Stanford University

NIH Research Projects · FY 2025 · 2024-06

Alzheimer’s Disease and Related Dementias (AD/ADRD) affect 15% of older US adults. Experiences in early life (e.g., differential exposure to childhood adversity) contribute to differences in AD/ADRD risk. Population distributions of these early life experiences, however, are themselves shaped by upstream factors that remain underexplored in the AD/ADRD literature. National, state, and local governmental investments in public goods, and which goods are prioritized, are one such set of intervenable upstream factors conditioning early life across place and time. For example, in 1965 the Elementary and Secondary Education Act facilitated intergovernmental grants (from federal to local governments via states) to enhance educational programing. By the 1980s, however, educational investments were outpaced by prison/jail expenditures. While upstream factors like governmental investments in early life could be linked to AD/ADRD risk and population distributions, and therefore serve as a lever for primary prevention, this has yet to be empirically tested. This K99/R00 leverages a novel longitudinal governmental spending database and two large, nationally representative, prospective datasets (National Longitudinal Survey of Youth 1979; US Health and Retirement Study) to estimate effects of federal, state, and local governmental investments in early life on midlife cognition and later life AD/ADRD risk. Triangulating across the strengths of confounder-control and quasi-experimental methods, this K99/R00 advances a nascent evidence base by (1) examining if county legal system or K-12 education investments in early life are independently associated with overall risk for, or differences in, midlife cognition and later life AD/ADRD; (2) characterizing how county legal system and K-12 education investments jointly co-vary over early life and evaluating if investment co-occurrence is associated with overall risk for, or differences in, midlife cognition and later life AD/ADRD; and (3) examining if early life exposure to federal policies monetarily investing in K-12 education affects overall, or differences in, midlife cognition and later life AD/ADRD. Under the guidance of an expert, multidisciplinary mentorship team, the accompanying training plan builds on the candidate’s subject matter and methodological background with additional skill building in the clinical/epidemiologic dimensions of AD/ADRD and its lifecourse determinants; database development; methods for characterizing longitudinal exposures; and quasi-experimental analysis methods. The proposed research aligns with several NIA strategic goals on identifying environmental and social factors in early life that create and sustain differences in cognitive function and AD/ADRD risk among older adults. Further, it initiates evaluation of early life governmental spending as an upstream driver of cognitive aging, develops a novel dataset – linkable to any individual outcome data – for future work, and is designed to directly inform prevention efforts.

NIH Research Projects · FY 2025 · 2024-06

PROJECT SUMMARY/ABSTRACT Myelin sheaths accelerate conduction velocity along axons, and its loss in neurological diseases, such as multiple sclerosis, leads to devastating disability. The importance of oligodendrocyte function and myelin for neuron health is also emerging in many neurological disorders, such as Alzheimer’s and Parkinson’s disease. Therefore, understanding how myelin is formed, remodeled, and regenerated may reveal new strategies with broad relevance to prevent or rescue neurological disorders. The majority of myelin generates during neurodevelopment, but recent discoveries demonstrate that new myelin forms following learning and sensory stimulation in humans and rodent models. Experiments in rodent models show that neuronal activity can directly stimulate new myelin formation and that new myelin formation is necessary for cognition, learning, and memory. This emerging form of neuroplasticity, termed activity-dependent myelination, can tune action potential timing and neural circuitry by adjusting myelination patterns along axons, changing the number, length, and thickness of myelin sheaths. Myelin sheaths form from oligodendrocytes that extend multiple processes and dramatically expand their cell surface to wrap axons in spiraling layers of membrane. How does neuronal activity regulate membrane expansion in oligodendrocytes? I recently discovered that exocytosis through VAMP2 and VAMP3 drive membrane expansion in oligodendrocytes during neurodevelopment. In many cell types, VAMP-mediated exocytosis can be stimulated by extracellular stimuli, but the cues that regulate oligodendrocyte exocytosis are unknown. I hypothesize that neuronal activity stimulates oligodendrocyte exocytosis to drive activity-dependent myelination within activated circuits. My preliminary data reveals that neuronal activity increases VAMP3 exocytosis in cultured primary oligodendrocytes by more than 2-fold. In my proposal, I will determine which VAMP proteins in primary oligodendrocytes are stimulated by neuronal activity (Aim 1.1) and which neuron-derived factors stimulate oligodendrocyte exocytosis (Aim 1.2). Then, I will obtain new training to investigate how human-derived neuron subtypes affect oligodendrocyte exocytosis in co-cultures (Aim 1.3). To determine the role of oligodendrocyte exocytosis in vivo, I will inhibit exocytosis specifically in oligodendrocytes of adult mice via AAVs (Aim 2.1) or Cre-inducible botulinum toxin (Aim 2.2) and use optogenetic stimulation to induce activity-dependent myelination. I will determine if oligodendrocyte exocytosis is necessary for activity-dependent myelin changes. Finally, with additional training, I will test if oligodendrocyte exocytosis is necessary for motor learning, a functional task that requires activity- dependent myelination (Aim 2.3). Altogether, my aims will uncover key cellular mechanisms that drive activity- dependent myelination and expand my scientific training to launch an exciting independent research laboratory. In the long term, my discoveries may provide mechanisms that can be harnessed to stimulate myelin regeneration or enhance neuroplasticity to change the course of neurological disorders.

NIH Research Projects · FY 2025 · 2024-05

Summary Tissue wide patterning is integral to robust development in multicellular organisms, requiring individual cells to generate polarity axes and coordinate this information in space and time. In order to establish cell polarity individual cells must first `break symmetry'. Imaging symmetry breaking in vivo suggests this is not a stochastic process, instead, symmetry breaking events are coordinated with in tissues and interconnected across the embryo. Using the C. elegans embryo, I will take a systems level approach to identify patterns of symmetry breaking events in the embryo that underlie synchronized, reproducible cell polarization needed for proper development. The Feldman lab has developed the C. elegans intestine as a tractable model to define cell- and tissue-level symmetry breaking events in the in vivo context of the developing embryo. The first cellular-level asymmetry we observe is the formation of `local polarity complexes' (LPCs). These macromolecular assemblies subsequently move coordinately to seed and establish the future apical surface, defining tissue-level asymmetry. In the proposed experiments, I will probe molecular assemblies to identify conserved mechanisms of polarity complex formation (aims 1 & 2) and ask if mechanical inputs are upstream of directed symmetry breaking in epithelia in vivo (aim 3). The overarching goal of this proposal is to identify where asymmetric information comes from to inform polarity programs in developing epithelia. Together these aims will inform core mechanisms of cell polarity establishment that are essential for organismal development and are key to maintaining healthy epithelia and preventing disruption of polarity programs that underlie disease states such as congenital malformations and tumorigenesis.

NIH Research Projects · FY 2026 · 2024-05

Project Summary G protein coupled receptors (GPCRs) are the largest family of receptors for neurotransmitters and hormones, and are therefore the largest group of targets for new therapeutics for a very broad spectrum of diseases including neurologic, cardiovascular, pulmonary and metabolic disorders. While initially thought to signal exclusively through G proteins and function as two-state switches activated by hormones and neurotransmitters, research over the past 30 years has revealed that most GPCRs have complex and diverse signaling behaviors. A single GPCR can activate more than one G protein subtype as well as G protein independent signaling pathways such as arrestins. Many GPCRs exhibit basal, agonist-independent activity. When considering one of the several possible downstream signaling pathways, a drug acting at the orthosteric binding pocket may exhibit one of four efficacy profiles. It may behave as an inverse agonist, suppressing basal activity, a full agonist, maximally activating the pathway, a partial agonist, promoting submaximal activity even at saturating concentrations, or a neutral antagonist, having no effect on basal signaling, but blocking the binding of other orthosteric ligands. The efficacy profile of a given ligand may differ for different signaling pathways such that a drug may behave as an agonist for a specific G protein subtype or arrestin while have no effect or inhibiting other signaling pathways. This pathway selective (or biased) signaling has become an important consideration for drug discovery, since one signaling pathway may produce therapeutic effects while another may lead to adverse effects. During the previous funding period we have applied cryo-electron microscopy and several biophysical methods to characterize the structure and dynamic character of several Family A GPCRs, as well as a Family B and Family C GPCR. These studies provide evidence that these GPCRs are highly dynamic and conformationally complex. We hypothesize that this complexity is essential for their functional versatility, and believe that a more detailed understanding of this complex conformational landscape will provide mechanistic insights into targeted activation of a specific pathway with biased ligands. The goal of this proposal will be to understand the structural basis for GPCR signaling through multiple pathways using methods that will provide high-resolution structural constraints and characterize protein dynamics under more physiologic conditions.

NIH Research Projects · FY 2026 · 2024-05

ABSTRACT Lung cancer is the leading cause of cancer-related deaths in the United States and worldwide. Around ~80% of lung cancer is non-small cell lung cancer (NSCLC), and most patients are diagnosed at an advanced stage. Immunotherapy, specifically immune checkpoint inhibitors (ICIs), has dramatically improved survival outcomes and is now the standard of care for treatment of advanced NSCLC without targetable oncogene mutations. However, only ~20% patients respond to ICIs radiologically and ~35% will experience durable clinical benefit. Given the potential toxicity and financial burden of these treatments, it is critical to identify which patients will benefit from ICIs as early as possible. Unfortunately, existing tissue-based biomarkers do not accurately predict ICI response for an individual patient. Moreover, they suffer from fundamental and practical limitations, including intra-tumor heterogeneity, insufficient sample quality and quantity. There is a critical need for reliable biomarkers of immunotherapy response and clinical benefit in NSCLC. To address this unmet need, we will develop noninvasive imaging and blood-based biomarkers and integrate these complementary approaches to improve prediction of immunotherapy response and outcome in NSCLC. Specifically, we will: (1) develop knowledge-guided radiomics and biology-informed deep learning models to enhance generalizability and interpretability; (2) propose novel methods to extract therapy-induced information from longitudinal images; and (3) integrate imaging and blood-based biomarkers to further improve prediction of response and outcomes. We will leverage a large institutional dataset for model training and establish the clinical validity through rigorous prospective validation. Successful completion of the project will afford a noninvasive approach to accurate prediction of immunotherapy response and clinical benefit in advanced lung cancer. This may lead to response-driven personalized treatment strategies by distinguishing patients who will respond to immunotherapy and for whom current standard treatment is sufficient; versus patients who will not respond and may benefit from novel combination treatment strategies. Additionally, early response evaluation using on-treatment imaging and blood information could be used to guide decisions of subsequent treatments. Given the routine use of CT scans and blood samples in lung cancer care, the proposed biomarkers can be readily integrated to current clinical workflow and may have a positive impact on broad patient populations.

NIH Research Projects · FY 2025 · 2024-05

Project Summary Moderate exercise is often recommended to patients for maintaining joint health, due to the strong scientific evidence showing that mechanical loading enhances cartilage formation from the chondrocytes in the joint tissue. Despite this understanding of joint physiology, a detailed mechanism by which cartilage formation enhancement occurs in chondrocytes under mechanical loading remains unclear. Seminal works have demonstrated the crucial role of the mechanosensitive ion channel TRPV4 in sensing physiological mechanical loads and expressing anabolic genes for matrix production. However, how TRPV4 is activated under such small mechanical loading environments remains unclear, especially as TRPV4 has been demonstrated to be insensitive to direct deformations of the cell membrane. Here, we present a hypothesis that TRPV4 activation and enhanced cartilage formation arises in chondrocytes due to the cell volume expansion facilitated by the accelerated dynamic remodeling of the constituents (i.e., viscoelasticity) of the surrounding extracellular matrix (ECM) under mechanical loading. This hypothesis is supported by emerging evidence that cells can sense the mechanical confinement by the ECM, wherein a dynamically remodeling ECM facilitates cellular volume expansion and thus activates TRPV4, and that small-strain mechanical loading can accelerate the dynamic remodeling of gels and biopolymer networks. We will explore this hypothesis through the following specific aims, by 1) exploring how anabolic loading conditions are influenced by the viscoelastic properties of the ECM, 2) establishing the biophysical consequence of anabolic loading on the viscoelastic ECM and the chondrocytes embedded within, and 3) exploring the ramifications of these findings on healthy and osteoarthritic (OA) tissues. The pursuit of these specific aims is innovative because it connects recently established physics of hydrogels to important biological consequences in vivo, which will help us address important health questions in other biological contexts in the future. Altogether, we will establish a detailed biophysical and biochemical understanding of enhanced cartilage formation in chondrocytes under mechanical loading. These results will be medically significant as they will advance our understanding of cartilage homeostasis in both healthy and OA patients, improve tissue engineering strategies for the treatment of cartilage defects, and unravel important insights into cell-ECM mechanotransduction overall. The project will be carried out at Stanford University, a leading institute for medical research, and tackled by a diverse team of experts, including the trainee who is an expert in the mechanics and viscoelasticity of soft materials, the sponsor Dr. Ovijit Chaudhuri who is an expert in cell-ECM mechanotransduction, the co-sponsor Dr. Marc Levenston who is an expert in cartilage mechanics, and collaborator Dr. Nidhi Bhutani who is an expert in cartilage disease and regeneration. The proposed research and training plan will prepare the trainee for a career as an independent researcher at the intersection of soft mechanics, mechanobiology, and biomaterials.

NIH Research Projects · FY 2026 · 2024-05

Abstract Pediatric Pulmonary hypertension (PPH) is a progressive and incurable disease hallmarked by abnormal development, muscularization and blockage of small pulmonary vessels by the formation of obstructive ‘neointimal lesions’. While most research has focused on arterial disease, venous changes including neointima, are described in nearly all forms of PPH but little is known about what controls vein neointima formation. Available therapies do not target lesion growth, neither prevent nor reverse disease, and are contraindicated when vein remodeling predominates. Early evidence suggests novel heterogeneity among pulmonary vascular smooth muscle cells (VSMCs) and neointima, but the molecular control and contribution of these subsets in PPH remains unknown. Understanding the biology of post-capillary vascular remodeling and, more generally, how heterogeneous VSMC and neointimal subsets contribute to PPH has the potential to significantly advance the understanding of the cellular and molecular controls of pathologic vascular remodeling in PPH. In Aim 1, Dr. Lea Steffes will train with mentors Dr. Maya Kumar in mouse transgenics, cutting-edge imaging and quantitation techniques and Dr. Mark Krasnow in advanced biocomputational analysis to define transcriptomic heterogeneity between pre- and post-capillary neointima and provide the first genomic-wide characterization of vein neointima. In addition to an in vivo pharmacologic inhibition study in mice using tools developed and published by Drs. Steffes and Kumar, in Aim 2, Dr. Steffes will train with advisor Dr. David Cornfield to perform a broad in vitro screen of VSMC growth modulators on vein neointima cells. With training in human pulmonary vascular histopathology from advisors Drs. Serena Tan and Csaba Galambos, Aim 3 will connect Dr. Steffes’s research and clinical expertise by interrogating the role of two novel developmental VSMC subsets in heritable PPH. The Candidate Training Plan provides a complimentary skillset of in vitro investigation, bio-computational analysis, and human lung vascular histopathology training to interrogate the cell-specific behaviors and molecular signatures of pathologic cell types (vein neointima, Aims 1&2 and developmental VSMC subsets, Aim3) integral to PPH. Mentor Dr. Maya Kumar is a thought-leader in the use of advanced mouse genetics and genomic tools to interrogate pathologic pulmonary vascular biology. Co-mentor Dr. Mark Krasnow (single cell analysis) and advisors Dr. David Cornfield (in vitro analysis) and Dr. Serena Tan (human lung histopathology) and Dr. Csaba Galambos (pediatric PPH pathology) offer complementary expertise. The environment at Stanford University is renowned for collaborative and innovative research. Supported by this infrastructure, candidate Dr. Steffes has demonstrated tremendous academic growth with 9 publications including 5 as first-author since 2020. In summary, this strong mentoring environment and training plan are anticipated to fully prepare Dr. Steffes to launch her independent career. The proposed studies will offer mechanistic insights into pediatric pulmonary vascular pathogenesis, and may identify therapeutic targets to improve the lives of children with PPH.

NIH Research Projects · FY 2026 · 2024-05

Project Summary/Abstract The lack of accessible, individual-level measurements suited to inform clinical decision-making is a critically unmet need in depression, the leading cause of disability globally. Persistent cognitive impairments from depression are a major contributor to disability. Our objective is to optimize, validate, and deploy a clinical cognitive signature using behavioral measures that have a basis in neural mechanisms, enabling individualized assessment at scale suited to personalized clinical prognostic and treatment selection decisions. We will extend our pioneering work in identifying a cognitive phenotype of depression derived from computerized behavioral ‘WebNeuro’ tasks that align with the RDoC cognitive control construct, to be complemented by a novel, research-based smartphone ‘BiAffect’ application for finer-grained, passively sampled behavioral metrics. In Aim 1, we will optimize a clinical cognitive signature for individual-level predictions based on our already identified cognitive phenotype. We leverage our unique, large existing multi-modal datasets with common cognitive data elements totaling 3,082 participants. These datasets span participants with major depressive disorder assessed pre-post treatment with pharmacotherapy and behavioral therapy, pre-post naturalistic trajectories, and matched healthy participants from the same sites. We will systematically optimize a clinical cognitive signature by generating trial-by-trial individualized scores on cognitive control tasks, with refined norms, and evaluate these scores in predictive models. We will also refine the mechanistic understanding of the clinical cognitive signature in the subset of participants who also have neuroimaging data. In Aim 2, we will evaluate the clinical cognitive signature in combination with digital phenotyping at scale in a new prospective sample of 1,200 adults with depression, to be recruited remotely. To enhance generalizability, the sample will span a broad range of symptom severity and functional impairment. We will complement WebNeuro with the BiAffect technology, both suited for remote administration, to quantify finer-grained individual variations in behavior throughout the day. This new cohort will complete repeat assessments for symptom and disability outcome predictions over 8 weeks with a 6-month follow-up. In Aim 3, we will validate the clinical cognitive signature for prospective stratification in a randomized clinical trial with 160 participants from the Stanford Bay Area and Chicago sites. We will prospectively identify participants with a prominent clinical cognitive signature (designated as C+) and those with a relative absence of the signature (designated as C-). Participants will be randomly assigned to receive sertraline plus guanfacine or sertraline plus placebo. Guanfacine is chosen because it has been shown to ameliorate cognitive deficits in depression based on the published preliminary findings from our team. The expected end product will be a clinically validated cognitive signature using a behavioral assessment tool that can be readily scaled and translated into routine clinical practice to inform prognostic and tailored treatment decisions. The project will generate a unique FAIR-compliant dataset enabling future scaling using machine learning and AI.

NIH Research Projects · FY 2025 · 2024-05

1 PROJECT SUMMARY 2 Cooperation and reciprocation are a hallmark of human behavior and key for creating and maintaining 3 social bonds. Yet despite their importance to both normal and abnormal social function, little is known 4 regarding their single neuronal and population underpinnings. 5 We propose to study, for the first time, how representations of recent social experience are formed 6 and maintained, then retrieved and updated with the goal of elucidating how these ultimately guide social 7 cooperative behavior. We will quantify cooperation using rhesus macaques playing the well-studied 8 iterated Prisoner’s dilemma game (iPD). In iPD, players can repeatedly cooperate for the common good 9 or exploit the other for their own benefit, and change their choices based on the other’s preceding move. 10 Using this approach, we previously described a neuronal circuit in the dorsal Anterior Cingulate Cortex 11 (dACC) where subsets of neural populations encode cooperative decisions and expected reward of other 12 individuals, distinct from neurons encoding one’s own decisions and reward. 13 Here, we build on these findings to investigate how the brain integrates recent interactions to support 14 cooperation. We will use large-scale simultaneous recordings in the primate Prefrontal Cortex to study 15 representations of one’s own and others’ actions, to delineate the functional neural architecture that 16 allow dynamic responses in ever-changing social contexts, and to study inter-brain neural synchrony 17 between monkeys cooperating while playing iPD. Such understanding is crucial for parsing how social 18 behavior falls apart in an array of neurological and psychiatric disorders and for devising future targeted 19 treatment of debilitating social disorders.

NIH Research Projects · FY 2026 · 2024-05

PROJECT SUMMARY Congenital heart disease (CHD) affects one in one hundred babies and is the leading cause of infant mortality in the US1. Single ventricle (SV) physiology is among the most complex and high-risk CHD diagnoses, in which patients are born with only one functional pumping chamber in the heart. These patients are typically palliated with three open heart surgeries culminating with a Fontan procedure, subjecting patients to a lifetime of elevated venous pressures and high rates of morbidity and mortality. As many as half of Fontan patients degenerate into heart failure and required a transplant by the age of 25. However, for a subset of patients with borderline SV physiology, drastic improvements in outcomes can be achieved if a bi-ventricular circulation can be restored. Despite these advantages, current reconstruction procedures require “on the fly” surgical planning in which the surgeon must customize a baffle design for each individual patient in the operating room. Computational modeling is well positioned to address these needs by providing surgical teams with predictive simulations. However, current simulation capabilities are hindered by several key factors: 1) anatomic models are laborious to construct, 2) there is a current lack of data characterizing CHD hearts, including material properties, fiber orientations, and Purkinje system structure and these quantities are critically needed for accurate simulations, and 3) current solvers do not combine all the relevant physics for whole-heart simulations. We aim to address these needs by developing a pediatric cardiac simulator to support surgical planning in complex congenital heart disease and to deploy it in a prospective clinical study. To accomplish these goals, we propose the following three specific aims: 1) To Enable Rapid Patient Specific Model Construction of Topologically Unique CHD Hearts With Machine Learning Methods Based On Signed Distance Fields. 2) To Characterize Mechanics and Microstructure in CHD Hearts Using Ex Vivo MR Acquisition and Finite-element Based Inverse Modeling. 3) To Prospectively Demonstrate and Validate a Novel Multi-Physics Cardiac Solver for Biventricular Reconstructive Surgical Planning in CHD Patients. Our proposed study will tightly integrate image processing and machine learning, advanced experimental magnetic resonance image acquisition methods, and development of state-of-the-art multi-physics finite element solvers (combining fluid and solid mechanics, active contraction, valves, and electrophysiology) to address an immediate clinical need in a high-risk and understudied patient population. A primary goal is to demonstrate improvements in short-term clinical outcomes before the end of the project. This proposal brings together an interdisciplinary team comprising experts in computational modeling of cardiovascular biomechanics, advanced MRI methods, microstructural and mechanical tissue characterization, and pediatric cardiac surgery. Our translational objectives are: 1) improve outcomes for borderline single ventricle patients, and 2) to advance the state of the art in cardiac simulation capabilities for broad applicability across CHD and cardiac surgery.

NIH Research Projects · FY 2025 · 2024-05

Project Summary/Abstract The lack of accessible, individual-level measurements suited to inform clinical decision-making is a critically unmet need in depression, the leading cause of disability globally. Persistent cognitive impairments from depression are a major contributor to disability. Our objective is to optimize, validate, and deploy a clinical cognitive signature using behavioral measures that have a basis in neural mechanisms, enabling individualized assessment at scale suited to personalized clinical prognostic and treatment selection decisions. We will extend our pioneering work in identifying a cognitive phenotype of depression derived from computerized behavioral ‘WebNeuro’ tasks that align with the RDoC cognitive control construct, to be complemented by a novel, research- based smartphone ‘BiAffect’ application for finer-grained, passively sampled behavioral metrics. In Aim 1, we will optimize a clinical cognitive signature for individual-level predictions based on our already identified cognitive phenotype. We leverage our unique, large existing multi-modal datasets with common cognitive data elements totaling 3,082 diverse participants. These datasets span participants with major depressive disorder assessed pre-post treatment with pharmacotherapy and behavioral therapy, pre-post naturalistic trajectories, and matched healthy participants from the same sites. We will systematically optimize a clinical cognitive signature by generating trial-by-trial individualized scores on cognitive control tasks, with refined norms, and evaluate these scores in predictive models. We will also refine the mechanistic understanding of the clinical cognitive signature in the subset of participants who also have neuroimaging data. In Aim 2, we will evaluate the clinical cognitive signature in combination with digital phenotyping at scale in a new prospective sample of 1,200 adults with depression, to be recruited remotely and representative of racially/ethnically and socioeconomically diverse population. We will complement WebNeuro with the BiAffect technology, both suited for remote administration, to quantify finer-grained individual variations in behavior throughout the day. This new cohort will complete repeat assessments for symptom and disability outcome predictions over 8 weeks with a 6-month follow-up. In Aim 3, we will validate the clinical cognitive signature for prospective stratification in a randomized clinical trial with 160 participants from the Stanford Bay Area and Chicago sites. We will prospectively identify participants with a prominent clinical cognitive signature (designated as C+) and those with a relative absence of the signature (designated as C-). Participants will be randomly assigned to receive sertraline plus guanfacine or sertraline plus placebo. Guanfacine is chosen because it has been shown to ameliorate cognitive deficits in depression based on the published preliminary findings from our team. The expected end product will be a clinically validated cognitive signature using a behavioral assessment tool that can be readily scaled and translated into routine clinical practice to inform prognostic and tailored treatment decisions. The project will generate a unique FAIR- compliant dataset enabling future scaling using machine learning and AI.

NIH Research Projects · FY 2025 · 2024-05

Project Summary / Abstract Our strongest memories often stem from our most rewarding experiences, allowing us to learn what features of experience predict reward and to use these predictions in the future. The ability to remember rewarding spatial locations, such as food sources, is crucial for survival. In humans, reward memory can become dysfunctional in memory disorders and mental illnesses like drug addiction, highlighting the need to understand how the brain amplifies information associated with rewards. The hippocampus and medial entorhinal cortex (MEC) comprise a potential neural circuit for this amplification process. Neurons within these regions construct and update a neural map of spatial experience, notably "overrepresenting" reward locations within the neural activity. However, it remains unclear exactly what aspects of the rewarding experience the overrepresentation encodes and how this information is learned. The goal of this proposal is to understand the neural dynamics of how the reward overrepresentation develops in both the hippocampus and MEC and how this process is synchronized within the hippocampal-MEC circuit. To achieve this goal, the proposal combines powerful neural recordings technologies across rodent species, using innovative behavioral tasks that disentangle the reward itself from sensory stimuli, movement dynamics, and the cognitive demand of remembering a specific location which predicts reward. Aim 1 (K99) will use calcium imaging to determine whether changing cognitive demands shape the hippocampal reward overrepresentation over learning. Aim 2 (K99/R00) will use high-density electrophysiology to disentangle reward and cognitive demand in the MEC code, tightly controlling for motor correlates around goals. Aim 3 (R00, pilot K99) will combine simultaneous recordings in the hippocampus and MEC with inactivation of each region to dissect their reciprocal contributions to spatial reward memory and decision-making. This work will build on the candidate’s extensive expertise in electrophysiology and behavior by providing training in three key scientific domains, under lead mentor Lisa Giocomo: (1) computational modeling and statistical analysis with the guidance of co-mentor Scott Linderman, to illuminate how neural coding properties change in different task states; (2) calcium imaging with advisor Jun Ding, to solidify a toolkit to monitor the circuit dynamics underlying flexible coding; and (3) hippocampal and cortical population dynamics with advisors William Newsome and André Fenton, to understand how population activity is structured and coordinated across regions at moments of decision-making. The training plan will build professional skills in inclusive mentorship, lab management, and scientific communication to propel a transition to independence. Stanford University offers a collaborative, interdisciplinary, and supportive environment to pursue cutting-edge science and launch an independent career. The proposed work will provide key insights into how and when spatial reward information is amplified in the brain, building a foundation for the candidate’s career goal: to investigate how neural circuits flexibly shape the information stored in memory according to behavioral demands.

NIH Research Projects · FY 2025 · 2024-05

PROJECT SUMMARY/ABSTRACT The molecular tools that allow for targeting specific cell types in mammalian retina are essential for understanding how this complex tissue works and responds to disease. Adeno-associated viruses (AAVs) provide safe and long-lasting expression and offer a powerful way to target retinal cells in a rapid, cost- effective, and efficient manner. The challenge is to develop AAV-based tools that allow for cell-type- or subtype-specific labeling and manipulation so that only the desired retinal cell types will be targeted. One of the major strategies for developing cell-type-specific AAVs is to integrate mini-promoters that can drive cell-type-specific gene expression into AAVs. To design such mini-promoters, Cis-regulatory modules (CRMs) in the genome, e.g., enhancers, which are considered as the primary determinants of cell-type-specific gene expression, are often combined with minimal basal promoters. Multiple methods have been developed to nominate cell-type-specific CRMs for AAVs. However, the efficiency has not been high, especially for non- abundant cell types or sub-types in the retina. We have pioneered the study of cell-type-specific CRMs in the retina and explored strategies that can increase the efficiency of identifying them. Putative CRMs are often nominated based on chromatin accessibility due to the binding of transcription factors (TFs) and consequent low nucleosome occupancy. However, many of the chromatin accessible putative CRMs are not active and fail to drive cell-type-specific gene expression in vivo. We found that pre-screening of chromatin accessible putative CRMs based on the density of cell-type-specific TF binding sites (TFBSs) can significantly increase the efficiency of identifying active cell-type-specific CRMs. Based on this result, we hypothesize that cell-type-specific CRMs can be efficiently designed based on cell-type-specific chromatin accessibility and by enriching for cell-type-specific TFBSs, and integrating these CRMs into AAVs can render specificity. The proposed studies will test this hypothesis in two aims. In Aim 1, we will determine whether cell-type- specific CRMs can be efficiently nominated based on cell-type-specific chromatin accessibility and TFBSs enrichment. In Aim 2, we will determine whether assembling cell-type-specific TFBSs into synthetic CRMs can provide cell-type-specificity in AAVs. In summary, the proposed studies will develop novel strategies for designing cell-type-specific CRMs and generate valuable AAV tools to advance retinal studies. As AAV-based gene therapy was approved by FDA for treating inherited retinal dystrophy (e.g., Luxturna), this study could also benefit future gene therapy.

NIH Research Projects · FY 2026 · 2024-05

Project Abstract Cellular stress response pathways are fundamental survival strategies that regulate protein homeostasis and are misregulated in myriad diseases and aging. The mechanisms by which stress response pathways regulate protein homeostasis, how well these mechanisms can perform, and why they fail in disease are major open questions. We explore these questions from both a molecular and biophysical perspective. Over the next five years, we plan to explore how cells detect and respond to defective protein translation, a process called Ribosome-associated Quality Control (RQC). A major focus area will be CArboxyl-terminal Tails (CAT tails), a form of protein synthesis we discovered in which ribosomes elongate defective proteins without guidance from an mRNA template. We will also study biophysical responses to stress, including viscoadaptation, a stress response we discovered in which cells regulate the diffusivity of biomolecules. We have a wealth of expertise and experimental tools to continue our track record of making fundamental discoveries in stress response pathways. Studying cellular stress response pathways at both the molecular and biophysical levels will lead to deep insights into cell survival and the cell biology of disease.

NIH Research Projects · FY 2026 · 2024-05

PROJECT SUMMARY Membrane transport systems are critical for controlling the central pathway of cellular energetics, from glucose transport across the membrane to regulating energy production in mitochondria. These systems mediate the movement of metabolites and ions between cellular compartments, which is fundamental to normal physiology. Their dysregulation is both a hallmark and driver of many pathologies. Elucidating the molecular basis of how mitochondrial transport systems work is a particularly rich vein: Insights into their transport mechanisms and regulations provide essential information for understanding their functions and roles in mitochondrial physiology. Defects in mitochondrial transport proteins have been implicated in diseases ranging from metabolic disorders to cardiovascular and neurodegenerative diseases, so mechanistic understanding can shed light on disease processes. Here, we propose to decipher the molecular mechanisms and regulation of three key mitochondrial membrane transport systems: 1) the mitochondria calcium uniporter, which constitutes the major calcium portal on mitochondria and mediates rapid calcium uptake, regulating ATP production and cellular calcium signaling; 2) the active calcium transporter NCLX, which plays important roles in various aspects of physiology; and 3) the mitochondrial pyruvate carrier (MPC), which transports pyruvate from cytosol into the mitochondrial matrix, controlling a key metabolic branch point. We take a multi-disciplinary approach to determine the mechanisms of these dynamic membrane protein machines. Our goal is to answer central questions in the field, including substrate selectivity, conformational transitions, small molecule modulations, and transport activity regulation. Successful completion of the proposed work will offer invaluable insights into these essential mitochondrial transport systems. This will deliver new and deeper understanding of mitochondrial physiology and provide novel insights into general principles of membrane transport processes. Furthermore, given that these membrane transport systems are promising drug targets, we expect our mechanistic insights will inform rational design for novel inhibitors and modulators, potentially leading to new therapies for patients.

NIH Research Projects · FY 2026 · 2024-05

Abstract Understanding how T cell receptors (TCRs) see tumor antigens presented by MHCs is necessary to fully understand how the immune system recognizes tumor antigens, and to reap the full potential of antigen-specific immunotherapy. To achieve this goal, a quantum leap forward is required in which the revolutionary advances in machine learning are combined with a large volume of structure, function, data on matched TCR-pMHC pairs. The development of accurate predictors of TCR-antigen recognition will be dependent on the creation and integration sequencing-based datasets with high-throughput structural and functional insights. Our proposal, submitted as a CRUK/NCI Grand Challenge team (MATCHMAKERS) will combine researchers with expertise in immunology, methods development, structural biology, and computation to enable generalized prediction and design of TCR recognition. This work will be spread across four Work Packages (WPs): WP1: Large-scale generation of TCR-pMHC pairs from naturally occurring sources. We will build datasets of naturally occurring TCR-pMHC pairs. Our team will use an array of approaches to collect these datasets, from humans and from mouse models, and in the context of both cancer and immunity more generally. WP2: Ultra-high throughput TCR-pMHC matching using molecular engineering. Efforts to create general models will require a broader array of data than feasible to collect from natural TCR systems. We will use an array of synthetic approaches developed by our team to comprehensively match TCRs with pMHCs to train computational models. WP3: Large-scale structural and biochemical analyses of TCR-pMHC interactions. A key to our team’s vision is to match interaction datasets with high throughput structural and functional insights. A deep understanding of how the TCR contacts with MHC helices control function and orientation will be essential for training and testing computational models. WP4 AI-based prediction and design of TCR-pMHC interactions. We will integrate our data to train next- generation algorithms capable of generally predicting and designing TCR-pMHC interactions. These predictions will proceed through a reiterative testing and feedback circuits for further model optimization.

NIH Research Projects · FY 2025 · 2024-05

eRA ASSIST for NCI – PROTECT Title: PROTECT – Harnessing PROTEin degradation for Advanced Childhood Tumors Abstract: Background Survival rates for children with solid tumors, including brain, have largely plateaued over the past three decades making them the most common cause of disease-related mortality in this age group. After decades of optimizing chemotherapy and radiotherapy protocols, higher cure rates for childhood solid tumors will no longer be achieved by “more of the same.” Rather, cures will require innovative interventions that specifically target the unique biology of these tumors, which are often driven by oncogenic fusions and other pediatric-specific oncoproteins historically considered difficult drug targets. With advances in targeted protein degradation and chemical interventions to inhibit protein-protein interactions, it has recently become tractable to target these proteins previously thought to be “undruggable”. Moreover, unbiased functional screening approaches, such as CRISPR-Cas9, have revealed new pediatric cancer synthetic lethal liabilities in need of targeted inhibitors. Aims We aim to lead the transformation of delivering such specific treatments to our young patients harnessing the power of a highly interdisciplinary and collaborative team of world-leading experts in pediatric oncology, targeted protein degradation, high-throughput chemical screening, medicinal chemistry, structural biology, tumor biology, preclinical drug testing, and clinical trials, complemented by a trans- Atlantic group of engaged patient representatives. Methods A bold plan will be pursued with a portfolio of projects that balance very high-risk efforts with others nearing clinical implementation. We will focus on drivers/targets in the following diseases: Ewing sarcoma, neuroblastoma, synovial sarcoma, ependymoma and high-grade glioma. We will explore different approaches to target these as yet undrugged paediatric drivers/dependencies, to overcome resistance to available targeted inhibitors, and to improve the efficacy and therapeutic window of CAR-T treatments. How the results will be used The aspiration of our team is to establish a sustainable platform for repeated developmental cycles of paediatric-specific drug development for emerging targets including a viable financial model to de-risk such developments for such rare pediatric tumors to the direct benefit of our patients. Specifically, we anticipate success through (i) delivering at least one optimised protein degrader for its application in early-phase clinical trials, (ii) enabling the druggability of previously “undruggable” targets, (iii) providing mechanistic insights into disease, novel targets, and therapy resistance mechanisms and ways to tackle them.

NIH Research Projects · FY 2025 · 2024-05

Project Summary Typhoid fever is a leading cause of invasive bacterial illness and death worldwide, with the majority of infections occurring in low- and middle-income countries where water and sanitation infrastructure is poor. Highly antimicrobial-resistant strains of Salmonella Typhi have been emerging and spreading internationally and intercontinentally, posing the risk of rising morbidity among reduced effectiveness of therapy. New typhoid conjugate vaccines have demonstrated a high level of effectiveness and are recommended by the WHO; however, many countries lack data on typhoid incidence, as the only reliable tool for typhoid diagnosis—blood culture—is not widely available in many resource-constrained settings where typhoid risk may be greatest. To address these gaps, we propose to leverage a large, cluster-randomized trial of a typhoid conjugate vaccine being performed in Vellore, India, to test three emerging tools to measure community burden of typhoid: 1) seroepidemiological models, utilizing recently characterized seroresponses to S. Typhi antigens; 2) detection of S. Typhi-specific bacteriophages in wastewater, using low-cost assays; 3) phylodynamic methods that track measures of transmission intensity. This project will provide rigorous testing of multiple innovative methods amid uniquely intensive clinical surveillance in a vaccine trial. Overall, this project will address a critical need for public health tools to make typhoid surveillance scalable in resource-constrained settings, to inform vaccine introductions and monitor their impact.

NIH Research Projects · FY 2026 · 2024-04

PROJECT SUMMARY Osteoarthritis (OA) is a leading cause of disability that reduces productivity and quality of life at tremendous economic cost. Despites its prevalence and cost, there is no therapy that prevents or cures OA. Synovial inflammation (synovitis), has been linked with pain, disease severity and progression of knee OA and is increasingly recognized for its role in the onset and pathogenesis of OA. However, studies of synovitis in OA have been limited by a lack of non-invasive and non-contrast methods to evaluate its role in whole-joint disease, particularly in early progression and in response to treatment. MRI has become the hallmark for imaging of OA yet conventional MRI struggles to differentiate synovial hypertrophy from adjacent fluid, thus making it difficult to identify and characterize synovitis. Contrast-enhanced (CE) MRI, following intravenous injection of a gadolinium- based contrast-agent, provides contrast to the highly vascularized synovium and is the current reference standard for imaging synovitis15. However, added time, cost, and contraindications in patients with renal dysfunction, have limited use of CE-MRI in OA. There remains a critical need for new, validated, and translatable imaging tools to better evaluate the role of synovitis in OA pathogenesis and response to treatment. MRI has shown promise to use differences in relaxation and diffusion properties between synovium and joint fluid to not only provide contrast to synovium but to also evaluate inflammatory activity without contrast injection. However, technical challenges remain for detection of low-grade hypertrophy, as well as isolating synovium and reducing distortions in diffusion MRI. Further, validation studies are necessary to understand these NC MRI markers and evaluate their utility as a target to predict and monitor treatment response and OA progression This project aims to develop and optimize non-contrast MRI methods to assess synovitis in knee OA, to validate these methods against histology, and to evaluate their ability to predict whole joint disease progression and as a target and monitor of treatment response. Our Specific Aims are (1a) to develop Non-Contrast MRI methods for assessing synovial hypertrophy and inflammation across both knees; (1b) to validate the sensitivity and specificity of these approaches against gold standard histologic measures of hypertrophy and inflammatory markers and reference contrast-based imaging metrics; and [2] to evaluate the potential of NC-MRI synovitis measures to predict and characterize treatment response to anti-inflammatory OA treatment (2a) as well as to predict OA progression and evaluate whole-joint spatial tissue relationships (2b). The significance of this work is new non-invasive and non-contrast tools that greatly expand the ability to evaluate synovitis in all aspects of OA: early diagnosis, pathogenesis and progression, as well as endotype evaluation and treatment monitoring. The innovation of this project is the development of novel NC methods to assess synovitis in OA and its role in OA pathogenesis and response to treatment. Our investigative team includes experts in novel imaging techniques, clinical and research studies of OA, and musculoskeletal clinicians.

NIH Research Projects · FY 2025 · 2024-04

Project Summary Implantable neuroelectronic interfaces for recording and modulating brain activity can treat drug-resistant neurological diseases; however, traditional electrode implantation requires invasive open-skull surgery and poses considerable risks, such as intracortical bleeding and infection, and inevitably damages the brain. To address these issues, this proposal aims to create a platform for endovascular delivery of chronically- stable probes for robust recording and modulation of neural activity. In related work, Dr. Anqi Zhang has demonstrated the feasibility of endovascular implantation and recording by developing flexible neural probes that can be delivered into sub-100-micron cortical vessels to acutely record local field potentials and single-unit activity in anesthetized rats. In this proposal, the capabilities of the endovascular probes will be expanded by first achieving controllable implantation into both superficial and deep cortical vessels adjacent to common therapeutic targets, followed by systematic studies and characterizations of endovas- cular recording and stimulation, with a focus on single-unit activity in anesthetized rats, and finally manu- facturing stretchable endovascular probes for long-term implantation and recording in awake, behaving rats. This proposal is significant because it will develop a platform technology that can be readily extended to the detection and treatment of other chronic and progressive neurological diseases, and serves as the foundation for the clinical translation of minimally invasive neuroelectronic interfaces to neurology, neuro- surgery, and interventional radiology practice. Dr. Zhang has suitable prior training in chemistry, materials science, neuroscience, and bioelectronics, and has extensive experience in mentoring and teaching. Dur- ing the K99 phase of this proposal, Dr. Zhang will be mentored by an experienced team of experts in neu- rological diseases, cerebrovascular surgery, optogenetics and calcium imaging, in vivo electrophysiology, and design and fabrication of stretchable devices. Stanford University also provides substantial resources and support for her professional training. Dr. Zhang’s advisory team will oversee her research progress and professional development through training in new techniques, clinical translation, job seeking and ne- gotiation, scientific writing and communication, mentoring, and promoting diversity, equity and inclusion. Upon completion of this mentored research project, Dr. Zhang will acquire the knowledge and skills neces- sary to use her strengths in physical sciences and engineering to develop minimally invasive chronic neu- ral interfaces, and the professional skills that will be extremely beneficial for her transition to become an independent investigator.

NIH Research Projects · FY 2025 · 2024-04

PROJECT SUMMARY / ABSTRACT Asthma affects 1 in 12 U.S. adults and leads to 1.9 million emergency department (ED) visits and 500,000 hospitalizations annually. Patients of lower socioeconomic status, as well as members of racial and ethnic minorities, are disproportionately more likely to suffer from asthma and experience worse health outcomes. Medicaid is the primary source of health insurance for low-income persons. However, rates of provider acceptance of Medicaid insurance remain low due to poor reimbursement rates, restricting access to needed care. At the same time, Medicaid managed care plans have proliferated and now account for over two-thirds of Medicaid enrollees. One strategy used by managed care organizations to reduce health costs is to limit participating provider networks to steer beneficiaries to high-value providers. While state and federal policy require minimum standards for network adequacy, recent evidence suggests that actual acceptance of Medicaid among providers may be even lower than reported. The extent to which these restrictive provider networks impact access to care among Medicaid beneficiaries with asthma and affect health outcomes remains unstudied. We have assembled a multi-disciplinary team with expertise in asthma outcomes, policy evaluation, and claims analysis to evaluate Medicaid provider network density, access to primary and specialty care, and ED visit and hospitalization rates among a national sample of adult Medicaid beneficiaries with asthma. We will first construct a claims-based measure of network density for each managed care plan by calculating the ratio of in-network primary care providers and specialists to the number of beneficiaries enrolled in each managed care plan (Aim 1). Next, we will test the hypothesis that lower provider network density is associated with less frequent primary and specialty care (Aim 2) and more frequent asthma-related ED visits and hospitalizations (Aim 3). This work builds on the PI’s K23 findings and will serve as critical preliminary data for an R01 proposal to evaluate the impact of managed care and state-level policies on asthma outcomes and health disparities, with a focus on asthma patients in structurally marginalized communities. Our findings can be used by advocates and policymakers to enhance standards for network adequacy and improve access to care among asthma patients who experience health disparities.

NIH Research Projects · FY 2025 · 2024-04

PROJECT SUMMARY Sleep is a very well conserved behavioral state across all animals. Though the exact function of sleep remains unknown, it is widely appreciated that good sleep quality is a cornerstone for any healthy organism. Indeed, several neurological disorders are co-morbid with sleep disturbances. Furthermore, altered sleep as observed in sleep apnea, insomnia or sleep deprivation show impairments in memory consolidation and increased risk for depression, cancer, Alzheimer’s disease (AD), and other neuropsychiatric disorders. AD patients have been shown to display altered sleep architecture. Sleep plays a role in clearance of beta-amyloid (Aβ) in interstitial space. Excessive accumulation of Aβ, a prominent feature of AD, has been shown to alter sleep. Recent work in our lab has demonstrated that hyperexcitability of wake-promoting hypocretin (Hcrt) neurons of the lateral hypothalamus (LH), resulting from natural aging, may underlie increased sleep fragmentation during aging. It is likely that these same neurons may have altered excitability in AD, exacerbated by the presence of Aβ accumulation, and may drive sleep fragmentation and sleep disturbances observed in AD patients. The overarching aim of this proposal is to understand how Aβ accumulation impacts hypocretin neuron activity leading to altered homeostatic sleep pressure and subsequent disrupted sleep architecture observed in Alzheimer’s disease. The central hypothesis is that accumulation of Aβ accelerates natural Hcrt neuron death leading to hyperexcitability of surviving Hcrt neurons and disrupted sleep pressure and architecture. This proposal focuses on Hcrt neurons as they have been suggested to be an integration hub which consolidates several streams of input and sends signals to downstream arousal-promoting regions. To understand this interaction, I will first need to demonstrate altered Hcrt neuron activity in the presence of Aβ accumulation, its impact on sleep (Aim 1), and demonstrate changes to the intrinsic and synaptic excitability of Hcrt neurons (Aim 2). Finally, I will consolidate the findings into a biophysically realistic computational network model with sleep-wake transitions to make viable predictions about the relative contributions of various ionic / synaptic currents to changes in intrinsic Hcrt neuron activity and its impact on overall sleep structure. These predictions will then be experimentally tested using CRISPR-SaCas9 technologies in vivo, the results of which will then further inform/refine the computational model (Aim 3). The end goal being a detailed theory / biophysical explanation for the impact of Aβ accumulation on Hcrt neuron activity and their role in sleep architecture.

NIH Research Projects · FY 2026 · 2024-04

Project Summary / Abstract Our ultimate goal is to discover causes of seizures in patients with temporal lobe epilepsy. The primary objective of the proposed project is to generate new data on reelin-positive interneurons in the dentate gyrus and test whether their loss is epileptogenic. The specific aims are to: Identify the type of reelin interneuron whose loss correlates with seizure frequency. Test whether loss of reelin interneurons in the dentate gyrus occurs in a large animal model of temporal lobe epilepsy. Test whether reelin-positive interneurons are total molecular layer cells. Measure the strength of synaptic output of reelin interneurons. And test whether loss of reelin causes seizures. To achieve these goals animal models will be evaluated: pilocarpine-treated rats and sea lions with naturally occurring temporal lobe epilepsy. Methods employed will include continuous telemetric video-EEG seizure monitoring, immunocytochemistry, stereology, whole cell recording in hippocampal slices, biocytin labeling, paired recording of unitary inhibitory postsynaptic currents, and prolonged focal brain infusion using mini-osmotic pumps.

NIH Research Projects · FY 2026 · 2024-04

Project Summary Tuberculosis remains one of the leading causes of death worldwide, despite the widespread availability of effective treatment and prevention measures. To accelerate progress in reducing the global burden of tuberculosis, there is a need for new tools and approaches to identify TB early, treat it effectively, minimizing toxicities, and prevent new TB cases through preventive therapy. The overarching goal of this K24 award is to train the next generation of scientists in patient-oriented, translational research on tuberculosis. Dr. Jason Andrews is an infectious diseases physician-scientist who leads a research group focused on developing and evaluating novel tools, from the laboratory to the field. He has served as a mentor to 30 students and postdoctoral fellows and is the primary mentor for three NIH career development awards. The proposed K24 award would: 1) protect his time to mentor early career investigators in patient-oriented research, investigating critical problems in tuberculosis diagnosis, treatment and prevention; 2) enhance his skills in mentorship through guidance from a committee of highly successful senior mentors; and 3) provide him opportunities for professional development, including advanced training in pharmacogenomics, translational research and personalized medicine. These proposed activities will leverage Dr. Andrews’ long-standing research collaborations, including three active NIH-funded clinical studies in Brazil. This award would support new studies to: 1) evaluate electrochemiluminescence assays for Mtb antigen detection in exhaled breath condensates as a novel approach to active case finding for TB; 2) test for human genomic polymorphisms associated with linezolid and bedaquiline metabolism and adverse events while validating a new amplicon- sequencing pharmacogenomic assay; and 3) evaluate a novel approach to predicting isoniazid and rifapentine metabolism by simultaneously measuring transcription of and polymorphisms in drug-metabolizing enzyme genes. Overall, this proposed K24 award would provide critical support for mentoring early career scientists while advancing innovative tools to improve the diagnosis and treatment of tuberculosis.

NIH Research Projects · FY 2026 · 2024-04

PROJECT SUMMARY Malaria and growth faltering continue to be major causes of child morbidity and mortality in sub- Saharan Africa where over 400,000 children under the age of 5 die from malaria1 and 57 million children are stunted2 each year. Given the high co-prevalence of these conditions in the region, interventions that synergistically address both malaria and growth failure may have a larger impact on child health than individual efforts to prevent either condition.3 There is increasing evidence that malaria infections in pregnancy and childhood may contribute to poor growth outcomes through increased risks of low birthweights4–9, systemic inflammation10–15, and gut microbiome dysbiosis16–19. Maternal and neonatal factors are the most influential for child growth20–22, so there is a critical need to identify interventions that prevent these malaria-associated risks in pregnancy and early childhood to reduce long-term growth faltering. Intermittent preventative treatments in pregnancy (IPTp) and childhood (IPTc), where pregnant women and young children are regularly given anti- malarial drugs, have emerged as key strategies to control malaria in high-transmission settings. These treatments have been shown to effectively lower malaria infections and could subsequently improve child growth outcomes, but no prior studies have systematically assessed the impact of IPTp and IPTc on growth faltering. Here, we propose a study that aims to (1) evaluate the effect of IPTp and IPTc on child growth and (2) investigate the causal pathways through which IPTp and IPTc affect child growth. We will leverage rich, longitudinal data from two ongoing randomized trials of IPTp and IPTc in Uganda, allowing us to measure child height and weight, inflammatory biomarkers, and gut microbiome composition over several years. Our findings will improve our understanding of how malaria chemoprevention impacts child growth and may guide the implementation of future interventions that target both malaria and growth faltering. This award will also support the career development of Anna Nguyen, a doctoral student in the Department of Epidemiology and Population Health at the Stanford School of Medicine. Through completing the proposed research, the applicant will pursue training in (1) the epidemiology of maternal and child malaria, (2) causal inference methods for longitudinal data, (3) gut microbiome data analysis for population health research, and (4) responsible conduct of global health research. The applicant will be supported by a mentorship team comprising of experts in casual inference methods, malaria intervention trials, gut microbiome analyses, and global health research. Through this fellowship, the applicant will develop strong methodological skills, gain subject expertise, and become a more independent epidemiologic researcher. The proposed study will provide a strong foundation for the applicant’s future academic research career and position her to become a leader in casual inference, infectious disease epidemiology, and global health.