University Of Chicago

NIH Research Projects · FY 2025 · 2023-09

Background: People at risk for HIV often experience co-occurring substance use disorders. Shifting trends in the opioid epidemic have been accompanied by increases in methamphetamine and polysubstance use, which also increase risk for HIV. Evidence suggests that factors such as housing instability, incarceration, and unemployment may interfere with engagement in HIV prevention and care, and these factors are also associated with substance use. Because such interventions are resource intensive and logistically challenging, particularly for those who are less likely to engage in research in traditional settings, guidance is needed at the intervention development stage to determine the most impactful and efficient intervention strategies. Agent-based models (ABMs) can be used to virtually evaluate candidate interventions to facilitate more efficient and timely intervention development. Because they allow for the conduct of counterfactual experiments, ABMs can also facilitate identification of effects that would be difficult to identify using traditional statistical approaches and can provide valuable insights to understand causal mechanisms that give rise to complex systems. Objective: Building on an existing ABM platform, this proposal will utilize multiple existing data sources to characterize relationships among demographic and behavioral risk factors, substance use, mental health, and HIV prevention and care engagement among people at risk for HIV. We will combine methods from epidemiology, ABM, and robust decision making (RDM) to understand the potential impact of interventions for reducing substance use, overdose, and HIV transmission. Methods: We will apply statistical and computational methods to better understand how individual demographic, behavioral, and contextual factors, substance use, and mental health impact engagement in HIV prevention and care. We will then conduct a series of experiments to evaluate how these factors impact the uptake of existing biomedical interventions and compare outcomes under scenarios with different combinations of interventions using RDM. Significance: A better understanding of where and how to focus intervention efforts offers potential to improve substance use and HIV prevention and care outcomes among people at risk for HIV. Once developed, our methods and models can be adapted to other geographic areas to reflect local prevention priorities and can serve as an example application of epidemiology, ABM, and RDM methods to advance HIV and substance use prevention science.

NIH Research Projects · FY 2024 · 2023-09

PROJECT SUMMARY The brain does not simply passively process visual information about the objects in the world. It is charged with placing this information about objects in the context of their environment relative to us in a way that helps us interact with them. To forage for food in the wild, an animal recognizes distant fruits, weighs the effort to get to each fruit against its perceived ripeness, makes and executes a route plan, and learns from the experience. This is possible because our vision enables two remarkable abilities – filtering out irrelevant information like inedible branches and leaves to focus on the fruit and creating flexible plans to reach the goal that can be altered on the fly. To study the neural basis of these abilities, I will use new conceptual and technological advances to study object vision in the context of cognition and naturalistic interactions like navigation and foraging to formulate a unified theory of how vision enables flexible behavior. Several computations in brain areas, like the prefrontal cortex, entorhinal cortex, etc., have been thought to mediate flexible behavior in various cognitive contexts like attention, working memory, and navigation. In this proposal, I will test the central hypothesis that signals in the dorsolateral prefrontal cortex (dlPFC) related to those different forms of flexibility reflect computations that guide how object properties are read out of visual area V4. To encourage the combination of several sources of visual information and interaction with objects in the task, I have designed a virtual reality foraging platform to test the following hypotheses about how object vision enables flexible behavior. In aim 1, I will test whether and how computations in dlPFC (previously identified in the context of attention) mediate the foraging of objects that have a narrow range of learned desirable properties by affecting the readout of relevant and irrelevant properties from V4. In aim 2, I will study how object familiarity is encoded in a viewpoint-invariant fashion and how interactions between V4 and dlPFC guide foraging behavior. In aim 3, I will explore how visual processing enables learned associations between objects and sequential actions by comparing the changes in neural activity in V4 and dlPFC that lead to the execution of sequential choices. The results of these studies will have broad scientific implications for models of visual perception that explain behavior and clinical implications for how object interaction, association, and action execution can be impaired in stroke and Alzheimer’s disease patients while visual processing is spared. Skills gained in the mentored portion – developing a visual foraging VR task and measuring and manipulating attention-like signals in dlPFC – along with my experience in generating visual scenes to analyze neural coding, will set the stage for future studies of the cognitive processes that shape visually guided experiences and actions in health and disease.

NIH Research Projects · FY 2025 · 2023-09

The pandemic has caused an increase in gun violence across the country, in rural and urban areas alike. While the focus has been on immediate causes like the pandemic's effect on mental health, economic conditions, other disruptions to social services, and the criminal justice system, much less attention has been devoted to the potential long-term effects on gun violence and other forms of violence due to the pandemic's effects on US education. Test score data show both the widespread prevalence and enormous magnitude of learning losses for children at all ages all across the country. These massive learning losses are concerning because of the strong correlation between education and violence (Lochner, 2020). Through a partnership between the University of Chicago and the Chicago Public Schools (CPS), we seek to produce evidence from randomized controlled trials (RCTs) about whether education causally reduces violence, and whether public policy can avert the increases in violence we expect from pandemic-induced learning loss at large scale. One of the most effective strategies for accelerating student learning is high- dosage tutoring, or HDT, which bolsters test scores by 0.2 to 0.4 standard deviations (see Nickow et al., 2020, Guryan et al., 2021). We seek to use government administrative data to measure violence-related outcomes for two retrospective RCTs of HDT carried out under ideal conditions in 2013-15 (like an efficacy trial), as well as a prospective RCT of an even larger-scale implementation in CPS right now (more like an effectiveness trial). The two retrospective RCTs enrolled 5,343 high school students, with test score gains of 0.18 and 0.40 SD (Guryan et al., 2021). While not the main focus of those RCTs, we did see suggestive indications of potential violence-reducing effects. The prospective RCT tests the even larger-scale HDT CPS seeks to deliver through its own in-house version of Saga tutoring, called CPS Tutor Corps, with 6,000 participants expected. We seek to link data on the retrospective and prospective RCT samples to data from several administrative data sources on violence-related outcomes like arrests and victimizations, and overall ER visits. The two retrospective (`efficacy') RCTs will let us measure impacts on violence involvement in both the short- and longer runs and understand whether gains in educational achievement can reduce it; in the prospective `effectiveness trial' of HDT, we will examine health outcomes in the short to learn of whether government efforts to scale-up HDT can help reduce violence-exposure disparities due to education disparities. Finally, we will focus on the mechanisms driving the impact on violence. We seek funding to complete the realization of the ongoing RCT in Chicago and to support the efforts of obtaining access to the relevant data on violence-related outcomes and linking it to the two studies.

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY Anticancer drug-induced cardiovascular toxicity (CT) is a major side effect for many patients undergoing treatment for oncological disorders. CT symptoms vary widely across individuals, both in presentation and in time to onset. Risk of CT complicates treatment protocols and places cancer patients under additional duress. Genetic background is broadly understood to be a component of CT susceptibility, but specific variants and mechanisms remain largely unknown. To understand the genetic basis for drug-induced CT, we need to understand how anticancer drugs stimulate transcriptomic responses in multiple cardiovascular cell types from individuals of different genetic backgrounds. Inter-individual variability in response to anticancer drugs is mediated by genetic variants that affect gene regulation in a drug-dependent manner (response eQTLs). In other words, genetic variants respond to anticancer drugs by regulating the activity of specific genes. Notably, different cell types can vary in their response eQTLs to anticancer drugs. I propose to determine the genetic basis for transcriptomic responses to the anticancer drugs doxorubicin (DOX), 5-fluorouracil (5-FU), and bevacizumab (BVC) in multiple cardiac cell types from a genetically diverse panel of 70 individuals. Identification of CT-associated response eQTLs necessitates a high-throughput model system comprised of multiple cardiac cell types. For Aim 1 of my proposal, I have developed a culture environment and guided differentiation protocol conducive to cardiac lineage and supporting cell types. This procedure reproducibly transforms induced pluripotent stem cell (iPSC)-derived embryoid bodies (EBs) into cardiac organoids. Preliminary data demonstrate that the cardiac organoids harbor cardiomyocytes, fibroblasts, vascular endothelial cells, and other mesodermal cell types. In Aim 2, I will perform single-cell RNA sequencing (scRNA-seq) on a panel of 70 cardiac organoids cultured in control and drug-treated conditions. Repeating this experiment across multiple individuals will allow me to identify the response eQTLs that regulate how different cardiovascular cell types respond to each drug. In Aim 3, I will quantify gene expression levels and identify response eQTLs that regulate transcriptional changes to each anticancer drug in cardiovascular cell types. Response eQTLs (which are anchored by genotype) provide a catalog of loci that interact either directly or indirectly with the treatment. These response eQTLs may reveal specific genes and pathways important for normal cardiovascular function. Elucidating the genetic architecture underlying CT risk will provide intuition on cardiotoxic mechanisms and associated genes and inform future studies that aim to classify individual patient susceptibility.

NIH Research Projects · FY 2025 · 2023-09

Project Summary We propose a collaborative research project in psychology, child development, and behavioral economics investigating the comparability and predictive power of measures of human potential that are regularly used in these fields. Using data collected on common measures of personality traits, executive function (EF) skills, and economic preferences across multiple countries, we will apply rigorous statistical methodology to investigate the relationships among these attributes beginning in pre-adolescence and assess which dimensions best predict health, wellbeing, educational outcomes, wages, and workforce decisions. We will also examine the stability and malleability of child and adolescent traits, skills, and preferences across environments with different contexts and incentive structures. (1) We examine the commonality of traits, and (2) their uniqueness, and (3) the evolution of unique and common traits. We will examine additional measures beyond the traditional ones (for example Guanxi, a trait capturing sociability that is widely used in China) to examine their relationship with the standard measures, and whether they have additional predictive power. Personality traits, EF skills, and economic preferences in childhood and adolescence are important predictors of adult outcomes, including physical and mental health, educational attainment, and employment. Measures of these attributes, such as perseverance and time preference, are increasingly used to evaluate the impacts of childhood interventions, monitor progress in school, forecast health outcomes, and study economic and social inequality. However, little is known about how traits, skills, and preferences evolve and co-evolve across childhood and adolescence. This grant will support collaborative efforts to measure child and adolescent personality traits, EF skills, and economic preferences drawing on expertise from the Center for the Economics of Human Development (University of Chicago), the Educational Testing Service, the briq Institute on Behavior & Inequality (University of Bonn), the Institute of Child Development (University of Minnesota), and the Institute for Economic and Social Research (Jinan University). Using existing data combined with new data collection, we will explore the relationships across elicited trait, skill, and preference measures to determine the extent to which different measurement schemes capture common or distinct aspects of human differences, and if these relationships vary across cultures, gender, ethnicity, and race. Our analysis will standardize across the measures to account for factors that influence responses, leading to increased comparability. We will use our elicited measures and the latent factors underlying them to predict performance in school (e.g., absenteeism, grades, promotion, behavioral problems, graduation), health (e.g., physical, emotional, social), and wages, employment, and occupation. We will examine the stability and evolution of the elicited measures, the malleability of traits, skills, and preferences, the factors that predict these measures (including institutional and family background and parental influences on their children), and the correlates of stability and change throughout childhood and adolescence.

NIH Research Projects · FY 2024 · 2023-09

Millions of women in the United States have a criminal record. Women with criminal records have high rates of behavioral health concerns, including post-traumatic stress disorder (PTSD), depressive symptoms, substance use problems, and suicidal ideation and attempts. They also experience some of the highest rates of interpersonal violence, including intimate partner violence and sexual assault, which are associated with and exacerbate women’s behavioral health concerns. In addition, they have low rates of receipt of needed behavioral health treatment and supportive services, such as victimization services. These gaps in care may be driven by dynamics of collateral consequences, i.e., forms of exclusion from resources, services, and opportunities due to the presence of a criminal record. Research is critically needed to improve women’s help-seeking and help-attainment for needed behavioral health care and services. This proposed mixed-methods study builds upon existing empirical work and a theoretically driven framework of help-attainment. We will examine how behavioral health, interpersonal victimization, and collateral consequences shape help-seeking and help-attainment processes for treatment and services among adult women with criminal records. Our proposed study will utilize an exploratory sequential mixed-methods design in which findings from the first, quantitative phase will inform the design of a second, qualitative phase, with both phases informing the third qualitative phase. In Phase I, N=500 women ages 25 to 54 with criminal records will be recruited to complete a web-based survey. Our survey will include measures of behavioral health concerns, victimization experiences, and theory-guided measures regarding dynamics of collateral consequences and help-seeking and help-attainment for behavioral health needs. These data will be used to identify patterns in domains influencing women’s help-seeking and help-attainment. In Phase II, we will conduct individual interviews using the life history calendar with N=40 women with criminal records, a stratified purposeful sub-sample of women who completed the Phase 1 survey. We will explore women’s trajectories of help-seeking and help-attainment, including dynamics of collateral consequences. Our findings from Phase I and II will inform our interviews with service providers in Phase III. We will conduct semi-structured interviews with N=30 service providers who work in treatment and service settings with women with criminal records. We will elucidate their perspectives of organizational and provider-based barriers and facilitators that impact women’s help-seeking and help-attainment processes. The collective findings will identify novel facilitators to help- attainment and intervention directions to improve the behavioral health and wellbeing of women with criminal records.

NIH Research Projects · FY 2026 · 2023-09

PROJECT SUMMARY Hospital-associated disability (HAD), defined as the new loss of ability to complete one or more activities of daily living without assistance at hospital discharge, occurs in nearly one-third of all hospitalized patients. HAD and low mobility during hospitalization are associated with readmissions, permanent disability, new institutionalization, death and escalating healthcare costs. While access to physical therapy (PT) is critical for functional improvement, my preliminary data from a single site suggests Black patients face disparities in both functional impairments and PT referrals. However, it is currently unclear whether this is true across sites, whether social factors affect these outcomes, or why this occurs. Therefore, this proposal aims to characterize the association of Black race and social factors with development of HAD and referral for acute and post-acute physical therapy across a set of Chicago area academic medical centers. I also aim to explore racial differences in perspectives on mobility loss and participation in PT. I hypothesize that Black race and social factors are associated with HAD and physical rehabilitation use. I will test my hypothesis in three aims: Aim 1) I will assess differences, by race and Area Deprivation Index (ADI), a measure of neighborhood-level resources, in HAD and inpatient physical therapy referrals in three academic medical centers across Chicago conferring a socioeconomically broad patient sample; Aim 2) Across these medical centers, I will also determine differences by race and ADI, in rates of recommendation for discharge to post-acute care (PAC) facilities for PT and actual discharge to PAC facilities for PT when recommended; Aim 3) I will use qualitative methods to explore patients’ experiences with mobility loss and participation in PT during hospitalization; and interdisciplinary care team documentation for Black vs. White patients. My long-term goal is to develop a model to predict HAD risk and likelihood of benefit from skilled physical rehabilitation during hospitalization to reduce HAD for broad populations of patients. To accomplish this, I have developed an exceptional interdisciplinary team of mentors (Drs. Meltzer, Arora, Lagu) and advisors (Drs. Peek, Chin, Jayaraman, Gibbons) who have a track record of NIH-funding and successful mentorship of early career investigators. I have formulated an in-depth career development plan to gain expertise in health disparities research (Chin, Peek, Meltzer), disability and physical rehabilitation in hospitalized patients, (Arora, Lagu, and Jayaraman), and incorporation of race and social determinants in statistical modeling (Gibbons, Peek, Chin). Completion of this proposal will train me to address each level of influence (individual, interpersonal, community, societal) within the “healthcare system” domain of influence outlined in the NIMHD’s research framework. Equipped with advanced skills and knowledge in health disparities research methodology and the role of race in healthcare, I will be able to design fair risk prediction tools and physical rehabilitation protocols and lead their culturally-tailored implementation in broad populations in future R01 level applications.

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY This research will break new ground in sensorimotor neuroscience by relating cortical and muscle activity data to shape change in a soft-bodied organ, making it possible to evaluate the generalizability of basic principles of motor control across musculoskeletal systems. It will develop and test a computational biomechanical model of tongue function that relates muscle activity to tongue movements, complementing ongoing modeling studies of human tongues based on more limited kinematic and muscle activity data. By using variation in natural feeding behavior to elicit a range of hyolingual kinematics, the research will provide insight into the impact of dietary modification—a treatment for dysphagia—on hyolingual kinematics. This research will lay the groundwork for development of hyolingual neuroprostheses driven by cortical signals to facilitate chewing and swallowing after (e.g., cancer) surgery or degenerative diseases, and for better techniques for non-invasive brain stimulation, muscle stimulation, and rehabilitation exercises used in treatment of, e.g., dysphagia and dysarthria.

NIH Research Projects · FY 2025 · 2023-09

Project Summary In response to membrane potential depolarization, voltage-dependent channels undergo a series of conformational changes from a non-conducting state (closed) to an activated (conducting), finally stabilizing in a non-conducting inactivated state. K+ channel function has been associated with such basic cellular functions as the regulation of electrical activity, signal transduction and osmotic balance. In higher organisms, K+ channel dysfunction may lead to uncontrolled periods of electrical hyperexcytability, like epileptic episodes, myotonia and cardiac arrhythmia. Consequently, efforts to understand K+ channel structure function and dynamics relate directly to human health and disease. The continuing long-term goal of this project is to further understand the molecular mechanisms of gating in voltage-dependent channels, by focusing on the analysis of K+ channel gating in prokaryotic and eukaryotic systems. Specifically we will address the following key questions: What are the atomic structures of the key conformations that determine channel activity? This question will be answered for membrane embedded systems as well as those ordered in a lattice. What are the molecular bases of voltage-dependent gating? We will be testing the hypothesis that a specific sliding helix movement (the one click motion) can explain charge translocation in certain voltage sensors, but perhaps not others. The more charge a sensor translocates, the larger the number of clicks its sensor needs to move. And how different parts of the channel interact to define open channel activity? We plan to study these problems by combining spectroscopic techniques (EPR and NMR), X-ray crystallography electrophysiological and computational methods. We intend to continue these structure-function studies by investigating a wealth of biochemically-defined systems from KcsA and KvAP, to the Shaker voltage sensor and the hyperpolarization-activated channel from Methanococcus janschii (MVP). In addition, we will focus our attention on the voltage-sensing domain from the Ciona intestinalis-Voltage-Sensor-containing Phosphatase (Ci- VSP) aiming to improve the resolution of our recent crystals structures. Finally, we will examine the structure of the human voltage- dependent proton channel Hv1 in membranes though an extensive site-directed spin labeling analysis and computational modeling. This proposal should open new experimental avenues that will contribute to our understanding of biologically important events such as electrical signaling, signal transduction and ion channel gating.

NIH Research Projects · FY 2025 · 2023-09

Project Summary/Abstract Neurofibromatosis type 2 (NF2), a human disease characterized by the formation of bilateral vestibular Schwannomas (resulting in deafness) and other tumors, is caused by loss of the tumor suppressor protein Merlin. Studies using the fruit fly Drosophila and subsequently confirmed in mammalian systems indicate that Merlin is an upstream component of the Hippo pathway, a conserved signal transduction pathway that regulates tissue growth. Mutations in Merlin and other Hippo pathway components are believed to cause tumors because they cause activation of an oncogenic protein Yorkie/YAP and increased expression of growth promoting genes. Identifying specific proteins and signal transduction pathways with which Merlin interacts is especially important because these partners may act as genetic modifiers of NF2 disease phenotypes and provide potential targets for therapeutic agents. We seek to understand how Merlin and the other HSW components are organized into a signaling complex at the cell cortex and how the activity of this complex is controlled. We have shown that Merlin and its binding partner Kibra nucleate formation of a signaling complex at a site separate from intercellular junctions, and thus that these proteins can function in parallel to another upstream regulator, Expanded. We also have shown that as these proteins assemble a signaling complex, they recruit an E3-ligase complex that degrades Kibra and represses signaling in a negative feedback loop. In the next funding period, we propose that Kibra degradation is promoted by mechanical tension and that this is one mechanism by which tension controls tissue growth. We also plan to test a model we propose in which Kibra and Merlin are recruited to the junctional cortex in an inactive state by the apical polarity protein aPKC in opposition to medial actomyosin networks which facilitate medial accumulation and activation of these proteins. To explore these novel hypotheses, we have developed tools and techniques that allow us to examine the localization and dynamics of Hippo pathway proteins expressed at endogenous levels in living tissues. Using with the exquisite genetic tools available in Drosophila, we can now elucidate the role of each pathway component in assembling and activating the Hippo pathway. These experiments are expected to provide insights into NF2, tumor suppression in general, and the role of actomyosin dynamics in regulating signaling processes. Finally, these studies should contribute to work on the mechanisms by which cellular interactions function to control tissue growth and determine cell fate during development and regeneration.

NIH Research Projects · FY 2024 · 2023-09

Project Abstract With the aging of the American population, the number of older adults at risk for developing cognitive impairment is staggering. Recent research points to age-related change in cognitive performance beginning as early as age 30, highlighting the potential for early interventions. Cognitive function has long been assessed using standardized cognitive tasks administered via neuropsychological evaluation. However, the traditional way to assess cognitive ability is time consuming, requires trained personnel, requires an office visit, and identifying decline among younger adults is particularly challenging because it can be masked by item redundancy effects. Here we propose developing a new computerized adaptive test (CAT) to assess cognitive function, either in clinic or remotely, that is based on recent advances in multidimensional item response theory (MIRT). We are calling it the CAT-COG. The CAT-COG will assess global cognitive ability as a primary domain as well as 5 cognitive subdomains: episodic memory, language/semantic memory, processing speed, attentional control/working memory, flexible cognition/reasoning. Our approach will revolutionize computer-based cognitive testing (ultimately in a platform independent way), providing precise estimation of an individual’s ability on these domains with minimal respondent burden, using a sufficiently large bank of items so that the same individual’s cognitive ability can be assessed repeatedly without reusing items or stimuli. This project brings together an accomplished interdisciplinary team of researchers and also builds on the unique resources of the Rush Alzheimer’s Disease Center (RADC). These are the key project steps: (1) We will develop a new 500 item bank of cognitive tasks and test them alongside a standard battery of neuropsychological tests through the RADC, and in an online Prolific sample that includes younger adults. (2) Based on these data, we will develop a computerized adaptive test (CAT- COG) appropriate for measuring global cognitive function and cognitive subdomains across the life course. (3) We will test and validate the CAT-COG among returning RADC participants who will also receive traditional neuropsychological testing. (4) We will study short-term variability of the CAT-COG based on daily assessment for a week to determine learning effects and develop a testing protocol that is immune to such effects. (5) we will harmonize the CAT-COG with the RADC standard battery of neuropsychological tests so that existing data can be linked to newly collected CAT-COG assessments.

NIH Research Projects · FY 2025 · 2023-09

Individuals impacted by the criminal legal system experience delays in accessing care and securing and maintaining gainful employment. Status neutral interventions are pertinent and urgently needed to support care and employment for this population. Our collaborative has prioritized three status neutral interventions (i.e., transitional case management [TCM], employment navigation [EN], and contingency management intervention [CMI]). Combining these interventions together will maximize their independent effectiveness and provide significant promise for improving health and employment outcomes. We will utilize seven prioritized bundled implementation strategies to support the adoption, implementation, and sustainability of these status neutral interventions within community and correctional settings. The overarching goals of the planned multi-site type 2 hybrid effectiveness-implementation study, J-RISE: Relevant Implementation Strategies to Enhance access to care and employment among individuals who have been impacted by the criminal legal system is to simultaneously evaluate the effectiveness and implementation of two packaged status neutral interventions within correctional and community settings. J-RISE is led by an academic, community, and correctional collaborative and conducted in three Ending the HIV Epidemic (EHE) jurisdictions in Illinois and Louisiana. Aim 1. Evaluate the effectiveness of two packaged status neutral interventions (TCM versus TCM+EN+CMI) on primary outcomes (linkages to HIV care, PrEP care, and employment-related services within 90 days) and secondary outcomes (receipt of mental health and substance use services, retention in HIV care, viral suppression, retention in PrEP care, and sustained employment). Aim 2. Evaluate the bundled implementation strategies and implementation outcomes at multiple levels using CFIR, RE-AIM, and MIPA. Key implementation outcomes include acceptability, adoption, costs, fidelity, penetration, and sustainability. J-RISE will generate novel information about the utility of our chosen implementation strategies as well as critical information about the effectiveness and cost of packaged status neutral interventions to optimize care and employment outcomes for individuals who have been impacted by the criminal legal system in multiple EHE jurisdictions.

NIH Research Projects · FY 2025 · 2023-09

To understand the function and dysfunction of the brain it is necessary to confront its complexity. Over the past two decades the field of neuroscience has leveraged the tremendous advances in electronics, genetics, and microscopy to collect a bewildering amount of neuronal data, especially when compared to the state of the field at the turn of the last century. More than ever these datasets require sophisticated analysis techniques to expose the salient aspects of brain dynamics and computation. Of equal importance is building a coherent theory of brain function. Theory can both organize these datasets under a conceptual umbrella, as well as suggest the next series of experiments to be performed. These realities require more neuroscience researchers to be trained in a variety of computational and mathematical techniques. This project outlines an ambitious graduate and undergraduate Training Program in Computational Neuroscience (TPCN) at the University of Chicago. The University of Chicago TPCN has 33 training faculty distributed over 10 departments. The training faculty are composed of 9 faculty in computational neuroscience (dry-lab), 9 training faculty whose laboratories are primarily experimental, and 15 training faculty whose laboratories are both computational and experimental. At the graduate level the TPCN offers a PhD program in Computational Neuroscience and a complementary PhD program in Neurobiology. At the undergraduate level the University of Chicago has a highly popular Major in Neuroscience, and students can Minor in Computational Neuroscience. The TPCN is set within a highly collegial, cross-disciplinary environment of our Neuroscience Institute and the Grossman Center for Quantitative Biology and Human Behavior. The Neuroscience Institute was established in 2014 to foster interdisciplinary research on the neural mechanisms of brain function, and now comprises 93 faculty having appointments in 16 departments. The Grossman Center was launched in 2020 and is a space within the Neuroscience Institute with an explicit focus on computational and theoretical neuroscience. Over the next five years the Grossman Center will grow to house 5 computational neuroscience faculty to complement our already existing community of theoretical neuroscientists. During this funding period the TPCN will (1) strengthen the course offerings in computational neuroscience at both the graduate and undergraduate level, and (2) create an undergraduate research program in computational neuroscience. TPCN trainees work in vertically integrated, cross-disciplinary research teams. Graduate students take a series of directed courses in computational neuroscience that span both statistical and modeling approaches. To ensure their competency in core neuroscience principles they also take courses in cellular, systems, and behavioral neuroscience. Their training will be supplemented with courses in a relevant quantitative discipline, such as computer science, engineering, mathematics, or statistics. All graduate students will have extended experience in at least one experimental laboratory, and they take part in journal clubs and seminars within the University of Chicago Neuroscience community. Supported undergraduates take courses in mathematics, computer programming, statistics, and neuroscience; they take an additional course in neuroscience or psychology and two courses in Computational Neuroscience; and they complete a research project. In addition, they complete the TPCN summer program. Undergraduate trainees in the summer program go through the boot camp on topics in computational neuroscience, including tutorials in Matlab, statistical methods, fundamentals of differential equations, and ideas of neural coding; they then complete a research project under careful guidance. All trainees will receive training in responsible conduct of research. Across 5 years of funding, the TPCN supports 20 NRSA graduate students, 10 non-NRSA graduate students, 30 undergraduate school-year and 30 summer fellows.

NIH Research Projects · FY 2025 · 2023-09

To understand the function and dysfunction of the brain it is necessary to confront its complexity. Over the past two decades the field of neuroscience has leveraged the tremendous advances in electronics, genetics, and microscopy to collect a bewildering amount of neuronal data, especially when compared to the state of the field at the turn of the last century. More than ever these datasets require sophisticated analysis techniques to expose the salient aspects of brain dynamics and computation. Of equal importance is building a coherent theory of brain function. Theory can both organize these datasets under a conceptual umbrella, as well as suggest the next series of experiments to be performed. These realities require more neuroscience researchers to be trained in a variety of computational and mathematical techniques. This project outlines an ambitious graduate and undergraduate Training Program in Computational Neuroscience (TPCN) at the University of Chicago. The University of Chicago TPCN has 33 training faculty distributed over 10 departments. The training faculty are composed of 9 faculty in computational neuroscience (dry-lab), 9 training faculty whose laboratories are primarily experimental, and 15 training faculty whose laboratories are both computational and experimental. At the graduate level the TPCN offers a PhD program in Computational Neuroscience and a complementary PhD program in Neurobiology. At the undergraduate level the University of Chicago has a highly popular Major in Neuroscience, and students can Minor in Computational Neuroscience. The TPCN is set within a highly collegial, cross-disciplinary environment of our Neuroscience Institute and the Grossman Center for Quantitative Biology and Human Behavior. The Neuroscience Institute was established in 2014 to foster interdisciplinary research on the neural mechanisms of brain function, and now comprises 93 faculty having appointments in 16 departments. The Grossman Center was launched in 2020 and is a space within the Neuroscience Institute with an explicit focus on computational and theoretical neuroscience. Over the next five years the Grossman Center will grow to house 5 computational neuroscience faculty to complement our already existing community of theoretical neuroscientists. During this funding period the TPCN will (1) strengthen the course offerings in computational neuroscience at both the graduate and undergraduate level, and (2) create an undergraduate research program in computational neuroscience. TPCN trainees work in vertically integrated, cross-disciplinary research teams. Graduate students take a series of directed courses in computational neuroscience that span both statistical and modeling approaches. To ensure their competency in core neuroscience principles they also take courses in cellular, systems, and behavioral neuroscience. Their training will be supplemented with courses in a relevant quantitative discipline, such as computer science, engineering, mathematics, or statistics. All graduate students will have extended experience in at least one experimental laboratory, and they take part in journal clubs and seminars within the University of Chicago Neuroscience community. Supported undergraduates take courses in mathematics, computer programming, statistics, and neuroscience; they take an additional course in neuroscience or psychology and two courses in Computational Neuroscience; and they complete a research project. In addition, they complete the TPCN summer program. Undergraduate trainees in the summer program go through the boot camp on topics in computational neuroscience, including tutorials in Matlab, statistical methods, fundamentals of differential equations, and ideas of neural coding; they then complete a research project under careful guidance. All trainees will receive training in responsible conduct of research. Across 5 years of funding, the TPCN supports 20 NRSA graduate students, 10 non-NRSA graduate students, 30 undergraduate school-year and 30 summer fellows.

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY Despite widespread efforts to implement lifestyle interventions aimed at restricting energy intake and increasing physical activity, weight loss success has been limited and obesity prevalence continues to rise. Thus, there is a critical need to develop novel strategies to prevent obesity and related cardiometabolic risks. Short sleep duration is a highly prevalent behavior and is strongly associated with obesity risk among young adults. Experimental laboratory evidence indicates that short sleep duration may increase obesity risk primarily through food-seeking behavior and overeating. We have recently demonstrated that short-term sleep extension in real- life settings in young adults with habitual short sleep reduces energy intake by a significant amount, and thus might be a potent strategy to improve weight loss outcomes in lifestyle interventions with calorie-restricting diets. To our knowledge, no prior weight loss intervention trial specifically examined the effects of extending sleep duration on weight loss outcomes in young adults. We, thus, propose a randomized clinical trial to determine whether weight loss outcomes in lifestyle interventions can be improved by adding an intervention component to extend sleep duration in overweight young adults with habitual short sleep duration. Overweight young adults who habitually sleep <6.5 hours will be randomized to either a lifestyle intervention alone (diet and activity counseling) or a lifestyle plus sleep intervention (diet, activity, and sleep counseling). All participants will receive a technology-supported intensive lifestyle intervention for weight loss with biweekly remote coaching for 6 months (Intervention). Participants assigned to lifestyle plus sleep intervention will also receive individualized sleep counseling to extend sleep duration, proven successful in our prior work, and tailored feedback. Participants will continue their assigned intervention for an additional 6 months without frequent contact (Maintenance). Sleep will be objectively assessed by accelerometry. Participants will self-monitor their diet (record all dietary intake into a custom smartphone app), physical activity (by accelerometry), and self-weigh daily on a wireless scale. Our specific aims are to determine whether lifestyle plus sleep intervention produces a greater weight loss (Aim1) and a greater reduction in objectively assessed (using doubly labeled water/energy balance method) energy intake (Aim2), as compared with lifestyle intervention alone. We will compare the change in weight (primary outcome) and energy intake (secondary outcome) at 6 months between groups. We will collect additional data on behavioral, biological, and psychosocial factors to explore their effects on intervention responses and generate novel insights. Weight change at 12 months (end maintenance) will be an exploratory outcome. If effective, data from this trial would strongly support incorporating sleep interventions into behavioral weight loss programs and provide the evidence base needed to guide tailored behavior change strategies for preventing obesity and related cardiometabolic risk in young adults with insufficient sleep duration.

NIH Research Projects · FY 2025 · 2023-09

Project Summary Anorexia Nervosa (AN) is a serious eating disorder with a mortality rate among the highest of any psychiatric illness. Identifying modifiable targets for the development of novel AN interventions is crucial because leading treatments achieve remission rates of less than 50%, and relapse is common. One aspect of AN that likely contributes to poor long-term outcomes is maladaptive food choice, i.e., the persistent and stereotyped choice of low-calorie, low-fat foods. Food choice requires individuals to construct the subjective value of foods from a number of attributes. Yet, despite the centrality of food choice in AN, little is known about how people with AN construct the subjective values placed on foods, leading to maladaptive food-choice behavior. The overall goal of this research is to elucidate the cognitive and neural mechanisms that contribute to subjective food valuation in AN. Leveraging fMRI, eyetracking, and computational models that have advanced understanding of decision-making in healthy individuals, we propose two studies to examine: (1) how individuals with AN combine across attributes to construct subjective value for food; (2) how the cognitive and neural mechanisms that contribute to valuation and food choice differ between individuals with AN and healthy controls (HC); and (3) how the value construction process can be biased to influence food choice. Study 1 will examine choices, reaction times, eyetracking, and fMRI measures obtained while individuals with AN (n=75) and HC (n=75) perform a novel multi-attribute decision task during which they will rate food items on attributes such as healthiness, tastiness, and savoriness, and then choose between 2 “meals” each composed of three different food items from different categories. We hypothesize that compared to HC, individuals with AN will base their subjective valuation of meal options largely on healthiness-related attributes and attend more to healthiness- related attributes. We also hypothesize that representations of healthiness in patterns of BOLD activity in the orbitofrontal cortex (OFC) will be more related to food choice in AN than HC. Study 2 will use cue-approach training (CAT), which has shown that the mere association of a cue and an action (a button press) with an image leads to enduring preference changes and attentional biases in favor of cued items. We will combine CAT with multi-attribute choices used in Study 1 and cue highly tasty foods for all participants. We hypothesize that attentional bias following CAT will alter the value construction process in AN (but not HCs) by increasing the value of tastiness attributes, and that healthiness representations in patterns of BOLD activity in AN OFC will be no more related to meal choices than tastiness representations. This research is the first effort to identify mechanisms underlying subjective food valuation in AN, and test whether value construction can be altered to normalize food-choice behavior. Results will inform the development of novel, neuroscience-based interventions designed to modify food preferences in AN and enhance the efficacy of existing treatments.

NIH Research Projects · FY 2023 · 2023-09

PROJECT SUMMARY Polyamines, namely spermidine, spermine, and their precursor putrescine are tightly regulated polycations essential for life. First indications linking polyamine metabolism and neurological disorders came from the observations of abnormal polyamine levels accompanying several brain injury conditions including ischemic brain damage and traumatic brain injury. The pivotal role of polyamine metabolism emerged with the mapping of causal mutation of Snyder-Robinson Intellectual Disability Syndrome (SRS, OMIM 309583) to spermine synthase (SMS), an enzyme that catalyzes the conversion of spermidine to spermine. Our work in the previous grant cycle (R01 NS109640) investigated the pathological consequence of polyamine imbalance in the nervous system in the context of SRS. We have established a Drosophila model for SRS to recapitulate several key features of SRS pathology, have uncovered altered redox state, dysregulated protein acetylation, and lysosomal dysfunction as primary neurotoxicity underlying SRS pathology, and most importantly, have identified phenylbutyrate (PBA) as a robust pharmacological suppressor of neurotoxicity in SRS in vivo models and in patient cells. Recently, we made the exciting discovery of the critical connection between polyamine metabolism and Tau aggregation-induced neurodegeneration. Specifically, we found that while complete loss of SMS causes SRS, partial loss of SMS (SMS+/-, carriers) showed resistance to Tau-induced neurodegeneration in Tauopathy models. This finding has two important implications: first, polyamines may regulate Tau aggregational toxicity; and second, progression of neurodegeneration in Tauopathy could be delayed by modulating polyamine metabolism. Our objectives for this renewal application are to establish the mechanistic link between polyamine metabolism and Tau/amyloid aggregational neurotoxicity, and identify neuroprotective strategies based on modulating polyamine metabolism using complementary model systems; 1) in vivo Drosophila models, 2) human fibroblasts cells from SRS patients (male, SMS-/y) and heterozygous carriers (female, SMS+/-), and 3) gene expression analyses of human Alzheimer’s Disease related dementia (ADRD) datasets. We hypothesize that modulating polyamine metabolism and shifting spermine/spermidine ratio enhances autophagic flux, regulates global acetylation landscape, facilitates the clearance of toxic Tau/amyloid oligomer species, and confers resistance to neurodegeneration in proteinopathy. We propose to define metabolic and cellular mechanisms underlying SMS+/- mediated neuroprotection against Tau/amyloid accumulation-induced neurodegeneration in vivo in Drosophila (Aim 1); characterize autophagic flux and proteostasis in human primary cells of SRS patient (male, SMS-/y), carriers (female, SMS-/+), and controls (+/+) (Aim 2); and carry out analysis of ADRD RNAseq and protein expression datasets to identify polyamine dysregulation risk factors and metabolic targets for neuroprotection against ADRD (Aim 3). The proposed research will reveal novel chemical and molecular connection between polyamine metabolism and global protein homeostasis, and more importantly reveal a previously unexplored therapeutic direction for AD pathogenesis.

NIH Research Projects · FY 2024 · 2023-09

Abstract Persistent prevalence of cardiovascular disease (CVD) and its high morbidity and mortality suggest that there are significant gaps in our understanding of the mechanisms that impair CVD health and better strategies are needed. It is well known in the scientific community that the impact of environmental justice on CVD extends beyond that of air pollution and encompasses neighborhood deprivation and social determinants. The literature also consistently demonstrates that low income, vulnerable, and underrepresented individuals are at the greatest risk of excessive exposure and lower resources to cope with and respond to the problems posed by these factors, including CVD. However, integrated, and comprehensive investigation of the multiple layers of environmental influence with individual-level factors is limited, especially in studies powered to investigate racial/ethnic disparities. We recently estimated that median All of Us participant PM2.5 level is 10 μg/m3, slightly higher than the US average of 7 μg/m3 and that people in the highest category have a 1.5 times increased risk of stroke. These preliminary results suggest that effects are certainly being detected, but the story is complex and requires analytic methods to tease apart correlated effects, weight influence, consider the effect of bias and offer insight into the factors commonly thought to be protective among diverse populations and communities. This project leverages the unprecedented opportunity to utilize existing data in the All of Us Researcher Workbench, our prior linkage of environmental factors into the dataset, and novel analytic methods to investigate how the social context and physical environment jointly contributes to disparities in CVD risk, and to further evaluate the impact of individual-level factors (e.g., established genes, individual demographics) on the modification and/or mitigation of these impacts. Our prior work in this area highlights how novel methods such as weighted quantile sum regression can offer interpretable effects and clear messaging on the percent contribution of different factors to chronic disease risk and disparities. As such, in addition to leveraging the unprecedented diversity in this national cohort, the approach is responsive to what our IPMC communities and community partners have requested in terms of areas of research interest and understandable answers.

NIH Research Projects · FY 2025 · 2023-09

Project Summary Many phenotypes, as well as the risk of developing many diseases, are genetically complex, and involve contributions from both genetic and non-genetic factors. Work in human genetics over the past two decades have shown that this variation is the result of contributions from a very large number of sites, on the order of thousands or tens of thousands. This presents challenges for both the measurement and interpretation of genetic association studies, as real genetic effects can be difficult to distinguish from the effects of confounding biases. On the other hand, biobank scale resources represent a tremendous opportunity to learn about both the biology of complex traits, and the evolutionary forces that have shaped modern patterns of variation. My group will develop statistical methods to overcome several current challenges in the study of genetically complex traits by apply tools from population, quantitative and statistical genetics. First, we will develop tools to diagnose and correct for ancestry stratification biases in polygenic scores. Even subtle stratification biases compound across loci to cause problems with polygenic predictions, so methods of carefully accounting for these biases are needed. Second, we will study the role of mutational pressure in maintaining complex disease and shaping its genetic architecture. The increasingly availability of exome and genome-wide sequencing association datasets make estimating the strength of mutational pressure toward increased disease risk increasingly feasible. New theoretical development will be needed to make and interpret these measurements. Third, we will develop models to study how mutation and selection jointly shape the distribution of heritability for complex traits across genomic regions with different functions. Current methods confound these two effects, so there is an opportunity for principled population genetic modeling to provide clarity on the biology of complex traits. Finally, we will develop improved methods for coalescent inference in population genetics. Recent breakthroughs in coalescent inference have begun to reshape our ability to learn about evolutionary events from genome sequencing data. However, these methods exhibit clear accuracy-scalability tradeoffs, suggesting that a thoughtful approach to inference is needed if the benefits of these methods are to be fully realized. My group will develop methods for accurately estimating coalescent times from sequencing data.

NIH Research Projects · FY 2024 · 2023-09

PROJECT SUMMARY/ABSTRACT The current lack of effective, targeted cancer therapies reflects a gap in knowledge surrounding the mechanisms that promote tumorigenesis and emphasizes the need for new therapeutic approaches. For decades, genetic drivers were thought to be the sole mechanism that promote tumorigenesis. Recent advances have established epitranscriptomics, which details the regulatory and functional roles of RNA modifications, as an emerging mechanism of tumorigenesis and potential therapeutic avenue. N6- methyladenosine (m6A) is the most prevalent modification on messenger RNA (mRNA) and serves key roles in gene regulation and expression. However, our understanding of how mRNA m6A methylation contributes to tumorigenesis is limited and warrants further investigation. The F99 phase of my proposal will determine the novel role of ALKBH1, a member of the AlkB family of Fe2+/𝛼𝛼-ketoglutarate-dependent dioxygenases, in regulating mRNA m6A methylation in arsenic-induced skin tumorigenicity. Chronic exposure to inorganic arsenic through contaminated drinking water is a major carcinogenic driver of skin cancer. However, the mechanisms that underlie arsenic-induced skin tumorigenicity remain poorly understood and few therapeutic targets have been identified. I hypothesize that ALKBH1 promotes arsenic-induced skin tumorigenesis by demethylating m6A on mRNA and regulating gene expression post-transcriptionally. The F99 phase of this proposal will address critical gaps in knowledge surrounding the molecular mechanisms that underlie arsenic- induced skin tumorigenicity and establish ALKBH1 and/or its targets as therapeutic targets for arsenic-induced skin cancer. The K00 phase will address a broader question and profile the dynamic role of m6A methylation in malignant transformation. Malignant transformation is a dynamic process. However, our understanding of the mechanisms that drive malignant transformation is limited to static comparisons across non-transformed and transformed cells and the transitional states that mediate the transformation between these cell types remain uncharacterized. The K00 phase will address this gap in knowledge by using m6A-sequencing to longitudinally profile the m6A-dependent epitranscriptome using validated models of in vitro transformation across a panel of carcinomas. I hypothesize that the m6A-dependent epitranscriptome changes dynamically throughout malignant transformation and that I will identify novel m6A-dependent targets that will increase our understanding of the processes that underlie the transformation from a normal cell to a tumorigenic cell. Successful completion of the F99 and K00 phases of this proposal will establish novel mechanisms of m6A regulation and function and identify new therapeutic targets and potential biomarkers of cancer development. My ultimate career goal is to become an independent investigator and run an interdisciplinary lab conducting NIH-funded work that investigates the interplay between epitranscriptomics and cancer.

NIH Research Projects · FY 2025 · 2023-09

The All of Us Research Program (AoURP) Illinois Precision Medicine Consortium (IPMC) award has created an impetus for precision health collaboration in Illinois that will leave a positive legacy for decades both locally and nationally. Since its inception, the IPMC has drawn strength from our institutional differences, varied scientific interests and expertise, broad geographic catchment areas, and different types of patient populations. To date, we have enrolled a cohort of nearly 52,000 participants from Chicago and greater Illinois, accounting for nearly 10% of the core AoURP participants nationwide – exceeding all expectations through high enrollment of informative research participants. Through the COVID-19 pandemic, the IPMC has proven that we can evolve and thrive in a new research context, pivoting operationally while ensuring project milestones. The experience of leading the AoURP in Illinois has generated insights, knowledge, best practices, new ideas, and partners to continue and build upon our work in Chicago and throughout Illinois. This includes a recognition of the crucial role that authentic and longstanding engagement plays in developing impactful biomedical research. We now have fully developed (and constantly expanding) clinical and community infrastructure, stakeholder buy-in, and integrated workflows. These will continue to guide IPMC performance and implementation strategies, supported by strategic investment and integrated expertise. We plan to continue enrollment and retention of participants into the AoURP by leveraging established leadership and frontline teams, infrastructure, workflows, and effective partnerships. We will work collectively to achieve the milestones outlined by the AoURP and implement the protocol fully and flexibly as national approaches, milestone priorities, and strategies and priorities evolve. To achieve these aims, the IPMC proposes to maintain our HPO institutional membership (University of Chicago, Northwestern University, University of Illinois Chicago) with Dr. Habibul Ahsan serving as the contact PI with MPIs Daviglus, Greenland, Aschebrook, Ho, and Pirzada. We are confident that our plan will bring significant value to the AoURP, with a precision medicine infrastructure based in Illinois that will ultimately enable discovery and impact communities we collectively serve and beyond.

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY Bacteria have a remarkable ability to sense diverse stimuli and make regulatory decisions to elicit an appropriate response. The objective of our research program is to understand the molecular underpinnings of this cellular decision-making process during the development of three dimensional (3D) structured communities called biofilms. Biofilms represent a predominant bacterial lifestyle and are crucial for antimicrobial tolerance, virulence, and environmental persistence in diverse pathogens including multi-drug resistant Pseudomonas aeruginosa. P. aeruginosa serves as an ideal clinically relevant model system for our basic research in biofilms because it adapts to and forms biofilms in a wide variety of environments, and the biofilm matrix components in this organism are well characterized. The overarching goal of the proposed research is to define how bacteria decode and integrate sensory cues – physical, chemical and biological – over the course of the biofilm development cycle. My work has shown that light (physical cue) detected via bacteriophytochrome BphP photoreceptor mediated photo sensing and population density (biological cue) detected via RhlR mediated quorum sensing represses biofilms. Furthermore, we have discovered that nutrient availability (chemical cue) converges with quorum sensing (biological cue) to control biofilm matrix components and architecture. Over the next five years, we will build on our recent discoveries and use a multidisciplinary approach combining bacterial genetics, molecular biology, biochemistry, fluorescence microscopy, mathematical modeling, structural biology and genome-scale studies to define sensory signaling in the context of a growing biofilm. First, we will investigate how light is perceived locally and globally in heterogenous biofilms and characterize the BphP photo-sensing signaling system to understand the regulation of photo sensing in P. aeruginosa (Project 1). Second, we will dissect the CbrA-Crc nutrient-sensing pathway to learn how nutrient availability controls biofilm development (Project 2). Third, we will delineate the different ways by which RhlR mediated quorum sensing represses biofilm formation (Project 3). Finally, we will define how information from two or more distinct sensory signaling pathways are combined in the control of collective behaviors (Project 4). Our research will establish a broadly relevant framework for understanding how information encoded in diverse sensory inputs is extracted and integrated to drive collective behaviors – knowledge that is crucial for designing successful synthetic strategies to enhance or to inhibit biofilms and for developing novel therapeutic interventions.

NIH Research Projects · FY 2025 · 2023-09

Enter the text here that is the new abstract information for your application. Complex traits result from interactions between many genetic and environmental factors. Nonetheless, most complex trait studies assume an additive model, in which genetic effects are independent of the environment and each other. This simple model has successfully identified many trait-associated loci, and these loci can be combined into Polygenic Scores (PGS) to predict disease. However, these results have not generally identified novel disease biology or therapies. Worse yet, current PGS have known and unknown statistical biases that will impede their accuracy in the clinic. I hypothesize that genetic interactions are the missing link in our understanding of complex trait biology. Genetic interactions are central to many fields of biology, and it is not likely that complex human traits are fundamentally different. However, prior studies of genetic interactions have generally been unsuccessful. I argue this results from limitations in our current models. In the next five years, I will develop genetic interaction models for complex traits to address these limitations. First, I will develop models to identify gene-gene interaction at the level of pathway-pathway interaction that build on my recent “Coordinated” framework for epistasis. Coordination is biologically plausible and statistically powerful. I will extend my Coordinated models to decompose pleiotropic effects on multiple traits and to unravel subtypes of common diseases. Second, I will develop rigorous and powerful models of gene-environment interaction that apply to novel areas of complex trait genetics. I will study cell type-specific heritability in single cell ‘omics data, I will incorporate context-specific effects to improve power and portability in PGS, and I will quantify the heritability of treatment response from biobank data. My methods will be mathematically rigorous and computationally efficient. They will build on my track record of developing robust and freely-distributed statistical genetics methods. I will apply my methods to phenome-wide scans in several large-scale cohorts, especially to ensure the PGS predictions are rigorous and replicable. I will also study Major Depressive Disorder in detail, a classic example of a heterogeneous complex disorder with a mix of poorly understood genetic and environmental causes. My interaction methods will close the gap between statistical explanation and biological understanding, revealing new paths to precision medicine that benefit everyone.

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY/ABSTRACT: Memory complaints are widespread among the elderly and aging is a major risk factor for Alzheimer's disease (AD), leading to the impression that a gradual loss of memory ability, eventually culminating in dementia, may be a nearly universal consequence of getting old. Our studies explore an alternative aging trajectory by studying 80+ year olds, who have episodic memory performance that appears to have escaped age-related decline and that remains in the range that is at least normal for 50-60 year-olds and we have labelled `SuperAgers'. We enrolled a dedicated and unique cohort of SuperAgers and Controls committed to longitudinal assessment and brain donation at death. Our initial studies identified domain-specific biologic, psychosocial, and genetic features of the SuperAgers, including maintenance of cortical integrity (especially in the anterior cingulate), an abundance of anterior cingulate Von Economo neurons and sparse cortical Alzheimer pathology compared to their cognitively average peers. These features may contribute in part to maintenance of superior memory performance past the 8th decade of life. This Project plans to extend the characterization of the SuperAging phenotype through hypothesis-driven novel evaluations of functional brain network connectivity, regional distribution of gene expression, and integrity of dendritic, synaptic and axonal markers. The proposed project will allow us to expand our unique group of SuperAgers and cognitively average peers and address important questions related to the neurobiology of resilience and cognitive reserve. By identifying neurobiologic features that contribute to superior memory performance in old age, outcomes from this project will help isolate factors that promote successful cognitive aging and perhaps also prevent age- related brain diseases such as AD. The project's reliance on a cohort that has already been partially recruited, its longitudinal design, multidisciplinary structure, and collaboration-friendly organization increases the likelihood that consequential progress will be achieved.

NIH Research Projects · FY 2025 · 2023-09

PROJECT SUMMARY Epithelial stem cells reside in the major barrier tissues, governing homeostatic regeneration and injury repair. As long-lived and indispensable cells, epithelial stem cells must endure bouts of inflammation. This ability is especially critical during wound healing when many immune cells infiltrate the tissue. These immune cells play important roles in controlling infections and clearing dead cells, but they also release toxic substances and create a very harsh inflammatory environment for stem cells. It has long been assumed that stem cells are vulnerable and must be protected within an ‘immune privileged’ niche. However, our recent study challenged this idea. We have found that, upon wounding, the epithelial stem cells must be mobilized to exit their natural niche and migrate into a highly inflammatory wounding environment for regenerating the damaged tissue. If stem cells failed to adapt to inflammation, it could cause nonhealing wounds, which still affect millions of people worldwide, causing significant economic and public health burdens. It is unclear how epithelial stem cells achieve self-renewal and differentiation within an inflammatory environment while preventing collateral damage. Addressing this question will transform our understanding of the fundamental biology underlying cellular fitness, stress tolerance, tissue homeostasis, barrier integrity, and wound repair. Driven by its importance, the central question of this proposal is to understand how epithelial stem cells adapt to the inflammatory environment and how this adaptive function promotes wound repair. A significant gap in technology preventing a thorough understanding of wound healing and stem cell adaptive functions is the lack of effective tools for rapid gene discovery and mechanistic studies in mouse models. To overcome this hurdle, in this project, we will adopt an ultrasound-guided in utero microinjection technique to establish a new experimental framework for rapid, functional, and mechanistic investigation of genes involved in stem cell adaptation and wound healing directly in live mice. We will leverage this experimental framework to deploy a full-fledged platform that will place us in a unique position to: first, design in vivo CRISPR screening platforms and stem cell interactome sensors to dissect how epithelial stem cells can remodel the fate and activities of surrounding immune cells to build a temporary protective niche, shielding stem cells from inflammatory damage. Second, we will focus on devising an in vivo Perturb-seq-based framework and cell/organelle tagging system to identify how epithelial stem cells reprogram their metabolism to tolerate inflammation. In sum, this proposal has the potential to reveal critical information and build a solid foundation for future efforts in developing strategies to manage non-healing wounds.