University Of Pennsylvania

NIH Research Projects · FY 2026 · 2024-12

Project Summary Progression to type 2 diabetes results from the inability of insulin secreting pancreatic  cells to compensate for increased insulin demand, usually in the setting of obesity. We have previously found that the homeodomain transcription factor and human diabetes gene Pdx1 coordinates islet compensation in the setting of diet-induced obesity and associated insulin resistance. We identified Gpt2 as a target of a PDX1- ATF transcriptional complex whose stress induction and PDX1 enrichment of regulatory CARE sites is conserved in both human and murine islets. Importantly, silencing of the transaminase Gpt2 ex vivo protects primary mouse β cells from stress induced apoptosis. GPT2 is a rapid equilibrium transaminase that catalyzes a bidirectional reaction converting glutamate and pyruvate to α-ketoglutarate (-KG) and alanine. Recent reports implicate Gpt2 upregulation as a key step in the reprogramming of glutamine metabolism of cancer cells. The production of -KG feeds into the tricarboxylic acid (TCA) cycle, resulting in synthesis of ATP which leads to closure of KATP channels, membrane depolarization, calcium influx and exocytosis. TCA cycle intermediates also act enzymes as a cofactors for several chromatin-modifying enzymes, including the Tet family of involved in DNA demethylation. Our preliminary findings support the exciting hypothesis that the induction of GPT2 during fuel excess reprograms beta cell metabolism, thereby causing beta cell dysfunction and death. This hypothesis and the underlying mechanisms will be tested in the following Aims: Aim 1: To uncover the mechanism whereby the transaminase Gpt2 promotes  cell dysfunction and death. We will (A) complete the in vivo characterization of Gpt2 deficiency in pancreatic  cells, (B) elucidate how Gpt2 deficiency affects mitochondrial morphology, function and metabolism, (C) explore the epigenetic impact of Gpt2 silencing and (D) assess the role of Gpt2 in human  cell function and survival during metabolic stress. Aim 2: To elucidate how Gpt2 influences sensitivity of the  cell to GLP1. We will (A) determine whether the sensitivity of GIP and other insulin secretagogues are also affected by Gpt2 expression, (B) investigate the molecular mechanism whereby GPT2 impacts GLP1 sensitivity, and (C) determine whether its impact on cell survival and function is linked to its effect on GLP1 sensitivity via intraislet paracrine signaling. These results will address an important gap in our understanding of how glucoliptoxicity promotes  cell dysfunction and death. Further we will then be poised to devise strategies to target Gpt2 activity or expression as a therapeutic means to protect beta cells during metabolic stress and to enhance sensitivity to Glp1 receptor agonists, an application of the proposed studies that is of the highest translational relevance.

NIH Research Projects · FY 2026 · 2024-11

Abstract While neuropsychiatric disorders are highly heritable, it is well recognized that environmental factors, such as chronic stress, contribute to the risk of developing mood-related psychiatric disorders. However, the epigenetic mechanisms underlying stress vulnerability and the pathogenic mechanisms linking stress to increased susceptibility of psychiatric conditions are not well understood. Based on our recent discovery that the transcription factor Yin Yang 1 (YY1) and YY1 regulon are selectively down-regulated in cortical excitatory neurons upon chronic stress exposure, and selective ablation of Yy1 in excitatory neurons enhances stress sensitivity in both male and female mice, we propose to employ a combination of genetic, genomic, molecular, and behavioral approaches to investigate the epigenetic mechanisms by which chronic stress elicits maladaptive behaviors and test a specific hypothesis that the stress related glucocorticoid receptor (GR)-YY1 reciprocal regulation contributes to stress vulnerability in mice. With currently available state-of-the-art genomic technologies and our newly developed, genetically modified mouse tools, we hope to improve our understanding of the underlying causes of stress-related psychiatric disorders and provide the necessary foundation for better diagnosis and intervention.

NIH Research Projects · FY 2025 · 2024-11

PROJECT SUMMARY The University of Pennsylvania (Penn) proposes to establish the Synthesize, Coordinate, Amplify, Learn, and Evaluate the AHRQ/PCORI LHS network (SCALE-LHS) coordinating center (“Hub”) for the AHRQ/PCORI LHS E-StaR Centers. The SCALE-LHS Hub will serve four key functions. First, the Hub will provide timely and effective coordination of network activities. Second, the Hub will support LHS activities focused on equity – the newest LHS competency domain – through the creation of an LHS Equity Enhancement Collaborative and through monthly LHS equity seminars. Third, the Hub will conduct annual formative and summative evaluations of the 16 LHS E-StaR Centers and the overall network using a robust mixed methods approach. Fourth, the Hub shall synthesize learnings across the network and disseminate these learnings using a multimodal approach. SCALE-LHS will leverage the expertise of three complementary centers at Penn: the implementation science expertise of the Penn Implementation Science Center (PISCE, led by MPI Lane-Fall), the health equity expertise of the Penn Center for Health Equity Advancement (CHEA, led by MPI Aysola), and the quality and safety capacity building expertise of the Penn Center for Healthcare Improvement and Patient Safety (CHIPS, led by MPI Myers). Key activities of the SCALE-LHS Hub will be conducted in partnership with AHRQ and PCORI staff and will include: planning and facilitating monthly program director (PD) meetings; planning and executing an annual meeting of PDs and LHS scientist trainees; distributing a monthly newsletter with network events, relevant readings, and other information of interest to the LHS E-StaR network; training and supporting LHS scientists in integrating equity considerations and meaningfully engaging with community members and other stakeholders; gathering program information from PDs and scientists; evaluating programs and delivering evaluation results to the LHS E-StaR sites; sharing learnings from the network through reports, white papers and policy briefs, blogs, peer-reviewed publications, and social media; and meeting with AHRQ and PCORI staff as needed to support the E-StaR centers. Deliverables include annual network reports of activities and learnings, annual equity reports, publications, and a Hub website with a YouTube channel for equity seminar recordings. The SCALE-LHS Hub will meet the needs of the LHS E-StaR network by supporting both operational needs (coordination, evaluation) and aspirational goals (fostering equity and stakeholder engagement, promoting learning across the network). In so doing, the SCALE-LHS Hub will catalyze the impact of embedded learning health system scientists in reaching the nation's goals for high-value, high-quality health care and outcomes.

NSF Awards · FY 2024 · 2024-11

Infectious diseases are a major global health concern. Rapid and accurate detection of the presence of disease-causing RNA is crucial for effective diagnosis and control of these diseases. The CRISPR-Cas13 system is a cutting-edge technology for RNA detection. However, the currently used Cas13 enzymes can become unstable and lose their effectiveness during long-term storage and in field applications. This project aims to improve the stability and sensitivity of a heat-resistant version of the Cas13 enzyme, making it more reliable and sensitive for detecting RNA. This includes enhancing the enzyme's ability to recognize and cut RNA and combine it with advanced electrochemical devices to create a highly sensitive and stable detection method. The proposed scientific advancements are closely connected to educational outreach activities. The project will involve high school and community college students, particularly from underrepresented backgrounds, in biological and bioengineering research. Students will receive training in experimental techniques, data analysis, and scientific writing. Additionally, high school students will be introduced to CRISPR technology through a biotech academy and integrate the research findings into university courses. The goal of the project is to combine mechanism-based protein engineering and cutting edge electrochemical devices to generate next-generation RNA detection tools for infectious disease diagnosis. The project will leverage the CRISPR-Cas13 system, which has shown great promise as next-generation diagnostics for in vitro RNA detection owing to its high specificity, programmability, and fast reaction rate. The collaborative project aims to first investigate the structure and mechanism of the recently discovered thermostable Cas13. Leveraging the mechanistic understanding, rational engineering of the thermostable Cas13 will be performed to produce new variants with superior thermostability and protease resistance, as well as enhanced target sensitivity and reaction speed. The engineered Cas13 variants will be combined with innovative electrochemical devices to enable ultrasensitive and robust RNA detection of various pathogens derived from clinical samples. Successful completion will provide superior RNA detection tools for medical and research applications, alongside novel insights into the Cas13 nuclease mechanism. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Mid-career researchers generally face a variety of distinct challenges: increased teaching loads, greater expectations for service and advising, a more competitive landscape for funding, and a lack of the variety of targeted programs that supported them as early-career scholars. As a result, many mid-career researchers do not make the impact they set out to achieve, or simply leave academia. Without a structured support system and training, these faculty do not have the skills they need to endure -- let alone flourish -- at this critical point in their careers. The absence of structured training leaves professionals in these fields ill-equipped to navigate difficult conversations, power dynamics, and the overwhelming demands of their multifaceted roles. Research suggests that leadership training programs improve leadership effectiveness, project outcomes, research engagement, emotional intelligence and confidence, while also reducing workplace conflict. Even though mid-career faculty comprise the largest segment of academia and that the benefits of mid-career leadership training are resounding, leadership programs are rarely available for them. ClimPraxis will develop a framework for climate and environmental scholars at the mid-career stage to build community and gain critical leadership skills. The goal of this project is to provide structure and opportunities for mid-career cryosphere scholars to interact and support each other. Through intentional leadership training and goal setting, this project will support new leaders and will enable scholars to work together on bigger, multidisciplinary problems that the traditionally siloed structure of academia discourages. This pilot program will include a cohort of scientists working in the cryosphere; focusing this effort on a small community with contiguous career goals and substantive, field-specific, leadership challenges will facilitate cross-pollination both within disciplines and between institutions and generate targeted support and training. This pilot program will focus on career reflection and assessment, leadership skill building, career planning, and career action. By documenting the process and collecting feedback from participants, this pilot will also investigate the individual needs of mid-career researchers and effective ways to meet those needs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Approximately 1 in 54 children in the US is diagnosed with autism spectrum disorder (ASD). Given its high prevalence, there is a need for an automatic and scalable method to inform diagnosis and behavioral therapies. While prior work on finding early-emerging and reliable quantitative biomarkers of ASD has focused on non-motor features, abundant research evidence has revealed patterns of impaired motor imitation in a wide range of children with ASD, making motor imitation deficits a promising avenue to find a phenotypic biomarker. However, traditional imitation assessment methods often rely on expert-based observation, which is costly, time-consuming and error-prone, and lacks objectivity and scalability. Recent advances in computer vision and machine learning make artificial intelligence a promising technology to design an objective, reproducible and highly-scalable multimodal system functioning not only in well-equipped clinical setups but also at home for assessing imitation performance in children with ASD. However, critical challenges such as the design of specific imitation tasks for ASD assessment, the collection and labeling of multimodal data for training machine learning algorithms, and the development of novel fine-grained representations human movements and metrics for comparing such movements need to be addressed to test the validity, scalability and reproducibility of automatic motor imitation assessment algorithms to inform ASD diagnosis. The overall goal of this project is to design, develop and test an objective, reproducible and highly-scalable multimodal system to observe children performing a brief video game-like motor imitation task, quantitatively assess their motor imitation performance, and investigate its validity as a phenotypic biomarker for autism. Accomplishing this goal will require an interdisciplinary approach which combines expertise in autism, child development, computer vision and machine learning. Specifically, this project will: (1) design motor imitation tasks that are relevant for ASD assessment, (2) design, test and validate a scalable and flexible system to collect and label multimodal data of children imitating a sequence of movements; (3) design a novel fine-grained representation of human movements that can be learned efficiently and is suitable for comparing the children's movements to the movements they need to imitate; (4) develop novel computer vision and metric learning algorithms for learning and comparing multimodal representations of human movements, and (5) use such metrics to generate candidate imitations scores that can be used as potential quantitative biomarkers for ASD. The motor imitation assessment methods to be developed in this project could be used in a wide variety of applications beyond assessing children with ASD, such as providing imitation performance scores for video-based rehabilitation therapy, surgical skill assessment, athletic activities and other movement-based instructional activities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Many cities are experiencing more frequent and more intense extreme heat events presenting an increasingly important public health hazard. But there is considerable variability of urban heat within cities resulting in disparate extreme heat impacts on different populations. Intra-city heat exposure varies as a function of multiple factors including building heights, tree canopy cover and surface characteristics. This project uses urban microclimate modeling and geospatial technologies to estimate and map the urban heat distribution at a spatial resolution of 1m and at the pedestrian level. Based on the hyperlocal variability of heat distribution, this project further evaluates the daily heat exposure of pedestrians walking from home to nearby destinations including parks, playgrounds, and public transit stations. This project provides a detailed understanding of how urban heat impacts people’s daily lives. This research also evaluates the impact of extreme weather on the heat exposure taking into consideration the socio-economic characteristics across neighborhoods. This project helps urban planners and city governments to develop plans to enhance climate resilience. High-resolution urban heat data developed by the project is disseminated through public websites to benefit public health researchers and urban environmental planning. Cities are experiencing more frequent and more intense extreme heat events which are an increasingly important public health hazard. Knowing the spatial distribution and the temporal variation of heat is of critical importance to understand the conditions that result in extreme heat exposure. The project applies geospatial data analytics, urban microclimate modeling, parallel geocomputing, and nationally available high-resolution geospatial datasets to model and map urban outdoor heat exposure. High-resolution heat exposure maps provide new understanding of the distribution of outdoor heat exposure across cities. This project also estimates heat exposure for routes connecting different origin-destination points. Researchers examine the spatial distribution of outdoor heat exposure among different socio-economic groups across neighborhoods to identify populations particularly at risk. This project develops data products and analysis to inform strategies to mitigate and adapt to the extreme heat in cities using a data portal and web-based geovisualization. The outcomes of this project help urban planners and city governments to develop plans to enhance climate resilience. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Graphs are structures used to describe relationship between objects. As such, their presence is pervasive in science and engineering. Graphs are at the core of a variety of disciplines that includes chemistry, communications, and transportation and are of increasing importance in a broader set of domains that includes integrated circuits, robotics, health and biology. The goal of this project is to extend generative artificial intelligence (AI) to the generation of graphs at scale. That is, it seeks to develop generative graph models capable of generating graphs with large numbers of nodes (objects) and a concomitant large number of edges (relationships). Scalability is a challenge of generative graph models that sets the problem apart from other generative models such as language and images. This is because it is more difficult to learn relationships than it is to learn objects. To attain scalability the project will advance the state of the art in three directions: (D1) Generative processes that focus on learning relationships, not objects. (D2) Generative process that work independent of scale and can therefore be trained at small scale and transferred to larger scales. (D3) Generative process that incorporate user-specified constraints in the generated graphs. Research Directions (D1)-(D3) are addressed in this international collaborative proposal in three research thrusts. Thrust I builds discrete diffusion processes that progressively add or remove edges form a random graph. The use of discrete diffusion is intended to reduce the combinatorial complexity of exploring the graph space and stands in contrast to the Gaussian diffusion processes used in audio and image generative AI systems. Thrust II learns by transference. It trains generative models for small graphs that are later transferred to larger graphs. This reduces the computational complexity of training diffusion models in large graphs. To build these generative models that work independent of scale we rely on graphon and manifold abstractions of graph and corresponding abstract learning architectures in the form of graphon and manifold neural networks. Thrust III incorporates requirements in generative models. This reduces the sample complexity of the search space by guiding the diffusion process towards graphs that satisfy user-specified constraints. Fundamental research is applied to the generation of molecular graphs that mimic molecules with known properties as is needed in, e.g., drug discovery aided by AI. Overall, this project will develop novel theory and methods for effective informed graph generation at scale. Advances in the use of AI for drug discovery are anticipated and impacts in communications, robotics, circuit design and health are likely. Further impact of this project will come from education activities related to the undergraduate AI major at the University of Pennsylvania. This research project will impact the major's introductory course for first year students in which students learn about machine learning architectures and training procedures. Labs in this course include simple examples of speech recognition, image classification, and recommendation systems that illustrate the role of learning architectures. Students also have labs on dynamical systems, reinforcement learning, generative diffusion models and language models to illustrate the different ways in which learning architectures are trained. This collaborative U.S.-Swiss project is supported by the U.S. National Science Foundation (NSF) and the Swiss National Science Foundation (SNSF), where NSF funds the U.S. investigator and SNSF funds the partners in Switzerland. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY The University of Pennsylvania Prevention Research Center (UPenn PRC) is submitting this application to become a Collaborating Center of the Prevention Research Centers’ Cancer Prevention and Control Research Network (CPCRN). This center will work with partners to accelerate the implementation of evidence-based cancer prevention and control strategies. The UPenn PRC’s CPCRN Collaborating Center will be an active participant in the Cancer Prevention and Control Research Network, engaging in research and practice activities that span the translation continuum from discovery to the dissemination and adoption, maintenance and sustainability of effective interventions. Promoting health equity in underserved and minority communities through improved access to evidence-based cancer prevention and control strategies is a major focus of the CPCRN center’s activities. The UPenn PRC Collaborating Center of the CPCRN will lead and manage a program of community-based cancer prevention and control research. The Center will strengthen partnerships to advance community-based intervention research in cancer prevention and control; translate and disseminate study tools, methods, and findings; and expand community-engaged dissemination and implementation research related to cancer prevention and control. Our center’s main activities will include CPCRN Network participation, collaboration on CPCRN Network workgroup projects, a core research project, and a training initiative. The core research project will implement and evaluate evidence-based strategies to increase cancer risk assessment and risk- stratified management for breast and colorectal cancer, for disadvantaged and minority adult patients at Federally Qualified Health Centers. The CPCRN Scholars Program will help to prepare the next generation of cancer prevention and control implementation science and health equity researchers. The diverse leadership of the proposed CPCRN center team has extensive experience in intervention and dissemination and implementation research, cancer prevention and control, and community-based participatory research. This center will support the work of a multidisciplinary team of co-investigators with expertise in cancer epidemiology, health services research, cancer screening, genetic counseling and testing, health disparities research and action, and health communication. Together with the network and our partners, this CPCRN center will advance research across the translation continuum to promote the adoption of effective cancer prevention and control interventions.

NIH Research Projects · FY 2025 · 2024-09

UNIVERSITY OF PENNSYLVANIA PREVENTION RESEARCH CENTER Multiple Principal Investigators (MPIs): Karen Glanz, PhD, MPH; Meghan Lane-Fall, MD, MSHP; and Oluwadamilola (Lola) M. Fayanju, MD, MA, MPHS The University of Pennsylvania Prevention Research Center (UPenn PRC) is submitting this application to support its Prevention Research Center for five years from 2024-2029. The aims of the UPenn PRC include strengthening public and private sector community partnerships; translating scientific knowledge into action to improve public health; and extending collaborative training, education, communication, and translation and dissemination activities in high-risk and disadvantaged groups in Southeastern Pennsylvania. The UPenn PRC will engage with community residents and organizations to adapt and study implementation science-informed strategies that focus on the prevention, reduction and treatment of chronic disease and on increasing health equity in Philadelphia, Southeastern Pennsylvania and beyond. We aim to strengthen community partnerships; implement an equity-focused prevention research agenda, reduce health risks, improve social-environmental contexts, and scale-up evidence-based interventions (EBI's) for wider reach. Our core research project will improve understanding of how to successfully implement community- and clinically-relevant EBI strategies to improve treatment decisions and quality of life of older adult cancer patients This proposal builds on the foundation of the UPenn PRC established in 2014 and a PCORI-funded Engagement Award for the Philadelphia Communities Conquering Cancer (PC3) Collaborative (2022-2024). The primary thematic focus of the Center and the focus of the core research project are on implementation of evidence-based strategies to improve patient and provider communication to optimize clinical and community- based management of cancer in diverse older adults. Using the processes, products, and findings of the core research project, the UPenn PRC will work with community partners to translate and disseminate implementation strategies to promote update of EBIs and improve shared decision-making, quality of life, and appropriate tertiary prevention for older cancer patients. Our proposal focuses on scalable approaches to address pressing health challenges for the public by working with community partners, using easily adapted strategies to improve communication between older cancer patients and providers, and leveraging implementation science techniques to improve adoption, fidelity and dissemination. Our Community Advisory Board (CAB) will be involved in all aspects of the Center and will help to ensure that all our efforts are designed to meet the needs of patients, providers, caregivers and the public.

NIH Research Projects · FY 2025 · 2024-09

The objective of the proposal is to test whether programs that improve housing security reduce exposure to violence for low-income renters who, in the city of Philadelphia, are disproportionately Black. This objective will be met using data from the PHLHousing+ Evaluation – a housing-focused guaranteed income experiment designed as a randomized controlled trial. The PHLHousing+ Evaluation comprises three groups, all of whom earn below 50% area median income and have at least one child under the age of 16 years living at home: 300 households who receive monthly cash payments in lieu of a rental voucher (Cash group), 300 households in receipt of a rental voucher (Voucher group), and 789 households on the Philadelphia Housing Authority (PHA) waitlist who have not, to date, been offered a rental voucher because of their randomized position on the waitlist (Control group). Of the 1,389 households in the study, 83% are headed by single women and 83% are Black. There are 2,678 children in the sample, ranging in age from 1 to 16 years (median = 10, IQR = 5-15). At enrollment, monthly cash payments ranged from $89 to $2079, with a median payment of $881; payments varied based on household income, family size, and fair market rent. Households in the Cash group will receive monthly payments for 2.5 years. All three groups are surveyed every six months for three years via an online survey; two waves of surveys have already been conducted, with the first deployed in August 2022. Surveys include questions about housing security, quality, and mobility, neighborhood quality, financial security and spending, and parent and child well-being. We propose to link household-level data on group membership with data on investigated and substantiated reports of child abuse and neglect from Philadelphia's Department of Human Services (DHS), Philadelphia county's child protective service. We also propose to link households' residential addresses with publicly-available block-level data from the Philadelphia Police Department on violent crime and fatal and nonfatal shootings. Aim 1 is to test whether randomization to the Cash or Voucher (versus Control) arms of the study reduces rates of substantiated child abuse and neglect and acceptance for formal child welfare services. Aim 2 is to test whether randomization to the Cash arm of the study (versus Voucher or Control) is associated with lower rates of exposure to gun violence and violent and nonviolent crime. Aim 3 is to test whether randomization to the Cash or Voucher (versus Control) arms of the study promotes equity by reducing oversurveillance of families in poverty. The proposed research is consistent with the National Center for Injury Prevention and Control's strategic priority to evaluate the effectiveness of policies designed to enhance the economic environment to reduce multiple forms of violence. Study findings will have immediate implications for the City of Philadelphia's model for providing housing assistance, inform efforts to establish similar programs in other cities as well as federal approaches to rental assistance, and provide actionable information about targeting housing security in efforts to prevent exposure to violence.

NIH Research Projects · FY 2025 · 2024-09

Project summary Alzheimer's Disease (AD) and AD-related dementias (ADRD) affect more than 6 million Americans and 55 million people worldwide. Environmental toxicant exposures from younger age have not been systematically investigated for their roles in AD/ADRD risk despite limited suggestive evidence for organochlorine pesticide DDT, organophosphate pesticides, lead, and cadmium. AD/ADRD pathogenesis may take decades to develop before clinical symptoms, thus the role of mid-life exposures on cognitive decline and brain magnetic resonance imaging (MRI) patterns may be critical to examine in identifying preventable environmental risk factors. A crucial mechanism through which these toxicants might act is via epigenetic alterations, alongside processes like neuroinflammation and oxidative stress. There's also a notable racial disparity, with Black older adults having a twice as high prevalence of AD as White older adults. This raises questions about the potential interplay between environmental exposures, epigenetic modifications, and social determinants of health (SDOH). In this proposal, we will leverage the ongoing NHLBI-funded Coronary Artery Risk Development in Young Adults (CARDIA) Study to examine the targeted and untargeted exposome and subsequent cognitive decline and brain MRI patterns in this biracial cohort of more than 5,000 Black and White young adults at baseline (mean age 25 years) with 35 years of follow-up completed. We will repeatedly measure organochlorine pesticides, polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), untargeted exposome in plasma, and metals and metabolites of organophosphate pesticides in urine samples (Aim 1). We will examine exposomic biomarkers for associations with cognitive decline and MRI patterns that increase the AD/ADRD risk (Aim 2). We will conduct an epigenomic- wide association study to identify epigenomic biomarkers associated with exposomic biomarkers and integrate multi-omic (genomic, epigenomic, transcriptomic, exposomic) data with neuroimaging and cognitive function data to decipher the biological links (Aim 3). Finally, we will examine the role of SDOH (including redlining, education, poverty, and discrimination) on the associations between exposomic, epigenomic, and AD/ADRD- related cognitive decline and brain MRI patterns (Aim 4). This project is highly responsive to the request for application that calls for the quantification of the impact of environmental toxicants on AD/ADRD risk in cohort studies, particularly exposure in the mid-age from 30-50 years. The findings will inform the scientific communities and the public about the environmental risk factor of AD/ADRD risk, address health disparities among Black population, and provide novel exposome data and biological insights for future scientific discoveries.

NIH Research Projects · FY 2025 · 2024-09

Project Abstract Frontotemporal lobar degeneration (FTLD) is a family of neurodegenerative proteinopathies with no treatment to cure or slow disease progression. Clinical trials for FTLD are hamstrung by the limited biomarkers in cerebrospinal fluid (CSF) or plasma for screening or prognosis of FTLD, due in part to the extensive clinical and pathological heterogeneity in FTLD. There are no in vivo biomarkers to classify the two major pathological forms of FTLD: FTLD due to tau (FTLD-tau) or TAR DNA-binding protein of 43 kDa (TDP-43; FTLD-TDP). Both FTLD-tau and FTLD-TDP can be sporadic or due to pathogenic mutations, and both subtypes are associated with several cognitive and motor syndromes which cannot reliably indicate underlying pathology. This heterogeneity, combined with the lack of FTLD biomarkers, means a biological study of the full spectrum of FTLD requires autopsy-confirmation, but these data are very rare. We propose a pathologically-grounded study of biofluid biomarkers in autopsy- and genetically-confirmed FTLD-tau and FTLD-TDP. Our clinical translational goal is to develop multi-analyte algorithms for screening and prognosis of FTLD. We leverage the unique FTLD cohort at University of Pennsylvania composed of >200 pathology-confirmed FTLD-tau and FTLD-TDP with banked CSF and plasma, as well as antemortem genetic, clinical, demographic, and neuroimaging data. We compare biomarkers in FTLD to healthy controls and autopsy- confirmed Alzheimer's disease (AD), a related proteinopathy. In lieu of FTLD-specific biomarkers, we test biofluid markers of disease processes central to FTLD pathogenesis: neurodegeneration (e.g., neurofilament light chain, total tau), neuroinflammation (e.g., glial fibrillary acidic protein, chitinase-3-like protein 1), and synaptic dysfunction (e.g., neuronal pentraxin-2, neurogranin). Advantages are that these biomarkers are analytically validated, can be precisely measured in CSF and plasma using high-sensitivity immunoassays, and preliminary data indicate their high potential to inform and track FTLD biology. Our study would be first to combine these biomarkers in autopsy-confirmed FTLD, to test their association with neuropathology, and to test changes over disease course. Findings will advance our understanding of FTLD biology and how pathogenesis differs across tau and TDP-43 molecular forms, and will expand the diagnostic and prognostic FTLD biomarker toolkit. Aim 1: Pathologically validate biomarkers in FTLD subtypes using autopsy and digital-histopathology data, compared to AD and controls. Test hypothesized direct and indirect effects with FTLD pathophysiology. Aim 2: Map the pathogenic disease cascades in FTLD subtypes by tracking the natural history of biomarker dynamics; use disease progression modeling to sequence biomarker abnormalities in FTLD. Aim 3: Develop multi-analyte algorithms to provide a differential diagnosis (FTLD vs. AD and controls, FTLD-tau vs. FTLD-TDP) and to estimate prognosis in FTLD; we ensure that our algorithms will generalize by verifying accuracy in an independent replication sample, using data from the multi-site ALLFTD consortium.

NIH Research Projects · FY 2025 · 2024-09

The anterior intervertebral disc and posterior diarthrodial facet joints form what is referred to the three-joint complex of the spine, working in concert to resist large magnitude axial loads and constrain range of motion to non-injurious levels. Degenerative pathology in both spinal structures is a known contributor to back pain, which has become the number one cause of years lived with disability globally. Intervertebral disc degeneration is associated with structural and biochemical changes to the disc tissues, which compromise the ability of the disc to bear load, potentially leading to overloading of the facet joints. The study of disc degeneration has been dominant in the field for decades, and as such, little is known the pathophysiology of facet osteoarthritis (OA), or how altered disc mechanical function may contribute to the progression of facet degeneration. This proposal will bring a new perspective to the study of spinal degeneration by investigating the mechanical crosstalk between the disc and its adjacent facet joints during degenerative processes and in the scenario of disc repair, using animal models and human tissues. In Aim 1A, we will first utilize a large animal model to characterize the progression of facet OA in an initially healthy spine following experimentally induced degeneration of the adjacent discs. Facet cartilage and subchondral bone pathology will be probed across length scales as a function of disc degeneration to determine the temporal relationship between disc degeneration and facet OA. In Aim 1B, we will also utilize human cadaveric tissues to determine how facet pathobiology and disc-facet crosstalk differ in males versus females, factors less easily studied in large animal models. In both goat experimental and human cadaveric tissues, we will assess inflammation, innervation and immune cell infiltration into the disc and facet joint synovium and capsule as surrogate measures of pain and biological dysfunction. Finally, quantitative structure-function outcomes from both goat and human spinal tissues (Aims 1A and B) will then be utilized to generate patient/animal-specific finite element models, which will be used to quantify stress distributions in the facet joints under simulated six degree of freedom physiologic loading to understand mechanistically how altered disc mechanical function during degeneration may contribute to the progression of facet OA. In Aim 2, we will then elucidate whether restoring intervertebral disc mechanical function can mitigate the progression of disc degeneration and facet OA. Using the same large animal model as Aim 1, we will deliver an injectable, granular hyaluronic acid hydrogel to the degenerative nucleus pulposus to acutely augment disc mechanical properties. The acute effects of NP augmentation via the granular hydrogel on facet loading will be assessed using the animal-specific finite element models utilized in Aim 1. The extent of disc repair and concomitant progression of facet OA in vivo will be assessed across length scales via a variety of structure-function outcomes. Overall, the knowledge gained from this study of disc-facet crosstalk can contribute to developing advanced diagnostics for spinal degeneration and elucidating new targets for tissue engineering and regenerative medicine strategies.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Studies in humans suggest that Neurexin1α (Nrxn1α), a presynaptically expressed organizer of synaptic structure, is a key genetic risk factor for multiple neuropsychiatric diseases, all of which exhibit impairments in goal-directed processing. Given the pernicious effects of goal-directed dysfunction on daily quality of life, a better understanding of the underlying neurobiology – both at the molecular and neural circuit level - is strongly warranted. Our prior work has developed quantitative behavioral and in vitro electrophysiological approaches while demonstrating that mice with mutations in Nrxn1α are an excellent system to study alterations in neural circuit activity driving impaired goal-directed behavior. Efficient goal-directed behavior relies on reinforcement, whereby outcomes shape future actions, as well as flexibility, the ability to adapt to changes in contingencies or context. Both processes are thought to occur in part within the striatum, where excitatory inputs representing choice-relevant information interact with neuromodulators, such as dopamine (DA) and acetylcholine (ACh), which signal information about rewards, surprise, and uncertainty from the external world. Nrxn1 is broadly expressed in these cortico-striatal-thalamic circuits including the presynaptic terminals of striatal-targeting cortical and thalamic neurons, as well as within striatal cholinergic interneurons and striatal-targeting dopaminergic projections from the midbrain. Here we examine how Nrxn1 functions within midbrain dopamine neurons and striatal cholinergic interneurons, the major sources of striatal dopamine and acetylcholine, respectively. We employ cell type specific Nrxn1 deletion together with acute slice recordings to mechanistically address how Nrxn1 contributes to the striatal release of these key neuromodulators. In parallel, we use in vivo imaging of novel sensors for dopamine and acetylcholine to investigate how these modulators are altered during value-based choice tasks in both circuit-specific and brain-wide Nrxn1 KOs. We will correlate abnormal neuromodulatory signals with abnormalities in choice behavior, focusing on reinforcement processes and choice flexibility. To probe the functional relevance of altered neuromodulatory signals for behavior, we optogenetically impose abnormal ACh and DA signals in WT mice and observe impacts on choice selection and flexibility. Finally, we examine how Nrxn1 mutations impact striatal processing during selection of actions via in vivo recordings in wildtype and Nrxn1 KO mice. The proposed work will inform us of how mutations in Nrxn1 alter striatal cholinergic and dopaminergic signals and striatal processing of goal-directed actions, while providing a framework to understand the diversity of goal-directed dysfunction seen across neuropsychiatric disorders.

NIH Research Projects · FY 2024 · 2024-09

Project Summary Cardiovascular disease is the leading cause of death in the United States and accounts for 1 in every 5 deaths. Sudden cardiac death is responsible for nearly half of all heart disease related mortality and is often attributed to the occurrence of lethal ventricular arrhythmias. Ventricular arrhythmias also are a major source of morbidity and mortality in patients with structural heart disease. Antiarrhythmic drug therapy provides only limited efficacy in preventing ventricular arrhythmias and while implantable cardioverter defibrillators provide life-saving therapy to terminate the arrhythmia once it has occurred, they do not prevent them from occurring. For these reasons, catheter ablation of ventricular arrhythmias has emerged as an additional therapy for many patients with refractory ventricular tachycardia (VT). However, VT ablation procedures are complex and multiple procedures are often required to achieve modest long-term success. Therefore, there is a critical need for additional VT therapies. Cardiac stereotactic body radiation therapy (cSBRT) has emerged as an adjunctive noninvasive approach that can be utilized to treat patients with VT that is refractory to standard antiarrhythmic drug therapy and catheter ablation with clinical efficacy observed in some very complex patients. However, the clinical response following cSBRT has been highly variable and the electrophysiologic mechanism is unclear. We believe that better understanding the mechanisms of cSBRT will help refine and guide clinical cSBRT paradigms, optimize patient selection, and better define the appropriate role this therapy should have in clinical practice. We propose a series of experiments to investigate the association between cSBRT dose and structural and electrophysiologic changes using longitudinal cardiac magnetic resonance (CMR) imaging and high-resolution electroanatomic mapping in a large animal model of chronic myocardial infarction and reentrant VT. In Aim 1, we will investigate the impact of cSBRT dose (15Gy, 25Gy, and 35Gy) at short and intermediate follow-up timepoints. We will also investigate the long-term impact of cSBRT delivered at the dose currently used clinically (25Gy) out to 1 year. In Aim 2, we will similarly investigate structural and electrophysiologic changes that occur in patients undergoing clinically indicated cSBRT compared to catheter ablation. This study will give a new understanding of the dose and time relationship of cSBRT on the heart that will be essential in moving this field forward.

NIH Research Projects · FY 2024 · 2024-09

ABSTRACT The US is currently on pace to fall short of achieving the goals set by the Ending the HIV Epidemic (EHE) initiative launched by the Department of Health and Human Services in 2019. A growing body of research suggests that the root causes of EHE's striking lack of progress are structural racism and social stratification that leads to poverty. Housing instability — a lack of stable, secure, and adequate housing that results from poverty and structural racism — is a major social determinant of health (SDOH). The Philadelphia Department of Health (PDPH) estimates that 4,000 people with HIV (PWH) experience housing instability in Philadelphia. While the National HIV/AIDS strategy specifically calls for approaches to address SDOH (including through the development and scaling up of housing interventions), the vast majority of EHE efforts continue to focus on facilitating healthcare access and uptake. There have been few rigorous evaluations of housing interventions for PWH, and even fewer during the modern era of universal treatment for HIV. In close partnership with the PDPH, we will rigorously evaluate a potentially transformative city-level transitional housing program for PWH experiencing housing instability (“Arms Around You” or AAY), leveraging lottery drawings from a waitlist to estimate causal effects. The program will be implemented by PDPH in 2024 and scaled up in the coming years (~200 anticipated enrollments during the first several years). AAY includes (1) intensive housing counseling, (2) housing medical case management, and (3) full rent payment support for 48 months (or longer if needed). We will use mixed methods to collect quantitative (survey data, pharmacy refill data, and PDPH surveillance/program data) and qualitative (key stakeholder interviews) data. If the AAY screening period begins before this proposal's full review by NIH, we have pilot funding from PDPH to collect baseline data. Since PDPH's lottery drawing is necessitated by high anticipated demand (PDPH estimates there are 4,000 PWH in Philadelphia experiencing housing instability) and limited initial availability (~200 available spots during the first few years), we will be able to estimate the long-term effects of the program on health, economic, and psychological outcomes. In addition to studying mechanisms through which housing interventions affect health outcomes, we will use implementation science methods to assess program acceptability, reach, sustainment, and costs to inform scalability to other cities. This proposal is innovative in that we will capitalize on a unique opportunity to use rigorous causal and implementation science methodology to evaluate the health and non-health effects of a population-level large- scale housing intervention that addresses an important SDOH. This approach could significantly impact both HIV- and non-HIV-related outcomes, such as viral suppression, ART adherence, engagement in care, substance use, financial well-being, housing security, food security, psychological distress, hope, and future orientation. This study will provide critical evidence to policymakers at a time when many cities are considering housing support programs and various other anti-poverty interventions (e.g., guaranteed income).

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY/ABSTRACT Background: Aging is an incredibly plastic process that is dictated by coordinated repair and regenerative mechanisms. Loss of this coordination marks the start of tissue decline and aging, thereby increasing disease susceptibility. Alarmingly, age-dependent diseases are disproportionately rising in young age groups without known cause. Early-Age Onset Colorectal Cancer (EAO CRC) is a prime example, which African Americans experience the highest disease burden. Rationale: Previously, we discovered a novel Hedgehog (Hh)-dependent mechanism that balances cellular repair and regeneration to sustain healthy tissue aging. Specifically, we identified the Hh effector Patched (Ptc) as a critical switch for balancing autophagy-based cellular repair and Hh-dependent regenerative proliferation. Importantly, loss of Ptc function drives accelerated cellular aging. Hypothesis: We propose that the cells are aging rapidly relative to chronological age, due to the loss of this Hh-dependent coordination of autophagy and proliferation. We predict factors that promote aberrant Hh signaling predispose individuals to EAO CRC onset. Specific Aims: To test this hypothesis, I will delineate the mechanism of Hh signaling in balancing autophagy and proliferation to preserve cellular aging (Aim 1); define the Hh-dependent transcriptome during aging, with a particular interest in identifying genes that are dysregulated in cancers impacting African Americans (Aim 2); and functionally test the intersection of Hh signaling and genetic determinants of cancer disparities using both the Drosophila intestines model and patient-derived colon organoids (Aim 3). This study will precisely define fundamental mechanisms and aging-dependent cellular markers that are applicable to diseases impacting African American communities. The culmination of this investigation will hone the required knowledge, technical skillsets, and professional networks to successfully launch my independent research program, focused on elucidating regulators of the autophagy-proliferation balance to reduce aging-related disease disparities.

NIH Research Projects · FY 2024 · 2024-09

Project Summary Although mild post-stroke aphasia is often disabling, there are no accepted treatments for this condition. Transcranial Magnetic Stimulation (TMS) in conjunction with Speech-Language Therapy, has been demonstrated to improve language function in subjects with moderate to severe chronic aphasia. We propose to study the effects of continuous Theta Burst Stimulation (a type of TMS) combined with a modified form of Constraint Induced Language Therapy (mCILT) in 24 subjects with chronic, mild (operationally defined as Western Aphasia Battery – Revised Aphasia Quotient >85) post-stroke aphasia. Subjects will be randomized in a 2:1 ratio to cTBS with mCILT or sham cTBS with mCILT. After pre-treatment evaluation, subjects will receive 10 days of treatment; post-treatment evaluations will be performed 3-5 days and again at 2 and 4 months after the completion of treatment. We will use electrical field modelling to personalize stimulation intensity for each subject. Change from baseline to 4 months post-treatment on measures of language performance previously demonstrated to distinguish people with mild, post-stroke aphasia from neurotypical will serve as the primary outcome measure. A secondary aim is to explore the effects of the treatment on non-linguistic cognitive functions and assess their role in the genesis of the communication impairment in mild aphasia.

NIH Research Projects · FY 2024 · 2024-09

Abstract Our health and wellbeing prenatally and during the earlier years of life affect all future health and disease risks. This time period is the most sensitive for a child’s developing brain and various other tissues of body. Studies of developmental biology have demonstrated that gene expression patterns are not only tissue-specific and cell type-specific, but also age regulated and controlled through coordinated action of complex tissue- and cell-type specific networks and pathways. The NIH Developmental Genotype-Tissue Expression (dGTEx) project aims to study gene expression patterns at a tissue-level over several early developmental windows and to char- acterize transcriptional profiles during human development. Complementary to the human dGTEx effort, the non-human primate (NHP) dGTEx aims to study gene expression patterns in multiple reference tissues across developmental stages in NHP model species and compare them to human gene expression patterns. The over- arching goal of Penn Data Integration and Statistical Analysis Methods (Penn-DISAM) project is to develop novel statistical and computational methods specifically for effective analysis of human dGTEx and NHP dGTEx data, including novel methods for analyzing a very large set of correlated regression functions that characterize the age-dependent gene expression functions across different tissues and between human and primates. The dG- TEx and NHP dGTEx data allow us to estimate the tissue-cell specific age-dependent gene expression functions by leveraging the gene expression data measured over different ages in postnatal, early childhood, pre-pubertal and post-pubertal developmental windows. We will particularly develop nonparametric B-spline regression to estimate the age-dependent gene expression regression functions and summarize the data as the matrix of functions. We will develop methods for data visualization and for statistical inference, including methods for iden- tifying genetic variants that are associated with different gene expression distribution functions in each of the tissues. We will also develop novel statistical warping methods to align gene expression trajectories between human and primates, which allow us to identify genes under strong stabilizing selection, to quantify the inter- species divergence in gene expression in each tissue and in each developmental stage, and to compare the difference of age-dependent weighted co-expression networks between human and primates. Penn-DISAM will work closely with the dGTEx consortium to develop, implement, test and apply these methods and the software tools to dGTEx data. Finally, we will make all the software available via AnVIL and GitHub.

NIH Research Projects · FY 2024 · 2024-09

PROJECT SUMMARY Stress is associated with insufficient sleep and poor quality sleep. In particular, fragmented non-rapid eye movement sleep (NREMs) due to frequent brief arousals (microarousals, MAs) disrupts sleep continuity, and rapid eye movement sleep (REMs) abnormalities are often observed in patients with insomnia and depression. Insufficient sleep and alterations in sleep microarchitecture caused by stress may in turn worsen the stress symptoms, such as cognitive impairment, and have been shown to increase the risk of developing psychiatric disorders. Nevertheless, the identity of the involved stress- and sleep-regulatory circuits, and the mechanisms by which stress perturbs distinct features of the sleep architecture and negatively impacts cognitive behaviors are still largely unclear. We have recently shown that acute psychosocial stress in mice decreases the amount of sleep and disrupts sleep quality by causing frequent MAs and suppressing REMs. We propose that the stress-induced decrease in the amount of sleep and changes in sleep microarchitecture are mediated by different circuit mechanisms. The preoptic area of the hypothalamus (POA), a crucial center regulating macro- and microarchitecture of sleep and wakefulness, is densely innervated by stress-regulatory noradrenergic neurons in the locus coeruleus (NELC) and corticotropin-releasing hormone neurons in the paraventricular nucleus (CRHPVN). The goal of this proposal is to investigate to what extent the NELC and CRHPVN neurons cause stress-induced sleep disturbances and memory impairment via projections to distinct POA subpopulations. Our central hypothesis is that stress-induced MAs and REMs dysregulation are mediated by inputs from NELC neurons to the POA (NELC→POA), while the overall decrease in sleep is mediated by inputs from CRHPVN neurons (CRHPVN→POA) and that reversing sleep disturbances attenuates stress-induced memory deficits. Aim 1 will determine the role of NELC→POA projections in stress-induced MAs and REMs dysregulation as well as related memory deficits. Aim 2 will determine the role of CRHPVN→POA projections in stress-induced wakefulness and related memory deficits. Accomplishing these aims will provide important insights into the neural basis of stress-induced sleep disturbances and the benefits of good quality and quantity sleep in reversing stress symptoms, with potential relevance to understand and develop novel therapeutic interventions for stress-related sleep disorders.

NIH Research Projects · FY 2025 · 2024-09

Project Summary/Abstract A large majority of heritable human traits and diseases are complex, with genetic variants of small effect spread throughout the genome. It is now understood that genetic contributions to disease are enriched in gene promoters and enhancers thought to regulate expression. This has led to the hypothesis that genetic variation leads to disease via disruption of an underlying gene regulatory network, either via trait-relevant pathways or distal perturbations propagating through the network to trait-specific core genes. At present, our lack of understanding of the networks themselves limits our ability to understand how their disruption can lead to disease state. In the long-term, causal models of these networks may reveal avenues for treatment by suggesting mechanisms for returning the system to proper functioning. Here, I propose to leverage recent developments in causal inference to show that novel computational methods enable integration across large-scale data generation efforts to highlight regulatory changes underlying common disease. I propose to i) improve causal structure learning methods to better leverage prior biological knowledge and improve network estimation for genes that are lowly expressed, poorly captured or difficult to intervene on experimentally and ii) construct a causal network integrating populationscale eQTL data and GWAS summary statistics, and conduct a thorough comparative analysis with large-scale CRISPR perturbation data in immortalized cell lines. The first aim will enable us to construct genome-wide causal networks using single cell CRISPR screen data, including many functionally-relevant genes that are difficult to capture using existing methods. Our second aim will enable identification of core disease-relevant genes and their pathways, and allow us to identify which traits and disease pathways are best studied by current in vitro immortalized cell line models. Completion of these aims will provide a framework for large-scale estimation of regulatory networks and their role in complex trait biology.

NIH Research Projects · FY 2025 · 2024-09

Project Summary Engineered T cells that express a chimeric antigen receptor (CAR) specific to tumor antigens have shown exceptional efficacy in hematologic malignancies. However, their success in treating solid tumors remains limited. Our understanding of the primary barriers faced by CAR T cells in solid tumors is hindered by a lack of tissue specimens and suitable high-depth tumor microenvironment (TME) profiling technologies. Model systems have largely been unsuccessful in accurately predicting human CAR T cell biology. To understand the barriers faced by CAR T cells in solid tumors, Andrew J. Rech proposes an integrated spatial multi-omic analytical platform. Dr. Rech plans to apply this platform to tissue specimens taken before and after CAR T cell infusion from five CAR T cell clinical trials. These trials focus on pancreatic cancer, prostate cancer, and highly active IL-18-secreting CAR T cells in non-Hodgkin lymphoma. Dr. Rech will leverage the significant differences in the TME in these diseases to understand the principles of response and resistance to therapy. Dr. Rech’s overarching hypothesis is that CAR T cell function and therapeutic efficacy are constrained by specific, actionable interactions between tumor, CAR T cells, and tumor-infiltrating myeloid cells. His preliminary data suggest that paracrine interactions between CAR T cells and myeloid cells could limit CAR T cell function and be linked to hyperinflammatory toxicity. In Aim 1, Dr. Rech will define the tumor and stromal features that influence CAR T cell tumor infiltration and function. In Aim 2, he will determine the impact of CAR T cell functional profile on myeloid tumor stroma. Lastly, in Aim 3, Dr. Rech will determine the impact of CAR T cell functional profile on tumor cell plasticity and antigenicity. In each Aim, he will also develop a relevant murine model to validate results mechanistically and enable a path to future phase I clinical trials. In summary, the spatial multi-omic profiling Dr. Rech proposes will identify response, resistance, and toxicity pathways that impact CAR T cell therapy in patients and that can be targeted to improve therapy. In this proposal, Dr. Rech leverages his background as an interdisciplinary wet lab scientist, computational scientist, and board-certified pathologist. He has developed a new line of investigation that is distinct from the research of current and previous mentors and has already achieved major landmarks of scientific independence. Dr. Rech has also garnered substantial institutional support at the University of Pennsylvania, a globally recognized leader in the field of T cell engineering. Along with his mentors and department, Dr. Rech has designed a six-component career development plan to facilitate his transition to independence. In summary, the proposed studies will identify TME response mechanisms to CAR T cell therapy in unprecedented detail in humans, guiding the development of next-generation CAR T cell therapy. The proposal also enables Dr. Rech to launch his independent career in the unexplored scientific area of understanding how engineered immune cells can reorganize the TME.

NIH Research Projects · FY 2025 · 2024-09

PROJECT SUMMARY Stress is associated with insufficient sleep and poor quality sleep. In particular, fragmented non-rapid eye movement sleep (NREMs) due to frequent brief arousals (microarousals, MAs) disrupts sleep continuity, and rapid eye movement sleep (REMs) abnormalities are often observed in patients with insomnia and depression. Insufficient sleep and alterations in sleep microarchitecture caused by stress may in turn worsen the stress symptoms, such as cognitive impairment, and have been shown to increase the risk of developing psychiatric disorders. Nevertheless, the identity of the involved stress- and sleep-regulatory circuits, and the mechanisms by which stress perturbs distinct features of the sleep architecture and negatively impacts cognitive behaviors are still largely unclear. We have recently shown that acute psychosocial stress in mice decreases the amount of sleep and disrupts sleep quality by causing frequent MAs and suppressing REMs. We propose that the stress-induced decrease in the amount of sleep and changes in sleep microarchitecture are mediated by different circuit mechanisms. The preoptic area of the hypothalamus (POA), a crucial center regulating macro- and microarchitecture of sleep and wakefulness, is densely innervated by stress-regulatory noradrenergic neurons in the locus coeruleus (NELC) and corticotropin-releasing hormone neurons in the paraventricular nucleus (CRHPVN). The goal of this proposal is to investigate to what extent the NELC and CRHPVN neurons cause stress-induced sleep disturbances and memory impairment via projections to distinct POA subpopulations. Our central hypothesis is that stress-induced MAs and REMs dysregulation are mediated by inputs from NELC neurons to the POA (NELC→POA), while the overall decrease in sleep is mediated by inputs from CRHPVN neurons (CRHPVN→POA) and that reversing sleep disturbances attenuates stress-induced memory deficits. Aim 1 will determine the role of NELC→POA projections in stress-induced MAs and REMs dysregulation as well as related memory deficits. Aim 2 will determine the role of CRHPVN→POA projections in stress-induced wakefulness and related memory deficits. Accomplishing these aims will provide important insights into the neural basis of stress-induced sleep disturbances and the benefits of good quality and quantity sleep in reversing stress symptoms, with potential relevance to understand and develop novel therapeutic interventions for stress-related sleep disorders.

NIH Research Projects · FY 2025 · 2024-09

Interstitial lung disease (ILD) is a highly morbid and potentially fatal complication of myositis. Current myositis phenotypes do not capture significant heterogeneity in ILD clinical behavior. Existing prediction models and biomarkers perform poorly in patients with myositis-ILD and require longitudinal validation in diverse patient populations. Because clinicians lack tools to prognosticate long-term myositis-ILD outcomes, many patients receive either inadequate or overly aggressive treatment. We have shown that the GAP-ILD Index performs poorly in myositis- ILD. Myositis-ILD specific prediction tools do not adequately model disease progression and do not generalize to populations outside of Asia. Previously, we demonstrated that specific human leukocyte antigen (HLA) alleles are myositis-ILD susceptibility factors. Our preliminary model of progression-free survival containing clinical data and HLA genotypes discriminated progression, suggesting that HLA haplotypes are also biomarkers of myositis-ILD disease activity and treatment responsiveness. As a next step, we plan to refine and validate our preliminary model. The goal of Specific Aim 1 is to utilize a large, diverse multicenter cohort of patients with myositis- ILD in North America to develop a prediction model of progression free survival using known and novel biomarkers. While increasingly recognized, there is no current strategy to confront the clinical and biological heterogeneity within myositis-ILD subgroups. Our preliminary data demonstrates two clusters of myositis-ILD. We hypothesize that these myositis-ILD clusters carry distinct pathobiology, treatment responsiveness, and outcomes. The goal of specific Aim 2 is to apply cluster analysis to clinical, genomic, and serological data from patients with myositis-ILD to identify novel subphenotypes. The data generated from this proposal will result in a novel classification of myositis-ILD subphenotypes and a superior tool for prognosticating important clinical outcomes. Our approach is feasible because we are building on existing clinical and biorepository data from five demographically diverse myositis-ILD referral centers in the United States. This contribution is significant because it will establish a validated clinical signature for precision therapy in patients with myositis-ILD and generate novel treatment approaches.