itself – which are currently not understood. (3) A molecular mechanism for Ca2+-dependent inactivation (CDI). Despite progress in identifying multiple residues and domains in STIM and Orai that are critical for CDI, an integrated mechanism is still lacking. We will use a pore accessibility assay to localize the position of the inactivation gate, and explore functional and physical interactions of CDI domains to understand how they cooperate to bring about CDI. Overall, the results of our studies will reveal fundamental cellular and molecular mechanisms that control the strength of store-operated calcium signals in diverse cells, and may suggest new strategies for regulating them to explore cellular functions and develop new treatments for human disease.

NIH Research Projects · FY 2025 · 2023-05

Project Summary/Abstract Auditory sensory hair cells transduce sound using a bundle of actin-filled cellular protrusions called stereocilia which are coupled together by tip links, top connectors and side connectors, and fluid forces. Activity of mechanoelectrical transduction (MET) channels, located near the tops of the shorter stereocilia, are modulated by the differential motion of stereocilia as conveyed via the tip link connection. Thus, stereocilia motion regulates the open probability of MET channels which drives communication of sound to the brain. The fundamental goal of this proposal is to characterize the mechanical underpinnings of the stereociliary connections that shape the force applied to MET channels. Many human deafness genes affect the molecular components of the MET machinery, including tip links and MET channels. The biophysical characteristics of components coupling the bundle dictate how they filter stimuli. Understanding the mechanical properties of coupling in mammalian hair bundles is essential to our understanding of hair cell function and hearing (Aim 1, 2). We hypothesize that channel open probability reflects tension in the tip link and that changes in hair bundle stiffness associated with channel gating will be present in mammalian cochlear hair bundles. To test these hypotheses, hair bundle mechanics will be investigated using newly developed technology that uses a ~1 µm diameter stiff probe to push on 1-3 stereocilia which will displace the remaining stereocilia through the connections coupling them. High- speed motion tracking will be used to reveal the rapid (<100 μs) movements of individual stereocilia in rows 1 and 2, allowing for characterization of stereociliary connectivity while whole cell voltage clamp provides the MET current response. The MET machinery and its regulation by calcium will be examined by raising or lowering open probability by changing intracellular free calcium levels, disrupting the tip link connections (Aim 1), and with channel blockade (Aim 2). The experiments in this proposal, their analyses, and the dissemination of their findings will serve as strong technical training for the applicant, providing the tools necessary to become an internationally competitive, rigorous, and independent research scientist. Professional development will be provided by experiences within the laboratory setting, the department, as well as by the environment and resources provided by Stanford University. Technical and career development are provided through excellent workshops, seminars, conferences, and collaborations with outstanding researchers inside and outside Stanford. The research training plan outlined in this proposal is designed to create a pathway to independence where both the technical expertise and foundational data will provide the cornerstone for independent work.

NIH Research Projects · FY 2026 · 2023-05

The mammalian cortex is spontaneously active even in the absence of external stimuli. Initially dismissed as neural noise, pioneering work established that the internal brain states produced by spontaneous activity are highly structured and responsible for the dramatic variability in both neural and perceptual responses to the same sensory stimulus. The discovery that varying spontaneous cortical states (SCS) drive different responses to identical stimuli suggested that altered perceptions of the environment across psychiatry could derive from aberrant SCS. On this basis, ongoing resting state fMRI studies continue to search for reproducible links between SCS and psychiatric diagnoses, including schizophrenia, depression, and PTSD, among others. Yet our fundamental understanding of the cognitive processes and circuit mechanisms underlying SCS remains limited. One leading theory, drawn from human fMRI recordings during visual detection tasks, suggests that SCS represent predictions about the environment. In this model, predictive spontaneous cortical states influence perceptual decision making on the basis of prior beliefs. However, several critical gaps remain in this theory. At present, there is no causal evidence, either through closed-loop behavior or direct neural modulation, linking SCS to perceptual decisions. Moreover, the circuit mechanisms of SCS, including the role of interneurons in producing SCS and specific cortical areas in driving spontaneous cortex-wide states, are completely unknown. My proposal aims to address these knowledge gaps by investigating SCS in a mouse model. Having trained mice in a two-alternative forced choice visual detection task, I have applied optical imaging of the dorsal cortex to find that specific spontaneous states predict behavioral response. Leveraging my preliminary data, I will investigate how specific interneuron types contribute to SCS (Aim 1), test the causal influence of predictive SCS over perceptual decisions through a closed-loop behavior (Aim 2), and apply optogenetic modulation of neural activity to test the role of a specific cortical area, the retrosplenial cortex, in driving predictive SCS (Aim 3). The proposed studies will offer novel insights into the neurocognitive mechanisms underlying spontaneous activity, including in human resting state fMRI. In the process, I will supplement my background in human resting state neuroimaging with critical training in rodent behavior, psychophysics methods, and optogenetics. My proposal will be guided by a world-class advisory committee consisting of my primary mentor Dr. Karl Deisseroth, an expert in optogenetics and animal behavior, Dr. Michael Stryker, a mouse visual system expert, Dr. Brian Wandell, an expert in perceptual decision making, Dr. Robert Malenka, a rodent nervous system expert, and Dr. Nolan Williams, an expert in human neuromodulation. I will further take full advantage of the vibrant training environment at Stanford by engaging in targeted coursework and high-quality professional development. By the end of the fellowship, I will be positioned to launch a career as an independent investigator studying how the neurocognitive processes embedded in spontaneous activity contribute to psychiatric illness.

NIH Research Projects · FY 2025 · 2023-05

Project Summary/Abstract Red blood cell (RBC) transfusions are commonly administered in the pediatric intensive care unit (PICU) with the goal of increasing oxygen delivery; however, storage of RBCs may limit efficacy to prevent or reverse oxygen debt. RBC transfusions have been independently associated with increased PICU morbidity and mortality and impart additional risk to patients due to infectious and non-infectious serious hazards of transfusion. Evidence-based guidelines were developed to restrict transfusion to those patients most likely to benefit. Liberal transfusion practices persist; however, placing nearly one quarter million children annually admitted to the PICU at risk for harm from transfusions. Threshold-based guidelines exist for hemodynamically stable patients with a hemoglobin (Hb) >7 g/dL where evidence is robust, whereas clinical judgement is recommended when Hb is 5-7 g/dL or in hemodynamically unstable patients with a Hb > 7 g/dL. Qualitative study of barriers and facilitators to implementation of the transfusion guidelines and intervention mapping informed the development of a bundle of implementation strategies directed at addressing specific contextual barriers to routine adoption of the transfusion guidelines in the PICU. The bundle of strategies, informed by the Consolidated Framework for Implementation Research (CFIR) includes building consensus, identifying, and empowering champions, educating providers, use of integrated computerized clinical decision support (CCDS) tools, and providing quantitative metric-based feedback to providers. The proposed pilot study aims to address two critical gaps in operationalization and evaluation of the implementation bundle across institutions that are necessary prior to execution of a multi-center type 2 hybrid effectiveness and implementation trial to formally evaluate the implementation bundle. These include the need for 1) validated, electronic cohort characterization of patients at-risk for unnecessary RBC transfusion and 2) optimization and integration of CCDS tools, which are anticipated to pose the greatest operational challenges in a multi-site study. Thus, we propose the following specific aims: Specific Aim 1. Create and validate a computable phenotype for a dynamic cohort of PICU patients at-risk for unnecessary transfusion, including children eligible for threshold-based and/or clinical judgment-based CCDS tools Specific Aim 2. Deploy and assess implementation of Computerized Clinical Decision Support (CCDS) tools as one component of the transfusion implementation bundle. Evaluation of the CCDS tools using a customized version of the RE-AIM evaluative implementation framework for clinical informatics will facilitate further optimization of the tools.

NIH Research Projects · FY 2026 · 2023-05

7. Project Summary/Abstract Adult human skin heals by developing fibrotic scar tissue, which can result in devastating disfigurement, growth restriction, and permanent functional loss. Despite a plethora of clinical options, no current treatment strategies successfully prevent or reverse this fibrotic process, and scars and their sequelae cost the United States over $20 billion every year. Progress towards the development of new therapies has been significantly hindered by a lack of understanding of the cell populations responsible for scarring and their molecular dynamics. Studies in recent years have reported that adipocytes in wounds are capable of transitioning into fibroblasts (and vice versa); however, the extent to which adipocyte-to-fibroblast transition contributes to wound fibrosis (scarring), and whether this process can be targeted to prevent scarring, remain unknown. In this proposal, we explore for the first time the role of tissue mechanics in conversion of dermal adipocytes to scarring fibroblasts within the wound environment. First, employing genetic lineage tracing, we will use histology, immunohistochemistry, and flow cytometry to study adipocyte-to-fibroblast transition and to interrogate the molecular phenotype of adipocyte lineage-derived fibroblasts within wounds. Second, we will use a Rainbow mouse model to interrogate clonal dynamics of adipocyte-to-fibroblast transition in wounds, and will apply an integrated multi-omic analysis, with single-cell transcriptomic (scRNA-seq) and epigenomic (scATAC-seq), spatial transcriptomic (Visium) and proteomic (CODEX), and quantitative extracellular matrix (ECM) ultrastructural analyses, in order to robustly define the molecular drivers and pathways involved in adipocyte-to-fibroblast conversion during scarring. Third, as our preliminary data strongly support a mechanotransduction mechanism underlying adipocyte-to-fibroblast transition during wound healing, we will inhibit mechanical signaling in adipocytes using both small molecule and transgenic approaches in order to block adipocyte-to-fibroblast transition. We will apply a similar multi-omic analysis to elucidate the molecular dynamics that differentiate wound adipocyte dynamics in the context of intact versus blocked mechanical signaling and determine how inhibiting mechanically driven adipocyte-to-fibroblast conversion may reduce fibrosis and yield wound regeneration. Our ultimate translational goal is to develop therapeutics that target fibrogenic wound cell dynamics to promote regenerative healing. Collectively, the proposed work will significantly enhance our understanding of the key molecular and cellular determinants of cutaneous scarring, inform the development of novel anti-scarring therapies, and shed light on the contributions of adipose tissue to wound fibrosis.

NIH Research Projects · FY 2025 · 2023-04

CD5+ B-1a cells are innate-like B cells in mouse and man. They emerge during fetal/neonatal development independent of the bone marrow (BM)-derived progenitors that later give rise to follicular B-2 cells. In essence, we see B-1a and B-2 (follicular B cell) as having evolved sequentially to create B cell layers that provide progressively more complex immune capabilities, including, for B-1a, the induction of self-tolerance. Thus, we show here that 1) B-1a express high levels of Aire, which promotes the expression/presentation of self-antigens by thymic APCs and hence promotes the induction of T cell tolerance; 2) B-1a activation and Aire induction in neonatal thymus depends on CD4+ T cell-mediated CD40 signaling, and requires T cells expressing a special repertoire; 3) Partial ablation of Foxp3+ CD4+ regulatory T (Treg) cells in neonatal thymus results in decreased numbers of thymic B-1a; and, reciprocally, 4) Depletion of thymic B-1a cells during neonatal life decreases Treg generation. Together, these findings demonstrate that B-1a cells interact with CD4+ thymocytes in neonatal thymus to generate cross talk that activates B-1a cells to differentiate to Aire+IgMnegIgDnegCD5+ APCs; and, 5) these cells in turn participate in the selection of neonatal Treg cells that play a key role in inducing/maintaining self-tolerance (21-23). In earlier studies, we have shown that T cell tolerance to B cells is impaired in B cell-deficient µMT mice, i.e., CD4+ T cells in µMT mice inhibit B cell reconstitution in adult µMT hosts. Most significantly, we find that B-1a cells in neonatal µMT mice condition CD4+ T cells to enable establishment of follicular B cells (24). Further, we find that Treg generation in neonatal µMT mice is decreased and, most strikingly, that Treg cells from normal neonatal mice suppress the inhibitory function of µMT CD4+ T cells, as these cells enable B cell reconstitution in µMT hosts when co-transferred with BM whereases co-transfer of Treg cells from µMT mice fails to do so. Taken together, these findings lead us to propose that B-1a cells play a key role in inducing T cell tolerance to B cells in neonatal thymus, where the B-1a cells interact with CD4+ thymocytes, internalize surface IgM, differentiate to Aire+IgMnegIgDnegCD5+ APCs, and then, select a population of neonatal Treg cells that confer B cell-tolerance. Studies proposed here will test this hypothesis and will clarify the B cell tolerance induction mechanism that is induced by B-1a and regulated by Treg in neonatal thymus. Findings from this study will thus shed key light on the fundamental mechanisms that governs the induction of neonatal immunological self-tolerance, and will offer new insights into the autoimmune diseases to which Aire-mediated B-1a cell function contributes.

NIH Research Projects · FY 2025 · 2023-04

Abstract Understanding somatic genomic variation presents unique challenges, primarily stemming from the individual rarity of most somatic mutations across cells in a multicellular organism. Hence, both sensitivity and accuracy (due to the need to distinguish somatic variation from noise) become crucially important. The Analysis of bulk DNA, even with ultraprecise approaches, only ascertains a portion of the human genome. The analysis of single cells, either by cloning or in vitro whole- genome amplification (WGA), enables discovering theoretically all mutations in a cell independent of their frequency in bulk. However, amplifying single cell genomes in vitro represents still a significant challenge in terms of accuracy of amplification. The novel PTA technique (primary template directed amplification) offers substantially improved quality of amplified DNA. However, PTA produces a relatively small amount of DNA fragments of moderate length. This limits the application of long read sequencing. Long read sequencing is expected to be the most comprehensive approach to somatic mutation detection. In the proposed project, we will, first, perform long-read sequencing in single cells cloned via the production of iPSC lines to study somatic mutation of all types using non-enzymatically amplified genomic DNA, from telomere to telomere, and generate a gold-standard benchmarking resource for methods development. Second, we will address a significant shortcoming of the analysis of single cell genomes, which is the lack of direct information about the exact type of cell being analyzed, or about potential functional consequences of mutations in that cell. For that, we will benchmark the new ResolveOme method, an expansion of PTA, that can analyze in parallel the genome and transcriptome of a single cell. Third, we will address the challenge of high-throughput analysis of single cells to detect somatic structural variants. Specifically, we will establish and benchmark for SMaHT the Strand-seq method that allows for high-throughput detection and characterization of structural variants (SVs) in single cells. Together, this will address 3 critical needs in the analysis of somatic mutations in normal tissues: comprehensive mosaic mutation discovery, phenotyping the cell harboring mutations and directly assessing functional consequences of mutations, and accurate and high-throughput detection of SVs. Another important aspect of the project will be comprehensive comparative analyses of detected somatic variants across all Aims.

NIH Research Projects · FY 2026 · 2023-04

Alzheimer’s Disease (AD) is one of the most devastating diseases in older adults, in which sleep disorders and cognitive function impairments usually require institutional care. A bidirectional link between alterations in sleep patterns and AD has been proposed by multiple authors. We have recently identified a new mechanism of sleep fragmentation in aged animals that involves downregulation of voltage-dependent KCNQ potassium channels in arousal-promoting hypocretin (Hcrt)-producing neurons. Aβ accumulation may also contribute to sleep fragmentation since sleep architecture is disrupted in both amyloid precursor protein knockin (APP-KI) and APP/PS1 animal models of AD, as well as human AD patients. These data strongly suggest a causal involvement of sleep alterations, Aβ accumulation in the progression of AD. Here propose to: i);monitor the activity of wake-promoting Hcrt and LC neurons in the context of AD and determine whether Aβ changes their intrinsic properties in slice recordings; ii) determine whether Aβ affects the activity of NREM and REM sleep-active neurons and their ability to maintain sleep archtecture; iii) determine whether pharmacological or optogenetic sleep enhancement delays Aβ accumulation and improves cognitive function in two mouse models of AD. The proposed pharmacological experiments targeting arousal circuits have high translational potential to increase sleep quality in the elderly and slow disease progression in AD patients.

NIH Research Projects · FY 2025 · 2023-04

ABSTRACT There is an urgent need to diversify the research workforce to meet current and future research demands that support a healthy aging society. Lack of diversity is an important problem in Medicine, Science, Technology, Engineering and Mathematics (MSTEM), where inadequate institutional preparation and economic challenges can serve as barriers to entry. Population health sits at the nexus of the MSTEM fields and thus a training program in population health aging research is uniquely suited to serve as a bridge linking underrepresented students to multiple MSTEM disciplines. Moreover, these fields are critical for developing solutions to support health equity in aging. Our goal is to support scholars from backgrounds underrepresented in MSTEM fields in the academic pathways to graduate education and research in aging and population health. The Stanford Population Health Aging Research - Advancing Health Equity and Diversity (PHAR-AHEaD) summer program is an 8- week training and research experience for college students from underrepresented and historically excluded groups in the health sciences. We bring together a diverse team of over 25 faculty members from across Stanford University to foster an inclusive academic environment where college students can explore the core foundations of population health sciences under the umbrella of a life course perspective on aging. Population health integrates a spectrum of disciplines; a unique strength of our program is the breadth of training in aging, epidemiology, statistics, health policy, and community engagement. We pair this instruction with a faculty mentored research project to build skills and support student contributions to team science. We enrich students with professional development opportunities to learn the “hidden curriculum” of academia; these unwritten lessons and values are disproportionately inaccessible to students from historically excluded backgrounds. PHAR-AHEaD was founded on the principles that research experiences, faculty networks, and professional development are crucial components in graduate school admissions and future success as a researcher. Access to these opportunities is not equitably distributed, leading to underrepresentation and exclusion in the field. We are committed to reducing known barriers and creating a more equitable educational experience. This program will ignite interest and lower the barriers for students from historically excluded and underrepresented groups to pursue further studies and careers in aging and population health research.

NIH Research Projects · FY 2026 · 2023-04

ABSTRACT Tumor infiltrating lymphocytes (TILs) are an important component of the immune cells that reside in the tumor microenvironment (TME). The type and number of TILs in the TME have an impact on overall survival and are an indicator of response to immunotherapy. Despite their importance as an indicator of a patient’s immune response to cancer, there are multiple challenges for analyzing TILS from large population data sets involving thousands of samples. There is a lack of methods that can automate an analysis of histopathologic images for different features such as the spatial distribution of TILs, their topological interactions with their neighboring cells in the TME and their association with specific clinical outcomes. Even more challenging is integrating TIL metrics with cancer genomic data. Most other methods provide qualitive metrics of TILs and frequently rely on manual inspection from pathologists – this approach lacks scalability and is subject to observer bias. To address these challenges, we developed a computational framework that uses a deep learning model to identify multiple cell types from histopathology images. The major innovation of our approach is molecular label transferring that annotates tens of thousands of small areas extracted from histopathology images without manual inspections. This approach is highly accurate, efficient, scalable and readily automated for the analysis of millions of images. The objective of this project is to address a key challenge in the application of deep learning to histopathological image: large number of labeled images as training data set. We have three specific aims to 1) identify spatial quantification of TILs from over 10,000 histopathological images from the Cancer Genome Atlas Project; 2) correlate TIL metrics with clonal tumor mutation burden (TMB); 3) determine association of TILs with immune checkpoint blockade responses. This research is significant because our approach enables for a comprehensive characterization of TILs from histopathological images at cellular level, using data that is commonly accessible in clinical settings and can be readily integrated with cancer genomic data.

NIH Research Projects · FY 2025 · 2023-04

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 use disorder (OUD) has proven to be a debilitating and deadly disease. Vulnerable populations including the homeless; racial and ethnic minority groups; people in poverty; and rural residents often bear the highest burden. Previous research suggests that localized sub-county analyses are necessary to understand the patterns and determinants of opiate overdoses. However, most local public health departments do not have the resources to laboriously collect, clean, and analyze the required data. We aim to provide sub-county analyses of opioid overdose hotspots and opioid treatment deserts that will reveal actionable patterns for California public health officials to directly address their county’s needs. Specific Aims: (1) to use emergency medical services data from 2022-2024 to detect opioid overdose hotspots using SaTScan and Bayesian spatial modeling, (2) to use emergency medical services and treatment center location data to map opioid treatment deserts defined by long travel times to treatment centers, and (3) to apply qualitative research methods with local OUD treatment providers to identify additional local determinants of hotspots and treatment deserts not obvious from quantitative analyses of population-level data. We will use advanced data processing and visualization to contextualize our conclusions about the link between hotspots; treatment deserts; and the social, economic, and environmental determinants of health. These relevant and easily comprehendible dashboards will lend themselves directly to resource allocation, policy changes, and development of targeted interventions. The training plan provides the skills needed for the fellowship applicant to begin a successful career as an independent investigator in translational public health research on opioid use disorder. He will undertake training in clinical opioid use and treatment; advanced geospatial methods and modeling; and qualitative methods to apply and tailor research findings for public health impact. The candidate will be mentored by faculty from across disciplines including epidemiology, psychiatry, data science, geospatial analyses, and statistics. Dr. Nelson, the primary sponsor, leads the T32 training grant in behavioral, social, and population health research that the candidate will continue to benefit from, and a fellow T32 director at Emory University, Dr. Waller, will serve an important mentoring role for the application of advanced geospatial analyses. Other mentors include leading researchers in opiate addiction from the Department of Psychiatry Drs. Humphries and McGovern; two social epidemiology research mentors Drs. Rehkopf and Kiang; and a health psychologist specializing in qualitative methods and citizen science Dr. King. Through this fellowship, the applicant will advance translational methods in opioid use disorder, receive training and mentorship from world-class sponsors and collaborators, and be prepared for independent public health research in his postdoctoral work.

NIH Research Projects · FY 2026 · 2023-04

PROJECT SUMMARY Recent exponential advancement of genome engineering technology has revived enthusiasm for its implementation in genetic cardiomyopathies. This is especially promising for arrhythmogenic cardiomyopathy (ACM), a cause of sudden cardiac death and end stage heart failure. Most early genome engineering therapies have focused on gene replacement; however, a significant minority of ACM variants likely act via dominant negative disease mechanisms that will not respond to gene replacement therapy. RNA Binding Motif 20 (RBM20) and plakophilin 2 (PKP2) are genes associated with deadly forms of ACM in which there are both dominant negative and haploinsufficient pathogenic variants. Variants in these genes cause cardiomyopathy and arrhythmia by disrupting global cardiomyocyte transcriptional splicing and desmosomal structure, respectively. hat these variants are clustered in pathogenic hotspots that align to known and novel functional protein domains, indicating that focused study of these hotspots can illuminate differential disease mechanisms and potentially reduce the burden of therapeutic design. Our central hypothesis is that variants in pathogenic hotspots of RBM20 and PKP2 have differential downstream mechanisms that converge on ACM disease phenotypes, and that these pathogenic hotspots allow the design of a genome engineering strategy to edit many pathogenic variants with a single reagent. In Aim 1, we will identify haploinsufficient vs. dominant negative variants in RBM20. We then use high throughput genome engineering techniques to create a library of these variants in induced pluripotent stem cell cardiomyocytes. We will apply a combination of single cell library preparation and long read RNAseq to define the downstream consequences of each disease mechanism on splicing of known and novel RBM20 targets. In Aim 2, we focus on a novel dominant negative mechanism for C-terminal PKP2 truncating variants in which they lose their plasma membrane localization, sequestering critical desmosome components in the cytoplasm. We will use variant effect mapping to define downstream mechanisms of a library of pathogenic PKP2 truncating variants, and will define the role of a novel PKP2 interactor on PKP2 membrane localization. In Aim 3, we will extend our work showing the feasibility of single prime editing (PE) reagents for correction of multiple variants in a pathogenic hotspot in vitro: We will design engineered prime editing (epe)gRNAs with the newest high efficiency PEmax construct for the PKP2 C- terminus hotspot and dominant negative RBM20 RS domain hotspot in vitro. We will then use innovative methods to package PEmax in AAVMYO to correct two pathogenic murine Rbm20 RS domain variants in vivo using the same epegRNA. We will go on to measure the effect of this editing on deep ACM phenotypes. In summary, this project will capitalize on our identification of pathogenic hotspots in RBM20 and PKP2 to provide a comprehensive evaluation of variant-level disease mechanism in these genes, and demonstrate the potential of hotspot directed prime editing as a tractable genome engineering therapeutic.

NIH Research Projects · FY 2026 · 2023-04

Care and outcomes for the 60,000 very low-birth weight (VLBW; <1500g) infants born annually in the United States varies widely. National guidelines recommend that care be organized along hierarchical regionalized care delivery networks, but too often these vulnerable infants are born in hospitals whose capabilities don't match patient need. This necessitates postnatal transfer which has been associated with excess morbidity and mortality. To date, research on regional care networks has been thwarted by a lack of appropriate linked data sets and mathematical tools to understand care network characteristics and their effect on neonatal outcomes. We propose to bridge this gap and advance health outcomes science by gaining a deep understanding of network characteristics and their links to clinical care and outcomes. We will accomplish this by using linked data sets, not available elsewhere, that allow for analysis of the individual and joint contributions of multi-level factors, including network factors on clinical outcomes. In addition, we will apply network analysis, a branch of graphical mathematics to visually display and quantify regionalized care network characteristics. We propose a large, near population-scale, observational study to analyze routinely collected data from 2010 to 2020 from >290,000 VLBW infants (>50% of all VLBW infants in the United States) in ~520 NICUs using linked vital records and patient discharge data from 17 states. This study is designed to achieve 3 specific aims: 1) Quantify regionalization and structure of transfer networks for VLBW infants across the United States; 2) Test the association of network structure with clinical quality of care and outcomes; and 3) Model optimized structure of perinatal transfers networks. Our analyses will employ network analysis as an innovative tool to measure care regionalization focusing on a high impact primary outcome (survival without major morbidity), as a substantive departure from prior work. Machine learning will be used to provide information on optimal network structures in terms of effectiveness, fairness and efficiency. These models will reveal how networks would need to be modified to satisfy optimization goals and reveal potential trade-offs. We have a long track record of impactful research funded by the National Institute of Health using this data. We also have an opportunity to investigate more granular questions in California (140 NICUs), which has unique existing linkages to maternal and infant clinical and transport data. We expect our research to have an immediate positive impact because it is designed to result in actionable information for policy makers, administrators and clinicians to improve perinatal care delivery.

NIH Research Projects · FY 2026 · 2023-04

Temporal lobe epilepsy (TLE) is the most common epilepsy syndrome in adults. Current treatment options for TLE remain often inadequate, as many patients suffer from uncontrolled seizures and negative treatment side effects. Endogenous cannabinoid signaling involving the cannabinoid type 1 receptor (CB1) is recognized to be a major presynaptic regulator of inhibitory neurotransmitter GABA release throughout the CNS. However, although the therapeutic potential of endo- and exogenous cannabinoids has been recognized for various neurological and psychiatric disorders, the in vivo mechanisms of cannabinoid signaling remain poorly understood, limiting the effective design of novel therapies. Major reasons for our incomplete understanding of cannabinoid signaling in the intact brain include the highly unstable nature of lipid-derived cannabinoid ligands and the prior lack of methods to study CB1-expressing neurons in behaving animals. Recently, we have introduced new tools that overcome these challenges, finally offering researchers both the ability to detect fast lipid signals in the hippocampus of behaving mice, and to selectively monitor and manipulate CB1-expressing GABAergic cells in vivo. Here, we propose to employ these new tools to test the hypothesis that activity-dependent endocannabinoid dynamics in the intact hippocampus are persistently modified in chronic TLE. We will then leverage novel, non-invasive, closed- loop interventions to target CB1-expressing GABAergic cells in order to control chronic seizures and ameliorate TLE-related disturbances in spatial information processing. We will test our hypothesis in experimental mouse models of chronic TLE, utilizing a variety of innovative in vivo calcium-imaging, electrophysiology, optogenetic and behavioral approaches. We anticipate that our project will have significant, potentially translatable, impact by overcoming major knowledge gaps about activity-dependent cannabinoid signaling in normal and epileptic neuronal circuits in behaving animals, and by accelerating the development of non-invasive closed-loop intervention strategies.

NIH Research Projects · FY 2026 · 2023-04

ABSTRACT Breast cancer is the second leading cause of cancer-related deaths in women in the United States, and its incidence is expected to grow by more than 50% by 2030. If detected early, the survival of women can be substantially increased compared to late-stage detection. Ultrasound molecular imaging, using molecularly- targeted contrast microbubbles, is a promising technique for the early detection of breast cancer, particularly in women with radiographically dense breast. In ultrasound molecular imaging, a molecularly-targeted ligand attached to a microbubble can bind to proteins expressed on the tumor neovasculature and produce contrast that can identify cancer early. This approach has large potential for improving the diagnostic accuracy of ultrasound and noninvasive characterization of focal breast lesions. The keys to successful ultrasound molecular imaging in this regard are: (1) having a molecular target that is highly specific to breast cancer, and (2) having a sensitive imaging system that can correctly visualize the microbubbles bound to breast cancer and differentiate those bubbles from background tissue. In addition, the system must integrate well with existing ultrasound imaging technology so as to be practically distributable to existing breast imaging clinics. In this application, we propose to build a real-time ultrasound molecular imaging platform that consisting of a novel ultrasound contrast imaging technology that is targeted to a newly identified biomarker of breast cancer. We propose to utilize targeted microbubbles to enhance the contrast signal and improve the sensitivity of the imaging system and propose to conjugate these microbubbles with a high-affinity affibody targeted to the B7-H3 biomarker, which is a vascular biomarker highly specific to breast cancer, and is not expressed in benign disease processes. In addition, our preliminary results demonstrate that this biomarker may potentially allow for the detection of metastatic disease at the time of imaging, potentially enabling the ability to image the extent of metastatic disease prior to treatment decisions. The real-time imaging technology in this proposal is based on a neural network design for contrast imaging that requires low computational resources and avoids destruction of bubbles, and enable real-time imaging of the targeted contrast agent. During this project, we will optimize the ultrasound parameters of these B7-H3 targeted microbubbles for breast ultrasound imaging frequencies and will utilize conjugation chemistry for the microbubbles to permit the potential for future clinical translation of the B7- H3-targeted microbubbles. We will design and construct this ultrasound molecular imaging platform (non- destructive imaging system plus monodisperse B7-H3-targeted microbubbles) and thoroughly test it in phantoms, in vitro flow chambers, and several preclinical animal models of primary and metastatic breast cancer.

NIH Research Projects · FY 2026 · 2023-04

Osteosarcoma (OS) is an aggressive primary bone cancer that mainly affects children and young adults, and is characterized by high genomic complexity. Current treatment relies on chemotherapy, yet many patients exhibit resistance or develop metastatic disease. Current experimental models for OS research rely primarily on 2D monolayer culture or xenograft models. However, 2D cultures culture generally fail to retain tumor phenotypes and drug response in vivo, whereas mouse models are costly and impractical for high-throughput drug screening. Recently tissue engineered 3D cancer models have emerged as new cancer research tools, which better recapitulate in vivo tumor signaling and drug responses than 2D cultures. However, most tissue engineered cancer models to date are limited to soft tissues. Unlike soft tissues, bone is characterized by a highly- mineralized extracellular matrix (ECM) comprised of 70% minerals such as hydroxyapatite (HA) crystals. However, the role of bone mineral in driving OS progression and drug response remains largely unknown. Furthermore, previous OS studies rely on a narrow set of cell lines that have been in culture for decades, which may no longer reflect the biology and drug response in vivo The overall goal of this proposal is to integrate a scalable and physiologically relevant 3D OS model with high-dimensional sequencing tools to elucidate OS genomic heterogeneity and drug resistance, as well as screening novel combination therapies using multiple patient-derived OS cell lines. Our 3D models is specifically designed with high-throughput screening in mind, and leverages on a patented microribbon (µRB)-based scaffold invented by the Yang (PI) lab. This multi-PI application will bring together expertise in biomaterials design and 3D tumor models (Yang lab/Stanford) with expertise in patient-derived xenograft (PDX) cell lines, genomics and preclinical therapeutics of OS (Sweet- Cordero lab/UCSF). We hypothesize that OS signaling and drug responses in 3D culture can be modulated by tuning the type and size of mineral cues 3D gelatin µRB scaffolds to better mimic the in vivo phenotype, and combinational therapies that target identified signaling using 3D OS model will lead to better treatment outcomes for OS in vivo. To test these hypotheses, we will carry out the following aims. Aim 1: Develop 3D OS models with optimized niche cues for deep characterization of OS signaling and heterogeneity using multiple OS PDX cell lines and compare results to mouse orthotopic OS models. AIM 2: To harness 3D OS models to determine the regulatory pathways involved in mediating receptor tyrosine kinase expression in OS and identify lead drug candidates by screening a panel of targeted drug therapies. Aim 3: To identify novel combination therapies for PDX OS cell lines and elucidate potential drug resistance mechanisms using 3D OS models. This study will pioneer integrating 3D OS model with PDX cell lines and high-dimensional sequencing expertise. The outcomes would significantly advance the understanding of OS biology and heterogeneity, identifying drug resistance mechanisms, and accelerate discovery of combination therapies that cannot be achieved using existing tools.

Fonds de recherche du Québec – Nature et technologies · FY 2023-2024 · 2023-04

Volet: Bourses de doctorat en recherche; Domaine: Structures abstraites; Objet: Analyse mathématique; Objet: Gravitation; Application: Sciences et technologies; Application: Fondements et avancement des connaissances; Mots-clés: GEOMETRIE, EQUATIONS DIFFERENTIELLES, ANALYSE MICROLOCALE, RELATIVITE GENERALE, TROUS NOIRS, ONDES GRAVITATIONNELLES

NIH Research Projects · FY 2026 · 2023-04

PROJECT SUMMARY/ABSTRACT Induced pluripotent stem cell (iPSC)-derived cardiomyocytes (iCMs) have generated great excitement for their promise to regenerate the injured myocardium. In pre-clinical studies, we have demonstrated that iCMs have significant functional benefit; however, substantial challenges remain, including ventricular arrhythmia, teratoma formation, and poor engraftment in the host myocardium. Furthermore, reliable regeneration of the injured myocardium has yet to be seen. While no effective strategy for permanent restoration has emerged, paracrine factors appear to underlie the beneficial effects of iCM therapy. Recently, we discovered the mitochondria-rich extracellular vesicles (M-EVs), which are secreted from the iCMs. These M-EVs effectively repair the injured cardiomyocytes and myocardium through restoration of intracellular bioenergetics. The paracrine effect is achieved by mitochondrial transfer and biogenesis to augment ATP production. This proposal will re-shape the future of heart failure (HF) therapeutics. There is clear clinical indication and need to improve the high mortality and morbidity of HF patients. The shortcoming of current standard of care may be due to the unmet need in understanding the bioenergetic imbalance in HF. The disruption of the balance between energy supply and demand underlies the pathogenesis of HF. Cardiac tissues from patients with hypertrophic, dilated, or ischemic cardiomyopathy all exhibit structural abnormalities of mitochondria and diminished ATP production despite increased metabolic energy demands in the failing heart. Although peroxisome proliferator-activated receptor γ coactivator-1α (PGC-1α) serves as a master regulator of mitochondrial biogenesis and function, PGC-1α levels are decreased in the myocardium of the HF patients. Insufficient energy generation results in the loss of cardiomyocyte contractility, myocardial dysfunction, and, ultimately, decompensated HF. Proteomic analysis of M-EVs demonstrated a novel cluster of 6 enriched M-EV proteins (PC), which interact with PGC-1α. PC was found to up-regulate energy metabolism, including oxidative phosphorylation, fatty acid metabolism, and glycolysis. Therefore, we hope to develop an innovative therapy that targets the intracellular bioenergetics directly through the following 3 Specific Aims: Specific Aim 1 – Confirm the role of enriched M-EV protein cluster (PC) in mitochondrial biogenesis. Specific Aim 2: Determine the mechanism of the protective effects of M-EVs in an in vitro iCM model of hypoxic injury. Specific Aim 3: Assess the functional benefits of mitochondrial augmentation and/or biogenesis in an in vivo mouse model of chronic myocardial injury. Upon conclusion of this study, the bioenergetic mechanism of mitochondrial augmentation and biogenesis will be confirmed in M-EVs for significant and sustained restoration of the injured myocardium.

NIH Research Projects · FY 2026 · 2023-04

7. Project Summary/Abstract Adult human skin heals by developing fibrotic scar tissue, which can result in devastating disfigurement, growth restriction, and permanent functional loss. Despite a plethora of clinical options, no current treatment strategies successfully prevent or reverse this fibrotic process, and over $20 billion is spent each year in the United States for the treatment of scars and their sequelae. Fibroblasts are recognized as the primary cell responsible for depositing extracellular matrix and causing skin fibrosis. However, progress towards the development of treatments aimed at reducing scars is impeded by a limited understanding of specific fibroblast subpopulations responsible for regenerative healing. We have observed that neural crest-derived facial skin wounds heal with less fibrosis than mesoderm-derived scalp wounds, somite-derived dorsal wounds, and lateral plate mesoderm- derived ventral wounds. Furthermore, through single cell RNA sequencing, we have identified that neural crest- derived facial fibroblasts promote regeneration following skin injury through a Robo2-EID1-EP300 axis, and bromodomain inhibition of EP300 guides fibroblasts to heal with reduced skin scarring. In this proposal, we examine the potential of the Robo2-Eid1-EP300 axis and EP300 bromodomain inhibition to guide dorsal scarring fibroblasts to heal with reduced fibrosis. We will employ both cell transplantation and CRISPR-Cas9 approaches, using histology, immunohistochemistry, transcriptional analysis, and flow cytometry to evaluate the regenerative capacity of Robo2+ fibroblasts within wounds. We will then determine the role of EP300 interacting inhibitor of differentiation 1 (EID1) in regulating Robo2 fibroblast activity in skin wounds. We will employ cell transplantation and CRISPR-Cas9 approaches to robustly determine whether activation of EID1 promotes regeneration of dorsal wounds to heal like facial wounds. Finally, having established that the Robo2-EID1-EP300 axis is responsible for regenerative healing, we will inhibit EP300 signaling using both small molecule and transgenic approaches to guide facial-like regenerative healing in dorsal wounds. Our ultimate translational goal is to develop therapeutics that target fibrogenic wound cell dynamics to promote regenerative healing. Collectively, the proposed work will significantly enhance our understanding of the key molecular and cellular determinants of cutaneous scarring, shedding light on the contributions of Robo2-EID1-EP300 activity in wound repair and scarring, and inform the development of novel anti-scarring therapeutics.

NIH Research Projects · FY 2026 · 2023-04

Project Summary The defining morbidity of heart failure (HF) is exercise intolerance, which reduces quality of life despite existing therapies. Currently, prescribed exercise in the form of cardiac rehabilitation can provide benefit, but is underutilized, thus there is a need to better understand the molecular transducers responsible for exercise’s benefit. Evidence suggests that cardiac-specific adaptation to exercise is muted in HF patients, thus peripheral adaptation at the level of the vasculature is hypothesized to be of increased importance in mediating exercise benefit. In support of this hypothesis, preliminary data from healthy adults using high-throughput proteomic profiling demonstrates an association between circulating levels of vascular extracellular matrix (ECM) proteins and exercise adaptation. Thus, the Research Strategy leverages Olink proteomic profiling before and after exercise training to test the hypothesis that changes in vascular ECM are associated with exercise adaptation, particularly among HF patients as compared to healthy adults. In Aim 1, the applicant Dr. Daniel Katz, will analyze Olink proteomic data from the Molecular Transducers of Physical Activity Consortium (MoTrPAC) to elucidate the relationship between vascular ECM proteins, as well as other proteins, and exercise training in healthy adults. Machine learning techniques will also differentiate molecular adaptation response subtypes. In Aim 2, 90 HF patients with non-ischemic cardiomyopathy and an ejection fraction < 35% will be randomized to 12 weeks of cardiac rehabilitation vs 12 weeks of no rehabilitation. Exercise testing and plasma samples (for proteomic profiling) will be obtained before and after the intervention period. The relationship between vascular ECM proteins, as well as other proteins, and exercise training will be determined and compared to healthy adults from MoTrPAC. In Aim 3, genetic variants which determine plasma levels for vascular ECM proteins, and other proteins identified in Aims 1 and 2, will be leveraged for Mendelian Randomization to support a causal link to cardiovascular health outcomes. Dr. Katz builds on prior proteomic training, and has produced 25 publications (13 as first or co-first author) since 2013. The career development plan will provide new training in exercise physiology and testing, clinical trials, bioinformatics, machine learning, and genetic causal analysis, through immersion and course work. Mentor Dr. Euan Ashley is an expert in exercise physiology and training, genetics, and precision medicine. Co-mentor Dr. Robert Gerszten is an expert in multi-omics, especially Olink proteomics, and both collaborate on the MoTrPAC proteomic working group. Drs. Matthew Wheeler (bioinformatics), Jon Myers (exercise testing and trials), and Michael Snyder (exercise biology) offer complimentary expertise as advisors. Together, the proposed work enhances understanding of exercise adaptation, and supports future efforts to expand profiling into peripheral tissue samples (e.g. muscle, adipose) to better understand peripheral exercise adaptation in HF as a therapeutic target, the subject of a planned R01.

NIH Research Projects · FY 2026 · 2023-04

SUMMARY Human brain development represents perhaps the pinnacle of complex organ specification, and an ideal model system for understanding 1) how normal development can produce all the cell types necessary for human cognition and 2) how genetic variation can perturb this process and lead to disease. We will generate large-scale single cell data sets to develop accurate models capable of predicting the effects of both genetic changes to regulatory elements and perturbations to trans-acting regulatory factors on gene expression during the complex developmental process of human brain development. We will study two highly medically relevant, human, in vitro, temporally dynamic differentiation systems that faithfully recapitulate fetal differentiation patterns: hiPSC- derived cerebral cortical and spinal cord organoids. For each of these differentiation trajectories, we will work in distinct aims toward mapping, perturbing, modeling, validating, and learning: Mapping: we will generate systematic, single cell multi-omic (RNA-seq, ATAC-seq, and protein quantification) data to map regulatory elements, chromatin contacts, RNA polymerase, protein binding, and gene expression through differentiation of hiPSCs to brain tissue. Perturbing: We will use CRISPR-based methods to comprehensively identify TFs required for differentiation and map the single-cell gene regulatory and expression impact of perturbing a subset of these factors at multiple time points across these differentiation trajectories. Modeling: We will develop multi- input nucleotide-resolved neural networks to learn dynamic gene regulatory networks using these mapping and perturbation data sets. These models will aim to understand the changing landscape of regulation and grammars of transcription factor motifs over differentiation time, and will predict both chromatin and gene expression effects expected from genetic perturbations. Validating: We will apply our network models to identify, investigate, and experimentally test perturbations relevant to understanding disease variation, by knocking down transcription factors, perturbing regulatory elements, and editing disease-associated noncoding variants. Learning and comparing: Finally, we will extract and test molecular properties of transcription factor function from validated models, and compare experimental and modeling approaches to better understand accuracy, advantages, and disadvantages. Successful completion of our project will provide mechanistic interpretations for how genetic variants may impact development (by disrupting regulatory element that in turn disrupt gene expression) in brain development. Our Stanford team comprises a diverse team of investigators with a history of productive collaboration, and with expertise in genomics methods development (Greenleaf, Engreitz), single cell methods and analysis (Greenleaf, Pasca), 3D cellular models of human brain (Pasca), and deep learning for genomic data sets (Kundaje). The output of this project will be a gold-standard data set defining the trans-acting factor network driving development, and a model capturing these complex dynamics capable of quantitatively linking changes in genotype to effects on genome function and phenotype in brain and spinal cord development.