University Of Pennsylvania

NIH Research Projects · FY 2026 · 2023-06

PROJECT SUMMARY Vibrio cholerae (Vc), the causative agent of cholera, colonizes the mucosal surface of the small intestine. Infec- tion is mediated via virulence factors to penetrate the mucus layer, attach to epithelial cells, and proliferate, all the while modulating interactions with both host cells and the gut microbiota. The human gut microbiota is highly diverse, and interpersonal variation in the structure and function of the microbiota drives dramatic differ- ences in Vc colonization. At the center of microbe-microbe and microbe-host interactions lies the host mucus layer, comprised of secreted mucin glycoproteins including the dominant mucin MUC-2. Mucus provides at- tachment sites and carbon sources for both pathogens and commensal members of the gut microbiota at the interface of the epithelium and the gut lumen, as provides a key physical barrier to infection. However, the role of mucin metabolism in metabolic interchanges between Vc and specific configurations of the gut microbiota, and the resulting impact on personalized Vc infection outcomes, has not been well studied. Here, we show that TagA, a secreted metalloprotease upregulated by the Vc virulence master regulator ToxT, promotes Vc growth in mucin, and that TagA is a bifunctional protein, acting as both mucinase and a mucus secretagogue that in- duces host mucin production. Using a combination of ex vivo tissue culture and in vivo gnotobiotic mouse colonization models combined with TagA mutants lacking either proteolytic activity or MUC2-inducing activity, we found that TagA’s two activities have different effects on Vc fitness during infection depending on the pres- ence of specific human gut microbes. We have generated model gut microbiota characteristic of human gut microbiota states: one model microbial community similar to that of healthy individuals, which promotes Vc in- fection resistance, and another model microbiota characteristic of the dysbiotic state found in cholera endemic areas associated with high susceptibility to Vc colonization. TagA mucolytic activity is important for Vc infection resistance within the colonization-resistant microbiota, while the mucin-inducing activity of TagA FN3 leads to increased Vc infection within dysbiotic communities. Therefore, we hypothesize that Tag drives Vc metabolic interactions with specific gut microbiota leading to community-specific attachment, growth, and overall infection outcomes. We will test aspects of this core hypothesis in four specific aims. Aim 1 will elucidate mechanisms driving mucin-dependent interactions of Vc with commensal gut microbes in epithelial attachment and growth. Aim 2 will examine how personalized gut microbiota structure in cholera endemic areas modulates mucin- and TagA-dependent disease phenotypes. Aim 3 will determine how TagA-microbiota interactions drives produc- tion and metabolism of host mucins. Finally, Aim 4 will elucidate the role of proximity and spatial specificity in driving microbiota-dependent Vc disease outcomes. The ultimate goal of this application is to shed light on the role of pathogen-mediated mucin metabolism in microbial interactions during enteric infection.

NIH Research Projects · FY 2026 · 2023-06

PROJECT SUMMARY/ABSTRACT Acute respiratory distress syndrome (ARDS) is a common and devastating cause of acute respiratory failure. There are 200,000 annual ARDS cases in the U.S. (2.5-5 million globally), which account for 60,000 deaths and enormous physical, cognitive, and psychosocial morbidity among survivors. Yet, despite more than 200 randomized clinical trials (RCTs), only two interventions – low-tidal-volume ventilation and prone positioning – have definitively improved outcomes using a traditional frequentist, null hypothesis, p-value-based trial design and analysis. The research team contends that assessing data in this framework may overlook informative trial data and delay or thwart the identification of promising therapies, especially when p-values fall just short of the 0.05 threshold, which has occurred in several major ARDS trials. As an alternative methodological approach to maximize the clinical insight gained from RCTs, the team will reanalyze 29 international and NHLBI-funded ARDS RCTs that enrolled more than 15,000 individuals using Bayesian causal inference and machine learning methods they have developed and validated. Most therapies they will examine are either low-cost or easily implemented practices and thus have the potential for high impact (e.g., ventilator settings, fluid management, corticosteroids, statins, beta-agonists, vitamin D). In Aim 1, instead of using statistical significance, they will quantify the probability of a beneficial treatment effect and its probable magnitude. That is, instead of using a pre-specified p-value to determine whether an intervention has at least the hypothesized mortality benefit, they will derive the probability that a given therapy is associated with clinically relevant absolute mortality reductions of at least 2%, 4%, and 6%. They will examine each intervention with noninformative Bayesian ‘priors’ and then with standardized and meta-analysis-derived priors to reduce subjectivity and interrogate clinical efficacy across the spectrum of harm and benefit possibilities. In Aim 2, they will use Bayesian Additive Regression Trees (BART) formulations they developed to understand which ARDS patient types are most likely to benefit from, or be harmed by, a therapy, i.e., so-called ‘heterogeneity of treatment effect’ (HTE). Unlike prior HTE research in ARDS, their approach does not focus on one-by-one, binary splits of characteristics but rather can identify complex, multivariable, nonlinear treatment effect modification. Aim 2a will focus on mortality and adverse events. Aim 2b will apply a novel BART variation to identify HTE in outcomes such as ventilator duration or hospital stay whose observation is truncated by death. By estimating causal effects on these outcomes among always-survivors, their new method avoids biases associated with prior approaches, enabling accurate identification of clinically meaningful subgroups. Aim 3 focuses on developing and disseminating free, cloud-based software to support future ARDS trials. This work promises to improve the value of the knowledge gained from past and future ARDS RCTs by identifying truly beneficial treatments and informing how these therapies can be individually tailored for this high-mortality, high-morbidity syndrome.

NIH Research Projects · FY 2025 · 2023-06

Project Summary Privacy-preserving distributed analysis has gained increasing interests in the broad biomedical research community in recent years, as it can a) eliminate the need to create, maintain, and secure access to central data repositories, b) minimize the need to disclose protected health information outside the data-owning entity, and c) mitigate many security, proprietary, privacy and other concerns. As such, it offers great promises in lowering regulatory and other hurdles for collaboration across multiple institutions and enhancing the public trust in biomedical research. Equally important, analysis of health data from multiple institutions across the US would yield more robust and generalizable findings. This is particularly relevant in cancer disparities research as the sample size for minority groups can be very small from one institution. However, there remain significant methodological gaps in the current state-of-the-art for privacy-preserving distributed analysis. Most notably, missing data present significant challenges, as they are ubiquitous in biomedical data including, but not limited to, electronic health records (EHR). It is well known that missing data is a major source of bias in EHR. For example, patients from minority groups and those who have less access to private insurance tend to have more missing data in their EHR. Biased data as a result of missing data are known to yield unfair statistical and machine learning models, which in turn can perpetuate and exacerbate health inequities and disparities. There has been no work on principled approaches for properly handling missing data in distributed analysis beyond our recent works. In addition, it is well-known that distributed analysis is still at risk of revealing important individual-level information and lacks rigorous guarantee in the sense of differential privacy, the prevailing notion and metric for privacy protection. To address these significant limitations, we propose three specific aims. In Aim 1, we will refine and develop state-of-the-art imputation methods for handling missing data in distributed analysis and develop advanced functionalities for enhanced privacy protection through differential privacy control and homomorphic encryption. Building on the methods developed in Aim 1, we will develop an open-source and open-access distributed analysis platform that includes a robust system architecture and user-friendly GUI in Aim 2. We will assess and validate our distributed analysis platform using real-world use cases in cancer disparities research in Aim 3. With the enhanced privacy protection, our proposed distributed analysis platform will have the potential to further enhance public trust and lowerhurdles for collaboration across multiple institutions in cancer research. As such, our platform will enable researchers to use more information and less biased data in cancer research, enhance the validity, robustness and generalizability of research findings, and offer research substantial benefits in areas including, but not limited to, cancer disparities and informatics practice.

NIH Research Projects · FY 2025 · 2023-06

Project Summary Predictive analytic algorithms built on electronic health record (EHR) inputs, such as patient characteristics, administrative codes, and lab values, are increasingly used in health care settings to direct resources to high- risk patients. Data play an indispensable role in the development and deployment of effective predictive models. The greatest, yet understudied, challenge in the maintenance of these tools arises from a data-related concern, namely dataset shift, in which training data distribution differs from the population on which the algorithm is deployed, leading to model deterioration and inaccurate risk predictions. Dataset shift is a pervasive cause of algorithmic unreliability in EHR-based models due to inevitable changes in physician behaviors and health system operations that alter (1) the input distribution (covariate drift); and (2) changes in the relationship between predictors and outcome (concept drift). Sudden changes in healthcare utilization during the COVID-19 pandemic may have impacted the data generation process and the performance of clinical predictive models. Our preliminary study showed that decreased collection of patient labs during the COVID-19 quarantine period led to sparse data generation for important predictors of a single-institution EHR-based mortality risk prediction algorithm, underpredicting risk for patients with advanced cancers. Despite the increasing use of predictive tools in high stakes clinical applications; and growing recognition of dataset shift, we lack a framework for reasoning shift and its effects on care delivery; and for proactively addressing shift to maintain performance over time. In Aim 1, we propose to extend prior works on shift to a nationally deployed risk prediction algorithm, the VA Care Assessment Need (CAN) model, used on millions of VA beneficiaries each year. The VA CAN model predicts the likelihood of hospitalization within 90 days or 1 year after a primary care encounter to identify high-risk patients who would benefit from additional outpatient interventions. We also investigate covariate and concept drift as two possible mechanisms for COVID-19 associated dataset shift. In Aim 2, we apply an interrupted time series design to study the association between sudden shift at the onset of the pandemic on case-management decisions. Current solutions to address dataset shift have primarily been reactive (i.e. model retraining with recent data), however, fail to be robust in new testing environments. In Aim 3, we consider revision of the VA CAN model via machine learning and inclusion of variables that reflect potential drivers of shift. This project is innovative as it is the first to leverage a rigorous statistical framework to study extent and mechanisms of shift and develop proactive guidelines for model maintenance. The training plan is rigorous for Ms. Kolla, an MD-PhD student in biostatistics. She is strongly supported by her department and institution as well as her two high- qualified sponsors: Dr. Jinbo Chen, an expert in EHR-based risk prediction modeling, and Dr. Ravi Parikh, an expert in implementation of predictive analytics. The proposed research and career development plan will be an essential step towards Ms. Kolla’s development as an interdisciplinary and independent physician-scientist.

NIH Research Projects · FY 2025 · 2023-06

PROJECT SUMMARY The mammalian respiratory system undergoes cyclical mechanical strain as part of its normal function. Lungs have evolved to be flexible to adapt to this strain, which involves rhythmic inflation and deflation of the alveoli for efficient gas exchange. Multiple cell lineages comprise the alveolar niche including alveolar type 1 (AT1) and alveolar type 2 (AT2) epithelial cells as well as various unique mesenchymal and endothelial cell types. AT1 cells are required for efficient gas exchange across the endothelial capillary plexus while AT2 cells generate pulmonary surfactant and act as facultative progenitors that differentiate into AT1 cells. While most studies on mechanotransduction have focused on the response of mesenchymal lineages, the ability of epithelial cells, in particular those within the lung alveoli, to respond to and maintain their identity and function in the face of this continuous and rhythmic biomechanical strain has not been well defined. Using multiple genetic and biophysical approaches, we present new preliminary data demonstrating that loss of cytoskeletal-extracellular matrix interactions via genetic, mechanical and chemical perturbations in AT1cells, leads to their rapid reprogramming into AT2 cells in vivo. Single cell RNA-seq (scRNA-seq) analysis shows that these reprogrammed AT2 cells are very similar to normal AT2 cells. Loss of AT1 cell fate is accompanied by coordinate changes in lamina- associated chromatin domain (LAD) organization, causing sequestration or release of AT1 or AT2 specific loci located in LAD sat the nuclear periphery. This phenomenon inversely correlates to the changes in alveolar epithelial cell fate. Importantly, we have developed a novel model of unilateral mechanical unloading of the cyclical strain from breathing movements in the lungs and show that this causes a profound reprogramming of AT1 into AT2 cells. In agreement with these new Preliminary Data, our laboratories recently demonstrated that Yap/Taz are found in the nucleus of AT1, but not AT2cells, and are essential for maintaining AT1 cell fate throughout the lifespan of mice. Loss of Yap/Taz results in a rapid reprogramming of AT1 cells into AT2 cells in the absence of injury. Since Yap/Taz can function as cytoplasmic mechanotransducers in cells and translocate to the nucleus upon actin-regulated cell stretch and strain, our combined preliminary and published data suggest that mechanotransduction plays a specific role in AT1cells to maintain alveolar function in the homeostatic lung. Thus, our published and preliminary data raise a provocative hypothesis that the lung has evolved specific epigenetic and transcriptional mechanisms to maintain cellular fate in the face of mechanical strain from normal respiration and these pathways are altered in the response to injury and disease. This proposal brings together two complementary laboratories with extensive experience in the study of lung development, epigenetic control of cell fate, and the inherent implications for regeneration and disease and we aim to address key unanswered questions in cell fate regulation in lung development and regeneration.

NIH Research Projects · FY 2025 · 2023-05

Project Summary (limited to 30 lines) Ovarian cancer is a devastating gynecologic malignancy with 13,770 estimated US deaths in 2021 with a 49.1% relative 5 year survival rate (SEER). Leveraging the considerable fraction of women with ovarian cancer who have germline or somatic homologous recombination deficiencies (HRD), poly (ADP-ribose) polymerase 1 inhibitors (PARPi) have become standard of care for ovarian cancer. Unfortunately, most patients treated with PARPi develop resistance. Interestingly, most PARPi resistant patients continue to express activated PARP-1 (the target of PARPi) in the nucleus. This finding has guided our alpha theranostic radiopharmaceutical approach to treating PARPi-resistant ovarian cancer to deliver cytotoxic alpha particles directly to the nucleus of cancer cells to create lethal, double stranded DNA breaks. Our platform is based on a small molecule similar to the approved PARPi, rucapararib, labeled with 18F for PET ([18F]fluorthanatrace, [18F]FTT) and 211At for alpha therapy ([211At]parthanatrace, [211At]PTT). Our overarching hypothesis is that [211At]PTT can overcome PARPi resistance with an acceptable therapeutic ratio and that the theranostic pair of [211At]PTT and [18F]FTT will allow accurate pre-treatment dosimetry to guide both efficacy and tolerability of therapy. Using mouse models of ovarian cancer, we plan to (1) measure the comparative dynamic biodistribution of the proposed theranostic pair, [18F]FTT and [211At]PTT to verify preliminary data supporting similar tumor uptake and tissue kinetics, (2) understand the dose-response relationship in tumor and organs at risk (both those expressing considerable PARP-1 and those with off target agent biodistribution); (3) carry out pre-clinical studies to assess toxicity and efficacy of the [211At]PTT /[18F]FTT theranostic approach with optimized dose fractionation. Our specific aims are as follows: SA1—Biodistribution and Pharmacokinetics: Test the comparative biodistribution of [18F]FTT and [211At]PTT in normal tissue and ovarian cancer. SA2—Dose-response relationship: Develop and validate on- and off-target normal organ dose limits and tumor dose-response relationship utilizing [18F]FTT PET/CT to predict dosimetry from [211At]PTT. SA3—Pre-clinical trials: Determine the optimal dosing scheme and estimate efficacy in patient derived ovarian cancer murine models. Successful completion of these aims will provide data needed for a first in human clinical trial of [18F]FTT -guided [211At]PTT therapy in women with advanced PARPi-resistant ovarian cancer and will provide insight into tumor factors mediating effective alpha particle therapy to guide patient selection in clinical trials and clinical practice.

NIH Research Projects · FY 2026 · 2023-05

More than 200,000 women are diagnosed with endometriosis every year and over half of those women do not receive a definitive diagnosis until 8.5 years after the onset of symptoms and many times when they present with additional comorbidities. While several studies have suggested that genomic markers, environmental risk factors and inflammatory markers play crucial roles in endometriosis symptomatology, there are no effective tools available to predict an individual's risk of developing endometriosis or to predict its downstream effects. The long-term goal is to develop effective and non-invasive early screening tools to identify patients at risk of developing endometriosis and predict long-term effects. The main objective of this project is the development of models to predict the risk of endometriosis across varied clinical manifestations and associated long-term health outcomes. Our central hypothesis is that integrative risk models will successfully identify patients at risk of developing endometriosis and associated diseases that occur either concurrently with endometriosis (reproductive age) or after endometriosis development (long-term health outcomes), enabling early diagnosis and prevention. This general hypothesis will be tested via the following specific aims:(1) Develop an integrative risk model to predict patients at high risk of developing endometriosis; (2) Develop an integrative risk model combining genetic and nongenetic risk factors to predict clinical manifestations among women with endometriosis ; (3) Create a lifelong chronological map of endometriosis to identify individuals at risk of developing associated comorbidities. In aim 1, we will integrate genetic and non-genetic risk factors extracted from Electronic Health Records in linear and non-linear fashion to generate an EndoRisk model. In aim 2, we will generate a catalog of additional risk factors linked to various clinical manifestations of endometriosis and develop risk model for varied manifestations. In aim 3, we will evaluate mediating risk of endometriosis on associated comorbidities and develop a mediator risk prediction model for concomitant conditions and long-term health outcomes. At the successful completion of the proposed research, the expected outcomes will be rigorously evaluated non-invasive computational methods for screening and diagnosing endometriosis across various clinical manifestations and its long-term effects based on genetic and non-genetic factors. The proposed research is innovative because our novel methodology for integrated risk models will have immediate translational implications. These results will provide a strong basis for future development of strategies for improving patient outcomes and translating the knowledge to clinical practice by providing support for identifying patients at high, moderate, and mild risk of endometriosis, which is expected to have a significant impact on women suffering from endometriosis or its long-term effects by tailoring personalized treatments based on their relative risk.

NIH Research Projects · FY 2026 · 2023-05

PROJECT SUMMARY Approximately 10% of US adults aged 65 years or older take levothyroxine to treat hypothyroidism. Guidance for its management has vast and important implications for the health and health care expenditures of millions of older people. Levothyroxine has a narrow therapeutic index that requires monitoring of dosing through thyroid stimulating hormone (TSH) testing. The current TSH reference range is based on the population distribution of younger people, despite evidence for a shift to higher levels with increasing age. Furthermore, observational data do not demonstrate adverse clinical consequences if people with TSH levels just above the reference range are left untreated, and a large clinical trial of people aged 65 years or older showed no benefit to treating this group of patients with levothyroxine. The trial of treatment of subclinical hypothyroidism used low doses of levothyroxine because of underlying endogenous thyroid function. These data may not be generalizable to individuals who have no endogenous thyroid function and rely entirely on exogenous levothyroxine. Small trials in younger people taking levothyroxine suggest that there are no physiologic differences between higher doses of levothyroxine that maintain TSH levels in the lower end of the reference range compared with lower doses of levothyroxine that maintain a TSH level just above the upper limit of the reference range. Our overall goal is to determine the clinical consequences that allowing greater flexibility in levothyroxine dosing would have in older individuals who take levothyroxine. We propose to perform a randomized, double-blind clinical trial of two 6-month dosing strategies of levothyroxine in patients aged 65 years and older who are already taking a stable dose of levothyroxine therapy, one to maintain a target TSH of 0.5-2.0 mU/L and another of a lower levothyroxine dose to achieve a target TSH of 5.5-7.0 mU/L. We will assess the effects of levothyroxine therapy at two different TSH targets on symptoms of hypothyroidism, mood, sleep, measures of memory and executive function, weight, lipids, and a marker of bone turnover. This clinical trial will provide essential data to inform the clinical value of increased flexibility in LT4 dosing for older LT4 users. Implications include widening the LT4 therapeutic window, decreasing the frequency of LT4 titration and TSH testing, and reducing the risk of LT4 overtreatment. In sum, this study could transform treatment of hypothyroidism into an easier, safer, and less costly clinical practice for millions of older adults.

NIH Research Projects · FY 2026 · 2023-05

Chronic vascular inflammation is a hallmark of atherosclerosis, pulmonary arterial hypertension (PAH) and related conditions. It is also one of the principal causes of endothelial- to-mesenchymal transition (EndMT). We have recently demonstrated that disruption of EndMT, achieved by inhibiting endothelial-specific TGFβ signaling input, results in extensive (~70%) regression of established atherosclerotic lesion and prevention of development of new ones. It also prevents development of hypoxia-induced PAH. These data suggest that EndMT is key to the development and progression of illnesses associated with chronic inflammation, such as atherosclerosis, PAH, and transplant arteriopathy. However, a therapeutic strategy that relies on suppressing EndMT via control of endothelial TGFβ signaling is complicated because of the need of endothelial-specific delivery of therapeutic agents (systemic inhibition of TGFβ signaling is fraught with side effects and has been shown to promote atherosclerosis via its effects on smooth muscle cells). For these reasons, we focused on identifying another EndMT control point that can serve as an effective therapeutic target. Since endothelial cells have unique metabolic requirements and pathways, we concentrated on identifying potential metabolic-related control of EndMT. Our preliminary studies indicate that there indeed is metabolic control of EndMT that operates via acetylation-dependent regulation of TGFβ signaling. Moreover, the Ac-CoA needed for these acetylation events appears to be in large part derived atypically from acetate. Our goal in this application is to rigorously define and characterize the unique endothelial metabolic pathway that leads to generation of cytoplasmic Ac-CoA from acetate and the role that this Ac- CoA plays in TGFβ signaling. This will be tested in vitro and in vivo using genetically engineered mice. Finally, we will test two distinct translational strategies – a nanoparticle-based EC-specific RNAi delivery, and an oral specific inhibitor to test the effect of suppression of acetate-based Ac-CoA production on the development and progression of atherosclerosis

NIH Research Projects · FY 2026 · 2023-05

Summary The overarching objective of this Program Project Grant is to understand fundamental mechanisms underlying communication between cancer cell genomic instability and the immune system. Foundational work from the investigators on this P01 demonstrates multivariate ways in which genomic damage is aberrantly detected as “foreign” by pattern recognition receptors that are typically used to sense viral nucleic acids. The collective body of work from our groups establish that DNA damage, changes in tissue architecture, mitotic errors, and nuclear envelope fragility serve to breach cell intrinsic barriers that prevent endogenous DNA and RNA from detection by innate immune pattern recognition sensors. These events critically affect the tumor microenvironment to either promote or suppress tumor growth. To achieve our goals, we have assembled three Projects that will work closely with three Cores to address critical questions on detection of genome instability in tumors by the immune response. Project 1 investigates the relationship between DNA damage responses and pattern recognition of endogenous DNA and RNA in the cytoplasm. Project 2 tests hypotheses on how disruption in tissue architecture and mechanical forces result in chromosome missegregation and instability. It describes an approach to understand innate immune system recognition of this instability. Project 3 investigates in vivo responses to DNA damage within tumors, while designing rational approaches to enhance anti- tumor immune activation. Integration of these multidisciplinary projects with Mammalian Artificial Chromosome and Chemical Biology Cores will advance our primary goal of defining the molecular basis for immune detection of genome instability in cancer.

NIH Research Projects · FY 2026 · 2023-05

More than one-quarter of U.S. adults report past-year binge drinking and 5.6% meet criteria for a past-year alcohol use disorder (AUD). These traits are associated with psychosocial disruption, medical co-morbidities, and nearly 10% of all U.S. deaths annually. Alcohol consumption and AUD have an estimated twin heritability of 43% and 49%, respectively. Genome-wide association studies (GWAS) of these traits have identified 380 genome-wide significant SNPs in 155 loci. In this revised application, we propose to use a “variant to gene mapping to clinical impact” approach, intersecting GWAS data with ATAC-seq and high-resolution promoter- focused Capture C neuronal datasets derived from human induced pluripotent stem cells (iPSCs) to identify potential effector genes. To prioritize SNPs, we will focus on those residing in open chromatin and with enhancer epigenetic marks; we will also use eQTL resources, as needed. We will validate these and newly identified candidates in three ways: 1) in established Drosophila models of alcohol behavioral effects, 2) initially with human iPSC-derived cortical and dopaminergic neurons and subsequently with neurons of other neurotransmitter systems, as indicated, to delete the genomic neighborhood harboring a putative causal variant to determine its effects on the gene's expression, and 3) with data from 4 biobanks to corroborate the association of the functionally validated genes with alcohol-related phenotypes. In Aim 1, we will expand our preliminary set of 43 loci from iPSC-derived cortical neurons, initially by applying similar methods to iPSC- derived dopaminergic neurons and other neuronal types, as indicated. In Aim 2a, we will screen candidate genes identified in preliminary findings and those identified in Aim 1 by knocking down or over-expressing their orthologs in fly models of alcohol consumption, preference, sensitivity, and tolerance. In Aim 2b, we will use SNP-CRISPR in human iPSC-derived neurons to test whether deleting the genomic neighborhood of putative causal variants from preliminary data or those identified in Aim 1 affects expression of their target gene(s). In Aim 3, we will use array and exome sequence data from both European- and African-ancestry individuals to validate all putative effector genes by examining their association with alcohol-related traits, conducting downstream analyses, testing rare variant effects, and examining pleiotropy in phenome-wide association studies. This project will identify novel genetic variants and the corresponding effector genes that contribute to alcohol-related traits, thereby shedding light on the biological pathways that influence the development of the traits. Study results will have fundamental implications for novel approaches to the diagnosis, prevention, and treatment of heavy drinking and AUD.

NIH Research Projects · FY 2026 · 2023-05

Interventional Oncology (IO) is emerging as the fourth pillar of cancer care alongside medical, radiation, and surgical oncology. Interventional oncologists provide minimally invasive image-guided therapies to treat cancers without the toxicities and disfigurement of chemotherapy, radiation or surgery. New clinical trial designs and collaborations are essential to determine how and when IO therapies should be integrated into multidisciplinary care plans to achieve optimal outcomes for cancer patients. Obstacles to this are many. Trial designs must accommodate staged and repeatable therapies, which complicates time-to-event analysis. There is a dearth of interventional oncology clinical investigators, who are needed to build collaborations with other oncologic disciplines to develop new concepts and protocols for clinical trials. The NCI cooperative group hierarchy is the domain of medical oncology. Surgical and interventional concepts struggle to hurdle the many layers of the review process, which is a barrier to the recruitment and retention of young investigators. Less than 5% of the >100 NCTN trials open at the applicant’s cancer center involve more than one cancer specialty, a stark indicator of the deficit in interdisciplinary clinical research. Conducting interdisciplinary trials is fraught with logistical and administrative challenges when the treating physicians practice in different departments, which historically is a major determinant of trial failure. The role of a senior IO clinical research specialist is to address each of these obstacles at the institutional and NCTN level. This starts with teaching clinical trial design and execution to a new cadre of young investigators from all cancer disciplines. Interdisciplinary collaborations can then be created within and across NCTN institutions to generate new trial concepts investigating the intersection of systemic and image-guided therapies to create new therapeutic synergies. Areas ripe for investigation include potentiation of ischemia by targeting HIF activation, autophagy, and free radical generation; potentiation of selective internal radiation with radiosensitizers; potentiation of thermal-based therapies to improve ablation margins; ablation and embolization as immunostimulants to potentiate immune checkpoint inhibition; image-guided delivery of CAR-T cells into solid tumors; direct injection and intralymphatic administration of vaccine-based agents; and nanoconstructs for delivery of therapeutic agents. These novel concepts need to be guided through the labyrinthian NCTN process, and new platforms developed for execution of interdepartmental clinical trials.

NIH Research Projects · FY 2026 · 2023-05

PROJECT SUMMARY Mutations in Crumbs homologue-1 (CRB1) gene cause severe inherited retinal dystrophies (IRDs). Worldwide ~80,000 CRB1 patients are affected, with a prevalence in the United States of 1 in 86,500. There is no treatment available. Gene augmentation in Crb mouse models has shown mixed results, with successful proof-of-concept (POC) using family member CRB2 but only limited morphological and no functional benefits in addition to adverse effects using CRB1-A. CRB1 proteins localize adjacent to adherens junctions and are essential in maintaining their stability in photoreceptors (PRCs) and Müller glial cells (MGCs). The role of CRB1 in retinal development and disease has been focused on CRB1-A. However, three human retinal CRB1 isoforms exist: CRB1-A, the human specific CRB1-C, and the newly identified CRB1-B. In mice, CRB1-A and CRB1-B operate in different cell types (MGCs and PRCs, respectively). Our long-term goal is to halt the progressive retinal degeneration found in CRB1 IRD patients. Our preliminary data confirm the predominate cell-type-distinct localizations of CRB1-A and CRB1-B in addition to the localization of CRB1-C in human cadaveric retina and induced pluripotent stem cell (iPSC)-derived retinal organoids. Further, the majority of CRB1 mutations affect more than one CRB1 isoform. Consequently, the objective of this grant is to determine an isoform-independent approach to treat CRB1 IRDs. Prime editing is a double-strand break-independent gene editing system that can correct all mutation types. Our central hypothesis is that prime editing is amenable to the correction of CRB1 mutations, allowing us to develop the tools necessary to ascertain its therapeutic efficacy in post-mitotic retinal cells. This hypothesis will be tested by pursuing the following three specific aims. Aim 1 (c.2843>A) and Aim 2 (c.3307G>A) will assess if prime editing is amenable for the installation and correction of CRB1 mutations and define its safety profile by evaluating off-targeting of the most efficient strategies. Further Aim 1 and 2 will characterize phenotypic, histopathological, and molecular changes in the derived retinal organoids. Lastly, in Aim3 we will define if a lentiviral all-in-one or AAV split-intein prime editing strategy is most amenable to perform post-mitotic editing in retinal organoids. Impact: Results of this novel project would create new CRB1 retinal organoid disease models, identify therapeutic outcome measures for CRB1 IRDs, and define the efficiency and safety profile for prime editing tools for the amelioration of CRB1 IRDs. This proposal is innovative, as our approach would correct all CRB1 isoforms affected by a given CRB1 mutation. Excitingly, the successful completion of this project will establish a preclinical pathway for showing POC for CRB1 prime editing therapeutics.

NIH Research Projects · FY 2026 · 2023-05

PROJECT SUMMARY Alzheimer's Disease and Alzheimer's Disease Related Dementias (AD/ADRD) are neurodegenerative diseases characterized by progressive loss of cognition and other neurobehavioral symptoms. In United States, there are approximately 5.8 million patients live with AD/ADRD, and 97% of these patients are older than 65. In the last decade, real-world data (RWD), including electronic health records (EHR) data and claims data, are becoming increasingly valuable for drug repurposing of AD. In this proposal, we plan to develop novel high dimensional semi-supervised learning and active learning methods, as well as associated high dimensional hypothesis testing procedures, to accelerate interventions of AD/ADRD, using drug repurposing of AD/ADRD as a motivating use case. We will address several key challenges in real-world data including the high dimensionality of the risk factors, concomitant medication use, and complex and heterogeneous progression trajectories of AD/ADRD. The success of this project will lead to novel machine learning and statistical learning methods for facilitating drug repurposing for AD/ADRD based on real-world data.

NIH Research Projects · FY 2025 · 2023-05

PROJECT SUMMARY Mutual exclusivity and co-occurrence of cancer causing mutations are due to pairwise genetic relationships that include oncogenic redundancy and synthetic lethality. These interactions suggest that the cancer-promoting effects of one mutation are dependent on the presence of another, a contingency that can be exploited in the development of new cancer therapies. Certain mutations have contrasting effects, promoting cancer in one mutational context but limiting it in another. SETD2 inactivation in lung adenocarcinoma occurs in 9% of tumors overall, and frequently co-occurs with oncogenic KRAS, but is mutually exclusive with oncogenic EGFR, the most frequent driver genes of this disease. Our lab was the first to identify SETD2 as a potent tumor suppressor in a KRAS-driven mouse model. However, paradoxically, Setd2 inactivation prevents tumor growth in the context of oncogenic EGFR, suggesting an antagonism between these alterations. The opposing effects of Setd2 inactivation are surprising given that KRAS is directly downstream of EGFR and activates the MAPK pathway, a driver of many cancer types. Given that KRAS and EGFR share this major tumorigenic pathway, I hypothesize that Setd2 inactivation is specifically synergistic with activation of the MAPK pathway, but incompatible with a separate pathway that is also downstream of EGFR. An important clue in deciphering this incompatibility is the epistatic relationship between SETD2 and LKB1, another frequently inactivated gene. Although both genes are powerful tumor suppressors in KRAS- driven models, co-mutation conferred no additional growth advantage, indicating that these genes act in the same pathway. Additionally, Lkb1 inactivation has the same paradoxical antagonism in EGFR-driven tumors. Inactivation of Lkb1 results in constitutively activated mTORC1 signaling which is a common feature of many cancers. My preliminary data demonstrate that Setd2 inactivation also promotes mTORC1 activity in KRAS- driven tumors. Likewise, oncogenic EGFR directs mTORC1 signaling via the PI3K-AKT axis and is reliant on this pathway for tumor maintenance, while oncogenic KRAS is not. Given the stimulation of mTORC1 signaling by Setd2 and its synthetic lethality with oncogenic EGFR which also activates mTOR, I hypothesize that the heightened mTORC1 activity present in Setd2-inactivated tumors is incompatible with oncogenic EGFR. To test these hypotheses, I first aim to determine whether Setd2 inactivation is synergistic with oncogenic MAPK signaling using a BRAF-driven mouse model. Second, I will determine whether excess mTORC1 signaling is responsible for EGFR-SETD2 antagonism by modulating this pathway in each driver context using tumor cell lines. This study will begin to characterize the synthetic lethal relationship between two frequently mutated genes in lung adenocarcinoma. Understanding these interactions will enable development of new therapies that target genotype specific vulnerabilities.

NIH Research Projects · FY 2026 · 2023-05

Project Summary During cardiac development, coordinate gene expression changes facilitate the progressive lineage restriction of multipotent progenitors into a terminal identity that is maintained over their lifespan. Compromised differentiation and/or cell state have been linked to multiple diseases, including aspects of congenital heart disease and heart failure. Thus, the mechanisms underlying cellular identity are of intense interest. Models underlying fate determination and the identity often focus on transcription factors and/or niche signals. Current paradigms fail to reconcile how the interplay between a finite number of morphogens and lineage specific transcription factors result in 200+ cell types with distinct and stable identities. I hypothesize that nuclear architecture represents a critical mechanism for achieving coordinated regulation of hundreds of genes underlying cellular identity by governing their accessibility or availability. Supporting our hypothesis, we have built a strong body of work demonstrating that nuclear architecture regulates cardiac cellular identity in development and disease. First, we discovered mechanisms by which critical transcription factors not only govern transcription, but also choreograph genome folding to regulate cardiac neural crest fate determination. Second, our work shows that spatial positioning of chromatin safeguards cardiac cellular identity and likely contributes to human cardiac disease (i.e. laminopathies). Decades of work have shown that gene expression programs are regulated by the recruitment and activity of activator and opposing repressor proteins. In addition to revolutionizing our understanding of transcription, this work has led to therapies directly targeting transcription factors. The mechanisms that similarly balance formation, maintenance and dissolution of nuclear architecture are poorly understood. In the EIA application I outline an interdisciplinary vision to uncover how these mechanisms control cardiac cellular identity. In Theme 1, I propose strategies to identify and decipher how molecular players guiding establishment, maintenance and disassembly of genome folding impact cardiac cell state. In Theme 2, I propose strategies to uncover how epigenetic, transcriptional, and mechanical inputs regulate spatial positioning of the genome in relation to the nuclear lamina in physiologic and pathologic conditions. We have established a multipronged program that will use high throughput 3D imaging, genetic manipulations with precise spatiotemporal resolution, tunable cardiac microtissues, epigenome engineering, super-resolution imaging and state-of-the-art genomics to tackle the propose studies, with a focus grounded in physiological relevance. The orthogonal approaches promote rigor, but require flexibility. My strong track record of building an impactful body of work support our pursuit of this paradigm shifting work. The proposed studies have the potential to reshape our understanding of how epigenetics, transcriptional, and mechano-related mechanisms direct 3D genome organization and orchestrate cardiac cellular identity. By viewing cardiac diseases through the prism of genome organization, we predict a wealth of unrealized therapeutic opportunities.

NIH Research Projects · FY 2026 · 2023-05

This proposal is to support a robust human cohort enrolling subjects with acute respiratory distress syndrome (ARDS), pneumonia, or sepsis (collectively termed APS) as part of the APS Consortium, and to identify clinical and molecular features that better predict, stratify, and explain organ failure, mortality, and disability following APS. We hypothesize that distinct and reproducible molecular subtypes are common and detectable across all 3 APS syndromes, and that we will identify the pathways that maximally contribute to organ failure and recovery trajectory through this well-powered molecular cohort. As part of the Consortium-Wide Longitudinal Cohort study, we propose to develop new tools for risk assessment, stratification, and recovery from APS. In aim 1a, we will use joint modeling to integrate multiple plasma markers of inflammation, vascular dysregulation, sarcopenia, and neural injury to identify the combinations most associated with organ failure, infer which plasma intermediates might contribute causally to organ failures, and identify the proportion of mortality risk mediated by specific organ failures. In aim 1b we focus on better prediction of long term disability post-APS, testing the ability of Katz- and Lawson-informed functional status features to predict persistent disability and asking whether prediction of disability is enhanced by added plasma markers of inflammation, vascular injury, or neuromuscular injury. Our Center-specific aims employ novel molecular phenotyping to better explain organ failure, death, and disability post-APS. In aim 2a we test specific hypothesis-driven candidate markers of immune dysregulation as potential organ failure markers. Aim 2b identifies patterns of host immune health during recovery using high dimensional flow cytometry to understand the peripheral blood host immune response, and asks whether immune cell trajectory associates with disability or recovery. Aim 2c focuses on vascular injury markers, and asks which components of vascular injury associate with specific organ failures and with post-APS disabilities. In aim 3, we integrate multiple streams of biologic data and identify patterns of response across APS acutely and during recovery, use machine learning to select the most informative features for joint modeling, and test the performance of the model of acute or long term disability in different APS states. Our site will make a lasting contribution to the APS Consortium and our completed aims will advance the prevention and personalized treatment of ARDS, pneumonia, and sepsis to improve overall health.

NIH Research Projects · FY 2026 · 2023-05

The neural determinants of cognition are not well understood in the human brain and particularly elusive in patients diagnosed with frontotemporal dementia (FTD). FTD is a heterogeneous spectrum of clinical disorders often associated with impairments in social cognition, executive function, or language. FTD is typically caused by frontotemporal lobar degeneration proteinopathies including tau or TDP-43 pathology not yet diagnosable during life. Thus, identification of the neurons that selectively degenerate in FTD with tau (FTD-tau) and FTD with TDP-43 (FTD-TDP) may be informative to the development of anatomically-grounded diagnostics and neuroprotective therapeutics lacking in FTD. However, the clinical relevance of neuron loss remains unclear due in part to clinicopathologic heterogeneity within the FTD spectrum. Another limiting factor is that traditional, low- throughput methods preclude large-scale postmortem studies of FTD and rarely examine the cyto- or myeloarchitectonic subdivisions of brain regions (e.g. cortical layers) where distinct neurons reside and microcircuits connect local and distant regions. My recent comparative study of cortical layer pathology found that tau and TDP-43 pathology accumulate distinct laminar distributions in clinically similar FTD patients. However, the layer-specific neurons that accrue pathology and the axonal pathways by which pathology may spread are understudied in FTD syndromes, despite the compelling experimental evidence for trans-synaptic transmission of pathologic proteins in diverse networks. To address these gaps in knowledge, the current project plans to examine laminar architecture to leverage the unique cellular organization and connectivity of cortical layers to identify differential loss of laminar microcircuits embedded in large-scale frontotemporal networks involved in FTD. I propose to develop a new high-throughput approach to quantify laminar neuronal features comprising short and long-range microcircuits with inhibitory or excitatory properties. Based on my preliminary data, I hypothesize that tau and TDP-43 pathology will be related to the loss of partly distinct laminar microcircuits in regional networks vulnerable to FTD, suggesting that different neural microcircuits may contribute to similar cognitive impairments across the FTD spectrum. My cortical layer framework is a unique approach to interrogate changes to laminar microcircuits, facilitating the discovery of new disease-specific patterns of neurodegeneration within gross anatomical regions to identify the neural substrates of pathologic subgroups and clinical symptoms of FTD. The differential loss of laminar microcircuits in FTD is a conceptual paradigm for advancing the study of selective vulnerability at the mesoscale, thereby serving as a critical bridge between emerging microscopic genetic expression data and macroscopic network/connectome studies. Completing this project will require I obtain interdisciplinary training in machine learning and segmentation methods, bioinformatics, and social cognition, all areas that will directly benefit my transition to becoming an independent neuroscientist conducting translational research for dementia syndromes.

NIH Research Projects · FY 2025 · 2023-05

Bioprosthetic heart valves (BHV), fabricated from heterograft biomaterials such as glutaraldehyde-fixed bovine pericardium (BP), are widely used as a replacement for patients who have severe heart valve disease (HVD), which affects millions of people worldwide. Despite being effective, a limitation of BHV fabricated from BP is that they undergo structural valve degeneration (SVD) which limits durability. Although most commonly attributed to calcification, recent research has shown that advanced glycation end products (AGE) and serum protein infiltration also contributes to SVD. AGE mechanisms impair endothelial cell growth and may mechanistically contribute to lack of endothelialization of BHV experimentally and clinically. Many studies to inhibit calcification of BP have been done; however, strategies to mitigate AGE-serum protein accumulation have just begun to be explored. Through our studies we have recently identified, the AGE-inhibitor pyridoxamine (PYR), a vitamin B6 vitamer, to be a leading model compound that is effective in significantly reducing AGE accumulation and serum protein uptake of BP both in vitro and in vivo in rat subdermal implant studies. Furthermore, we have also established an innovative modification of BP with Poly-2-methyl-2- oxazoline (POZ), which significantly reduced serum protein uptake both in vitro and in rat subdermal explants. The central hypothesis of both my dissertation and this proposal is: Pretreatment of BP with PYR and POZ can mitigate AGE and serum protein pathophysiology that contributes to noncalcific SVD mechanisms. Ethanol (EtOH) pretreatment of BP, an FDA approved anti-calcification methodology, will be a mechanistically based experimental intervention in my study design, that will help explore the interactions between calcific and non- calcific SVD mechanisms. Aim 1: Investigate in vitro the mechanism and efficacy of inhibition of AGE and serum protein infiltration to enhance heterograft biocompatibility by studying endothelial cell-BP interactions. Subaim 1a: Evaluate the effects of PYR pretreatment of BP to mitigate AGE and serum protein mechanisms: blood outgrowth endothelial cell (BOEC) culture studies with high shear flow simulation. Subaim 1b: To determine the effect of POZ mediated serum protein exclusion on promotion of BOEC adhesion and reduction of endothelial activation. Aim 2: To investigate the mechanism and efficacy of inhibition of AGE and serum protein SVD pathology, and interactions with calcification using rat subdermal BP implants: PYR and POZ studies. Subaim 2a: To study the efficacy of PYR pretreated BP, with or without ethanol pretreatment, on mitigating AGE-serum protein pathophysiology and calcification using a rat subdermal implant model. Subaim 2b: To study the efficacy of POZ alone, and the combined BP pretreatment with PYR, POZ, and ethanol for mitigating AGE, serum protein uptake and calcification in the rat subdermal implant model. The findings from this proposal will advance my research training and contribute to advances in our knowledge of SVD of BHV.

NIH Research Projects · FY 2026 · 2023-05

Project Summary/Abstract Accelerated aging, or the earlier onset and faster pace of cognitive decline along with broader declines in physical and mental health, is a distinctive yet poorly understood hallmark of aging in domestic and global low-income populations where individuals are often exposed to multiple recurrent adversities. Research that integrates biological and social data promises key insights into the biosocial lifecourse dynamics that shape the aging process and contribute to accelerated aging and Alzheimer's Disease and Related Dementia (ADRD). However, the vast majority of biosocial research on aging and ADRD has been conducted using samples from relatively high-income populations that inadequately represent the varied socioeconomic contexts and ancestral backgrounds of future older populations in the US and globally. This project will help fill this gap by collecting genomic and epigenomic data on adults aged 45 plus in an African low-income cohort (N=3,500). Over 25 years of existing lifecourse social, contextual, and health data in this cohort will be supplemented with epigenetic aging biomarkers and additional longitudinal measures of cognition to study the risk and resilience factors that shape the evolution of accelerated aging and cognitive decline. The resulting longitudinal biosocial data will generate a public resource that attenuates limitations of publicly available genomic and epigenomic data that currently constrain the generalizability of novel biosocial aging and ADRD research findings to the socially and ancestrally heterogeneous US and global aging population. Specifically, the exceptional data generated in this project will allow us to pursue two aims that are at the forefront of current biosocial aging research and that will enhance our understanding of the pathways through which lifecourse adversities affect aging and ADRD risk: Aim 1-Lifecourse adversities and epigenetic aging biomarkers: Investigate critical factors contributing to accelerated aging in a low-income population with extensive lifecourse adversities by (a) evaluating existing and novel epigenetic biomarkers of aging, and (b) testing their relationship to lifecourse adversities, health behaviors, and underlying genetic predisposition. Aim 2-Epigenetic aging biomarkers and ADRD risk among older adults in low-income populations: Investigate the relationship between epigenetic biomarkers and cognitive function/decline and ADRD to evaluate the biosocial determinants of ADRD in a population experiencing high levels of adversities. The overall hypothesis guiding this project is that new epigenetic aging biomarkers derived from this cohort will illuminate distinct biosocial pathways of aging that are unique to, for example, low-income and/or African ancestry populations, thereby providing new evidence for the weathering hypothesis that is often used to explain US health disparities and the health disadvantages of US low-income populations. Results will enhance our understanding of the biosocial determinants of aging and cognitive decline, and results will inform potential areas for healthy-aging interventions in low-income populations in the US and globally where the lack of effective health-system responses has been a barrier to enhancing the health and quality of life in older adults.

NIH Research Projects · FY 2026 · 2023-04

Alzheimer's disease (AD) is associated with surprisingly high degree of pathologic heterogeneity. In most individuals diagnosed with AD at autopsy, the brain not only harbors the β-amyloid and tau pathologies that are the hallmarks of AD, but also one or more co-pathologies, including TDP-43, α-synuclein, non-AD tauopathy, and cerebral small vessel disease (SVD). The primary AD pathologies and co-pathologies all contribute to neurodegeneration in AD, but their relative contribution in different brain regions and the degree in which co- pathologies modulate the progression of primary pathologies is not well understood. It is widely recognized that it is important for clinical trials in AD to account for these additional drivers of neurodegeneration, but there is a lack of in vivo biomarkers that can reliably detect and quantify co-pathology. Pathologic heterogeneity may help explain why AD treatments targeting a single pathological mechanism have been largely ineffective. This project seeks to address this limitation by using ex vivo human brain MRI to characterize the contributions of primary AD pathologies and co-pathologies to neuronal loss and cortical thinning in AD. The project leverages a prospective dataset from 100-120 autopsies conducted at the University of Pennsylvania AD Research Center that will include high-resolution 7 Tesla MRI of intact brain hemispheres with co-registered histology at selected gray matter locations and around white matter lesions. Moreover, the temporal lobe, part of the brain where earliest and most severe AD-related neurodegeneration occurs, will be scanned at 9.4 Tesla, and undergo serial histological imaging, allowing three-dimensional mapping of tau pathology (tangles, threads, etc.) and neuronal density across the entire temporal lobe. This unique ex vivo imaging dataset will represent a convergence of structural and pathological imaging data in the same 3D space, allowing a broad range of studies analyzing trajectories of pathology deposition and pathology-neurodegeneration relationships. The specific aims of the proposal are as follows. Aim 1 is to develop deep learning-based image analysis techniques for 7 Tesla whole- hemisphere MRI, which are currently lacking, including segmentation of cortical gray matter, white matter lesions, normal-appearing white matter, and subcortical structures; groupwise registration to both ex vivo and in vivo MRI templates; and extraction of both MRI-based and histological features to characterize white matter lesions associated with SVD. Aim 2 is to analyze the complete 100-120 specimen dataset to characterize the distribution of tau pathology, neuronal loss, and cortical thinning both in the temporal lobe and in the whole brain and to describe the impact of co-pathologies on these distributions and on the relationships between them. Aim 3 is to leverage pathology-specific “signatures” extracted from analyzing this ex vivo dataset to improve the sensitivity of in vivo biomarkers for inferring the presence of co-pathology and tracking disease progression.

NIH Research Projects · FY 2026 · 2023-04

PROJECT SUMMARY Frontotemporal lobar degeneration (FTLD) is a debilitating neurodegenerative disease that in almost all cases has one of two underlying proteinopathies – FTLD-tau and FTLD-TDP. To date MRI-based measures have not been able to reliably distinguish clinical syndromes or their underlying proteinopathies. A key feature of FTLD is the localized pattern of degeneration associated with various disease subtypes. These spatial patterns have been associated with clinical syndromes, as well as the underlying proteinopathies that are most-relevant for treatment studies. However, to date these patterns alone are not sufficiently specific to fully predict syndromes or separate FTLD-tau from FTLD-TDP in a single patient. We have recently shown that, in addition to atrophy, FTLD is associated with iron-rich cortical pathology. Moreover, our findings indicate that the specific cortical layers impacted by this pathology are distinct in FTLD-tau and FTLD-TDP, offering a potential target for the development of imaging biomarkers. We propose to use iron-sensitive MRI as the basis for the development of novel imaging biomarkers, with the aim of both monitoring disease progression and diagnosing underlying pathologic subtypes, addressing a highest priority recommendation of the 2019 ADRD Summit. We propose a two-pronged approach to this goal: First, we will use joint ex vivo MRI and histopathology in 50 human hemispheres, donated by patients with FTLD and typical age-matched controls, to quantify the distributions of iron-rich pathology. In particular, we will quantify both the laminar distribution and its relation to the patients’ underlying proteinopathies. In addition, we will evaluate the distribution of disease across the cortex, and associate this with clinical information collected during the patients’ lifetimes, including clinical syndrome and more fine-grained measures of symptoms. Second, we will use in vivo MRI at 3T and 7T with 100 FTLD patients an typical volunteers to develop and validate imaging protocols sensitive to the pathologic iron. At 3T, we will focus on quantifying the distribution of iron across the cortex. We will correlate these cortical findings with MRI-based measures of atrophy, and clinical measures including both symptoms and blood and CSF-based measures of degeneration and pathology. At 7T, we will develop and validate focal laminar imaging methods, with the aim of recapitulating our ex vivo findings in living patients and age-matched controls. The overall goal of this study is to develop and validate novel, iron-sensitive imaging biomarkers for FTLD to both monitor and diagnose underlying syndromes and pathologies. The ability to disciminate underlying proteinopathies is a key need in treatment trials which focus on either FTLD-tau or FTLD-TDP. Moreover, measuring the quantity and distribution of iron in the brain will also be valuable for monitoring disease progression, both in treatment trials, and more generally for FTLD patients in clinical care.

NIH Research Projects · FY 2026 · 2023-04

This study proposes to refine, integrate and disseminate the NeuroImaging Brain Chart (NIBCh) software toolbox and machine learning (ML) model library, an ecosystem of software components enabling constructive integration, statistical harmonization, and ML-centric data analyses across studies. NIBCh enables large-scale analyses of multi-modal brain MRI data by mapping such data into a compact coordinate system of informative neuroimaging signatures implemented by our library of ML models. The axes of this coordinate system represent two types of information: 1) a variety of structural (sMRI and dMRI) and functional connectomic (rsfMRI) imaging derived phenotypes (IDPs), such as multi-scale brain parcelations and brain networks; 2) complex ML-based imaging signatures (ML-IDPs), which capture multi-variate imaging patterns that reflect the heterogeneity of brain aging, neurodegeneration, as well as of neuropsychiatic disorders and have been previously derived from carefully processed and curated data of over 65,000 individuals. Using our software toolboxes (Tbx), researchers will be able to map new data into NIBCh, and hence to use ML-IDP models trained in NIBCh, as well as perform statistical tests against NIBCh normative ranges and compare their results with those of other studies using the same Tbx. The software suite will include a set of containerized pre-processing and analysis pipelines, as well as statistical harmonization and ML inference toolboxes, which will be accessible via a standalone python front-end visualization, as cloud-based containers, and via a web-interface supported by our high-performance computing cluster. Several dissemination plans are discussed, including a github user community, tutorials at major technical and clinical meetings, and support of both standalone pipelines locally or on the cloud, and web-based access of harmonization and ML inference modules. The over-arching primary goal of our program is to provide the software tools that will allow users to contribute to an actively growing community-based dimensional neuroimaging system that will utilize machine learning models to provide rich, yet precise, compact, concise, and informative representations of brain structure, function and connectivity.

NIH Research Projects · FY 2025 · 2023-04

This randomized controlled trial addresses social and organizational differences to reduce severe maternal morbidity (SMM) and maternal mortality in the most at-risk patients). Specifically, our intervention will implement and evaluate an integrated, multi-level maternity care home model (MCHM) that incorporates maternity care navigation, benefits navigation, social work, doula and mental health resources all within one care-delivery model. While previous studies have evaluated single social determinants (e.g. education and insurance) or single solutions (e.g. care navigator), these approaches lack a comprehensive, integrated approach that is responsive to all patient needs. Our study will test our central hypothesis that a patient-centered MCHM will address the gap in social, organizational, and health system factors that contribute to differences in outcomes between low and high risk individuals, thereby reducing SMM. To test the effectiveness of this MCHM and ensure timely implementation of the results, we propose a type 1 hybrid effectiveness-implementation trial to evaluate the effectiveness and implementation of an integrated MCHM that provides a comprehensive approach by partnering a unified model of social and organizational service delivery with medical service delivery in all prenatal offices affiliated with the two largest birthing hospitals in Philadelphia. Within this study we will determine the effectiveness of an integrated MCHM in reducing SMM among high-risk patients (Aim 1). Patients will be randomized (n=2300) to a MCHM (office-based prenatal care that is integrated with social services within the MCHM) or standard of care (office-based prenatal care with individually outsourced social services referrals) and followed throughout pregnancy and for 1 year postpartum. To determine mechanisms by which this integrated MCHM impacts SMM (Sub-Aim 1a), we will evaluate numerous factors that could plausibly mitigate the effects of health system failures, provider bias and adverse social conditions (e.g. improved health system access, care coordination). We will also characterize patient, provider and organizational implementation determinants relevant to an integrated MCHM and identify barriers and facilitators to implementation and sustainability (Aim 2) as well as determine resource utilization and total cost/cost savings associated with the MCHM (Sub-Aim 2a) by partnering with commercial and Medicaid payers. Importantly, the results of the proposed study will provide actionable evidence to support effective maternity care delivery that results in optimal and balanced outcomes, thereby revolutionizing the way in which prenatal, intrapartum and postpartum care is delivered and experienced. Additionally, even if the trial is negative in reducing SMM, there are still numerous other potential benefits to an integrated MCHM (including many of the secondary outcomes we are evaluating) and we will have therefore collected valuable information to inform the implementation of this model into clinical practice.

NIH Research Projects · FY 2025 · 2023-04

About 10-20% of persons who contract SARS CoV-2 will experience persistent post-acute sequelae of SARS- CoV-2 infection (referred here as PASC). Given that persistent symptoms are heterogeneous with multisystem involvement, recent consensus recommendations suggest that a holistic rehabilitation program may be required to manage PASC and restore function. While treatments offered at emerging outpatient COVID recovery clinics are being informed by previous similar diseases, the need is great for a better understanding of the unique needs of this growing population and for tested, efficacious rehabilitation programs to address them. We provide both here. Specifically, our aims are: (1) To quantify the incidence and severity of PASC across different variants and their effects on health and functioning; (2) To develop and evaluate the effectiveness of a patient-centered, interdisciplinary, multimodal comprehensive rehabilitation program among patients with PASC; and (3)To estimate the costs associated with the proposed PASC rehabilitation intervention and to examine the relationship between intervention’s costs and effectiveness and their implication for rehabilitation program initiatives. Data from a large and diverse ongoing longitudinal survey of persons who tested for COVID-19 at the study health system will serve as the sampling frame from which to identify and enroll PASC patients in the study. The targeted six-week program will be comprised of a core set of therapies, including individually titrated stretching and flexibility, strengthening of accessory breathing muscles and diaphragm, resistance and aerobic conditioning, and vestibular rehabilitation, supplemented by neuropsychological and cognitive remediation tailored to patients’ needs. Using a randomized controlled trial (RCT) design, the effectiveness of the intervention will be compared to that of usual care augmented by a one- time in-person assessment and patient education materials. In addition to walking speed, a widely used global measure of aerobic capacity and endurance, and patient-reported health and functioning (primary outcomes), we will assess the intervention effectiveness on: (i) cognitive functioning, (ii) pain, (iii) fatigue, (iv) tension, stress, anxiety, and depression, and (v) self-management of PASC symptoms (secondary outcomes). Outcomes will be measured at fixed points in time at 8 weeks (shortly after therapy completion) and at 90 day’s post- study entry to examine sustainability of effects. Our overarching hypothesis is that that higher intervention costs in the intervention group will be more than offset by greater improvements in outcomes implying that, overall, persons in the intervention group will receive more cost-effective care than those in usual care group. Given the dearth of rigorous scientific evidence regarding effective assessment and treatment of PASC and the unresolved questions concerning access to and value of post-COVID rehabilitation care, the results of this study will have significant implications for both policy and program development.